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(Float16 1 × 512 × 1 × 1500)", + "shortDescription" : "", + "shape" : "[1, 512, 1, 1500]", + "name" : "encoder_output_embeds", + "type" : "MultiArray" + } + ], + "modelParameters" : [ + + ], + "specificationVersion" : 7, + "mlProgramOperationTypeHistogram" : { + "Concat" : 54, + "Ios16.rsqrt" : 13, + "Ios16.mul" : 218, + "SliceByIndex" : 336, + "Ios16.sub" : 13, + "Transpose" : 6, + "Ios16.einsum" : 384, + "Ios16.conv" : 38, + "Ios16.add" : 26, + "Ios16.reduceMean" : 26, + "Ios16.softmax" : 192, + "Ios16.gelu" : 8, + "Ios16.batchNorm" : 13 + }, + "computePrecision" : "Mixed (Float16, Int32)", + "isUpdatable" : "0", + "availability" : { + "macOS" : "13.0", + "tvOS" : "16.0", + "visionOS" : "1.0", + "watchOS" : "9.0", + "iOS" : "16.0", + "macCatalyst" : "16.0" + }, + "modelType" : { + "name" : "MLModelType_mlProgram" + }, + "userDefinedMetadata" : { + "com.github.apple.coremltools.source_dialect" : "TorchScript", + "com.github.apple.coremltools.source" : "torch==2.2.1", + "com.github.apple.coremltools.version" : "7.1" + }, + "inputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float16", + "formattedType" : "MultiArray (Float16 1 × 80 × 1 × 3000)", + "shortDescription" : "", + "shape" : "[1, 80, 1, 3000]", + "name" : "melspectrogram_features", + "type" : "MultiArray" + } + ], + "generatedClassName" : "AudioEncoder", + "method" : "predict" + } +] \ No newline at end of file diff --git a/openai_whisper-base/AudioEncoder.mlmodelc/model.mil b/openai_whisper-base/AudioEncoder.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..31b155b9b8384df140e6f7080248842f9aea1c90 --- /dev/null +++ b/openai_whisper-base/AudioEncoder.mlmodelc/model.mil @@ -0,0 +1,3322 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.2.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})] +{ + func main(tensor melspectrogram_features) { + tensor var_38 = const()[name = tensor("op_38"), val = tensor([1, 1])]; + tensor var_44 = const()[name = tensor("op_44"), val = tensor([1, 1])]; + tensor var_49 = const()[name = tensor("op_49"), val = tensor(1)]; + tensor var_54_pad_type_0 = const()[name = tensor("op_54_pad_type_0"), val = tensor("custom")]; + tensor var_54_pad_0 = const()[name = tensor("op_54_pad_0"), val = tensor([0, 0, 1, 1])]; + tensor var_29_to_fp16 = const()[name = tensor("op_29_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor var_35_to_fp16 = const()[name = tensor("op_35_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(245888)))]; + tensor var_54_cast_fp16 = conv(bias = var_35_to_fp16, dilations = var_44, groups = var_49, pad = var_54_pad_0, pad_type = var_54_pad_type_0, strides = var_38, weight = var_29_to_fp16, x = melspectrogram_features)[name = tensor("op_54_cast_fp16")]; + tensor hidden_states_1_mode_0 = const()[name = tensor("hidden_states_1_mode_0"), val = tensor("EXACT")]; + tensor hidden_states_1_cast_fp16 = gelu(mode = hidden_states_1_mode_0, x = var_54_cast_fp16)[name = tensor("hidden_states_1_cast_fp16")]; + tensor var_78 = const()[name = tensor("op_78"), val = tensor([2, 2])]; + tensor var_84 = const()[name = tensor("op_84"), val = tensor([1, 1])]; + tensor var_89 = const()[name = tensor("op_89"), val = tensor(1)]; + tensor var_94_pad_type_0 = const()[name = tensor("op_94_pad_type_0"), val = tensor("custom")]; + tensor var_94_pad_0 = const()[name = tensor("op_94_pad_0"), val = tensor([0, 0, 1, 1])]; + tensor var_69_to_fp16 = const()[name = tensor("op_69_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246976)))]; + tensor var_75_to_fp16 = const()[name = tensor("op_75_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1819904)))]; + tensor var_94_cast_fp16 = conv(bias = var_75_to_fp16, dilations = var_84, groups = var_89, pad = var_94_pad_0, pad_type = var_94_pad_type_0, strides = var_78, weight = var_69_to_fp16, x = hidden_states_1_cast_fp16)[name = tensor("op_94_cast_fp16")]; + tensor hidden_states_3_mode_0 = const()[name = tensor("hidden_states_3_mode_0"), val = tensor("EXACT")]; + tensor hidden_states_3_cast_fp16 = gelu(mode = hidden_states_3_mode_0, x = var_94_cast_fp16)[name = tensor("hidden_states_3_cast_fp16")]; + tensor var_112_to_fp16 = const()[name = tensor("op_112_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1820992)))]; + tensor inputs_1_cast_fp16 = add(x = hidden_states_3_cast_fp16, y = var_112_to_fp16)[name = tensor("inputs_1_cast_fp16")]; + tensor var_122 = const()[name = tensor("op_122"), val = tensor(3)]; + tensor var_135 = const()[name = tensor("op_135"), val = tensor(1)]; + tensor var_136 = const()[name = tensor("op_136"), val = tensor(true)]; + tensor var_146 = const()[name = tensor("op_146"), val = tensor([1])]; + tensor channels_mean_1_cast_fp16 = reduce_mean(axes = var_146, keep_dims = var_136, x = inputs_1_cast_fp16)[name = tensor("channels_mean_1_cast_fp16")]; + tensor zero_mean_1_cast_fp16 = sub(x = inputs_1_cast_fp16, y = channels_mean_1_cast_fp16)[name = tensor("zero_mean_1_cast_fp16")]; + tensor zero_mean_sq_1_cast_fp16 = mul(x = zero_mean_1_cast_fp16, y = zero_mean_1_cast_fp16)[name = tensor("zero_mean_sq_1_cast_fp16")]; + tensor var_150 = const()[name = tensor("op_150"), val = tensor([1])]; + tensor var_151_cast_fp16 = reduce_mean(axes = var_150, keep_dims = var_136, x = zero_mean_sq_1_cast_fp16)[name = tensor("op_151_cast_fp16")]; + tensor var_152_to_fp16 = const()[name = tensor("op_152_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_153_cast_fp16 = add(x = var_151_cast_fp16, y = var_152_to_fp16)[name = tensor("op_153_cast_fp16")]; + tensor denom_1_epsilon_0_to_fp16 = const()[name = tensor("denom_1_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_1_cast_fp16 = rsqrt(epsilon = denom_1_epsilon_0_to_fp16, x = var_153_cast_fp16)[name = tensor("denom_1_cast_fp16")]; + tensor out_1_cast_fp16 = mul(x = zero_mean_1_cast_fp16, y = denom_1_cast_fp16)[name = tensor("out_1_cast_fp16")]; + tensor obj_1_mean_0_to_fp16 = const()[name = tensor("obj_1_mean_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3357056)))]; + tensor obj_1_variance_0_to_fp16 = const()[name = tensor("obj_1_variance_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3358144)))]; + tensor obj_1_gamma_0_to_fp16 = const()[name = tensor("obj_1_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3359232)))]; + tensor obj_1_beta_0_to_fp16 = const()[name = tensor("obj_1_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3360320)))]; + tensor obj_1_epsilon_0_to_fp16 = const()[name = tensor("obj_1_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_1_cast_fp16 = batch_norm(beta = obj_1_beta_0_to_fp16, epsilon = obj_1_epsilon_0_to_fp16, gamma = obj_1_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_1_cast_fp16)[name = tensor("obj_1_cast_fp16")]; + tensor var_168 = const()[name = tensor("op_168"), val = tensor([1, 1])]; + tensor var_170 = const()[name = tensor("op_170"), val = tensor([1, 1])]; + tensor query_1_pad_type_0 = const()[name = tensor("query_1_pad_type_0"), val = tensor("custom")]; + tensor query_1_pad_0 = const()[name = tensor("query_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3361408)))]; + tensor layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3885760)))]; + tensor query_1_cast_fp16 = conv(bias = layers_0_self_attn_q_proj_bias_to_fp16, dilations = var_170, groups = var_135, pad = query_1_pad_0, pad_type = query_1_pad_type_0, strides = var_168, weight = layers_0_self_attn_q_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("query_1_cast_fp16")]; + tensor var_174 = const()[name = tensor("op_174"), val = tensor([1, 1])]; + tensor var_176 = const()[name = tensor("op_176"), val = tensor([1, 1])]; + tensor key_1_pad_type_0 = const()[name = tensor("key_1_pad_type_0"), val = tensor("custom")]; + tensor key_1_pad_0 = const()[name = tensor("key_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3886848)))]; + tensor key_1_cast_fp16 = conv(dilations = var_176, groups = var_135, pad = key_1_pad_0, pad_type = key_1_pad_type_0, strides = var_174, weight = layers_0_self_attn_k_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("key_1_cast_fp16")]; + tensor var_181 = const()[name = tensor("op_181"), val = tensor([1, 1])]; + tensor var_183 = const()[name = tensor("op_183"), val = tensor([1, 1])]; + tensor value_1_pad_type_0 = const()[name = tensor("value_1_pad_type_0"), val = tensor("custom")]; + tensor value_1_pad_0 = const()[name = tensor("value_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4411200)))]; + tensor layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4935552)))]; + tensor value_1_cast_fp16 = conv(bias = layers_0_self_attn_v_proj_bias_to_fp16, dilations = var_183, groups = var_135, pad = value_1_pad_0, pad_type = value_1_pad_type_0, strides = var_181, weight = layers_0_self_attn_v_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("value_1_cast_fp16")]; + tensor var_190_begin_0 = const()[name = tensor("op_190_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_190_end_0 = const()[name = tensor("op_190_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_190_end_mask_0 = const()[name = tensor("op_190_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_190_cast_fp16 = slice_by_index(begin = var_190_begin_0, end = var_190_end_0, end_mask = var_190_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_190_cast_fp16")]; + tensor var_194_begin_0 = const()[name = tensor("op_194_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_194_end_0 = const()[name = tensor("op_194_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_194_end_mask_0 = const()[name = tensor("op_194_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_194_cast_fp16 = slice_by_index(begin = var_194_begin_0, end = var_194_end_0, end_mask = var_194_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_194_cast_fp16")]; + tensor var_198_begin_0 = const()[name = tensor("op_198_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_198_end_0 = const()[name = tensor("op_198_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_198_end_mask_0 = const()[name = tensor("op_198_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_198_cast_fp16 = slice_by_index(begin = var_198_begin_0, end = var_198_end_0, end_mask = var_198_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_198_cast_fp16")]; + tensor var_202_begin_0 = const()[name = tensor("op_202_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_202_end_0 = const()[name = tensor("op_202_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_202_end_mask_0 = const()[name = tensor("op_202_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_202_cast_fp16 = slice_by_index(begin = var_202_begin_0, end = var_202_end_0, end_mask = var_202_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_202_cast_fp16")]; + tensor var_206_begin_0 = const()[name = tensor("op_206_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_206_end_0 = const()[name = tensor("op_206_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_206_end_mask_0 = const()[name = tensor("op_206_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_206_cast_fp16 = slice_by_index(begin = var_206_begin_0, end = var_206_end_0, end_mask = var_206_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_206_cast_fp16")]; + tensor var_210_begin_0 = const()[name = tensor("op_210_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_210_end_0 = const()[name = tensor("op_210_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_210_end_mask_0 = const()[name = tensor("op_210_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_210_cast_fp16 = slice_by_index(begin = var_210_begin_0, end = var_210_end_0, end_mask = var_210_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_210_cast_fp16")]; + tensor var_214_begin_0 = const()[name = tensor("op_214_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_214_end_0 = const()[name = tensor("op_214_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_214_end_mask_0 = const()[name = tensor("op_214_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_214_cast_fp16 = slice_by_index(begin = var_214_begin_0, end = var_214_end_0, end_mask = var_214_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_214_cast_fp16")]; + tensor var_218_begin_0 = const()[name = tensor("op_218_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_218_end_0 = const()[name = tensor("op_218_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_218_end_mask_0 = const()[name = tensor("op_218_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_218_cast_fp16 = slice_by_index(begin = var_218_begin_0, end = var_218_end_0, end_mask = var_218_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_218_cast_fp16")]; + tensor var_227_begin_0 = const()[name = tensor("op_227_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_227_end_0 = const()[name = tensor("op_227_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_227_end_mask_0 = const()[name = tensor("op_227_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_227_cast_fp16 = slice_by_index(begin = var_227_begin_0, end = var_227_end_0, end_mask = var_227_end_mask_0, x = var_190_cast_fp16)[name = tensor("op_227_cast_fp16")]; + tensor var_234_begin_0 = const()[name = tensor("op_234_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_234_end_0 = const()[name = tensor("op_234_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_234_end_mask_0 = const()[name = tensor("op_234_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_234_cast_fp16 = slice_by_index(begin = var_234_begin_0, end = var_234_end_0, end_mask = var_234_end_mask_0, x = var_190_cast_fp16)[name = tensor("op_234_cast_fp16")]; + tensor var_241_begin_0 = const()[name = tensor("op_241_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_241_end_0 = const()[name = tensor("op_241_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_241_end_mask_0 = const()[name = tensor("op_241_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_241_cast_fp16 = slice_by_index(begin = var_241_begin_0, end = var_241_end_0, end_mask = var_241_end_mask_0, x = var_190_cast_fp16)[name = tensor("op_241_cast_fp16")]; + tensor var_248_begin_0 = const()[name = tensor("op_248_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_248_end_0 = const()[name = tensor("op_248_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_248_end_mask_0 = const()[name = tensor("op_248_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_248_cast_fp16 = slice_by_index(begin = var_248_begin_0, end = var_248_end_0, end_mask = var_248_end_mask_0, x = var_190_cast_fp16)[name = tensor("op_248_cast_fp16")]; + tensor var_255_begin_0 = const()[name = tensor("op_255_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_255_end_0 = const()[name = tensor("op_255_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_255_end_mask_0 = const()[name = tensor("op_255_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_255_cast_fp16 = slice_by_index(begin = var_255_begin_0, end = var_255_end_0, end_mask = var_255_end_mask_0, x = var_194_cast_fp16)[name = tensor("op_255_cast_fp16")]; + tensor var_262_begin_0 = const()[name = tensor("op_262_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_262_end_0 = const()[name = tensor("op_262_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_262_end_mask_0 = const()[name = tensor("op_262_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_262_cast_fp16 = slice_by_index(begin = var_262_begin_0, end = var_262_end_0, end_mask = var_262_end_mask_0, x = var_194_cast_fp16)[name = tensor("op_262_cast_fp16")]; + tensor var_269_begin_0 = const()[name = tensor("op_269_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_269_end_0 = const()[name = tensor("op_269_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_269_end_mask_0 = const()[name = tensor("op_269_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_269_cast_fp16 = slice_by_index(begin = var_269_begin_0, end = var_269_end_0, end_mask = var_269_end_mask_0, x = var_194_cast_fp16)[name = tensor("op_269_cast_fp16")]; + tensor var_276_begin_0 = const()[name = tensor("op_276_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_276_end_0 = const()[name = tensor("op_276_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_276_end_mask_0 = const()[name = tensor("op_276_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_276_cast_fp16 = slice_by_index(begin = var_276_begin_0, end = var_276_end_0, end_mask = var_276_end_mask_0, x = var_194_cast_fp16)[name = tensor("op_276_cast_fp16")]; + tensor var_283_begin_0 = const()[name = tensor("op_283_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_283_end_0 = const()[name = tensor("op_283_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_283_end_mask_0 = const()[name = tensor("op_283_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_283_cast_fp16 = slice_by_index(begin = var_283_begin_0, end = var_283_end_0, end_mask = var_283_end_mask_0, x = var_198_cast_fp16)[name = tensor("op_283_cast_fp16")]; + tensor var_290_begin_0 = const()[name = tensor("op_290_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_290_end_0 = const()[name = tensor("op_290_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_290_end_mask_0 = const()[name = tensor("op_290_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_290_cast_fp16 = slice_by_index(begin = var_290_begin_0, end = var_290_end_0, end_mask = var_290_end_mask_0, x = var_198_cast_fp16)[name = tensor("op_290_cast_fp16")]; + tensor var_297_begin_0 = const()[name = tensor("op_297_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_297_end_0 = const()[name = tensor("op_297_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_297_end_mask_0 = const()[name = tensor("op_297_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_297_cast_fp16 = slice_by_index(begin = var_297_begin_0, end = var_297_end_0, end_mask = var_297_end_mask_0, x = var_198_cast_fp16)[name = tensor("op_297_cast_fp16")]; + tensor var_304_begin_0 = const()[name = tensor("op_304_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_304_end_0 = const()[name = tensor("op_304_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_304_end_mask_0 = const()[name = tensor("op_304_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_304_cast_fp16 = slice_by_index(begin = var_304_begin_0, end = var_304_end_0, end_mask = var_304_end_mask_0, x = var_198_cast_fp16)[name = tensor("op_304_cast_fp16")]; + tensor var_311_begin_0 = const()[name = tensor("op_311_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_311_end_0 = const()[name = tensor("op_311_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_311_end_mask_0 = const()[name = tensor("op_311_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_311_cast_fp16 = slice_by_index(begin = var_311_begin_0, end = var_311_end_0, end_mask = var_311_end_mask_0, x = var_202_cast_fp16)[name = tensor("op_311_cast_fp16")]; + tensor var_318_begin_0 = const()[name = tensor("op_318_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_318_end_0 = const()[name = tensor("op_318_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_318_end_mask_0 = const()[name = tensor("op_318_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_318_cast_fp16 = slice_by_index(begin = var_318_begin_0, end = var_318_end_0, end_mask = var_318_end_mask_0, x = var_202_cast_fp16)[name = tensor("op_318_cast_fp16")]; + tensor var_325_begin_0 = const()[name = tensor("op_325_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_325_end_0 = const()[name = tensor("op_325_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_325_end_mask_0 = const()[name = tensor("op_325_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_325_cast_fp16 = slice_by_index(begin = var_325_begin_0, end = var_325_end_0, end_mask = var_325_end_mask_0, x = var_202_cast_fp16)[name = tensor("op_325_cast_fp16")]; + tensor var_332_begin_0 = const()[name = tensor("op_332_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_332_end_0 = const()[name = tensor("op_332_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_332_end_mask_0 = const()[name = tensor("op_332_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_332_cast_fp16 = slice_by_index(begin = var_332_begin_0, end = var_332_end_0, end_mask = var_332_end_mask_0, x = var_202_cast_fp16)[name = tensor("op_332_cast_fp16")]; + tensor var_339_begin_0 = const()[name = tensor("op_339_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_339_end_0 = const()[name = tensor("op_339_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_339_end_mask_0 = const()[name = tensor("op_339_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_339_cast_fp16 = slice_by_index(begin = var_339_begin_0, end = var_339_end_0, end_mask = var_339_end_mask_0, x = var_206_cast_fp16)[name = tensor("op_339_cast_fp16")]; + tensor var_346_begin_0 = const()[name = tensor("op_346_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_346_end_0 = const()[name = tensor("op_346_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_346_end_mask_0 = const()[name = tensor("op_346_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_346_cast_fp16 = slice_by_index(begin = var_346_begin_0, end = var_346_end_0, end_mask = var_346_end_mask_0, x = var_206_cast_fp16)[name = tensor("op_346_cast_fp16")]; + tensor var_353_begin_0 = const()[name = tensor("op_353_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_353_end_0 = const()[name = tensor("op_353_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_353_end_mask_0 = const()[name = tensor("op_353_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_353_cast_fp16 = slice_by_index(begin = var_353_begin_0, end = var_353_end_0, end_mask = var_353_end_mask_0, x = var_206_cast_fp16)[name = tensor("op_353_cast_fp16")]; + tensor var_360_begin_0 = const()[name = tensor("op_360_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_360_end_0 = const()[name = tensor("op_360_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_360_end_mask_0 = const()[name = tensor("op_360_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_360_cast_fp16 = slice_by_index(begin = var_360_begin_0, end = var_360_end_0, end_mask = var_360_end_mask_0, x = var_206_cast_fp16)[name = tensor("op_360_cast_fp16")]; + tensor var_367_begin_0 = const()[name = tensor("op_367_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_367_end_0 = const()[name = tensor("op_367_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_367_end_mask_0 = const()[name = tensor("op_367_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_367_cast_fp16 = slice_by_index(begin = var_367_begin_0, end = var_367_end_0, end_mask = var_367_end_mask_0, x = var_210_cast_fp16)[name = tensor("op_367_cast_fp16")]; + tensor var_374_begin_0 = const()[name = tensor("op_374_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_374_end_0 = const()[name = tensor("op_374_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_374_end_mask_0 = const()[name = tensor("op_374_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_374_cast_fp16 = slice_by_index(begin = var_374_begin_0, end = var_374_end_0, end_mask = var_374_end_mask_0, x = var_210_cast_fp16)[name = tensor("op_374_cast_fp16")]; + tensor var_381_begin_0 = const()[name = tensor("op_381_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_381_end_0 = const()[name = tensor("op_381_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_381_end_mask_0 = const()[name = tensor("op_381_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_381_cast_fp16 = slice_by_index(begin = var_381_begin_0, end = var_381_end_0, end_mask = var_381_end_mask_0, x = var_210_cast_fp16)[name = tensor("op_381_cast_fp16")]; + tensor var_388_begin_0 = const()[name = tensor("op_388_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_388_end_0 = const()[name = tensor("op_388_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_388_end_mask_0 = const()[name = tensor("op_388_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_388_cast_fp16 = slice_by_index(begin = var_388_begin_0, end = var_388_end_0, end_mask = var_388_end_mask_0, x = var_210_cast_fp16)[name = tensor("op_388_cast_fp16")]; + tensor var_395_begin_0 = const()[name = tensor("op_395_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_395_end_0 = const()[name = tensor("op_395_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_395_end_mask_0 = const()[name = tensor("op_395_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_395_cast_fp16 = slice_by_index(begin = var_395_begin_0, end = var_395_end_0, end_mask = var_395_end_mask_0, x = var_214_cast_fp16)[name = tensor("op_395_cast_fp16")]; + tensor var_402_begin_0 = const()[name = tensor("op_402_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_402_end_0 = const()[name = tensor("op_402_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_402_end_mask_0 = const()[name = tensor("op_402_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_402_cast_fp16 = slice_by_index(begin = var_402_begin_0, end = var_402_end_0, end_mask = var_402_end_mask_0, x = var_214_cast_fp16)[name = tensor("op_402_cast_fp16")]; + tensor var_409_begin_0 = const()[name = tensor("op_409_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_409_end_0 = const()[name = tensor("op_409_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_409_end_mask_0 = const()[name = tensor("op_409_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_409_cast_fp16 = slice_by_index(begin = var_409_begin_0, end = var_409_end_0, end_mask = var_409_end_mask_0, x = var_214_cast_fp16)[name = tensor("op_409_cast_fp16")]; + tensor var_416_begin_0 = const()[name = tensor("op_416_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_416_end_0 = const()[name = tensor("op_416_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_416_end_mask_0 = const()[name = tensor("op_416_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_416_cast_fp16 = slice_by_index(begin = var_416_begin_0, end = var_416_end_0, end_mask = var_416_end_mask_0, x = var_214_cast_fp16)[name = tensor("op_416_cast_fp16")]; + tensor var_423_begin_0 = const()[name = tensor("op_423_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_423_end_0 = const()[name = tensor("op_423_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_423_end_mask_0 = const()[name = tensor("op_423_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_423_cast_fp16 = slice_by_index(begin = var_423_begin_0, end = var_423_end_0, end_mask = var_423_end_mask_0, x = var_218_cast_fp16)[name = tensor("op_423_cast_fp16")]; + tensor var_430_begin_0 = const()[name = tensor("op_430_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_430_end_0 = const()[name = tensor("op_430_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_430_end_mask_0 = const()[name = tensor("op_430_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_430_cast_fp16 = slice_by_index(begin = var_430_begin_0, end = var_430_end_0, end_mask = var_430_end_mask_0, x = var_218_cast_fp16)[name = tensor("op_430_cast_fp16")]; + tensor var_437_begin_0 = const()[name = tensor("op_437_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_437_end_0 = const()[name = tensor("op_437_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_437_end_mask_0 = const()[name = tensor("op_437_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_437_cast_fp16 = slice_by_index(begin = var_437_begin_0, end = var_437_end_0, end_mask = var_437_end_mask_0, x = var_218_cast_fp16)[name = tensor("op_437_cast_fp16")]; + tensor var_444_begin_0 = const()[name = tensor("op_444_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_444_end_0 = const()[name = tensor("op_444_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_444_end_mask_0 = const()[name = tensor("op_444_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_444_cast_fp16 = slice_by_index(begin = var_444_begin_0, end = var_444_end_0, end_mask = var_444_end_mask_0, x = var_218_cast_fp16)[name = tensor("op_444_cast_fp16")]; + tensor k_1_perm_0 = const()[name = tensor("k_1_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_449_begin_0 = const()[name = tensor("op_449_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_449_end_0 = const()[name = tensor("op_449_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_449_end_mask_0 = const()[name = tensor("op_449_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_5 = transpose(perm = k_1_perm_0, x = key_1_cast_fp16)[name = tensor("transpose_5")]; + tensor var_449_cast_fp16 = slice_by_index(begin = var_449_begin_0, end = var_449_end_0, end_mask = var_449_end_mask_0, x = transpose_5)[name = tensor("op_449_cast_fp16")]; + tensor var_453_begin_0 = const()[name = tensor("op_453_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_453_end_0 = const()[name = tensor("op_453_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_453_end_mask_0 = const()[name = tensor("op_453_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_453_cast_fp16 = slice_by_index(begin = var_453_begin_0, end = var_453_end_0, end_mask = var_453_end_mask_0, x = transpose_5)[name = tensor("op_453_cast_fp16")]; + tensor var_457_begin_0 = const()[name = tensor("op_457_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_457_end_0 = const()[name = tensor("op_457_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_457_end_mask_0 = const()[name = tensor("op_457_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_457_cast_fp16 = slice_by_index(begin = var_457_begin_0, end = var_457_end_0, end_mask = var_457_end_mask_0, x = transpose_5)[name = tensor("op_457_cast_fp16")]; + tensor var_461_begin_0 = const()[name = tensor("op_461_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_461_end_0 = const()[name = tensor("op_461_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_461_end_mask_0 = const()[name = tensor("op_461_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_461_cast_fp16 = slice_by_index(begin = var_461_begin_0, end = var_461_end_0, end_mask = var_461_end_mask_0, x = transpose_5)[name = tensor("op_461_cast_fp16")]; + tensor var_465_begin_0 = const()[name = tensor("op_465_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_465_end_0 = const()[name = tensor("op_465_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_465_end_mask_0 = const()[name = tensor("op_465_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_465_cast_fp16 = slice_by_index(begin = var_465_begin_0, end = var_465_end_0, end_mask = var_465_end_mask_0, x = transpose_5)[name = tensor("op_465_cast_fp16")]; + tensor var_469_begin_0 = const()[name = tensor("op_469_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_469_end_0 = const()[name = tensor("op_469_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_469_end_mask_0 = const()[name = tensor("op_469_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_469_cast_fp16 = slice_by_index(begin = var_469_begin_0, end = var_469_end_0, end_mask = var_469_end_mask_0, x = transpose_5)[name = tensor("op_469_cast_fp16")]; + tensor var_473_begin_0 = const()[name = tensor("op_473_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_473_end_0 = const()[name = tensor("op_473_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_473_end_mask_0 = const()[name = tensor("op_473_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_473_cast_fp16 = slice_by_index(begin = var_473_begin_0, end = var_473_end_0, end_mask = var_473_end_mask_0, x = transpose_5)[name = tensor("op_473_cast_fp16")]; + tensor var_477_begin_0 = const()[name = tensor("op_477_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_477_end_0 = const()[name = tensor("op_477_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_477_end_mask_0 = const()[name = tensor("op_477_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_477_cast_fp16 = slice_by_index(begin = var_477_begin_0, end = var_477_end_0, end_mask = var_477_end_mask_0, x = transpose_5)[name = tensor("op_477_cast_fp16")]; + tensor var_479_begin_0 = const()[name = tensor("op_479_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_479_end_0 = const()[name = tensor("op_479_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_479_end_mask_0 = const()[name = tensor("op_479_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_479_cast_fp16 = slice_by_index(begin = var_479_begin_0, end = var_479_end_0, end_mask = var_479_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_479_cast_fp16")]; + tensor var_483_begin_0 = const()[name = tensor("op_483_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_483_end_0 = const()[name = tensor("op_483_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_483_end_mask_0 = const()[name = tensor("op_483_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_483_cast_fp16 = slice_by_index(begin = var_483_begin_0, end = var_483_end_0, end_mask = var_483_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_483_cast_fp16")]; + tensor var_487_begin_0 = const()[name = tensor("op_487_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_487_end_0 = const()[name = tensor("op_487_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_487_end_mask_0 = const()[name = tensor("op_487_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_487_cast_fp16 = slice_by_index(begin = var_487_begin_0, end = var_487_end_0, end_mask = var_487_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_487_cast_fp16")]; + tensor var_491_begin_0 = const()[name = tensor("op_491_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_491_end_0 = const()[name = tensor("op_491_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_491_end_mask_0 = const()[name = tensor("op_491_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_491_cast_fp16 = slice_by_index(begin = var_491_begin_0, end = var_491_end_0, end_mask = var_491_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_491_cast_fp16")]; + tensor var_495_begin_0 = const()[name = tensor("op_495_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_495_end_0 = const()[name = tensor("op_495_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_495_end_mask_0 = const()[name = tensor("op_495_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_495_cast_fp16 = slice_by_index(begin = var_495_begin_0, end = var_495_end_0, end_mask = var_495_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_495_cast_fp16")]; + tensor var_499_begin_0 = const()[name = tensor("op_499_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_499_end_0 = const()[name = tensor("op_499_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_499_end_mask_0 = const()[name = tensor("op_499_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_499_cast_fp16 = slice_by_index(begin = var_499_begin_0, end = var_499_end_0, end_mask = var_499_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_499_cast_fp16")]; + tensor var_503_begin_0 = const()[name = tensor("op_503_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_503_end_0 = const()[name = tensor("op_503_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_503_end_mask_0 = const()[name = tensor("op_503_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_503_cast_fp16 = slice_by_index(begin = var_503_begin_0, end = var_503_end_0, end_mask = var_503_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_503_cast_fp16")]; + tensor var_507_begin_0 = const()[name = tensor("op_507_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_507_end_0 = const()[name = tensor("op_507_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_507_end_mask_0 = const()[name = tensor("op_507_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_507_cast_fp16 = slice_by_index(begin = var_507_begin_0, end = var_507_end_0, end_mask = var_507_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_507_cast_fp16")]; + tensor var_511_equation_0 = const()[name = tensor("op_511_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_511_cast_fp16 = einsum(equation = var_511_equation_0, values = (var_449_cast_fp16, var_227_cast_fp16))[name = tensor("op_511_cast_fp16")]; + tensor var_512_to_fp16 = const()[name = tensor("op_512_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1_cast_fp16 = mul(x = var_511_cast_fp16, y = var_512_to_fp16)[name = tensor("aw_chunk_1_cast_fp16")]; + tensor var_515_equation_0 = const()[name = tensor("op_515_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_515_cast_fp16 = einsum(equation = var_515_equation_0, values = (var_449_cast_fp16, var_234_cast_fp16))[name = tensor("op_515_cast_fp16")]; + tensor var_516_to_fp16 = const()[name = tensor("op_516_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_3_cast_fp16 = mul(x = var_515_cast_fp16, y = var_516_to_fp16)[name = tensor("aw_chunk_3_cast_fp16")]; + tensor var_519_equation_0 = const()[name = tensor("op_519_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_519_cast_fp16 = einsum(equation = var_519_equation_0, values = (var_449_cast_fp16, var_241_cast_fp16))[name = tensor("op_519_cast_fp16")]; + tensor var_520_to_fp16 = const()[name = tensor("op_520_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_5_cast_fp16 = mul(x = var_519_cast_fp16, y = var_520_to_fp16)[name = tensor("aw_chunk_5_cast_fp16")]; + tensor var_523_equation_0 = const()[name = tensor("op_523_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_523_cast_fp16 = einsum(equation = var_523_equation_0, values = (var_449_cast_fp16, var_248_cast_fp16))[name = tensor("op_523_cast_fp16")]; + tensor var_524_to_fp16 = const()[name = tensor("op_524_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_7_cast_fp16 = mul(x = var_523_cast_fp16, y = var_524_to_fp16)[name = tensor("aw_chunk_7_cast_fp16")]; + tensor var_527_equation_0 = const()[name = tensor("op_527_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_527_cast_fp16 = einsum(equation = var_527_equation_0, values = (var_453_cast_fp16, var_255_cast_fp16))[name = tensor("op_527_cast_fp16")]; + tensor var_528_to_fp16 = const()[name = tensor("op_528_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_9_cast_fp16 = mul(x = var_527_cast_fp16, y = var_528_to_fp16)[name = tensor("aw_chunk_9_cast_fp16")]; + tensor var_531_equation_0 = const()[name = tensor("op_531_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_531_cast_fp16 = einsum(equation = var_531_equation_0, values = (var_453_cast_fp16, var_262_cast_fp16))[name = tensor("op_531_cast_fp16")]; + tensor var_532_to_fp16 = const()[name = tensor("op_532_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_11_cast_fp16 = mul(x = var_531_cast_fp16, y = var_532_to_fp16)[name = tensor("aw_chunk_11_cast_fp16")]; + tensor var_535_equation_0 = const()[name = tensor("op_535_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_535_cast_fp16 = einsum(equation = var_535_equation_0, values = (var_453_cast_fp16, var_269_cast_fp16))[name = tensor("op_535_cast_fp16")]; + tensor var_536_to_fp16 = const()[name = tensor("op_536_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_13_cast_fp16 = mul(x = var_535_cast_fp16, y = var_536_to_fp16)[name = tensor("aw_chunk_13_cast_fp16")]; + tensor var_539_equation_0 = const()[name = tensor("op_539_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_539_cast_fp16 = einsum(equation = var_539_equation_0, values = (var_453_cast_fp16, var_276_cast_fp16))[name = tensor("op_539_cast_fp16")]; + tensor var_540_to_fp16 = const()[name = tensor("op_540_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_15_cast_fp16 = mul(x = var_539_cast_fp16, y = var_540_to_fp16)[name = tensor("aw_chunk_15_cast_fp16")]; + tensor var_543_equation_0 = const()[name = tensor("op_543_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_543_cast_fp16 = einsum(equation = var_543_equation_0, values = (var_457_cast_fp16, var_283_cast_fp16))[name = tensor("op_543_cast_fp16")]; + tensor var_544_to_fp16 = const()[name = tensor("op_544_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_17_cast_fp16 = mul(x = var_543_cast_fp16, y = var_544_to_fp16)[name = tensor("aw_chunk_17_cast_fp16")]; + tensor var_547_equation_0 = const()[name = tensor("op_547_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_547_cast_fp16 = einsum(equation = var_547_equation_0, values = (var_457_cast_fp16, var_290_cast_fp16))[name = tensor("op_547_cast_fp16")]; + tensor var_548_to_fp16 = const()[name = tensor("op_548_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_19_cast_fp16 = mul(x = var_547_cast_fp16, y = var_548_to_fp16)[name = tensor("aw_chunk_19_cast_fp16")]; + tensor var_551_equation_0 = const()[name = tensor("op_551_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_551_cast_fp16 = einsum(equation = var_551_equation_0, values = (var_457_cast_fp16, var_297_cast_fp16))[name = tensor("op_551_cast_fp16")]; + tensor var_552_to_fp16 = const()[name = tensor("op_552_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_21_cast_fp16 = mul(x = var_551_cast_fp16, y = var_552_to_fp16)[name = tensor("aw_chunk_21_cast_fp16")]; + tensor var_555_equation_0 = const()[name = tensor("op_555_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_555_cast_fp16 = einsum(equation = var_555_equation_0, values = (var_457_cast_fp16, var_304_cast_fp16))[name = tensor("op_555_cast_fp16")]; + tensor var_556_to_fp16 = const()[name = tensor("op_556_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_23_cast_fp16 = mul(x = var_555_cast_fp16, y = var_556_to_fp16)[name = tensor("aw_chunk_23_cast_fp16")]; + tensor var_559_equation_0 = const()[name = tensor("op_559_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_559_cast_fp16 = einsum(equation = var_559_equation_0, values = (var_461_cast_fp16, var_311_cast_fp16))[name = tensor("op_559_cast_fp16")]; + tensor var_560_to_fp16 = const()[name = tensor("op_560_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_25_cast_fp16 = mul(x = var_559_cast_fp16, y = var_560_to_fp16)[name = tensor("aw_chunk_25_cast_fp16")]; + tensor var_563_equation_0 = const()[name = tensor("op_563_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_563_cast_fp16 = einsum(equation = var_563_equation_0, values = (var_461_cast_fp16, var_318_cast_fp16))[name = tensor("op_563_cast_fp16")]; + tensor var_564_to_fp16 = const()[name = tensor("op_564_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_27_cast_fp16 = mul(x = var_563_cast_fp16, y = var_564_to_fp16)[name = tensor("aw_chunk_27_cast_fp16")]; + tensor var_567_equation_0 = const()[name = tensor("op_567_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_567_cast_fp16 = einsum(equation = var_567_equation_0, values = (var_461_cast_fp16, var_325_cast_fp16))[name = tensor("op_567_cast_fp16")]; + tensor var_568_to_fp16 = const()[name = tensor("op_568_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_29_cast_fp16 = mul(x = var_567_cast_fp16, y = var_568_to_fp16)[name = tensor("aw_chunk_29_cast_fp16")]; + tensor var_571_equation_0 = const()[name = tensor("op_571_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_571_cast_fp16 = einsum(equation = var_571_equation_0, values = (var_461_cast_fp16, var_332_cast_fp16))[name = tensor("op_571_cast_fp16")]; + tensor var_572_to_fp16 = const()[name = tensor("op_572_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_31_cast_fp16 = mul(x = var_571_cast_fp16, y = var_572_to_fp16)[name = tensor("aw_chunk_31_cast_fp16")]; + tensor var_575_equation_0 = const()[name = tensor("op_575_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_575_cast_fp16 = einsum(equation = var_575_equation_0, values = (var_465_cast_fp16, var_339_cast_fp16))[name = tensor("op_575_cast_fp16")]; + tensor var_576_to_fp16 = const()[name = tensor("op_576_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_33_cast_fp16 = mul(x = var_575_cast_fp16, y = var_576_to_fp16)[name = tensor("aw_chunk_33_cast_fp16")]; + tensor var_579_equation_0 = const()[name = tensor("op_579_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_579_cast_fp16 = einsum(equation = var_579_equation_0, values = (var_465_cast_fp16, var_346_cast_fp16))[name = tensor("op_579_cast_fp16")]; + tensor var_580_to_fp16 = const()[name = tensor("op_580_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_35_cast_fp16 = mul(x = var_579_cast_fp16, y = var_580_to_fp16)[name = tensor("aw_chunk_35_cast_fp16")]; + tensor var_583_equation_0 = const()[name = tensor("op_583_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_583_cast_fp16 = einsum(equation = var_583_equation_0, values = (var_465_cast_fp16, var_353_cast_fp16))[name = tensor("op_583_cast_fp16")]; + tensor var_584_to_fp16 = const()[name = tensor("op_584_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_37_cast_fp16 = mul(x = var_583_cast_fp16, y = var_584_to_fp16)[name = tensor("aw_chunk_37_cast_fp16")]; + tensor var_587_equation_0 = const()[name = tensor("op_587_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_587_cast_fp16 = einsum(equation = var_587_equation_0, values = (var_465_cast_fp16, var_360_cast_fp16))[name = tensor("op_587_cast_fp16")]; + tensor var_588_to_fp16 = const()[name = tensor("op_588_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_39_cast_fp16 = mul(x = var_587_cast_fp16, y = var_588_to_fp16)[name = tensor("aw_chunk_39_cast_fp16")]; + tensor var_591_equation_0 = const()[name = tensor("op_591_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_591_cast_fp16 = einsum(equation = var_591_equation_0, values = (var_469_cast_fp16, var_367_cast_fp16))[name = tensor("op_591_cast_fp16")]; + tensor var_592_to_fp16 = const()[name = tensor("op_592_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_41_cast_fp16 = mul(x = var_591_cast_fp16, y = var_592_to_fp16)[name = tensor("aw_chunk_41_cast_fp16")]; + tensor var_595_equation_0 = const()[name = tensor("op_595_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_595_cast_fp16 = einsum(equation = var_595_equation_0, values = (var_469_cast_fp16, var_374_cast_fp16))[name = tensor("op_595_cast_fp16")]; + tensor var_596_to_fp16 = const()[name = tensor("op_596_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_43_cast_fp16 = mul(x = var_595_cast_fp16, y = var_596_to_fp16)[name = tensor("aw_chunk_43_cast_fp16")]; + tensor var_599_equation_0 = const()[name = tensor("op_599_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_599_cast_fp16 = einsum(equation = var_599_equation_0, values = (var_469_cast_fp16, var_381_cast_fp16))[name = tensor("op_599_cast_fp16")]; + tensor var_600_to_fp16 = const()[name = tensor("op_600_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_45_cast_fp16 = mul(x = var_599_cast_fp16, y = var_600_to_fp16)[name = tensor("aw_chunk_45_cast_fp16")]; + tensor var_603_equation_0 = const()[name = tensor("op_603_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_603_cast_fp16 = einsum(equation = var_603_equation_0, values = (var_469_cast_fp16, var_388_cast_fp16))[name = tensor("op_603_cast_fp16")]; + tensor var_604_to_fp16 = const()[name = tensor("op_604_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_47_cast_fp16 = mul(x = var_603_cast_fp16, y = var_604_to_fp16)[name = tensor("aw_chunk_47_cast_fp16")]; + tensor var_607_equation_0 = const()[name = tensor("op_607_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_607_cast_fp16 = einsum(equation = var_607_equation_0, values = (var_473_cast_fp16, var_395_cast_fp16))[name = tensor("op_607_cast_fp16")]; + tensor var_608_to_fp16 = const()[name = tensor("op_608_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_49_cast_fp16 = mul(x = var_607_cast_fp16, y = var_608_to_fp16)[name = tensor("aw_chunk_49_cast_fp16")]; + tensor var_611_equation_0 = const()[name = tensor("op_611_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_611_cast_fp16 = einsum(equation = var_611_equation_0, values = (var_473_cast_fp16, var_402_cast_fp16))[name = tensor("op_611_cast_fp16")]; + tensor var_612_to_fp16 = const()[name = tensor("op_612_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_51_cast_fp16 = mul(x = var_611_cast_fp16, y = var_612_to_fp16)[name = tensor("aw_chunk_51_cast_fp16")]; + tensor var_615_equation_0 = const()[name = tensor("op_615_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_615_cast_fp16 = einsum(equation = var_615_equation_0, values = (var_473_cast_fp16, var_409_cast_fp16))[name = tensor("op_615_cast_fp16")]; + tensor var_616_to_fp16 = const()[name = tensor("op_616_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_53_cast_fp16 = mul(x = var_615_cast_fp16, y = var_616_to_fp16)[name = tensor("aw_chunk_53_cast_fp16")]; + tensor var_619_equation_0 = const()[name = tensor("op_619_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_619_cast_fp16 = einsum(equation = var_619_equation_0, values = (var_473_cast_fp16, var_416_cast_fp16))[name = tensor("op_619_cast_fp16")]; + tensor var_620_to_fp16 = const()[name = tensor("op_620_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_55_cast_fp16 = mul(x = var_619_cast_fp16, y = var_620_to_fp16)[name = tensor("aw_chunk_55_cast_fp16")]; + tensor var_623_equation_0 = const()[name = tensor("op_623_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_623_cast_fp16 = einsum(equation = var_623_equation_0, values = (var_477_cast_fp16, var_423_cast_fp16))[name = tensor("op_623_cast_fp16")]; + tensor var_624_to_fp16 = const()[name = tensor("op_624_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_57_cast_fp16 = mul(x = var_623_cast_fp16, y = var_624_to_fp16)[name = tensor("aw_chunk_57_cast_fp16")]; + tensor var_627_equation_0 = const()[name = tensor("op_627_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_627_cast_fp16 = einsum(equation = var_627_equation_0, values = (var_477_cast_fp16, var_430_cast_fp16))[name = tensor("op_627_cast_fp16")]; + tensor var_628_to_fp16 = const()[name = tensor("op_628_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_59_cast_fp16 = mul(x = var_627_cast_fp16, y = var_628_to_fp16)[name = tensor("aw_chunk_59_cast_fp16")]; + tensor var_631_equation_0 = const()[name = tensor("op_631_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_631_cast_fp16 = einsum(equation = var_631_equation_0, values = (var_477_cast_fp16, var_437_cast_fp16))[name = tensor("op_631_cast_fp16")]; + tensor var_632_to_fp16 = const()[name = tensor("op_632_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_61_cast_fp16 = mul(x = var_631_cast_fp16, y = var_632_to_fp16)[name = tensor("aw_chunk_61_cast_fp16")]; + tensor var_635_equation_0 = const()[name = tensor("op_635_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_635_cast_fp16 = einsum(equation = var_635_equation_0, values = (var_477_cast_fp16, var_444_cast_fp16))[name = tensor("op_635_cast_fp16")]; + tensor var_636_to_fp16 = const()[name = tensor("op_636_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_63_cast_fp16 = mul(x = var_635_cast_fp16, y = var_636_to_fp16)[name = tensor("aw_chunk_63_cast_fp16")]; + tensor var_638_cast_fp16 = softmax(axis = var_135, x = aw_chunk_1_cast_fp16)[name = tensor("op_638_cast_fp16")]; + tensor var_639_cast_fp16 = softmax(axis = var_135, x = aw_chunk_3_cast_fp16)[name = tensor("op_639_cast_fp16")]; + tensor var_640_cast_fp16 = softmax(axis = var_135, x = aw_chunk_5_cast_fp16)[name = tensor("op_640_cast_fp16")]; + tensor var_641_cast_fp16 = softmax(axis = var_135, x = aw_chunk_7_cast_fp16)[name = tensor("op_641_cast_fp16")]; + tensor var_642_cast_fp16 = softmax(axis = var_135, x = aw_chunk_9_cast_fp16)[name = tensor("op_642_cast_fp16")]; + tensor var_643_cast_fp16 = softmax(axis = var_135, x = aw_chunk_11_cast_fp16)[name = tensor("op_643_cast_fp16")]; + tensor var_644_cast_fp16 = softmax(axis = var_135, x = aw_chunk_13_cast_fp16)[name = tensor("op_644_cast_fp16")]; + tensor var_645_cast_fp16 = softmax(axis = var_135, x = aw_chunk_15_cast_fp16)[name = tensor("op_645_cast_fp16")]; + tensor var_646_cast_fp16 = softmax(axis = var_135, x = aw_chunk_17_cast_fp16)[name = tensor("op_646_cast_fp16")]; + tensor var_647_cast_fp16 = softmax(axis = var_135, x = aw_chunk_19_cast_fp16)[name = tensor("op_647_cast_fp16")]; + tensor var_648_cast_fp16 = softmax(axis = var_135, x = aw_chunk_21_cast_fp16)[name = tensor("op_648_cast_fp16")]; + tensor var_649_cast_fp16 = softmax(axis = var_135, x = aw_chunk_23_cast_fp16)[name = tensor("op_649_cast_fp16")]; + tensor var_650_cast_fp16 = softmax(axis = var_135, x = aw_chunk_25_cast_fp16)[name = tensor("op_650_cast_fp16")]; + tensor var_651_cast_fp16 = softmax(axis = var_135, x = aw_chunk_27_cast_fp16)[name = tensor("op_651_cast_fp16")]; + tensor var_652_cast_fp16 = softmax(axis = var_135, x = aw_chunk_29_cast_fp16)[name = tensor("op_652_cast_fp16")]; + tensor var_653_cast_fp16 = softmax(axis = var_135, x = aw_chunk_31_cast_fp16)[name = tensor("op_653_cast_fp16")]; + tensor var_654_cast_fp16 = softmax(axis = var_135, x = aw_chunk_33_cast_fp16)[name = tensor("op_654_cast_fp16")]; + tensor var_655_cast_fp16 = softmax(axis = var_135, x = aw_chunk_35_cast_fp16)[name = tensor("op_655_cast_fp16")]; + tensor var_656_cast_fp16 = softmax(axis = var_135, x = aw_chunk_37_cast_fp16)[name = tensor("op_656_cast_fp16")]; + tensor var_657_cast_fp16 = softmax(axis = var_135, x = aw_chunk_39_cast_fp16)[name = tensor("op_657_cast_fp16")]; + tensor var_658_cast_fp16 = softmax(axis = var_135, x = aw_chunk_41_cast_fp16)[name = tensor("op_658_cast_fp16")]; + tensor var_659_cast_fp16 = softmax(axis = var_135, x = aw_chunk_43_cast_fp16)[name = tensor("op_659_cast_fp16")]; + tensor var_660_cast_fp16 = softmax(axis = var_135, x = aw_chunk_45_cast_fp16)[name = tensor("op_660_cast_fp16")]; + tensor var_661_cast_fp16 = softmax(axis = var_135, x = aw_chunk_47_cast_fp16)[name = tensor("op_661_cast_fp16")]; + tensor var_662_cast_fp16 = softmax(axis = var_135, x = aw_chunk_49_cast_fp16)[name = tensor("op_662_cast_fp16")]; + tensor var_663_cast_fp16 = softmax(axis = var_135, x = aw_chunk_51_cast_fp16)[name = tensor("op_663_cast_fp16")]; + tensor var_664_cast_fp16 = softmax(axis = var_135, x = aw_chunk_53_cast_fp16)[name = tensor("op_664_cast_fp16")]; + tensor var_665_cast_fp16 = softmax(axis = var_135, x = aw_chunk_55_cast_fp16)[name = tensor("op_665_cast_fp16")]; + tensor var_666_cast_fp16 = softmax(axis = var_135, x = aw_chunk_57_cast_fp16)[name = tensor("op_666_cast_fp16")]; + tensor var_667_cast_fp16 = softmax(axis = var_135, x = aw_chunk_59_cast_fp16)[name = tensor("op_667_cast_fp16")]; + tensor var_668_cast_fp16 = softmax(axis = var_135, x = aw_chunk_61_cast_fp16)[name = tensor("op_668_cast_fp16")]; + tensor var_669_cast_fp16 = softmax(axis = var_135, x = aw_chunk_63_cast_fp16)[name = tensor("op_669_cast_fp16")]; + tensor var_671_equation_0 = const()[name = tensor("op_671_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_671_cast_fp16 = einsum(equation = var_671_equation_0, values = (var_479_cast_fp16, var_638_cast_fp16))[name = tensor("op_671_cast_fp16")]; + tensor var_673_equation_0 = const()[name = tensor("op_673_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_673_cast_fp16 = einsum(equation = var_673_equation_0, values = (var_479_cast_fp16, var_639_cast_fp16))[name = tensor("op_673_cast_fp16")]; + tensor var_675_equation_0 = const()[name = tensor("op_675_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_675_cast_fp16 = einsum(equation = var_675_equation_0, values = (var_479_cast_fp16, var_640_cast_fp16))[name = tensor("op_675_cast_fp16")]; + tensor var_677_equation_0 = const()[name = tensor("op_677_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_677_cast_fp16 = einsum(equation = var_677_equation_0, values = (var_479_cast_fp16, var_641_cast_fp16))[name = tensor("op_677_cast_fp16")]; + tensor var_679_equation_0 = const()[name = tensor("op_679_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_679_cast_fp16 = einsum(equation = var_679_equation_0, values = (var_483_cast_fp16, var_642_cast_fp16))[name = tensor("op_679_cast_fp16")]; + tensor var_681_equation_0 = const()[name = tensor("op_681_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_681_cast_fp16 = einsum(equation = var_681_equation_0, values = (var_483_cast_fp16, var_643_cast_fp16))[name = tensor("op_681_cast_fp16")]; + tensor var_683_equation_0 = const()[name = tensor("op_683_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_683_cast_fp16 = einsum(equation = var_683_equation_0, values = (var_483_cast_fp16, var_644_cast_fp16))[name = tensor("op_683_cast_fp16")]; + tensor var_685_equation_0 = const()[name = tensor("op_685_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_685_cast_fp16 = einsum(equation = var_685_equation_0, values = (var_483_cast_fp16, var_645_cast_fp16))[name = tensor("op_685_cast_fp16")]; + tensor var_687_equation_0 = const()[name = tensor("op_687_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_687_cast_fp16 = einsum(equation = var_687_equation_0, values = (var_487_cast_fp16, var_646_cast_fp16))[name = tensor("op_687_cast_fp16")]; + tensor var_689_equation_0 = const()[name = tensor("op_689_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_689_cast_fp16 = einsum(equation = var_689_equation_0, values = (var_487_cast_fp16, var_647_cast_fp16))[name = tensor("op_689_cast_fp16")]; + tensor var_691_equation_0 = const()[name = tensor("op_691_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_691_cast_fp16 = einsum(equation = var_691_equation_0, values = (var_487_cast_fp16, var_648_cast_fp16))[name = tensor("op_691_cast_fp16")]; + tensor var_693_equation_0 = const()[name = tensor("op_693_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_693_cast_fp16 = einsum(equation = var_693_equation_0, values = (var_487_cast_fp16, var_649_cast_fp16))[name = tensor("op_693_cast_fp16")]; + tensor var_695_equation_0 = const()[name = tensor("op_695_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_695_cast_fp16 = einsum(equation = var_695_equation_0, values = (var_491_cast_fp16, var_650_cast_fp16))[name = tensor("op_695_cast_fp16")]; + tensor var_697_equation_0 = const()[name = tensor("op_697_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_697_cast_fp16 = einsum(equation = var_697_equation_0, values = (var_491_cast_fp16, var_651_cast_fp16))[name = tensor("op_697_cast_fp16")]; + tensor var_699_equation_0 = const()[name = tensor("op_699_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_699_cast_fp16 = einsum(equation = var_699_equation_0, values = (var_491_cast_fp16, var_652_cast_fp16))[name = tensor("op_699_cast_fp16")]; + tensor var_701_equation_0 = const()[name = tensor("op_701_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_701_cast_fp16 = einsum(equation = var_701_equation_0, values = (var_491_cast_fp16, var_653_cast_fp16))[name = tensor("op_701_cast_fp16")]; + tensor var_703_equation_0 = const()[name = tensor("op_703_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_703_cast_fp16 = einsum(equation = var_703_equation_0, values = (var_495_cast_fp16, var_654_cast_fp16))[name = tensor("op_703_cast_fp16")]; + tensor var_705_equation_0 = const()[name = tensor("op_705_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_705_cast_fp16 = einsum(equation = var_705_equation_0, values = (var_495_cast_fp16, var_655_cast_fp16))[name = tensor("op_705_cast_fp16")]; + tensor var_707_equation_0 = const()[name = tensor("op_707_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_707_cast_fp16 = einsum(equation = var_707_equation_0, values = (var_495_cast_fp16, var_656_cast_fp16))[name = tensor("op_707_cast_fp16")]; + tensor var_709_equation_0 = const()[name = tensor("op_709_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_709_cast_fp16 = einsum(equation = var_709_equation_0, values = (var_495_cast_fp16, var_657_cast_fp16))[name = tensor("op_709_cast_fp16")]; + tensor var_711_equation_0 = const()[name = tensor("op_711_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_711_cast_fp16 = einsum(equation = var_711_equation_0, values = (var_499_cast_fp16, var_658_cast_fp16))[name = tensor("op_711_cast_fp16")]; + tensor var_713_equation_0 = const()[name = tensor("op_713_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_713_cast_fp16 = einsum(equation = var_713_equation_0, values = (var_499_cast_fp16, var_659_cast_fp16))[name = tensor("op_713_cast_fp16")]; + tensor var_715_equation_0 = const()[name = tensor("op_715_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_715_cast_fp16 = einsum(equation = var_715_equation_0, values = (var_499_cast_fp16, var_660_cast_fp16))[name = tensor("op_715_cast_fp16")]; + tensor var_717_equation_0 = const()[name = tensor("op_717_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_717_cast_fp16 = einsum(equation = var_717_equation_0, values = (var_499_cast_fp16, var_661_cast_fp16))[name = tensor("op_717_cast_fp16")]; + tensor var_719_equation_0 = const()[name = tensor("op_719_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_719_cast_fp16 = einsum(equation = var_719_equation_0, values = (var_503_cast_fp16, var_662_cast_fp16))[name = tensor("op_719_cast_fp16")]; + tensor var_721_equation_0 = const()[name = tensor("op_721_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_721_cast_fp16 = einsum(equation = var_721_equation_0, values = (var_503_cast_fp16, var_663_cast_fp16))[name = tensor("op_721_cast_fp16")]; + tensor var_723_equation_0 = const()[name = tensor("op_723_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_723_cast_fp16 = einsum(equation = var_723_equation_0, values = (var_503_cast_fp16, var_664_cast_fp16))[name = tensor("op_723_cast_fp16")]; + tensor var_725_equation_0 = const()[name = tensor("op_725_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_725_cast_fp16 = einsum(equation = var_725_equation_0, values = (var_503_cast_fp16, var_665_cast_fp16))[name = tensor("op_725_cast_fp16")]; + tensor var_727_equation_0 = const()[name = tensor("op_727_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_727_cast_fp16 = einsum(equation = var_727_equation_0, values = (var_507_cast_fp16, var_666_cast_fp16))[name = tensor("op_727_cast_fp16")]; + tensor var_729_equation_0 = const()[name = tensor("op_729_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_729_cast_fp16 = einsum(equation = var_729_equation_0, values = (var_507_cast_fp16, var_667_cast_fp16))[name = tensor("op_729_cast_fp16")]; + tensor var_731_equation_0 = const()[name = tensor("op_731_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_731_cast_fp16 = einsum(equation = var_731_equation_0, values = (var_507_cast_fp16, var_668_cast_fp16))[name = tensor("op_731_cast_fp16")]; + tensor var_733_equation_0 = const()[name = tensor("op_733_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_733_cast_fp16 = einsum(equation = var_733_equation_0, values = (var_507_cast_fp16, var_669_cast_fp16))[name = tensor("op_733_cast_fp16")]; + tensor var_735_interleave_0 = const()[name = tensor("op_735_interleave_0"), val = tensor(false)]; + tensor var_735_cast_fp16 = concat(axis = var_122, interleave = var_735_interleave_0, values = (var_671_cast_fp16, var_673_cast_fp16, var_675_cast_fp16, var_677_cast_fp16))[name = tensor("op_735_cast_fp16")]; + tensor var_737_interleave_0 = const()[name = tensor("op_737_interleave_0"), val = tensor(false)]; + tensor var_737_cast_fp16 = concat(axis = var_122, interleave = var_737_interleave_0, values = (var_679_cast_fp16, var_681_cast_fp16, var_683_cast_fp16, var_685_cast_fp16))[name = tensor("op_737_cast_fp16")]; + tensor var_739_interleave_0 = const()[name = tensor("op_739_interleave_0"), val = tensor(false)]; + tensor var_739_cast_fp16 = concat(axis = var_122, interleave = var_739_interleave_0, values = (var_687_cast_fp16, var_689_cast_fp16, var_691_cast_fp16, var_693_cast_fp16))[name = tensor("op_739_cast_fp16")]; + tensor var_741_interleave_0 = const()[name = tensor("op_741_interleave_0"), val = tensor(false)]; + tensor var_741_cast_fp16 = concat(axis = var_122, interleave = var_741_interleave_0, values = (var_695_cast_fp16, var_697_cast_fp16, var_699_cast_fp16, var_701_cast_fp16))[name = tensor("op_741_cast_fp16")]; + tensor var_743_interleave_0 = const()[name = tensor("op_743_interleave_0"), val = tensor(false)]; + tensor var_743_cast_fp16 = concat(axis = var_122, interleave = var_743_interleave_0, values = (var_703_cast_fp16, var_705_cast_fp16, var_707_cast_fp16, var_709_cast_fp16))[name = tensor("op_743_cast_fp16")]; + tensor var_745_interleave_0 = const()[name = tensor("op_745_interleave_0"), val = tensor(false)]; + tensor var_745_cast_fp16 = concat(axis = var_122, interleave = var_745_interleave_0, values = (var_711_cast_fp16, var_713_cast_fp16, var_715_cast_fp16, var_717_cast_fp16))[name = tensor("op_745_cast_fp16")]; + tensor var_747_interleave_0 = const()[name = tensor("op_747_interleave_0"), val = tensor(false)]; + tensor var_747_cast_fp16 = concat(axis = var_122, interleave = var_747_interleave_0, values = (var_719_cast_fp16, var_721_cast_fp16, var_723_cast_fp16, var_725_cast_fp16))[name = tensor("op_747_cast_fp16")]; + tensor var_749_interleave_0 = const()[name = tensor("op_749_interleave_0"), val = tensor(false)]; + tensor var_749_cast_fp16 = concat(axis = var_122, interleave = var_749_interleave_0, values = (var_727_cast_fp16, var_729_cast_fp16, var_731_cast_fp16, var_733_cast_fp16))[name = tensor("op_749_cast_fp16")]; + tensor input_1_interleave_0 = const()[name = tensor("input_1_interleave_0"), val = tensor(false)]; + tensor input_1_cast_fp16 = concat(axis = var_135, interleave = input_1_interleave_0, values = (var_735_cast_fp16, var_737_cast_fp16, var_739_cast_fp16, var_741_cast_fp16, var_743_cast_fp16, var_745_cast_fp16, var_747_cast_fp16, var_749_cast_fp16))[name = tensor("input_1_cast_fp16")]; + tensor var_754 = const()[name = tensor("op_754"), val = tensor([1, 1])]; + tensor var_756 = const()[name = tensor("op_756"), val = tensor([1, 1])]; + tensor obj_3_pad_type_0 = const()[name = tensor("obj_3_pad_type_0"), val = tensor("custom")]; + tensor obj_3_pad_0 = const()[name = tensor("obj_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4936640)))]; + tensor layers_0_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5460992)))]; + tensor obj_3_cast_fp16 = conv(bias = layers_0_self_attn_o_proj_bias_to_fp16, dilations = var_756, groups = var_135, pad = obj_3_pad_0, pad_type = obj_3_pad_type_0, strides = var_754, weight = layers_0_self_attn_o_proj_weight_to_fp16, x = input_1_cast_fp16)[name = tensor("obj_3_cast_fp16")]; + tensor inputs_3_cast_fp16 = add(x = inputs_1_cast_fp16, y = obj_3_cast_fp16)[name = tensor("inputs_3_cast_fp16")]; + tensor var_762 = const()[name = tensor("op_762"), val = tensor([1])]; + tensor channels_mean_3_cast_fp16 = reduce_mean(axes = var_762, keep_dims = var_136, x = inputs_3_cast_fp16)[name = tensor("channels_mean_3_cast_fp16")]; + tensor zero_mean_3_cast_fp16 = sub(x = inputs_3_cast_fp16, y = channels_mean_3_cast_fp16)[name = tensor("zero_mean_3_cast_fp16")]; + tensor zero_mean_sq_3_cast_fp16 = mul(x = zero_mean_3_cast_fp16, y = zero_mean_3_cast_fp16)[name = tensor("zero_mean_sq_3_cast_fp16")]; + tensor var_766 = const()[name = tensor("op_766"), val = tensor([1])]; + tensor var_767_cast_fp16 = reduce_mean(axes = var_766, keep_dims = var_136, x = zero_mean_sq_3_cast_fp16)[name = tensor("op_767_cast_fp16")]; + tensor var_768_to_fp16 = const()[name = tensor("op_768_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_769_cast_fp16 = add(x = var_767_cast_fp16, y = var_768_to_fp16)[name = tensor("op_769_cast_fp16")]; + tensor denom_3_epsilon_0_to_fp16 = const()[name = tensor("denom_3_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_3_cast_fp16 = rsqrt(epsilon = denom_3_epsilon_0_to_fp16, x = var_769_cast_fp16)[name = tensor("denom_3_cast_fp16")]; + tensor out_3_cast_fp16 = mul(x = zero_mean_3_cast_fp16, y = denom_3_cast_fp16)[name = tensor("out_3_cast_fp16")]; + tensor input_3_gamma_0_to_fp16 = const()[name = tensor("input_3_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5462080)))]; + tensor input_3_beta_0_to_fp16 = const()[name = tensor("input_3_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5463168)))]; + tensor input_3_epsilon_0_to_fp16 = const()[name = tensor("input_3_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_3_cast_fp16 = batch_norm(beta = input_3_beta_0_to_fp16, epsilon = input_3_epsilon_0_to_fp16, gamma = input_3_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_3_cast_fp16)[name = tensor("input_3_cast_fp16")]; + tensor var_780 = const()[name = tensor("op_780"), val = tensor([1, 1])]; + tensor var_782 = const()[name = tensor("op_782"), val = tensor([1, 1])]; + tensor input_5_pad_type_0 = const()[name = tensor("input_5_pad_type_0"), val = tensor("custom")]; + tensor input_5_pad_0 = const()[name = tensor("input_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_fc1_weight_to_fp16 = const()[name = tensor("layers_0_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5464256)))]; + tensor layers_0_fc1_bias_to_fp16 = const()[name = tensor("layers_0_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7561472)))]; + tensor input_5_cast_fp16 = conv(bias = layers_0_fc1_bias_to_fp16, dilations = var_782, groups = var_135, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = var_780, weight = layers_0_fc1_weight_to_fp16, x = input_3_cast_fp16)[name = tensor("input_5_cast_fp16")]; + tensor input_7_mode_0 = const()[name = tensor("input_7_mode_0"), val = tensor("EXACT")]; + tensor input_7_cast_fp16 = gelu(mode = input_7_mode_0, x = input_5_cast_fp16)[name = tensor("input_7_cast_fp16")]; + tensor var_788 = const()[name = tensor("op_788"), val = tensor([1, 1])]; + tensor var_790 = const()[name = tensor("op_790"), val = tensor([1, 1])]; + tensor hidden_states_5_pad_type_0 = const()[name = tensor("hidden_states_5_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_5_pad_0 = const()[name = tensor("hidden_states_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_fc2_weight_to_fp16 = const()[name = tensor("layers_0_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7565632)))]; + tensor layers_0_fc2_bias_to_fp16 = const()[name = tensor("layers_0_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9662848)))]; + tensor hidden_states_5_cast_fp16 = conv(bias = layers_0_fc2_bias_to_fp16, dilations = var_790, groups = var_135, pad = hidden_states_5_pad_0, pad_type = hidden_states_5_pad_type_0, strides = var_788, weight = layers_0_fc2_weight_to_fp16, x = input_7_cast_fp16)[name = tensor("hidden_states_5_cast_fp16")]; + tensor inputs_5_cast_fp16 = add(x = inputs_3_cast_fp16, y = hidden_states_5_cast_fp16)[name = tensor("inputs_5_cast_fp16")]; + tensor var_797 = const()[name = tensor("op_797"), val = tensor(3)]; + tensor var_810 = const()[name = tensor("op_810"), val = tensor(1)]; + tensor var_811 = const()[name = tensor("op_811"), val = tensor(true)]; + tensor var_821 = const()[name = tensor("op_821"), val = tensor([1])]; + tensor channels_mean_5_cast_fp16 = reduce_mean(axes = var_821, keep_dims = var_811, x = inputs_5_cast_fp16)[name = tensor("channels_mean_5_cast_fp16")]; + tensor zero_mean_5_cast_fp16 = sub(x = inputs_5_cast_fp16, y = channels_mean_5_cast_fp16)[name = tensor("zero_mean_5_cast_fp16")]; + tensor zero_mean_sq_5_cast_fp16 = mul(x = zero_mean_5_cast_fp16, y = zero_mean_5_cast_fp16)[name = tensor("zero_mean_sq_5_cast_fp16")]; + tensor var_825 = const()[name = tensor("op_825"), val = tensor([1])]; + tensor var_826_cast_fp16 = reduce_mean(axes = var_825, keep_dims = var_811, x = zero_mean_sq_5_cast_fp16)[name = tensor("op_826_cast_fp16")]; + tensor var_827_to_fp16 = const()[name = tensor("op_827_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_828_cast_fp16 = add(x = var_826_cast_fp16, y = var_827_to_fp16)[name = tensor("op_828_cast_fp16")]; + tensor denom_5_epsilon_0_to_fp16 = const()[name = tensor("denom_5_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_5_cast_fp16 = rsqrt(epsilon = denom_5_epsilon_0_to_fp16, x = var_828_cast_fp16)[name = tensor("denom_5_cast_fp16")]; + tensor out_5_cast_fp16 = mul(x = zero_mean_5_cast_fp16, y = denom_5_cast_fp16)[name = tensor("out_5_cast_fp16")]; + tensor obj_5_gamma_0_to_fp16 = const()[name = tensor("obj_5_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9663936)))]; + tensor obj_5_beta_0_to_fp16 = const()[name = tensor("obj_5_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9665024)))]; + tensor obj_5_epsilon_0_to_fp16 = const()[name = tensor("obj_5_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_5_cast_fp16 = batch_norm(beta = obj_5_beta_0_to_fp16, epsilon = obj_5_epsilon_0_to_fp16, gamma = obj_5_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_5_cast_fp16)[name = tensor("obj_5_cast_fp16")]; + tensor var_843 = const()[name = tensor("op_843"), val = tensor([1, 1])]; + tensor var_845 = const()[name = tensor("op_845"), val = tensor([1, 1])]; + tensor query_3_pad_type_0 = const()[name = tensor("query_3_pad_type_0"), val = tensor("custom")]; + tensor query_3_pad_0 = const()[name = tensor("query_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9666112)))]; + tensor layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10190464)))]; + tensor query_3_cast_fp16 = conv(bias = layers_1_self_attn_q_proj_bias_to_fp16, dilations = var_845, groups = var_810, pad = query_3_pad_0, pad_type = query_3_pad_type_0, strides = var_843, weight = layers_1_self_attn_q_proj_weight_to_fp16, x = obj_5_cast_fp16)[name = tensor("query_3_cast_fp16")]; + tensor var_849 = const()[name = tensor("op_849"), val = tensor([1, 1])]; + tensor var_851 = const()[name = tensor("op_851"), val = tensor([1, 1])]; + tensor key_3_pad_type_0 = const()[name = tensor("key_3_pad_type_0"), val = tensor("custom")]; + tensor key_3_pad_0 = const()[name = tensor("key_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10191552)))]; + tensor key_3_cast_fp16 = conv(dilations = var_851, groups = var_810, pad = key_3_pad_0, pad_type = key_3_pad_type_0, strides = var_849, weight = layers_1_self_attn_k_proj_weight_to_fp16, x = obj_5_cast_fp16)[name = tensor("key_3_cast_fp16")]; + tensor var_856 = const()[name = tensor("op_856"), val = tensor([1, 1])]; + tensor var_858 = const()[name = tensor("op_858"), val = tensor([1, 1])]; + tensor value_3_pad_type_0 = const()[name = tensor("value_3_pad_type_0"), val = tensor("custom")]; + tensor value_3_pad_0 = const()[name = tensor("value_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10715904)))]; + tensor layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11240256)))]; + tensor value_3_cast_fp16 = conv(bias = layers_1_self_attn_v_proj_bias_to_fp16, dilations = var_858, groups = var_810, pad = value_3_pad_0, pad_type = value_3_pad_type_0, strides = var_856, weight = layers_1_self_attn_v_proj_weight_to_fp16, x = obj_5_cast_fp16)[name = tensor("value_3_cast_fp16")]; + tensor var_865_begin_0 = const()[name = tensor("op_865_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_865_end_0 = const()[name = tensor("op_865_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_865_end_mask_0 = const()[name = tensor("op_865_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_865_cast_fp16 = slice_by_index(begin = var_865_begin_0, end = var_865_end_0, end_mask = var_865_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_865_cast_fp16")]; + tensor var_869_begin_0 = const()[name = tensor("op_869_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_869_end_0 = const()[name = tensor("op_869_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_869_end_mask_0 = const()[name = tensor("op_869_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_869_cast_fp16 = slice_by_index(begin = var_869_begin_0, end = var_869_end_0, end_mask = var_869_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_869_cast_fp16")]; + tensor var_873_begin_0 = const()[name = tensor("op_873_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_873_end_0 = const()[name = tensor("op_873_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_873_end_mask_0 = const()[name = tensor("op_873_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_873_cast_fp16 = slice_by_index(begin = var_873_begin_0, end = var_873_end_0, end_mask = var_873_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_873_cast_fp16")]; + tensor var_877_begin_0 = const()[name = tensor("op_877_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_877_end_0 = const()[name = tensor("op_877_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_877_end_mask_0 = const()[name = tensor("op_877_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_877_cast_fp16 = slice_by_index(begin = var_877_begin_0, end = var_877_end_0, end_mask = var_877_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_877_cast_fp16")]; + tensor var_881_begin_0 = const()[name = tensor("op_881_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_881_end_0 = const()[name = tensor("op_881_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_881_end_mask_0 = const()[name = tensor("op_881_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_881_cast_fp16 = slice_by_index(begin = var_881_begin_0, end = var_881_end_0, end_mask = var_881_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_881_cast_fp16")]; + tensor var_885_begin_0 = const()[name = tensor("op_885_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_885_end_0 = const()[name = tensor("op_885_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_885_end_mask_0 = const()[name = tensor("op_885_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_885_cast_fp16 = slice_by_index(begin = var_885_begin_0, end = var_885_end_0, end_mask = var_885_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_885_cast_fp16")]; + tensor var_889_begin_0 = const()[name = tensor("op_889_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_889_end_0 = const()[name = tensor("op_889_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_889_end_mask_0 = const()[name = tensor("op_889_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_889_cast_fp16 = slice_by_index(begin = var_889_begin_0, end = var_889_end_0, end_mask = var_889_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_889_cast_fp16")]; + tensor var_893_begin_0 = const()[name = tensor("op_893_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_893_end_0 = const()[name = tensor("op_893_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_893_end_mask_0 = const()[name = tensor("op_893_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_893_cast_fp16 = slice_by_index(begin = var_893_begin_0, end = var_893_end_0, end_mask = var_893_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_893_cast_fp16")]; + tensor var_902_begin_0 = const()[name = tensor("op_902_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_902_end_0 = const()[name = tensor("op_902_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_902_end_mask_0 = const()[name = tensor("op_902_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_902_cast_fp16 = slice_by_index(begin = var_902_begin_0, end = var_902_end_0, end_mask = var_902_end_mask_0, x = var_865_cast_fp16)[name = tensor("op_902_cast_fp16")]; + tensor var_909_begin_0 = const()[name = tensor("op_909_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_909_end_0 = const()[name = tensor("op_909_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_909_end_mask_0 = const()[name = tensor("op_909_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_909_cast_fp16 = slice_by_index(begin = var_909_begin_0, end = var_909_end_0, end_mask = var_909_end_mask_0, x = var_865_cast_fp16)[name = tensor("op_909_cast_fp16")]; + tensor var_916_begin_0 = const()[name = tensor("op_916_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_916_end_0 = const()[name = tensor("op_916_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_916_end_mask_0 = const()[name = tensor("op_916_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_916_cast_fp16 = slice_by_index(begin = var_916_begin_0, end = var_916_end_0, end_mask = var_916_end_mask_0, x = var_865_cast_fp16)[name = tensor("op_916_cast_fp16")]; + tensor var_923_begin_0 = const()[name = tensor("op_923_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_923_end_0 = const()[name = tensor("op_923_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_923_end_mask_0 = const()[name = tensor("op_923_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_923_cast_fp16 = slice_by_index(begin = var_923_begin_0, end = var_923_end_0, end_mask = var_923_end_mask_0, x = var_865_cast_fp16)[name = tensor("op_923_cast_fp16")]; + tensor var_930_begin_0 = const()[name = tensor("op_930_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_930_end_0 = const()[name = tensor("op_930_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_930_end_mask_0 = const()[name = tensor("op_930_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_930_cast_fp16 = slice_by_index(begin = var_930_begin_0, end = var_930_end_0, end_mask = var_930_end_mask_0, x = var_869_cast_fp16)[name = tensor("op_930_cast_fp16")]; + tensor var_937_begin_0 = const()[name = tensor("op_937_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_937_end_0 = const()[name = tensor("op_937_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_937_end_mask_0 = const()[name = tensor("op_937_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_937_cast_fp16 = slice_by_index(begin = var_937_begin_0, end = var_937_end_0, end_mask = var_937_end_mask_0, x = var_869_cast_fp16)[name = tensor("op_937_cast_fp16")]; + tensor var_944_begin_0 = const()[name = tensor("op_944_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_944_end_0 = const()[name = tensor("op_944_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_944_end_mask_0 = const()[name = tensor("op_944_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_944_cast_fp16 = slice_by_index(begin = var_944_begin_0, end = var_944_end_0, end_mask = var_944_end_mask_0, x = var_869_cast_fp16)[name = tensor("op_944_cast_fp16")]; + tensor var_951_begin_0 = const()[name = tensor("op_951_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_951_end_0 = const()[name = tensor("op_951_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_951_end_mask_0 = const()[name = tensor("op_951_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_951_cast_fp16 = slice_by_index(begin = var_951_begin_0, end = var_951_end_0, end_mask = var_951_end_mask_0, x = var_869_cast_fp16)[name = tensor("op_951_cast_fp16")]; + tensor var_958_begin_0 = const()[name = tensor("op_958_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_958_end_0 = const()[name = tensor("op_958_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_958_end_mask_0 = const()[name = tensor("op_958_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_958_cast_fp16 = slice_by_index(begin = var_958_begin_0, end = var_958_end_0, end_mask = var_958_end_mask_0, x = var_873_cast_fp16)[name = tensor("op_958_cast_fp16")]; + tensor var_965_begin_0 = const()[name = tensor("op_965_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_965_end_0 = const()[name = tensor("op_965_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_965_end_mask_0 = const()[name = tensor("op_965_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_965_cast_fp16 = slice_by_index(begin = var_965_begin_0, end = var_965_end_0, end_mask = var_965_end_mask_0, x = var_873_cast_fp16)[name = tensor("op_965_cast_fp16")]; + tensor var_972_begin_0 = const()[name = tensor("op_972_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_972_end_0 = const()[name = tensor("op_972_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_972_end_mask_0 = const()[name = tensor("op_972_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_972_cast_fp16 = slice_by_index(begin = var_972_begin_0, end = var_972_end_0, end_mask = var_972_end_mask_0, x = var_873_cast_fp16)[name = tensor("op_972_cast_fp16")]; + tensor var_979_begin_0 = const()[name = tensor("op_979_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_979_end_0 = const()[name = tensor("op_979_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_979_end_mask_0 = const()[name = tensor("op_979_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_979_cast_fp16 = slice_by_index(begin = var_979_begin_0, end = var_979_end_0, end_mask = var_979_end_mask_0, x = var_873_cast_fp16)[name = tensor("op_979_cast_fp16")]; + tensor var_986_begin_0 = const()[name = tensor("op_986_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_986_end_0 = const()[name = tensor("op_986_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_986_end_mask_0 = const()[name = tensor("op_986_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_986_cast_fp16 = slice_by_index(begin = var_986_begin_0, end = var_986_end_0, end_mask = var_986_end_mask_0, x = var_877_cast_fp16)[name = tensor("op_986_cast_fp16")]; + tensor var_993_begin_0 = const()[name = tensor("op_993_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_993_end_0 = const()[name = tensor("op_993_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_993_end_mask_0 = const()[name = tensor("op_993_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_993_cast_fp16 = slice_by_index(begin = var_993_begin_0, end = var_993_end_0, end_mask = var_993_end_mask_0, x = var_877_cast_fp16)[name = tensor("op_993_cast_fp16")]; + tensor var_1000_begin_0 = const()[name = tensor("op_1000_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1000_end_0 = const()[name = tensor("op_1000_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1000_end_mask_0 = const()[name = tensor("op_1000_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1000_cast_fp16 = slice_by_index(begin = var_1000_begin_0, end = var_1000_end_0, end_mask = var_1000_end_mask_0, x = var_877_cast_fp16)[name = tensor("op_1000_cast_fp16")]; + tensor var_1007_begin_0 = const()[name = tensor("op_1007_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1007_end_0 = const()[name = tensor("op_1007_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1007_end_mask_0 = const()[name = tensor("op_1007_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1007_cast_fp16 = slice_by_index(begin = var_1007_begin_0, end = var_1007_end_0, end_mask = var_1007_end_mask_0, x = var_877_cast_fp16)[name = tensor("op_1007_cast_fp16")]; + tensor var_1014_begin_0 = const()[name = tensor("op_1014_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1014_end_0 = const()[name = tensor("op_1014_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1014_end_mask_0 = const()[name = tensor("op_1014_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1014_cast_fp16 = slice_by_index(begin = var_1014_begin_0, end = var_1014_end_0, end_mask = var_1014_end_mask_0, x = var_881_cast_fp16)[name = tensor("op_1014_cast_fp16")]; + tensor var_1021_begin_0 = const()[name = tensor("op_1021_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1021_end_0 = const()[name = tensor("op_1021_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1021_end_mask_0 = const()[name = tensor("op_1021_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1021_cast_fp16 = slice_by_index(begin = var_1021_begin_0, end = var_1021_end_0, end_mask = var_1021_end_mask_0, x = var_881_cast_fp16)[name = tensor("op_1021_cast_fp16")]; + tensor var_1028_begin_0 = const()[name = tensor("op_1028_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1028_end_0 = const()[name = tensor("op_1028_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1028_end_mask_0 = const()[name = tensor("op_1028_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1028_cast_fp16 = slice_by_index(begin = var_1028_begin_0, end = var_1028_end_0, end_mask = var_1028_end_mask_0, x = var_881_cast_fp16)[name = tensor("op_1028_cast_fp16")]; + tensor var_1035_begin_0 = const()[name = tensor("op_1035_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1035_end_0 = const()[name = tensor("op_1035_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1035_end_mask_0 = const()[name = tensor("op_1035_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1035_cast_fp16 = slice_by_index(begin = var_1035_begin_0, end = var_1035_end_0, end_mask = var_1035_end_mask_0, x = var_881_cast_fp16)[name = tensor("op_1035_cast_fp16")]; + tensor var_1042_begin_0 = const()[name = tensor("op_1042_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1042_end_0 = const()[name = tensor("op_1042_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1042_end_mask_0 = const()[name = tensor("op_1042_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1042_cast_fp16 = slice_by_index(begin = var_1042_begin_0, end = var_1042_end_0, end_mask = var_1042_end_mask_0, x = var_885_cast_fp16)[name = tensor("op_1042_cast_fp16")]; + tensor var_1049_begin_0 = const()[name = tensor("op_1049_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1049_end_0 = const()[name = tensor("op_1049_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1049_end_mask_0 = const()[name = tensor("op_1049_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1049_cast_fp16 = slice_by_index(begin = var_1049_begin_0, end = var_1049_end_0, end_mask = var_1049_end_mask_0, x = var_885_cast_fp16)[name = tensor("op_1049_cast_fp16")]; + tensor var_1056_begin_0 = const()[name = tensor("op_1056_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1056_end_0 = const()[name = tensor("op_1056_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1056_end_mask_0 = const()[name = tensor("op_1056_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1056_cast_fp16 = slice_by_index(begin = var_1056_begin_0, end = var_1056_end_0, end_mask = var_1056_end_mask_0, x = var_885_cast_fp16)[name = tensor("op_1056_cast_fp16")]; + tensor var_1063_begin_0 = const()[name = tensor("op_1063_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1063_end_0 = const()[name = tensor("op_1063_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1063_end_mask_0 = const()[name = tensor("op_1063_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1063_cast_fp16 = slice_by_index(begin = var_1063_begin_0, end = var_1063_end_0, end_mask = var_1063_end_mask_0, x = var_885_cast_fp16)[name = tensor("op_1063_cast_fp16")]; + tensor var_1070_begin_0 = const()[name = tensor("op_1070_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1070_end_0 = const()[name = tensor("op_1070_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1070_end_mask_0 = const()[name = tensor("op_1070_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1070_cast_fp16 = slice_by_index(begin = var_1070_begin_0, end = var_1070_end_0, end_mask = var_1070_end_mask_0, x = var_889_cast_fp16)[name = tensor("op_1070_cast_fp16")]; + tensor var_1077_begin_0 = const()[name = tensor("op_1077_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1077_end_0 = const()[name = tensor("op_1077_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1077_end_mask_0 = const()[name = tensor("op_1077_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1077_cast_fp16 = slice_by_index(begin = var_1077_begin_0, end = var_1077_end_0, end_mask = var_1077_end_mask_0, x = var_889_cast_fp16)[name = tensor("op_1077_cast_fp16")]; + tensor var_1084_begin_0 = const()[name = tensor("op_1084_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1084_end_0 = const()[name = tensor("op_1084_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1084_end_mask_0 = const()[name = tensor("op_1084_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1084_cast_fp16 = slice_by_index(begin = var_1084_begin_0, end = var_1084_end_0, end_mask = var_1084_end_mask_0, x = var_889_cast_fp16)[name = tensor("op_1084_cast_fp16")]; + tensor var_1091_begin_0 = const()[name = tensor("op_1091_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1091_end_0 = const()[name = tensor("op_1091_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1091_end_mask_0 = const()[name = tensor("op_1091_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1091_cast_fp16 = slice_by_index(begin = var_1091_begin_0, end = var_1091_end_0, end_mask = var_1091_end_mask_0, x = var_889_cast_fp16)[name = tensor("op_1091_cast_fp16")]; + tensor var_1098_begin_0 = const()[name = tensor("op_1098_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1098_end_0 = const()[name = tensor("op_1098_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1098_end_mask_0 = const()[name = tensor("op_1098_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1098_cast_fp16 = slice_by_index(begin = var_1098_begin_0, end = var_1098_end_0, end_mask = var_1098_end_mask_0, x = var_893_cast_fp16)[name = tensor("op_1098_cast_fp16")]; + tensor var_1105_begin_0 = const()[name = tensor("op_1105_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1105_end_0 = const()[name = tensor("op_1105_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1105_end_mask_0 = const()[name = tensor("op_1105_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1105_cast_fp16 = slice_by_index(begin = var_1105_begin_0, end = var_1105_end_0, end_mask = var_1105_end_mask_0, x = var_893_cast_fp16)[name = tensor("op_1105_cast_fp16")]; + tensor var_1112_begin_0 = const()[name = tensor("op_1112_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1112_end_0 = const()[name = tensor("op_1112_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1112_end_mask_0 = const()[name = tensor("op_1112_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1112_cast_fp16 = slice_by_index(begin = var_1112_begin_0, end = var_1112_end_0, end_mask = var_1112_end_mask_0, x = var_893_cast_fp16)[name = tensor("op_1112_cast_fp16")]; + tensor var_1119_begin_0 = const()[name = tensor("op_1119_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1119_end_0 = const()[name = tensor("op_1119_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1119_end_mask_0 = const()[name = tensor("op_1119_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1119_cast_fp16 = slice_by_index(begin = var_1119_begin_0, end = var_1119_end_0, end_mask = var_1119_end_mask_0, x = var_893_cast_fp16)[name = tensor("op_1119_cast_fp16")]; + tensor k_3_perm_0 = const()[name = tensor("k_3_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_1124_begin_0 = const()[name = tensor("op_1124_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1124_end_0 = const()[name = tensor("op_1124_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_1124_end_mask_0 = const()[name = tensor("op_1124_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_4 = transpose(perm = k_3_perm_0, x = key_3_cast_fp16)[name = tensor("transpose_4")]; + tensor var_1124_cast_fp16 = slice_by_index(begin = var_1124_begin_0, end = var_1124_end_0, end_mask = var_1124_end_mask_0, x = transpose_4)[name = tensor("op_1124_cast_fp16")]; + tensor var_1128_begin_0 = const()[name = tensor("op_1128_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_1128_end_0 = const()[name = tensor("op_1128_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_1128_end_mask_0 = const()[name = tensor("op_1128_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1128_cast_fp16 = slice_by_index(begin = var_1128_begin_0, end = var_1128_end_0, end_mask = var_1128_end_mask_0, x = transpose_4)[name = tensor("op_1128_cast_fp16")]; + tensor var_1132_begin_0 = const()[name = tensor("op_1132_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_1132_end_0 = const()[name = tensor("op_1132_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_1132_end_mask_0 = const()[name = tensor("op_1132_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1132_cast_fp16 = slice_by_index(begin = var_1132_begin_0, end = var_1132_end_0, end_mask = var_1132_end_mask_0, x = transpose_4)[name = tensor("op_1132_cast_fp16")]; + tensor var_1136_begin_0 = const()[name = tensor("op_1136_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_1136_end_0 = const()[name = tensor("op_1136_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_1136_end_mask_0 = const()[name = tensor("op_1136_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1136_cast_fp16 = slice_by_index(begin = var_1136_begin_0, end = var_1136_end_0, end_mask = var_1136_end_mask_0, x = transpose_4)[name = tensor("op_1136_cast_fp16")]; + tensor var_1140_begin_0 = const()[name = tensor("op_1140_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_1140_end_0 = const()[name = tensor("op_1140_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_1140_end_mask_0 = const()[name = tensor("op_1140_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1140_cast_fp16 = slice_by_index(begin = var_1140_begin_0, end = var_1140_end_0, end_mask = var_1140_end_mask_0, x = transpose_4)[name = tensor("op_1140_cast_fp16")]; + tensor var_1144_begin_0 = const()[name = tensor("op_1144_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_1144_end_0 = const()[name = tensor("op_1144_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_1144_end_mask_0 = const()[name = tensor("op_1144_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1144_cast_fp16 = slice_by_index(begin = var_1144_begin_0, end = var_1144_end_0, end_mask = var_1144_end_mask_0, x = transpose_4)[name = tensor("op_1144_cast_fp16")]; + tensor var_1148_begin_0 = const()[name = tensor("op_1148_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_1148_end_0 = const()[name = tensor("op_1148_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_1148_end_mask_0 = const()[name = tensor("op_1148_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1148_cast_fp16 = slice_by_index(begin = var_1148_begin_0, end = var_1148_end_0, end_mask = var_1148_end_mask_0, x = transpose_4)[name = tensor("op_1148_cast_fp16")]; + tensor var_1152_begin_0 = const()[name = tensor("op_1152_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_1152_end_0 = const()[name = tensor("op_1152_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_1152_end_mask_0 = const()[name = tensor("op_1152_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1152_cast_fp16 = slice_by_index(begin = var_1152_begin_0, end = var_1152_end_0, end_mask = var_1152_end_mask_0, x = transpose_4)[name = tensor("op_1152_cast_fp16")]; + tensor var_1154_begin_0 = const()[name = tensor("op_1154_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1154_end_0 = const()[name = tensor("op_1154_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1154_end_mask_0 = const()[name = tensor("op_1154_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1154_cast_fp16 = slice_by_index(begin = var_1154_begin_0, end = var_1154_end_0, end_mask = var_1154_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1154_cast_fp16")]; + tensor var_1158_begin_0 = const()[name = tensor("op_1158_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_1158_end_0 = const()[name = tensor("op_1158_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_1158_end_mask_0 = const()[name = tensor("op_1158_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1158_cast_fp16 = slice_by_index(begin = var_1158_begin_0, end = var_1158_end_0, end_mask = var_1158_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1158_cast_fp16")]; + tensor var_1162_begin_0 = const()[name = tensor("op_1162_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_1162_end_0 = const()[name = tensor("op_1162_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_1162_end_mask_0 = const()[name = tensor("op_1162_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1162_cast_fp16 = slice_by_index(begin = var_1162_begin_0, end = var_1162_end_0, end_mask = var_1162_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1162_cast_fp16")]; + tensor var_1166_begin_0 = const()[name = tensor("op_1166_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_1166_end_0 = const()[name = tensor("op_1166_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_1166_end_mask_0 = const()[name = tensor("op_1166_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1166_cast_fp16 = slice_by_index(begin = var_1166_begin_0, end = var_1166_end_0, end_mask = var_1166_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1166_cast_fp16")]; + tensor var_1170_begin_0 = const()[name = tensor("op_1170_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_1170_end_0 = const()[name = tensor("op_1170_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_1170_end_mask_0 = const()[name = tensor("op_1170_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1170_cast_fp16 = slice_by_index(begin = var_1170_begin_0, end = var_1170_end_0, end_mask = var_1170_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1170_cast_fp16")]; + tensor var_1174_begin_0 = const()[name = tensor("op_1174_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_1174_end_0 = const()[name = tensor("op_1174_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_1174_end_mask_0 = const()[name = tensor("op_1174_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1174_cast_fp16 = slice_by_index(begin = var_1174_begin_0, end = var_1174_end_0, end_mask = var_1174_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1174_cast_fp16")]; + tensor var_1178_begin_0 = const()[name = tensor("op_1178_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_1178_end_0 = const()[name = tensor("op_1178_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_1178_end_mask_0 = const()[name = tensor("op_1178_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1178_cast_fp16 = slice_by_index(begin = var_1178_begin_0, end = var_1178_end_0, end_mask = var_1178_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1178_cast_fp16")]; + tensor var_1182_begin_0 = const()[name = tensor("op_1182_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_1182_end_0 = const()[name = tensor("op_1182_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_1182_end_mask_0 = const()[name = tensor("op_1182_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1182_cast_fp16 = slice_by_index(begin = var_1182_begin_0, end = var_1182_end_0, end_mask = var_1182_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1182_cast_fp16")]; + tensor var_1186_equation_0 = const()[name = tensor("op_1186_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1186_cast_fp16 = einsum(equation = var_1186_equation_0, values = (var_1124_cast_fp16, var_902_cast_fp16))[name = tensor("op_1186_cast_fp16")]; + tensor var_1187_to_fp16 = const()[name = tensor("op_1187_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_65_cast_fp16 = mul(x = var_1186_cast_fp16, y = var_1187_to_fp16)[name = tensor("aw_chunk_65_cast_fp16")]; + tensor var_1190_equation_0 = const()[name = tensor("op_1190_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1190_cast_fp16 = einsum(equation = var_1190_equation_0, values = (var_1124_cast_fp16, var_909_cast_fp16))[name = tensor("op_1190_cast_fp16")]; + tensor var_1191_to_fp16 = const()[name = tensor("op_1191_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_67_cast_fp16 = mul(x = var_1190_cast_fp16, y = var_1191_to_fp16)[name = tensor("aw_chunk_67_cast_fp16")]; + tensor var_1194_equation_0 = const()[name = tensor("op_1194_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1194_cast_fp16 = einsum(equation = var_1194_equation_0, values = (var_1124_cast_fp16, var_916_cast_fp16))[name = tensor("op_1194_cast_fp16")]; + tensor var_1195_to_fp16 = const()[name = tensor("op_1195_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_69_cast_fp16 = mul(x = var_1194_cast_fp16, y = var_1195_to_fp16)[name = tensor("aw_chunk_69_cast_fp16")]; + tensor var_1198_equation_0 = const()[name = tensor("op_1198_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1198_cast_fp16 = einsum(equation = var_1198_equation_0, values = (var_1124_cast_fp16, var_923_cast_fp16))[name = tensor("op_1198_cast_fp16")]; + tensor var_1199_to_fp16 = const()[name = tensor("op_1199_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_71_cast_fp16 = mul(x = var_1198_cast_fp16, y = var_1199_to_fp16)[name = tensor("aw_chunk_71_cast_fp16")]; + tensor var_1202_equation_0 = const()[name = tensor("op_1202_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1202_cast_fp16 = einsum(equation = var_1202_equation_0, values = (var_1128_cast_fp16, var_930_cast_fp16))[name = tensor("op_1202_cast_fp16")]; + tensor var_1203_to_fp16 = const()[name = tensor("op_1203_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_73_cast_fp16 = mul(x = var_1202_cast_fp16, y = var_1203_to_fp16)[name = tensor("aw_chunk_73_cast_fp16")]; + tensor var_1206_equation_0 = const()[name = tensor("op_1206_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1206_cast_fp16 = einsum(equation = var_1206_equation_0, values = (var_1128_cast_fp16, var_937_cast_fp16))[name = tensor("op_1206_cast_fp16")]; + tensor var_1207_to_fp16 = const()[name = tensor("op_1207_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_75_cast_fp16 = mul(x = var_1206_cast_fp16, y = var_1207_to_fp16)[name = tensor("aw_chunk_75_cast_fp16")]; + tensor var_1210_equation_0 = const()[name = tensor("op_1210_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1210_cast_fp16 = einsum(equation = var_1210_equation_0, values = (var_1128_cast_fp16, var_944_cast_fp16))[name = tensor("op_1210_cast_fp16")]; + tensor var_1211_to_fp16 = const()[name = tensor("op_1211_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_77_cast_fp16 = mul(x = var_1210_cast_fp16, y = var_1211_to_fp16)[name = tensor("aw_chunk_77_cast_fp16")]; + tensor var_1214_equation_0 = const()[name = tensor("op_1214_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1214_cast_fp16 = einsum(equation = var_1214_equation_0, values = (var_1128_cast_fp16, var_951_cast_fp16))[name = tensor("op_1214_cast_fp16")]; + tensor var_1215_to_fp16 = const()[name = tensor("op_1215_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_79_cast_fp16 = mul(x = var_1214_cast_fp16, y = var_1215_to_fp16)[name = tensor("aw_chunk_79_cast_fp16")]; + tensor var_1218_equation_0 = const()[name = tensor("op_1218_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1218_cast_fp16 = einsum(equation = var_1218_equation_0, values = (var_1132_cast_fp16, var_958_cast_fp16))[name = tensor("op_1218_cast_fp16")]; + tensor var_1219_to_fp16 = const()[name = tensor("op_1219_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_81_cast_fp16 = mul(x = var_1218_cast_fp16, y = var_1219_to_fp16)[name = tensor("aw_chunk_81_cast_fp16")]; + tensor var_1222_equation_0 = const()[name = tensor("op_1222_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1222_cast_fp16 = einsum(equation = var_1222_equation_0, values = (var_1132_cast_fp16, var_965_cast_fp16))[name = tensor("op_1222_cast_fp16")]; + tensor var_1223_to_fp16 = const()[name = tensor("op_1223_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_83_cast_fp16 = mul(x = var_1222_cast_fp16, y = var_1223_to_fp16)[name = tensor("aw_chunk_83_cast_fp16")]; + tensor var_1226_equation_0 = const()[name = tensor("op_1226_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1226_cast_fp16 = einsum(equation = var_1226_equation_0, values = (var_1132_cast_fp16, var_972_cast_fp16))[name = tensor("op_1226_cast_fp16")]; + tensor var_1227_to_fp16 = const()[name = tensor("op_1227_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_85_cast_fp16 = mul(x = var_1226_cast_fp16, y = var_1227_to_fp16)[name = tensor("aw_chunk_85_cast_fp16")]; + tensor var_1230_equation_0 = const()[name = tensor("op_1230_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1230_cast_fp16 = einsum(equation = var_1230_equation_0, values = (var_1132_cast_fp16, var_979_cast_fp16))[name = tensor("op_1230_cast_fp16")]; + tensor var_1231_to_fp16 = const()[name = tensor("op_1231_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_87_cast_fp16 = mul(x = var_1230_cast_fp16, y = var_1231_to_fp16)[name = tensor("aw_chunk_87_cast_fp16")]; + tensor var_1234_equation_0 = const()[name = tensor("op_1234_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1234_cast_fp16 = einsum(equation = var_1234_equation_0, values = (var_1136_cast_fp16, var_986_cast_fp16))[name = tensor("op_1234_cast_fp16")]; + tensor var_1235_to_fp16 = const()[name = tensor("op_1235_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_89_cast_fp16 = mul(x = var_1234_cast_fp16, y = var_1235_to_fp16)[name = tensor("aw_chunk_89_cast_fp16")]; + tensor var_1238_equation_0 = const()[name = tensor("op_1238_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1238_cast_fp16 = einsum(equation = var_1238_equation_0, values = (var_1136_cast_fp16, var_993_cast_fp16))[name = tensor("op_1238_cast_fp16")]; + tensor var_1239_to_fp16 = const()[name = tensor("op_1239_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_91_cast_fp16 = mul(x = var_1238_cast_fp16, y = var_1239_to_fp16)[name = tensor("aw_chunk_91_cast_fp16")]; + tensor var_1242_equation_0 = const()[name = tensor("op_1242_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1242_cast_fp16 = einsum(equation = var_1242_equation_0, values = (var_1136_cast_fp16, var_1000_cast_fp16))[name = tensor("op_1242_cast_fp16")]; + tensor var_1243_to_fp16 = const()[name = tensor("op_1243_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_93_cast_fp16 = mul(x = var_1242_cast_fp16, y = var_1243_to_fp16)[name = tensor("aw_chunk_93_cast_fp16")]; + tensor var_1246_equation_0 = const()[name = tensor("op_1246_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1246_cast_fp16 = einsum(equation = var_1246_equation_0, values = (var_1136_cast_fp16, var_1007_cast_fp16))[name = tensor("op_1246_cast_fp16")]; + tensor var_1247_to_fp16 = const()[name = tensor("op_1247_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_95_cast_fp16 = mul(x = var_1246_cast_fp16, y = var_1247_to_fp16)[name = tensor("aw_chunk_95_cast_fp16")]; + tensor var_1250_equation_0 = const()[name = tensor("op_1250_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1250_cast_fp16 = einsum(equation = var_1250_equation_0, values = (var_1140_cast_fp16, var_1014_cast_fp16))[name = tensor("op_1250_cast_fp16")]; + tensor var_1251_to_fp16 = const()[name = tensor("op_1251_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_97_cast_fp16 = mul(x = var_1250_cast_fp16, y = var_1251_to_fp16)[name = tensor("aw_chunk_97_cast_fp16")]; + tensor var_1254_equation_0 = const()[name = tensor("op_1254_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1254_cast_fp16 = einsum(equation = var_1254_equation_0, values = (var_1140_cast_fp16, var_1021_cast_fp16))[name = tensor("op_1254_cast_fp16")]; + tensor var_1255_to_fp16 = const()[name = tensor("op_1255_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_99_cast_fp16 = mul(x = var_1254_cast_fp16, y = var_1255_to_fp16)[name = tensor("aw_chunk_99_cast_fp16")]; + tensor var_1258_equation_0 = const()[name = tensor("op_1258_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1258_cast_fp16 = einsum(equation = var_1258_equation_0, values = (var_1140_cast_fp16, var_1028_cast_fp16))[name = tensor("op_1258_cast_fp16")]; + tensor var_1259_to_fp16 = const()[name = tensor("op_1259_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_101_cast_fp16 = mul(x = var_1258_cast_fp16, y = var_1259_to_fp16)[name = tensor("aw_chunk_101_cast_fp16")]; + tensor var_1262_equation_0 = const()[name = tensor("op_1262_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1262_cast_fp16 = einsum(equation = var_1262_equation_0, values = (var_1140_cast_fp16, var_1035_cast_fp16))[name = tensor("op_1262_cast_fp16")]; + tensor var_1263_to_fp16 = const()[name = tensor("op_1263_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_103_cast_fp16 = mul(x = var_1262_cast_fp16, y = var_1263_to_fp16)[name = tensor("aw_chunk_103_cast_fp16")]; + tensor var_1266_equation_0 = const()[name = tensor("op_1266_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1266_cast_fp16 = einsum(equation = var_1266_equation_0, values = (var_1144_cast_fp16, var_1042_cast_fp16))[name = tensor("op_1266_cast_fp16")]; + tensor var_1267_to_fp16 = const()[name = tensor("op_1267_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_105_cast_fp16 = mul(x = var_1266_cast_fp16, y = var_1267_to_fp16)[name = tensor("aw_chunk_105_cast_fp16")]; + tensor var_1270_equation_0 = const()[name = tensor("op_1270_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1270_cast_fp16 = einsum(equation = var_1270_equation_0, values = (var_1144_cast_fp16, var_1049_cast_fp16))[name = tensor("op_1270_cast_fp16")]; + tensor var_1271_to_fp16 = const()[name = tensor("op_1271_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_107_cast_fp16 = mul(x = var_1270_cast_fp16, y = var_1271_to_fp16)[name = tensor("aw_chunk_107_cast_fp16")]; + tensor var_1274_equation_0 = const()[name = tensor("op_1274_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1274_cast_fp16 = einsum(equation = var_1274_equation_0, values = (var_1144_cast_fp16, var_1056_cast_fp16))[name = tensor("op_1274_cast_fp16")]; + tensor var_1275_to_fp16 = const()[name = tensor("op_1275_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_109_cast_fp16 = mul(x = var_1274_cast_fp16, y = var_1275_to_fp16)[name = tensor("aw_chunk_109_cast_fp16")]; + tensor var_1278_equation_0 = const()[name = tensor("op_1278_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1278_cast_fp16 = einsum(equation = var_1278_equation_0, values = (var_1144_cast_fp16, var_1063_cast_fp16))[name = tensor("op_1278_cast_fp16")]; + tensor var_1279_to_fp16 = const()[name = tensor("op_1279_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_111_cast_fp16 = mul(x = var_1278_cast_fp16, y = var_1279_to_fp16)[name = tensor("aw_chunk_111_cast_fp16")]; + tensor var_1282_equation_0 = const()[name = tensor("op_1282_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1282_cast_fp16 = einsum(equation = var_1282_equation_0, values = (var_1148_cast_fp16, var_1070_cast_fp16))[name = tensor("op_1282_cast_fp16")]; + tensor var_1283_to_fp16 = const()[name = tensor("op_1283_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_113_cast_fp16 = mul(x = var_1282_cast_fp16, y = var_1283_to_fp16)[name = tensor("aw_chunk_113_cast_fp16")]; + tensor var_1286_equation_0 = const()[name = tensor("op_1286_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1286_cast_fp16 = einsum(equation = var_1286_equation_0, values = (var_1148_cast_fp16, var_1077_cast_fp16))[name = tensor("op_1286_cast_fp16")]; + tensor var_1287_to_fp16 = const()[name = tensor("op_1287_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_115_cast_fp16 = mul(x = var_1286_cast_fp16, y = var_1287_to_fp16)[name = tensor("aw_chunk_115_cast_fp16")]; + tensor var_1290_equation_0 = const()[name = tensor("op_1290_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1290_cast_fp16 = einsum(equation = var_1290_equation_0, values = (var_1148_cast_fp16, var_1084_cast_fp16))[name = tensor("op_1290_cast_fp16")]; + tensor var_1291_to_fp16 = const()[name = tensor("op_1291_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_117_cast_fp16 = mul(x = var_1290_cast_fp16, y = var_1291_to_fp16)[name = tensor("aw_chunk_117_cast_fp16")]; + tensor var_1294_equation_0 = const()[name = tensor("op_1294_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1294_cast_fp16 = einsum(equation = var_1294_equation_0, values = (var_1148_cast_fp16, var_1091_cast_fp16))[name = tensor("op_1294_cast_fp16")]; + tensor var_1295_to_fp16 = const()[name = tensor("op_1295_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_119_cast_fp16 = mul(x = var_1294_cast_fp16, y = var_1295_to_fp16)[name = tensor("aw_chunk_119_cast_fp16")]; + tensor var_1298_equation_0 = const()[name = tensor("op_1298_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1298_cast_fp16 = einsum(equation = var_1298_equation_0, values = (var_1152_cast_fp16, var_1098_cast_fp16))[name = tensor("op_1298_cast_fp16")]; + tensor var_1299_to_fp16 = const()[name = tensor("op_1299_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_121_cast_fp16 = mul(x = var_1298_cast_fp16, y = var_1299_to_fp16)[name = tensor("aw_chunk_121_cast_fp16")]; + tensor var_1302_equation_0 = const()[name = tensor("op_1302_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1302_cast_fp16 = einsum(equation = var_1302_equation_0, values = (var_1152_cast_fp16, var_1105_cast_fp16))[name = tensor("op_1302_cast_fp16")]; + tensor var_1303_to_fp16 = const()[name = tensor("op_1303_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_123_cast_fp16 = mul(x = var_1302_cast_fp16, y = var_1303_to_fp16)[name = tensor("aw_chunk_123_cast_fp16")]; + tensor var_1306_equation_0 = const()[name = tensor("op_1306_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1306_cast_fp16 = einsum(equation = var_1306_equation_0, values = (var_1152_cast_fp16, var_1112_cast_fp16))[name = tensor("op_1306_cast_fp16")]; + tensor var_1307_to_fp16 = const()[name = tensor("op_1307_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_125_cast_fp16 = mul(x = var_1306_cast_fp16, y = var_1307_to_fp16)[name = tensor("aw_chunk_125_cast_fp16")]; + tensor var_1310_equation_0 = const()[name = tensor("op_1310_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1310_cast_fp16 = einsum(equation = var_1310_equation_0, values = (var_1152_cast_fp16, var_1119_cast_fp16))[name = tensor("op_1310_cast_fp16")]; + tensor var_1311_to_fp16 = const()[name = tensor("op_1311_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_127_cast_fp16 = mul(x = var_1310_cast_fp16, y = var_1311_to_fp16)[name = tensor("aw_chunk_127_cast_fp16")]; + tensor var_1313_cast_fp16 = softmax(axis = var_810, x = aw_chunk_65_cast_fp16)[name = tensor("op_1313_cast_fp16")]; + tensor var_1314_cast_fp16 = softmax(axis = var_810, x = aw_chunk_67_cast_fp16)[name = tensor("op_1314_cast_fp16")]; + tensor var_1315_cast_fp16 = softmax(axis = var_810, x = aw_chunk_69_cast_fp16)[name = tensor("op_1315_cast_fp16")]; + tensor var_1316_cast_fp16 = softmax(axis = var_810, x = aw_chunk_71_cast_fp16)[name = tensor("op_1316_cast_fp16")]; + tensor var_1317_cast_fp16 = softmax(axis = var_810, x = aw_chunk_73_cast_fp16)[name = tensor("op_1317_cast_fp16")]; + tensor var_1318_cast_fp16 = softmax(axis = var_810, x = aw_chunk_75_cast_fp16)[name = tensor("op_1318_cast_fp16")]; + tensor var_1319_cast_fp16 = softmax(axis = var_810, x = aw_chunk_77_cast_fp16)[name = tensor("op_1319_cast_fp16")]; + tensor var_1320_cast_fp16 = softmax(axis = var_810, x = aw_chunk_79_cast_fp16)[name = tensor("op_1320_cast_fp16")]; + tensor var_1321_cast_fp16 = softmax(axis = var_810, x = aw_chunk_81_cast_fp16)[name = tensor("op_1321_cast_fp16")]; + tensor var_1322_cast_fp16 = softmax(axis = var_810, x = aw_chunk_83_cast_fp16)[name = tensor("op_1322_cast_fp16")]; + tensor var_1323_cast_fp16 = softmax(axis = var_810, x = aw_chunk_85_cast_fp16)[name = tensor("op_1323_cast_fp16")]; + tensor var_1324_cast_fp16 = softmax(axis = var_810, x = aw_chunk_87_cast_fp16)[name = tensor("op_1324_cast_fp16")]; + tensor var_1325_cast_fp16 = softmax(axis = var_810, x = aw_chunk_89_cast_fp16)[name = tensor("op_1325_cast_fp16")]; + tensor var_1326_cast_fp16 = softmax(axis = var_810, x = aw_chunk_91_cast_fp16)[name = tensor("op_1326_cast_fp16")]; + tensor var_1327_cast_fp16 = softmax(axis = var_810, x = aw_chunk_93_cast_fp16)[name = tensor("op_1327_cast_fp16")]; + tensor var_1328_cast_fp16 = softmax(axis = var_810, x = aw_chunk_95_cast_fp16)[name = tensor("op_1328_cast_fp16")]; + tensor var_1329_cast_fp16 = softmax(axis = var_810, x = aw_chunk_97_cast_fp16)[name = tensor("op_1329_cast_fp16")]; + tensor var_1330_cast_fp16 = softmax(axis = var_810, x = aw_chunk_99_cast_fp16)[name = tensor("op_1330_cast_fp16")]; + tensor var_1331_cast_fp16 = softmax(axis = var_810, x = aw_chunk_101_cast_fp16)[name = tensor("op_1331_cast_fp16")]; + tensor var_1332_cast_fp16 = softmax(axis = var_810, x = aw_chunk_103_cast_fp16)[name = tensor("op_1332_cast_fp16")]; + tensor var_1333_cast_fp16 = softmax(axis = var_810, x = aw_chunk_105_cast_fp16)[name = tensor("op_1333_cast_fp16")]; + tensor var_1334_cast_fp16 = softmax(axis = var_810, x = aw_chunk_107_cast_fp16)[name = tensor("op_1334_cast_fp16")]; + tensor var_1335_cast_fp16 = softmax(axis = var_810, x = aw_chunk_109_cast_fp16)[name = tensor("op_1335_cast_fp16")]; + tensor var_1336_cast_fp16 = softmax(axis = var_810, x = aw_chunk_111_cast_fp16)[name = tensor("op_1336_cast_fp16")]; + tensor var_1337_cast_fp16 = softmax(axis = var_810, x = aw_chunk_113_cast_fp16)[name = tensor("op_1337_cast_fp16")]; + tensor var_1338_cast_fp16 = softmax(axis = var_810, x = aw_chunk_115_cast_fp16)[name = tensor("op_1338_cast_fp16")]; + tensor var_1339_cast_fp16 = softmax(axis = var_810, x = aw_chunk_117_cast_fp16)[name = tensor("op_1339_cast_fp16")]; + tensor var_1340_cast_fp16 = softmax(axis = var_810, x = aw_chunk_119_cast_fp16)[name = tensor("op_1340_cast_fp16")]; + tensor var_1341_cast_fp16 = softmax(axis = var_810, x = aw_chunk_121_cast_fp16)[name = tensor("op_1341_cast_fp16")]; + tensor var_1342_cast_fp16 = softmax(axis = var_810, x = aw_chunk_123_cast_fp16)[name = tensor("op_1342_cast_fp16")]; + tensor var_1343_cast_fp16 = softmax(axis = var_810, x = aw_chunk_125_cast_fp16)[name = tensor("op_1343_cast_fp16")]; + tensor var_1344_cast_fp16 = softmax(axis = var_810, x = aw_chunk_127_cast_fp16)[name = tensor("op_1344_cast_fp16")]; + tensor var_1346_equation_0 = const()[name = tensor("op_1346_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1346_cast_fp16 = einsum(equation = var_1346_equation_0, values = (var_1154_cast_fp16, var_1313_cast_fp16))[name = tensor("op_1346_cast_fp16")]; + tensor var_1348_equation_0 = const()[name = tensor("op_1348_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1348_cast_fp16 = einsum(equation = var_1348_equation_0, values = (var_1154_cast_fp16, var_1314_cast_fp16))[name = tensor("op_1348_cast_fp16")]; + tensor var_1350_equation_0 = const()[name = tensor("op_1350_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1350_cast_fp16 = einsum(equation = var_1350_equation_0, values = (var_1154_cast_fp16, var_1315_cast_fp16))[name = tensor("op_1350_cast_fp16")]; + tensor var_1352_equation_0 = const()[name = tensor("op_1352_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1352_cast_fp16 = einsum(equation = var_1352_equation_0, values = (var_1154_cast_fp16, var_1316_cast_fp16))[name = tensor("op_1352_cast_fp16")]; + tensor var_1354_equation_0 = const()[name = tensor("op_1354_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1354_cast_fp16 = einsum(equation = var_1354_equation_0, values = (var_1158_cast_fp16, var_1317_cast_fp16))[name = tensor("op_1354_cast_fp16")]; + tensor var_1356_equation_0 = const()[name = tensor("op_1356_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1356_cast_fp16 = einsum(equation = var_1356_equation_0, values = (var_1158_cast_fp16, var_1318_cast_fp16))[name = tensor("op_1356_cast_fp16")]; + tensor var_1358_equation_0 = const()[name = tensor("op_1358_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1358_cast_fp16 = einsum(equation = var_1358_equation_0, values = (var_1158_cast_fp16, var_1319_cast_fp16))[name = tensor("op_1358_cast_fp16")]; + tensor var_1360_equation_0 = const()[name = tensor("op_1360_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1360_cast_fp16 = einsum(equation = var_1360_equation_0, values = (var_1158_cast_fp16, var_1320_cast_fp16))[name = tensor("op_1360_cast_fp16")]; + tensor var_1362_equation_0 = const()[name = tensor("op_1362_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1362_cast_fp16 = einsum(equation = var_1362_equation_0, values = (var_1162_cast_fp16, var_1321_cast_fp16))[name = tensor("op_1362_cast_fp16")]; + tensor var_1364_equation_0 = const()[name = tensor("op_1364_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1364_cast_fp16 = einsum(equation = var_1364_equation_0, values = (var_1162_cast_fp16, var_1322_cast_fp16))[name = tensor("op_1364_cast_fp16")]; + tensor var_1366_equation_0 = const()[name = tensor("op_1366_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1366_cast_fp16 = einsum(equation = var_1366_equation_0, values = (var_1162_cast_fp16, var_1323_cast_fp16))[name = tensor("op_1366_cast_fp16")]; + tensor var_1368_equation_0 = const()[name = tensor("op_1368_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1368_cast_fp16 = einsum(equation = var_1368_equation_0, values = (var_1162_cast_fp16, var_1324_cast_fp16))[name = tensor("op_1368_cast_fp16")]; + tensor var_1370_equation_0 = const()[name = tensor("op_1370_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1370_cast_fp16 = einsum(equation = var_1370_equation_0, values = (var_1166_cast_fp16, var_1325_cast_fp16))[name = tensor("op_1370_cast_fp16")]; + tensor var_1372_equation_0 = const()[name = tensor("op_1372_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1372_cast_fp16 = einsum(equation = var_1372_equation_0, values = (var_1166_cast_fp16, var_1326_cast_fp16))[name = tensor("op_1372_cast_fp16")]; + tensor var_1374_equation_0 = const()[name = tensor("op_1374_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1374_cast_fp16 = einsum(equation = var_1374_equation_0, values = (var_1166_cast_fp16, var_1327_cast_fp16))[name = tensor("op_1374_cast_fp16")]; + tensor var_1376_equation_0 = const()[name = tensor("op_1376_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1376_cast_fp16 = einsum(equation = var_1376_equation_0, values = (var_1166_cast_fp16, var_1328_cast_fp16))[name = tensor("op_1376_cast_fp16")]; + tensor var_1378_equation_0 = const()[name = tensor("op_1378_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1378_cast_fp16 = einsum(equation = var_1378_equation_0, values = (var_1170_cast_fp16, var_1329_cast_fp16))[name = tensor("op_1378_cast_fp16")]; + tensor var_1380_equation_0 = const()[name = tensor("op_1380_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1380_cast_fp16 = einsum(equation = var_1380_equation_0, values = (var_1170_cast_fp16, var_1330_cast_fp16))[name = tensor("op_1380_cast_fp16")]; + tensor var_1382_equation_0 = const()[name = tensor("op_1382_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1382_cast_fp16 = einsum(equation = var_1382_equation_0, values = (var_1170_cast_fp16, var_1331_cast_fp16))[name = tensor("op_1382_cast_fp16")]; + tensor var_1384_equation_0 = const()[name = tensor("op_1384_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1384_cast_fp16 = einsum(equation = var_1384_equation_0, values = (var_1170_cast_fp16, var_1332_cast_fp16))[name = tensor("op_1384_cast_fp16")]; + tensor var_1386_equation_0 = const()[name = tensor("op_1386_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1386_cast_fp16 = einsum(equation = var_1386_equation_0, values = (var_1174_cast_fp16, var_1333_cast_fp16))[name = tensor("op_1386_cast_fp16")]; + tensor var_1388_equation_0 = const()[name = tensor("op_1388_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1388_cast_fp16 = einsum(equation = var_1388_equation_0, values = (var_1174_cast_fp16, var_1334_cast_fp16))[name = tensor("op_1388_cast_fp16")]; + tensor var_1390_equation_0 = const()[name = tensor("op_1390_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1390_cast_fp16 = einsum(equation = var_1390_equation_0, values = (var_1174_cast_fp16, var_1335_cast_fp16))[name = tensor("op_1390_cast_fp16")]; + tensor var_1392_equation_0 = const()[name = tensor("op_1392_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1392_cast_fp16 = einsum(equation = var_1392_equation_0, values = (var_1174_cast_fp16, var_1336_cast_fp16))[name = tensor("op_1392_cast_fp16")]; + tensor var_1394_equation_0 = const()[name = tensor("op_1394_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1394_cast_fp16 = einsum(equation = var_1394_equation_0, values = (var_1178_cast_fp16, var_1337_cast_fp16))[name = tensor("op_1394_cast_fp16")]; + tensor var_1396_equation_0 = const()[name = tensor("op_1396_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1396_cast_fp16 = einsum(equation = var_1396_equation_0, values = (var_1178_cast_fp16, var_1338_cast_fp16))[name = tensor("op_1396_cast_fp16")]; + tensor var_1398_equation_0 = const()[name = tensor("op_1398_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1398_cast_fp16 = einsum(equation = var_1398_equation_0, values = (var_1178_cast_fp16, var_1339_cast_fp16))[name = tensor("op_1398_cast_fp16")]; + tensor var_1400_equation_0 = const()[name = tensor("op_1400_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1400_cast_fp16 = einsum(equation = var_1400_equation_0, values = (var_1178_cast_fp16, var_1340_cast_fp16))[name = tensor("op_1400_cast_fp16")]; + tensor var_1402_equation_0 = const()[name = tensor("op_1402_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1402_cast_fp16 = einsum(equation = var_1402_equation_0, values = (var_1182_cast_fp16, var_1341_cast_fp16))[name = tensor("op_1402_cast_fp16")]; + tensor var_1404_equation_0 = const()[name = tensor("op_1404_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1404_cast_fp16 = einsum(equation = var_1404_equation_0, values = (var_1182_cast_fp16, var_1342_cast_fp16))[name = tensor("op_1404_cast_fp16")]; + tensor var_1406_equation_0 = const()[name = tensor("op_1406_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1406_cast_fp16 = einsum(equation = var_1406_equation_0, values = (var_1182_cast_fp16, var_1343_cast_fp16))[name = tensor("op_1406_cast_fp16")]; + tensor var_1408_equation_0 = const()[name = tensor("op_1408_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1408_cast_fp16 = einsum(equation = var_1408_equation_0, values = (var_1182_cast_fp16, var_1344_cast_fp16))[name = tensor("op_1408_cast_fp16")]; + tensor var_1410_interleave_0 = const()[name = tensor("op_1410_interleave_0"), val = tensor(false)]; + tensor var_1410_cast_fp16 = concat(axis = var_797, interleave = var_1410_interleave_0, values = (var_1346_cast_fp16, var_1348_cast_fp16, var_1350_cast_fp16, var_1352_cast_fp16))[name = tensor("op_1410_cast_fp16")]; + tensor var_1412_interleave_0 = const()[name = tensor("op_1412_interleave_0"), val = tensor(false)]; + tensor var_1412_cast_fp16 = concat(axis = var_797, interleave = var_1412_interleave_0, values = (var_1354_cast_fp16, var_1356_cast_fp16, var_1358_cast_fp16, var_1360_cast_fp16))[name = tensor("op_1412_cast_fp16")]; + tensor var_1414_interleave_0 = const()[name = tensor("op_1414_interleave_0"), val = tensor(false)]; + tensor var_1414_cast_fp16 = concat(axis = var_797, interleave = var_1414_interleave_0, values = (var_1362_cast_fp16, var_1364_cast_fp16, var_1366_cast_fp16, var_1368_cast_fp16))[name = tensor("op_1414_cast_fp16")]; + tensor var_1416_interleave_0 = const()[name = tensor("op_1416_interleave_0"), val = tensor(false)]; + tensor var_1416_cast_fp16 = concat(axis = var_797, interleave = var_1416_interleave_0, values = (var_1370_cast_fp16, var_1372_cast_fp16, var_1374_cast_fp16, var_1376_cast_fp16))[name = tensor("op_1416_cast_fp16")]; + tensor var_1418_interleave_0 = const()[name = tensor("op_1418_interleave_0"), val = tensor(false)]; + tensor var_1418_cast_fp16 = concat(axis = var_797, interleave = var_1418_interleave_0, values = (var_1378_cast_fp16, var_1380_cast_fp16, var_1382_cast_fp16, var_1384_cast_fp16))[name = tensor("op_1418_cast_fp16")]; + tensor var_1420_interleave_0 = const()[name = tensor("op_1420_interleave_0"), val = tensor(false)]; + tensor var_1420_cast_fp16 = concat(axis = var_797, interleave = var_1420_interleave_0, values = (var_1386_cast_fp16, var_1388_cast_fp16, var_1390_cast_fp16, var_1392_cast_fp16))[name = tensor("op_1420_cast_fp16")]; + tensor var_1422_interleave_0 = const()[name = tensor("op_1422_interleave_0"), val = tensor(false)]; + tensor var_1422_cast_fp16 = concat(axis = var_797, interleave = var_1422_interleave_0, values = (var_1394_cast_fp16, var_1396_cast_fp16, var_1398_cast_fp16, var_1400_cast_fp16))[name = tensor("op_1422_cast_fp16")]; + tensor var_1424_interleave_0 = const()[name = tensor("op_1424_interleave_0"), val = tensor(false)]; + tensor var_1424_cast_fp16 = concat(axis = var_797, interleave = var_1424_interleave_0, values = (var_1402_cast_fp16, var_1404_cast_fp16, var_1406_cast_fp16, var_1408_cast_fp16))[name = tensor("op_1424_cast_fp16")]; + tensor input_9_interleave_0 = const()[name = tensor("input_9_interleave_0"), val = tensor(false)]; + tensor input_9_cast_fp16 = concat(axis = var_810, interleave = input_9_interleave_0, values = (var_1410_cast_fp16, var_1412_cast_fp16, var_1414_cast_fp16, var_1416_cast_fp16, var_1418_cast_fp16, var_1420_cast_fp16, var_1422_cast_fp16, var_1424_cast_fp16))[name = tensor("input_9_cast_fp16")]; + tensor var_1429 = const()[name = tensor("op_1429"), val = tensor([1, 1])]; + tensor var_1431 = const()[name = tensor("op_1431"), val = tensor([1, 1])]; + tensor obj_7_pad_type_0 = const()[name = tensor("obj_7_pad_type_0"), val = tensor("custom")]; + tensor obj_7_pad_0 = const()[name = tensor("obj_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11241344)))]; + tensor layers_1_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11765696)))]; + tensor obj_7_cast_fp16 = conv(bias = layers_1_self_attn_o_proj_bias_to_fp16, dilations = var_1431, groups = var_810, pad = obj_7_pad_0, pad_type = obj_7_pad_type_0, strides = var_1429, weight = layers_1_self_attn_o_proj_weight_to_fp16, x = input_9_cast_fp16)[name = tensor("obj_7_cast_fp16")]; + tensor inputs_7_cast_fp16 = add(x = inputs_5_cast_fp16, y = obj_7_cast_fp16)[name = tensor("inputs_7_cast_fp16")]; + tensor var_1437 = const()[name = tensor("op_1437"), val = tensor([1])]; + tensor channels_mean_7_cast_fp16 = reduce_mean(axes = var_1437, keep_dims = var_811, x = inputs_7_cast_fp16)[name = tensor("channels_mean_7_cast_fp16")]; + tensor zero_mean_7_cast_fp16 = sub(x = inputs_7_cast_fp16, y = channels_mean_7_cast_fp16)[name = tensor("zero_mean_7_cast_fp16")]; + tensor zero_mean_sq_7_cast_fp16 = mul(x = zero_mean_7_cast_fp16, y = zero_mean_7_cast_fp16)[name = tensor("zero_mean_sq_7_cast_fp16")]; + tensor var_1441 = const()[name = tensor("op_1441"), val = tensor([1])]; + tensor var_1442_cast_fp16 = reduce_mean(axes = var_1441, keep_dims = var_811, x = zero_mean_sq_7_cast_fp16)[name = tensor("op_1442_cast_fp16")]; + tensor var_1443_to_fp16 = const()[name = tensor("op_1443_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1444_cast_fp16 = add(x = var_1442_cast_fp16, y = var_1443_to_fp16)[name = tensor("op_1444_cast_fp16")]; + tensor denom_7_epsilon_0_to_fp16 = const()[name = tensor("denom_7_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_7_cast_fp16 = rsqrt(epsilon = denom_7_epsilon_0_to_fp16, x = var_1444_cast_fp16)[name = tensor("denom_7_cast_fp16")]; + tensor out_7_cast_fp16 = mul(x = zero_mean_7_cast_fp16, y = denom_7_cast_fp16)[name = tensor("out_7_cast_fp16")]; + tensor input_11_gamma_0_to_fp16 = const()[name = tensor("input_11_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11766784)))]; + tensor input_11_beta_0_to_fp16 = const()[name = tensor("input_11_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11767872)))]; + tensor input_11_epsilon_0_to_fp16 = const()[name = tensor("input_11_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_11_cast_fp16 = batch_norm(beta = input_11_beta_0_to_fp16, epsilon = input_11_epsilon_0_to_fp16, gamma = input_11_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_7_cast_fp16)[name = tensor("input_11_cast_fp16")]; + tensor var_1455 = const()[name = tensor("op_1455"), val = tensor([1, 1])]; + tensor var_1457 = const()[name = tensor("op_1457"), val = tensor([1, 1])]; + tensor input_13_pad_type_0 = const()[name = tensor("input_13_pad_type_0"), val = tensor("custom")]; + tensor input_13_pad_0 = const()[name = tensor("input_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_fc1_weight_to_fp16 = const()[name = tensor("layers_1_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11768960)))]; + tensor layers_1_fc1_bias_to_fp16 = const()[name = tensor("layers_1_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13866176)))]; + tensor input_13_cast_fp16 = conv(bias = layers_1_fc1_bias_to_fp16, dilations = var_1457, groups = var_810, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = var_1455, weight = layers_1_fc1_weight_to_fp16, x = input_11_cast_fp16)[name = tensor("input_13_cast_fp16")]; + tensor input_15_mode_0 = const()[name = tensor("input_15_mode_0"), val = tensor("EXACT")]; + tensor input_15_cast_fp16 = gelu(mode = input_15_mode_0, x = input_13_cast_fp16)[name = tensor("input_15_cast_fp16")]; + tensor var_1463 = const()[name = tensor("op_1463"), val = tensor([1, 1])]; + tensor var_1465 = const()[name = tensor("op_1465"), val = tensor([1, 1])]; + tensor hidden_states_7_pad_type_0 = const()[name = tensor("hidden_states_7_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_7_pad_0 = const()[name = tensor("hidden_states_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_fc2_weight_to_fp16 = const()[name = tensor("layers_1_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13870336)))]; + tensor layers_1_fc2_bias_to_fp16 = const()[name = tensor("layers_1_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15967552)))]; + tensor hidden_states_7_cast_fp16 = conv(bias = layers_1_fc2_bias_to_fp16, dilations = var_1465, groups = var_810, pad = hidden_states_7_pad_0, pad_type = hidden_states_7_pad_type_0, strides = var_1463, weight = layers_1_fc2_weight_to_fp16, x = input_15_cast_fp16)[name = tensor("hidden_states_7_cast_fp16")]; + tensor inputs_9_cast_fp16 = add(x = inputs_7_cast_fp16, y = hidden_states_7_cast_fp16)[name = tensor("inputs_9_cast_fp16")]; + tensor var_1472 = const()[name = tensor("op_1472"), val = tensor(3)]; + tensor var_1485 = const()[name = tensor("op_1485"), val = tensor(1)]; + tensor var_1486 = const()[name = tensor("op_1486"), val = tensor(true)]; + tensor var_1496 = const()[name = tensor("op_1496"), val = tensor([1])]; + tensor channels_mean_9_cast_fp16 = reduce_mean(axes = var_1496, keep_dims = var_1486, x = inputs_9_cast_fp16)[name = tensor("channels_mean_9_cast_fp16")]; + tensor zero_mean_9_cast_fp16 = sub(x = inputs_9_cast_fp16, y = channels_mean_9_cast_fp16)[name = tensor("zero_mean_9_cast_fp16")]; + tensor zero_mean_sq_9_cast_fp16 = mul(x = zero_mean_9_cast_fp16, y = zero_mean_9_cast_fp16)[name = tensor("zero_mean_sq_9_cast_fp16")]; + tensor var_1500 = const()[name = tensor("op_1500"), val = tensor([1])]; + tensor var_1501_cast_fp16 = reduce_mean(axes = var_1500, keep_dims = var_1486, x = zero_mean_sq_9_cast_fp16)[name = tensor("op_1501_cast_fp16")]; + tensor var_1502_to_fp16 = const()[name = tensor("op_1502_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1503_cast_fp16 = add(x = var_1501_cast_fp16, y = var_1502_to_fp16)[name = tensor("op_1503_cast_fp16")]; + tensor denom_9_epsilon_0_to_fp16 = const()[name = tensor("denom_9_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_9_cast_fp16 = rsqrt(epsilon = denom_9_epsilon_0_to_fp16, x = var_1503_cast_fp16)[name = tensor("denom_9_cast_fp16")]; + tensor out_9_cast_fp16 = mul(x = zero_mean_9_cast_fp16, y = denom_9_cast_fp16)[name = tensor("out_9_cast_fp16")]; + tensor obj_9_gamma_0_to_fp16 = const()[name = tensor("obj_9_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15968640)))]; + tensor obj_9_beta_0_to_fp16 = const()[name = tensor("obj_9_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15969728)))]; + tensor obj_9_epsilon_0_to_fp16 = const()[name = tensor("obj_9_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_9_cast_fp16 = batch_norm(beta = obj_9_beta_0_to_fp16, epsilon = obj_9_epsilon_0_to_fp16, gamma = obj_9_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_9_cast_fp16)[name = tensor("obj_9_cast_fp16")]; + tensor var_1518 = const()[name = tensor("op_1518"), val = tensor([1, 1])]; + tensor var_1520 = const()[name = tensor("op_1520"), val = tensor([1, 1])]; + tensor query_5_pad_type_0 = const()[name = tensor("query_5_pad_type_0"), val = tensor("custom")]; + tensor query_5_pad_0 = const()[name = tensor("query_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15970816)))]; + tensor layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16495168)))]; + tensor query_5_cast_fp16 = conv(bias = layers_2_self_attn_q_proj_bias_to_fp16, dilations = var_1520, groups = var_1485, pad = query_5_pad_0, pad_type = query_5_pad_type_0, strides = var_1518, weight = layers_2_self_attn_q_proj_weight_to_fp16, x = obj_9_cast_fp16)[name = tensor("query_5_cast_fp16")]; + tensor var_1524 = const()[name = tensor("op_1524"), val = tensor([1, 1])]; + tensor var_1526 = const()[name = tensor("op_1526"), val = tensor([1, 1])]; + tensor key_5_pad_type_0 = const()[name = tensor("key_5_pad_type_0"), val = tensor("custom")]; + tensor key_5_pad_0 = const()[name = tensor("key_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16496256)))]; + tensor key_5_cast_fp16 = conv(dilations = var_1526, groups = var_1485, pad = key_5_pad_0, pad_type = key_5_pad_type_0, strides = var_1524, weight = layers_2_self_attn_k_proj_weight_to_fp16, x = obj_9_cast_fp16)[name = tensor("key_5_cast_fp16")]; + tensor var_1531 = const()[name = tensor("op_1531"), val = tensor([1, 1])]; + tensor var_1533 = const()[name = tensor("op_1533"), val = tensor([1, 1])]; + tensor value_5_pad_type_0 = const()[name = tensor("value_5_pad_type_0"), val = tensor("custom")]; + tensor value_5_pad_0 = const()[name = tensor("value_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17020608)))]; + tensor layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17544960)))]; + tensor value_5_cast_fp16 = conv(bias = layers_2_self_attn_v_proj_bias_to_fp16, dilations = var_1533, groups = var_1485, pad = value_5_pad_0, pad_type = value_5_pad_type_0, strides = var_1531, weight = layers_2_self_attn_v_proj_weight_to_fp16, x = obj_9_cast_fp16)[name = tensor("value_5_cast_fp16")]; + tensor var_1540_begin_0 = const()[name = tensor("op_1540_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1540_end_0 = const()[name = tensor("op_1540_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1540_end_mask_0 = const()[name = tensor("op_1540_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1540_cast_fp16 = slice_by_index(begin = var_1540_begin_0, end = var_1540_end_0, end_mask = var_1540_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_1540_cast_fp16")]; + tensor var_1544_begin_0 = const()[name = tensor("op_1544_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_1544_end_0 = const()[name = tensor("op_1544_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_1544_end_mask_0 = const()[name = tensor("op_1544_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1544_cast_fp16 = slice_by_index(begin = var_1544_begin_0, end = var_1544_end_0, end_mask = var_1544_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_1544_cast_fp16")]; + tensor var_1548_begin_0 = const()[name = tensor("op_1548_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_1548_end_0 = const()[name = tensor("op_1548_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_1548_end_mask_0 = const()[name = tensor("op_1548_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1548_cast_fp16 = slice_by_index(begin = var_1548_begin_0, end = var_1548_end_0, end_mask = var_1548_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_1548_cast_fp16")]; + tensor var_1552_begin_0 = const()[name = tensor("op_1552_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_1552_end_0 = const()[name = tensor("op_1552_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_1552_end_mask_0 = const()[name = tensor("op_1552_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1552_cast_fp16 = slice_by_index(begin = var_1552_begin_0, end = var_1552_end_0, end_mask = var_1552_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_1552_cast_fp16")]; + tensor var_1556_begin_0 = const()[name = tensor("op_1556_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_1556_end_0 = const()[name = tensor("op_1556_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_1556_end_mask_0 = const()[name = tensor("op_1556_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1556_cast_fp16 = slice_by_index(begin = var_1556_begin_0, end = var_1556_end_0, end_mask = var_1556_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_1556_cast_fp16")]; + tensor var_1560_begin_0 = const()[name = tensor("op_1560_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_1560_end_0 = const()[name = tensor("op_1560_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_1560_end_mask_0 = const()[name = tensor("op_1560_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1560_cast_fp16 = slice_by_index(begin = var_1560_begin_0, end = var_1560_end_0, end_mask = var_1560_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_1560_cast_fp16")]; + tensor var_1564_begin_0 = const()[name = tensor("op_1564_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_1564_end_0 = const()[name = tensor("op_1564_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_1564_end_mask_0 = const()[name = tensor("op_1564_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1564_cast_fp16 = slice_by_index(begin = var_1564_begin_0, end = var_1564_end_0, end_mask = var_1564_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_1564_cast_fp16")]; + tensor var_1568_begin_0 = const()[name = tensor("op_1568_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_1568_end_0 = const()[name = tensor("op_1568_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_1568_end_mask_0 = const()[name = tensor("op_1568_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1568_cast_fp16 = slice_by_index(begin = var_1568_begin_0, end = var_1568_end_0, end_mask = var_1568_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_1568_cast_fp16")]; + tensor var_1577_begin_0 = const()[name = tensor("op_1577_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1577_end_0 = const()[name = tensor("op_1577_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1577_end_mask_0 = const()[name = tensor("op_1577_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1577_cast_fp16 = slice_by_index(begin = var_1577_begin_0, end = var_1577_end_0, end_mask = var_1577_end_mask_0, x = var_1540_cast_fp16)[name = tensor("op_1577_cast_fp16")]; + tensor var_1584_begin_0 = const()[name = tensor("op_1584_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1584_end_0 = const()[name = tensor("op_1584_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1584_end_mask_0 = const()[name = tensor("op_1584_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1584_cast_fp16 = slice_by_index(begin = var_1584_begin_0, end = var_1584_end_0, end_mask = var_1584_end_mask_0, x = var_1540_cast_fp16)[name = tensor("op_1584_cast_fp16")]; + tensor var_1591_begin_0 = const()[name = tensor("op_1591_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1591_end_0 = const()[name = tensor("op_1591_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1591_end_mask_0 = const()[name = tensor("op_1591_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1591_cast_fp16 = slice_by_index(begin = var_1591_begin_0, end = var_1591_end_0, end_mask = var_1591_end_mask_0, x = var_1540_cast_fp16)[name = tensor("op_1591_cast_fp16")]; + tensor var_1598_begin_0 = const()[name = tensor("op_1598_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1598_end_0 = const()[name = tensor("op_1598_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1598_end_mask_0 = const()[name = tensor("op_1598_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1598_cast_fp16 = slice_by_index(begin = var_1598_begin_0, end = var_1598_end_0, end_mask = var_1598_end_mask_0, x = var_1540_cast_fp16)[name = tensor("op_1598_cast_fp16")]; + tensor var_1605_begin_0 = const()[name = tensor("op_1605_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1605_end_0 = const()[name = tensor("op_1605_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1605_end_mask_0 = const()[name = tensor("op_1605_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1605_cast_fp16 = slice_by_index(begin = var_1605_begin_0, end = var_1605_end_0, end_mask = var_1605_end_mask_0, x = var_1544_cast_fp16)[name = tensor("op_1605_cast_fp16")]; + tensor var_1612_begin_0 = const()[name = tensor("op_1612_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1612_end_0 = const()[name = tensor("op_1612_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1612_end_mask_0 = const()[name = tensor("op_1612_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1612_cast_fp16 = slice_by_index(begin = var_1612_begin_0, end = var_1612_end_0, end_mask = var_1612_end_mask_0, x = var_1544_cast_fp16)[name = tensor("op_1612_cast_fp16")]; + tensor var_1619_begin_0 = const()[name = tensor("op_1619_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1619_end_0 = const()[name = tensor("op_1619_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1619_end_mask_0 = const()[name = tensor("op_1619_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1619_cast_fp16 = slice_by_index(begin = var_1619_begin_0, end = var_1619_end_0, end_mask = var_1619_end_mask_0, x = var_1544_cast_fp16)[name = tensor("op_1619_cast_fp16")]; + tensor var_1626_begin_0 = const()[name = tensor("op_1626_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1626_end_0 = const()[name = tensor("op_1626_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1626_end_mask_0 = const()[name = tensor("op_1626_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1626_cast_fp16 = slice_by_index(begin = var_1626_begin_0, end = var_1626_end_0, end_mask = var_1626_end_mask_0, x = var_1544_cast_fp16)[name = tensor("op_1626_cast_fp16")]; + tensor var_1633_begin_0 = const()[name = tensor("op_1633_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1633_end_0 = const()[name = tensor("op_1633_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1633_end_mask_0 = const()[name = tensor("op_1633_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1633_cast_fp16 = slice_by_index(begin = var_1633_begin_0, end = var_1633_end_0, end_mask = var_1633_end_mask_0, x = var_1548_cast_fp16)[name = tensor("op_1633_cast_fp16")]; + tensor var_1640_begin_0 = const()[name = tensor("op_1640_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1640_end_0 = const()[name = tensor("op_1640_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1640_end_mask_0 = const()[name = tensor("op_1640_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1640_cast_fp16 = slice_by_index(begin = var_1640_begin_0, end = var_1640_end_0, end_mask = var_1640_end_mask_0, x = var_1548_cast_fp16)[name = tensor("op_1640_cast_fp16")]; + tensor var_1647_begin_0 = const()[name = tensor("op_1647_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1647_end_0 = const()[name = tensor("op_1647_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1647_end_mask_0 = const()[name = tensor("op_1647_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1647_cast_fp16 = slice_by_index(begin = var_1647_begin_0, end = var_1647_end_0, end_mask = var_1647_end_mask_0, x = var_1548_cast_fp16)[name = tensor("op_1647_cast_fp16")]; + tensor var_1654_begin_0 = const()[name = tensor("op_1654_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1654_end_0 = const()[name = tensor("op_1654_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1654_end_mask_0 = const()[name = tensor("op_1654_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1654_cast_fp16 = slice_by_index(begin = var_1654_begin_0, end = var_1654_end_0, end_mask = var_1654_end_mask_0, x = var_1548_cast_fp16)[name = tensor("op_1654_cast_fp16")]; + tensor var_1661_begin_0 = const()[name = tensor("op_1661_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1661_end_0 = const()[name = tensor("op_1661_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1661_end_mask_0 = const()[name = tensor("op_1661_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1661_cast_fp16 = slice_by_index(begin = var_1661_begin_0, end = var_1661_end_0, end_mask = var_1661_end_mask_0, x = var_1552_cast_fp16)[name = tensor("op_1661_cast_fp16")]; + tensor var_1668_begin_0 = const()[name = tensor("op_1668_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1668_end_0 = const()[name = tensor("op_1668_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1668_end_mask_0 = const()[name = tensor("op_1668_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1668_cast_fp16 = slice_by_index(begin = var_1668_begin_0, end = var_1668_end_0, end_mask = var_1668_end_mask_0, x = var_1552_cast_fp16)[name = tensor("op_1668_cast_fp16")]; + tensor var_1675_begin_0 = const()[name = tensor("op_1675_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1675_end_0 = const()[name = tensor("op_1675_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1675_end_mask_0 = const()[name = tensor("op_1675_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1675_cast_fp16 = slice_by_index(begin = var_1675_begin_0, end = var_1675_end_0, end_mask = var_1675_end_mask_0, x = var_1552_cast_fp16)[name = tensor("op_1675_cast_fp16")]; + tensor var_1682_begin_0 = const()[name = tensor("op_1682_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1682_end_0 = const()[name = tensor("op_1682_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1682_end_mask_0 = const()[name = tensor("op_1682_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1682_cast_fp16 = slice_by_index(begin = var_1682_begin_0, end = var_1682_end_0, end_mask = var_1682_end_mask_0, x = var_1552_cast_fp16)[name = tensor("op_1682_cast_fp16")]; + tensor var_1689_begin_0 = const()[name = tensor("op_1689_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1689_end_0 = const()[name = tensor("op_1689_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1689_end_mask_0 = const()[name = tensor("op_1689_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1689_cast_fp16 = slice_by_index(begin = var_1689_begin_0, end = var_1689_end_0, end_mask = var_1689_end_mask_0, x = var_1556_cast_fp16)[name = tensor("op_1689_cast_fp16")]; + tensor var_1696_begin_0 = const()[name = tensor("op_1696_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1696_end_0 = const()[name = tensor("op_1696_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1696_end_mask_0 = const()[name = tensor("op_1696_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1696_cast_fp16 = slice_by_index(begin = var_1696_begin_0, end = var_1696_end_0, end_mask = var_1696_end_mask_0, x = var_1556_cast_fp16)[name = tensor("op_1696_cast_fp16")]; + tensor var_1703_begin_0 = const()[name = tensor("op_1703_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1703_end_0 = const()[name = tensor("op_1703_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1703_end_mask_0 = const()[name = tensor("op_1703_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1703_cast_fp16 = slice_by_index(begin = var_1703_begin_0, end = var_1703_end_0, end_mask = var_1703_end_mask_0, x = var_1556_cast_fp16)[name = tensor("op_1703_cast_fp16")]; + tensor var_1710_begin_0 = const()[name = tensor("op_1710_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1710_end_0 = const()[name = tensor("op_1710_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1710_end_mask_0 = const()[name = tensor("op_1710_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1710_cast_fp16 = slice_by_index(begin = var_1710_begin_0, end = var_1710_end_0, end_mask = var_1710_end_mask_0, x = var_1556_cast_fp16)[name = tensor("op_1710_cast_fp16")]; + tensor var_1717_begin_0 = const()[name = tensor("op_1717_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1717_end_0 = const()[name = tensor("op_1717_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1717_end_mask_0 = const()[name = tensor("op_1717_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1717_cast_fp16 = slice_by_index(begin = var_1717_begin_0, end = var_1717_end_0, end_mask = var_1717_end_mask_0, x = var_1560_cast_fp16)[name = tensor("op_1717_cast_fp16")]; + tensor var_1724_begin_0 = const()[name = tensor("op_1724_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1724_end_0 = const()[name = tensor("op_1724_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1724_end_mask_0 = const()[name = tensor("op_1724_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1724_cast_fp16 = slice_by_index(begin = var_1724_begin_0, end = var_1724_end_0, end_mask = var_1724_end_mask_0, x = var_1560_cast_fp16)[name = tensor("op_1724_cast_fp16")]; + tensor var_1731_begin_0 = const()[name = tensor("op_1731_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1731_end_0 = const()[name = tensor("op_1731_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1731_end_mask_0 = const()[name = tensor("op_1731_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1731_cast_fp16 = slice_by_index(begin = var_1731_begin_0, end = var_1731_end_0, end_mask = var_1731_end_mask_0, x = var_1560_cast_fp16)[name = tensor("op_1731_cast_fp16")]; + tensor var_1738_begin_0 = const()[name = tensor("op_1738_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1738_end_0 = const()[name = tensor("op_1738_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1738_end_mask_0 = const()[name = tensor("op_1738_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1738_cast_fp16 = slice_by_index(begin = var_1738_begin_0, end = var_1738_end_0, end_mask = var_1738_end_mask_0, x = var_1560_cast_fp16)[name = tensor("op_1738_cast_fp16")]; + tensor var_1745_begin_0 = const()[name = tensor("op_1745_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1745_end_0 = const()[name = tensor("op_1745_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1745_end_mask_0 = const()[name = tensor("op_1745_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1745_cast_fp16 = slice_by_index(begin = var_1745_begin_0, end = var_1745_end_0, end_mask = var_1745_end_mask_0, x = var_1564_cast_fp16)[name = tensor("op_1745_cast_fp16")]; + tensor var_1752_begin_0 = const()[name = tensor("op_1752_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1752_end_0 = const()[name = tensor("op_1752_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1752_end_mask_0 = const()[name = tensor("op_1752_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1752_cast_fp16 = slice_by_index(begin = var_1752_begin_0, end = var_1752_end_0, end_mask = var_1752_end_mask_0, x = var_1564_cast_fp16)[name = tensor("op_1752_cast_fp16")]; + tensor var_1759_begin_0 = const()[name = tensor("op_1759_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1759_end_0 = const()[name = tensor("op_1759_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1759_end_mask_0 = const()[name = tensor("op_1759_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1759_cast_fp16 = slice_by_index(begin = var_1759_begin_0, end = var_1759_end_0, end_mask = var_1759_end_mask_0, x = var_1564_cast_fp16)[name = tensor("op_1759_cast_fp16")]; + tensor var_1766_begin_0 = const()[name = tensor("op_1766_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1766_end_0 = const()[name = tensor("op_1766_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1766_end_mask_0 = const()[name = tensor("op_1766_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1766_cast_fp16 = slice_by_index(begin = var_1766_begin_0, end = var_1766_end_0, end_mask = var_1766_end_mask_0, x = var_1564_cast_fp16)[name = tensor("op_1766_cast_fp16")]; + tensor var_1773_begin_0 = const()[name = tensor("op_1773_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1773_end_0 = const()[name = tensor("op_1773_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1773_end_mask_0 = const()[name = tensor("op_1773_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1773_cast_fp16 = slice_by_index(begin = var_1773_begin_0, end = var_1773_end_0, end_mask = var_1773_end_mask_0, x = var_1568_cast_fp16)[name = tensor("op_1773_cast_fp16")]; + tensor var_1780_begin_0 = const()[name = tensor("op_1780_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1780_end_0 = const()[name = tensor("op_1780_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1780_end_mask_0 = const()[name = tensor("op_1780_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1780_cast_fp16 = slice_by_index(begin = var_1780_begin_0, end = var_1780_end_0, end_mask = var_1780_end_mask_0, x = var_1568_cast_fp16)[name = tensor("op_1780_cast_fp16")]; + tensor var_1787_begin_0 = const()[name = tensor("op_1787_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1787_end_0 = const()[name = tensor("op_1787_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1787_end_mask_0 = const()[name = tensor("op_1787_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1787_cast_fp16 = slice_by_index(begin = var_1787_begin_0, end = var_1787_end_0, end_mask = var_1787_end_mask_0, x = var_1568_cast_fp16)[name = tensor("op_1787_cast_fp16")]; + tensor var_1794_begin_0 = const()[name = tensor("op_1794_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1794_end_0 = const()[name = tensor("op_1794_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1794_end_mask_0 = const()[name = tensor("op_1794_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1794_cast_fp16 = slice_by_index(begin = var_1794_begin_0, end = var_1794_end_0, end_mask = var_1794_end_mask_0, x = var_1568_cast_fp16)[name = tensor("op_1794_cast_fp16")]; + tensor k_5_perm_0 = const()[name = tensor("k_5_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_1799_begin_0 = const()[name = tensor("op_1799_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1799_end_0 = const()[name = tensor("op_1799_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_1799_end_mask_0 = const()[name = tensor("op_1799_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_3 = transpose(perm = k_5_perm_0, x = key_5_cast_fp16)[name = tensor("transpose_3")]; + tensor var_1799_cast_fp16 = slice_by_index(begin = var_1799_begin_0, end = var_1799_end_0, end_mask = var_1799_end_mask_0, x = transpose_3)[name = tensor("op_1799_cast_fp16")]; + tensor var_1803_begin_0 = const()[name = tensor("op_1803_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_1803_end_0 = const()[name = tensor("op_1803_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_1803_end_mask_0 = const()[name = tensor("op_1803_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1803_cast_fp16 = slice_by_index(begin = var_1803_begin_0, end = var_1803_end_0, end_mask = var_1803_end_mask_0, x = transpose_3)[name = tensor("op_1803_cast_fp16")]; + tensor var_1807_begin_0 = const()[name = tensor("op_1807_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_1807_end_0 = const()[name = tensor("op_1807_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_1807_end_mask_0 = const()[name = tensor("op_1807_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1807_cast_fp16 = slice_by_index(begin = var_1807_begin_0, end = var_1807_end_0, end_mask = var_1807_end_mask_0, x = transpose_3)[name = tensor("op_1807_cast_fp16")]; + tensor var_1811_begin_0 = const()[name = tensor("op_1811_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_1811_end_0 = const()[name = tensor("op_1811_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_1811_end_mask_0 = const()[name = tensor("op_1811_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1811_cast_fp16 = slice_by_index(begin = var_1811_begin_0, end = var_1811_end_0, end_mask = var_1811_end_mask_0, x = transpose_3)[name = tensor("op_1811_cast_fp16")]; + tensor var_1815_begin_0 = const()[name = tensor("op_1815_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_1815_end_0 = const()[name = tensor("op_1815_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_1815_end_mask_0 = const()[name = tensor("op_1815_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1815_cast_fp16 = slice_by_index(begin = var_1815_begin_0, end = var_1815_end_0, end_mask = var_1815_end_mask_0, x = transpose_3)[name = tensor("op_1815_cast_fp16")]; + tensor var_1819_begin_0 = const()[name = tensor("op_1819_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_1819_end_0 = const()[name = tensor("op_1819_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_1819_end_mask_0 = const()[name = tensor("op_1819_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1819_cast_fp16 = slice_by_index(begin = var_1819_begin_0, end = var_1819_end_0, end_mask = var_1819_end_mask_0, x = transpose_3)[name = tensor("op_1819_cast_fp16")]; + tensor var_1823_begin_0 = const()[name = tensor("op_1823_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_1823_end_0 = const()[name = tensor("op_1823_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_1823_end_mask_0 = const()[name = tensor("op_1823_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1823_cast_fp16 = slice_by_index(begin = var_1823_begin_0, end = var_1823_end_0, end_mask = var_1823_end_mask_0, x = transpose_3)[name = tensor("op_1823_cast_fp16")]; + tensor var_1827_begin_0 = const()[name = tensor("op_1827_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_1827_end_0 = const()[name = tensor("op_1827_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_1827_end_mask_0 = const()[name = tensor("op_1827_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1827_cast_fp16 = slice_by_index(begin = var_1827_begin_0, end = var_1827_end_0, end_mask = var_1827_end_mask_0, x = transpose_3)[name = tensor("op_1827_cast_fp16")]; + tensor var_1829_begin_0 = const()[name = tensor("op_1829_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1829_end_0 = const()[name = tensor("op_1829_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1829_end_mask_0 = const()[name = tensor("op_1829_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1829_cast_fp16 = slice_by_index(begin = var_1829_begin_0, end = var_1829_end_0, end_mask = var_1829_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_1829_cast_fp16")]; + tensor var_1833_begin_0 = const()[name = tensor("op_1833_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_1833_end_0 = const()[name = tensor("op_1833_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_1833_end_mask_0 = const()[name = tensor("op_1833_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1833_cast_fp16 = slice_by_index(begin = var_1833_begin_0, end = var_1833_end_0, end_mask = var_1833_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_1833_cast_fp16")]; + tensor var_1837_begin_0 = const()[name = tensor("op_1837_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_1837_end_0 = const()[name = tensor("op_1837_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_1837_end_mask_0 = const()[name = tensor("op_1837_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1837_cast_fp16 = slice_by_index(begin = var_1837_begin_0, end = var_1837_end_0, end_mask = var_1837_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_1837_cast_fp16")]; + tensor var_1841_begin_0 = const()[name = tensor("op_1841_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_1841_end_0 = const()[name = tensor("op_1841_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_1841_end_mask_0 = const()[name = tensor("op_1841_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1841_cast_fp16 = slice_by_index(begin = var_1841_begin_0, end = var_1841_end_0, end_mask = var_1841_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_1841_cast_fp16")]; + tensor var_1845_begin_0 = const()[name = tensor("op_1845_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_1845_end_0 = const()[name = tensor("op_1845_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_1845_end_mask_0 = const()[name = tensor("op_1845_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1845_cast_fp16 = slice_by_index(begin = var_1845_begin_0, end = var_1845_end_0, end_mask = var_1845_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_1845_cast_fp16")]; + tensor var_1849_begin_0 = const()[name = tensor("op_1849_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_1849_end_0 = const()[name = tensor("op_1849_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_1849_end_mask_0 = const()[name = tensor("op_1849_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1849_cast_fp16 = slice_by_index(begin = var_1849_begin_0, end = var_1849_end_0, end_mask = var_1849_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_1849_cast_fp16")]; + tensor var_1853_begin_0 = const()[name = tensor("op_1853_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_1853_end_0 = const()[name = tensor("op_1853_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_1853_end_mask_0 = const()[name = tensor("op_1853_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1853_cast_fp16 = slice_by_index(begin = var_1853_begin_0, end = var_1853_end_0, end_mask = var_1853_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_1853_cast_fp16")]; + tensor var_1857_begin_0 = const()[name = tensor("op_1857_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_1857_end_0 = const()[name = tensor("op_1857_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_1857_end_mask_0 = const()[name = tensor("op_1857_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1857_cast_fp16 = slice_by_index(begin = var_1857_begin_0, end = var_1857_end_0, end_mask = var_1857_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_1857_cast_fp16")]; + tensor var_1861_equation_0 = const()[name = tensor("op_1861_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1861_cast_fp16 = einsum(equation = var_1861_equation_0, values = (var_1799_cast_fp16, var_1577_cast_fp16))[name = tensor("op_1861_cast_fp16")]; + tensor var_1862_to_fp16 = const()[name = tensor("op_1862_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_129_cast_fp16 = mul(x = var_1861_cast_fp16, y = var_1862_to_fp16)[name = tensor("aw_chunk_129_cast_fp16")]; + tensor var_1865_equation_0 = const()[name = tensor("op_1865_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1865_cast_fp16 = einsum(equation = var_1865_equation_0, values = (var_1799_cast_fp16, var_1584_cast_fp16))[name = tensor("op_1865_cast_fp16")]; + tensor var_1866_to_fp16 = const()[name = tensor("op_1866_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_131_cast_fp16 = mul(x = var_1865_cast_fp16, y = var_1866_to_fp16)[name = tensor("aw_chunk_131_cast_fp16")]; + tensor var_1869_equation_0 = const()[name = tensor("op_1869_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1869_cast_fp16 = einsum(equation = var_1869_equation_0, values = (var_1799_cast_fp16, var_1591_cast_fp16))[name = tensor("op_1869_cast_fp16")]; + tensor var_1870_to_fp16 = const()[name = tensor("op_1870_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_133_cast_fp16 = mul(x = var_1869_cast_fp16, y = var_1870_to_fp16)[name = tensor("aw_chunk_133_cast_fp16")]; + tensor var_1873_equation_0 = const()[name = tensor("op_1873_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1873_cast_fp16 = einsum(equation = var_1873_equation_0, values = (var_1799_cast_fp16, var_1598_cast_fp16))[name = tensor("op_1873_cast_fp16")]; + tensor var_1874_to_fp16 = const()[name = tensor("op_1874_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_135_cast_fp16 = mul(x = var_1873_cast_fp16, y = var_1874_to_fp16)[name = tensor("aw_chunk_135_cast_fp16")]; + tensor var_1877_equation_0 = const()[name = tensor("op_1877_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1877_cast_fp16 = einsum(equation = var_1877_equation_0, values = (var_1803_cast_fp16, var_1605_cast_fp16))[name = tensor("op_1877_cast_fp16")]; + tensor var_1878_to_fp16 = const()[name = tensor("op_1878_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_137_cast_fp16 = mul(x = var_1877_cast_fp16, y = var_1878_to_fp16)[name = tensor("aw_chunk_137_cast_fp16")]; + tensor var_1881_equation_0 = const()[name = tensor("op_1881_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1881_cast_fp16 = einsum(equation = var_1881_equation_0, values = (var_1803_cast_fp16, var_1612_cast_fp16))[name = tensor("op_1881_cast_fp16")]; + tensor var_1882_to_fp16 = const()[name = tensor("op_1882_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_139_cast_fp16 = mul(x = var_1881_cast_fp16, y = var_1882_to_fp16)[name = tensor("aw_chunk_139_cast_fp16")]; + tensor var_1885_equation_0 = const()[name = tensor("op_1885_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1885_cast_fp16 = einsum(equation = var_1885_equation_0, values = (var_1803_cast_fp16, var_1619_cast_fp16))[name = tensor("op_1885_cast_fp16")]; + tensor var_1886_to_fp16 = const()[name = tensor("op_1886_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_141_cast_fp16 = mul(x = var_1885_cast_fp16, y = var_1886_to_fp16)[name = tensor("aw_chunk_141_cast_fp16")]; + tensor var_1889_equation_0 = const()[name = tensor("op_1889_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1889_cast_fp16 = einsum(equation = var_1889_equation_0, values = (var_1803_cast_fp16, var_1626_cast_fp16))[name = tensor("op_1889_cast_fp16")]; + tensor var_1890_to_fp16 = const()[name = tensor("op_1890_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_143_cast_fp16 = mul(x = var_1889_cast_fp16, y = var_1890_to_fp16)[name = tensor("aw_chunk_143_cast_fp16")]; + tensor var_1893_equation_0 = const()[name = tensor("op_1893_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1893_cast_fp16 = einsum(equation = var_1893_equation_0, values = (var_1807_cast_fp16, var_1633_cast_fp16))[name = tensor("op_1893_cast_fp16")]; + tensor var_1894_to_fp16 = const()[name = tensor("op_1894_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_145_cast_fp16 = mul(x = var_1893_cast_fp16, y = var_1894_to_fp16)[name = tensor("aw_chunk_145_cast_fp16")]; + tensor var_1897_equation_0 = const()[name = tensor("op_1897_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1897_cast_fp16 = einsum(equation = var_1897_equation_0, values = (var_1807_cast_fp16, var_1640_cast_fp16))[name = tensor("op_1897_cast_fp16")]; + tensor var_1898_to_fp16 = const()[name = tensor("op_1898_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_147_cast_fp16 = mul(x = var_1897_cast_fp16, y = var_1898_to_fp16)[name = tensor("aw_chunk_147_cast_fp16")]; + tensor var_1901_equation_0 = const()[name = tensor("op_1901_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1901_cast_fp16 = einsum(equation = var_1901_equation_0, values = (var_1807_cast_fp16, var_1647_cast_fp16))[name = tensor("op_1901_cast_fp16")]; + tensor var_1902_to_fp16 = const()[name = tensor("op_1902_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_149_cast_fp16 = mul(x = var_1901_cast_fp16, y = var_1902_to_fp16)[name = tensor("aw_chunk_149_cast_fp16")]; + tensor var_1905_equation_0 = const()[name = tensor("op_1905_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1905_cast_fp16 = einsum(equation = var_1905_equation_0, values = (var_1807_cast_fp16, var_1654_cast_fp16))[name = tensor("op_1905_cast_fp16")]; + tensor var_1906_to_fp16 = const()[name = tensor("op_1906_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_151_cast_fp16 = mul(x = var_1905_cast_fp16, y = var_1906_to_fp16)[name = tensor("aw_chunk_151_cast_fp16")]; + tensor var_1909_equation_0 = const()[name = tensor("op_1909_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1909_cast_fp16 = einsum(equation = var_1909_equation_0, values = (var_1811_cast_fp16, var_1661_cast_fp16))[name = tensor("op_1909_cast_fp16")]; + tensor var_1910_to_fp16 = const()[name = tensor("op_1910_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_153_cast_fp16 = mul(x = var_1909_cast_fp16, y = var_1910_to_fp16)[name = tensor("aw_chunk_153_cast_fp16")]; + tensor var_1913_equation_0 = const()[name = tensor("op_1913_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1913_cast_fp16 = einsum(equation = var_1913_equation_0, values = (var_1811_cast_fp16, var_1668_cast_fp16))[name = tensor("op_1913_cast_fp16")]; + tensor var_1914_to_fp16 = const()[name = tensor("op_1914_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_155_cast_fp16 = mul(x = var_1913_cast_fp16, y = var_1914_to_fp16)[name = tensor("aw_chunk_155_cast_fp16")]; + tensor var_1917_equation_0 = const()[name = tensor("op_1917_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1917_cast_fp16 = einsum(equation = var_1917_equation_0, values = (var_1811_cast_fp16, var_1675_cast_fp16))[name = tensor("op_1917_cast_fp16")]; + tensor var_1918_to_fp16 = const()[name = tensor("op_1918_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_157_cast_fp16 = mul(x = var_1917_cast_fp16, y = var_1918_to_fp16)[name = tensor("aw_chunk_157_cast_fp16")]; + tensor var_1921_equation_0 = const()[name = tensor("op_1921_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1921_cast_fp16 = einsum(equation = var_1921_equation_0, values = (var_1811_cast_fp16, var_1682_cast_fp16))[name = tensor("op_1921_cast_fp16")]; + tensor var_1922_to_fp16 = const()[name = tensor("op_1922_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_159_cast_fp16 = mul(x = var_1921_cast_fp16, y = var_1922_to_fp16)[name = tensor("aw_chunk_159_cast_fp16")]; + tensor var_1925_equation_0 = const()[name = tensor("op_1925_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1925_cast_fp16 = einsum(equation = var_1925_equation_0, values = (var_1815_cast_fp16, var_1689_cast_fp16))[name = tensor("op_1925_cast_fp16")]; + tensor var_1926_to_fp16 = const()[name = tensor("op_1926_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_161_cast_fp16 = mul(x = var_1925_cast_fp16, y = var_1926_to_fp16)[name = tensor("aw_chunk_161_cast_fp16")]; + tensor var_1929_equation_0 = const()[name = tensor("op_1929_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1929_cast_fp16 = einsum(equation = var_1929_equation_0, values = (var_1815_cast_fp16, var_1696_cast_fp16))[name = tensor("op_1929_cast_fp16")]; + tensor var_1930_to_fp16 = const()[name = tensor("op_1930_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_163_cast_fp16 = mul(x = var_1929_cast_fp16, y = var_1930_to_fp16)[name = tensor("aw_chunk_163_cast_fp16")]; + tensor var_1933_equation_0 = const()[name = tensor("op_1933_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1933_cast_fp16 = einsum(equation = var_1933_equation_0, values = (var_1815_cast_fp16, var_1703_cast_fp16))[name = tensor("op_1933_cast_fp16")]; + tensor var_1934_to_fp16 = const()[name = tensor("op_1934_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_165_cast_fp16 = mul(x = var_1933_cast_fp16, y = var_1934_to_fp16)[name = tensor("aw_chunk_165_cast_fp16")]; + tensor var_1937_equation_0 = const()[name = tensor("op_1937_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1937_cast_fp16 = einsum(equation = var_1937_equation_0, values = (var_1815_cast_fp16, var_1710_cast_fp16))[name = tensor("op_1937_cast_fp16")]; + tensor var_1938_to_fp16 = const()[name = tensor("op_1938_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_167_cast_fp16 = mul(x = var_1937_cast_fp16, y = var_1938_to_fp16)[name = tensor("aw_chunk_167_cast_fp16")]; + tensor var_1941_equation_0 = const()[name = tensor("op_1941_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1941_cast_fp16 = einsum(equation = var_1941_equation_0, values = (var_1819_cast_fp16, var_1717_cast_fp16))[name = tensor("op_1941_cast_fp16")]; + tensor var_1942_to_fp16 = const()[name = tensor("op_1942_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_169_cast_fp16 = mul(x = var_1941_cast_fp16, y = var_1942_to_fp16)[name = tensor("aw_chunk_169_cast_fp16")]; + tensor var_1945_equation_0 = const()[name = tensor("op_1945_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1945_cast_fp16 = einsum(equation = var_1945_equation_0, values = (var_1819_cast_fp16, var_1724_cast_fp16))[name = tensor("op_1945_cast_fp16")]; + tensor var_1946_to_fp16 = const()[name = tensor("op_1946_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_171_cast_fp16 = mul(x = var_1945_cast_fp16, y = var_1946_to_fp16)[name = tensor("aw_chunk_171_cast_fp16")]; + tensor var_1949_equation_0 = const()[name = tensor("op_1949_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1949_cast_fp16 = einsum(equation = var_1949_equation_0, values = (var_1819_cast_fp16, var_1731_cast_fp16))[name = tensor("op_1949_cast_fp16")]; + tensor var_1950_to_fp16 = const()[name = tensor("op_1950_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_173_cast_fp16 = mul(x = var_1949_cast_fp16, y = var_1950_to_fp16)[name = tensor("aw_chunk_173_cast_fp16")]; + tensor var_1953_equation_0 = const()[name = tensor("op_1953_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1953_cast_fp16 = einsum(equation = var_1953_equation_0, values = (var_1819_cast_fp16, var_1738_cast_fp16))[name = tensor("op_1953_cast_fp16")]; + tensor var_1954_to_fp16 = const()[name = tensor("op_1954_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_175_cast_fp16 = mul(x = var_1953_cast_fp16, y = var_1954_to_fp16)[name = tensor("aw_chunk_175_cast_fp16")]; + tensor var_1957_equation_0 = const()[name = tensor("op_1957_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1957_cast_fp16 = einsum(equation = var_1957_equation_0, values = (var_1823_cast_fp16, var_1745_cast_fp16))[name = tensor("op_1957_cast_fp16")]; + tensor var_1958_to_fp16 = const()[name = tensor("op_1958_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_177_cast_fp16 = mul(x = var_1957_cast_fp16, y = var_1958_to_fp16)[name = tensor("aw_chunk_177_cast_fp16")]; + tensor var_1961_equation_0 = const()[name = tensor("op_1961_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1961_cast_fp16 = einsum(equation = var_1961_equation_0, values = (var_1823_cast_fp16, var_1752_cast_fp16))[name = tensor("op_1961_cast_fp16")]; + tensor var_1962_to_fp16 = const()[name = tensor("op_1962_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_179_cast_fp16 = mul(x = var_1961_cast_fp16, y = var_1962_to_fp16)[name = tensor("aw_chunk_179_cast_fp16")]; + tensor var_1965_equation_0 = const()[name = tensor("op_1965_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1965_cast_fp16 = einsum(equation = var_1965_equation_0, values = (var_1823_cast_fp16, var_1759_cast_fp16))[name = tensor("op_1965_cast_fp16")]; + tensor var_1966_to_fp16 = const()[name = tensor("op_1966_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_181_cast_fp16 = mul(x = var_1965_cast_fp16, y = var_1966_to_fp16)[name = tensor("aw_chunk_181_cast_fp16")]; + tensor var_1969_equation_0 = const()[name = tensor("op_1969_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1969_cast_fp16 = einsum(equation = var_1969_equation_0, values = (var_1823_cast_fp16, var_1766_cast_fp16))[name = tensor("op_1969_cast_fp16")]; + tensor var_1970_to_fp16 = const()[name = tensor("op_1970_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_183_cast_fp16 = mul(x = var_1969_cast_fp16, y = var_1970_to_fp16)[name = tensor("aw_chunk_183_cast_fp16")]; + tensor var_1973_equation_0 = const()[name = tensor("op_1973_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1973_cast_fp16 = einsum(equation = var_1973_equation_0, values = (var_1827_cast_fp16, var_1773_cast_fp16))[name = tensor("op_1973_cast_fp16")]; + tensor var_1974_to_fp16 = const()[name = tensor("op_1974_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_185_cast_fp16 = mul(x = var_1973_cast_fp16, y = var_1974_to_fp16)[name = tensor("aw_chunk_185_cast_fp16")]; + tensor var_1977_equation_0 = const()[name = tensor("op_1977_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1977_cast_fp16 = einsum(equation = var_1977_equation_0, values = (var_1827_cast_fp16, var_1780_cast_fp16))[name = tensor("op_1977_cast_fp16")]; + tensor var_1978_to_fp16 = const()[name = tensor("op_1978_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_187_cast_fp16 = mul(x = var_1977_cast_fp16, y = var_1978_to_fp16)[name = tensor("aw_chunk_187_cast_fp16")]; + tensor var_1981_equation_0 = const()[name = tensor("op_1981_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1981_cast_fp16 = einsum(equation = var_1981_equation_0, values = (var_1827_cast_fp16, var_1787_cast_fp16))[name = tensor("op_1981_cast_fp16")]; + tensor var_1982_to_fp16 = const()[name = tensor("op_1982_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_189_cast_fp16 = mul(x = var_1981_cast_fp16, y = var_1982_to_fp16)[name = tensor("aw_chunk_189_cast_fp16")]; + tensor var_1985_equation_0 = const()[name = tensor("op_1985_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1985_cast_fp16 = einsum(equation = var_1985_equation_0, values = (var_1827_cast_fp16, var_1794_cast_fp16))[name = tensor("op_1985_cast_fp16")]; + tensor var_1986_to_fp16 = const()[name = tensor("op_1986_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_191_cast_fp16 = mul(x = var_1985_cast_fp16, y = var_1986_to_fp16)[name = tensor("aw_chunk_191_cast_fp16")]; + tensor var_1988_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_129_cast_fp16)[name = tensor("op_1988_cast_fp16")]; + tensor var_1989_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_131_cast_fp16)[name = tensor("op_1989_cast_fp16")]; + tensor var_1990_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_133_cast_fp16)[name = tensor("op_1990_cast_fp16")]; + tensor var_1991_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_135_cast_fp16)[name = tensor("op_1991_cast_fp16")]; + tensor var_1992_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_137_cast_fp16)[name = tensor("op_1992_cast_fp16")]; + tensor var_1993_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_139_cast_fp16)[name = tensor("op_1993_cast_fp16")]; + tensor var_1994_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_141_cast_fp16)[name = tensor("op_1994_cast_fp16")]; + tensor var_1995_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_143_cast_fp16)[name = tensor("op_1995_cast_fp16")]; + tensor var_1996_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_145_cast_fp16)[name = tensor("op_1996_cast_fp16")]; + tensor var_1997_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_147_cast_fp16)[name = tensor("op_1997_cast_fp16")]; + tensor var_1998_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_149_cast_fp16)[name = tensor("op_1998_cast_fp16")]; + tensor var_1999_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_151_cast_fp16)[name = tensor("op_1999_cast_fp16")]; + tensor var_2000_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_153_cast_fp16)[name = tensor("op_2000_cast_fp16")]; + tensor var_2001_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_155_cast_fp16)[name = tensor("op_2001_cast_fp16")]; + tensor var_2002_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_157_cast_fp16)[name = tensor("op_2002_cast_fp16")]; + tensor var_2003_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_159_cast_fp16)[name = tensor("op_2003_cast_fp16")]; + tensor var_2004_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_161_cast_fp16)[name = tensor("op_2004_cast_fp16")]; + tensor var_2005_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_163_cast_fp16)[name = tensor("op_2005_cast_fp16")]; + tensor var_2006_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_165_cast_fp16)[name = tensor("op_2006_cast_fp16")]; + tensor var_2007_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_167_cast_fp16)[name = tensor("op_2007_cast_fp16")]; + tensor var_2008_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_169_cast_fp16)[name = tensor("op_2008_cast_fp16")]; + tensor var_2009_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_171_cast_fp16)[name = tensor("op_2009_cast_fp16")]; + tensor var_2010_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_173_cast_fp16)[name = tensor("op_2010_cast_fp16")]; + tensor var_2011_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_175_cast_fp16)[name = tensor("op_2011_cast_fp16")]; + tensor var_2012_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_177_cast_fp16)[name = tensor("op_2012_cast_fp16")]; + tensor var_2013_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_179_cast_fp16)[name = tensor("op_2013_cast_fp16")]; + tensor var_2014_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_181_cast_fp16)[name = tensor("op_2014_cast_fp16")]; + tensor var_2015_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_183_cast_fp16)[name = tensor("op_2015_cast_fp16")]; + tensor var_2016_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_185_cast_fp16)[name = tensor("op_2016_cast_fp16")]; + tensor var_2017_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_187_cast_fp16)[name = tensor("op_2017_cast_fp16")]; + tensor var_2018_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_189_cast_fp16)[name = tensor("op_2018_cast_fp16")]; + tensor var_2019_cast_fp16 = softmax(axis = var_1485, x = aw_chunk_191_cast_fp16)[name = tensor("op_2019_cast_fp16")]; + tensor var_2021_equation_0 = const()[name = tensor("op_2021_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2021_cast_fp16 = einsum(equation = var_2021_equation_0, values = (var_1829_cast_fp16, var_1988_cast_fp16))[name = tensor("op_2021_cast_fp16")]; + tensor var_2023_equation_0 = const()[name = tensor("op_2023_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2023_cast_fp16 = einsum(equation = var_2023_equation_0, values = (var_1829_cast_fp16, var_1989_cast_fp16))[name = tensor("op_2023_cast_fp16")]; + tensor var_2025_equation_0 = const()[name = tensor("op_2025_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2025_cast_fp16 = einsum(equation = var_2025_equation_0, values = (var_1829_cast_fp16, var_1990_cast_fp16))[name = tensor("op_2025_cast_fp16")]; + tensor var_2027_equation_0 = const()[name = tensor("op_2027_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2027_cast_fp16 = einsum(equation = var_2027_equation_0, values = (var_1829_cast_fp16, var_1991_cast_fp16))[name = tensor("op_2027_cast_fp16")]; + tensor var_2029_equation_0 = const()[name = tensor("op_2029_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2029_cast_fp16 = einsum(equation = var_2029_equation_0, values = (var_1833_cast_fp16, var_1992_cast_fp16))[name = tensor("op_2029_cast_fp16")]; + tensor var_2031_equation_0 = const()[name = tensor("op_2031_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2031_cast_fp16 = einsum(equation = var_2031_equation_0, values = (var_1833_cast_fp16, var_1993_cast_fp16))[name = tensor("op_2031_cast_fp16")]; + tensor var_2033_equation_0 = const()[name = tensor("op_2033_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2033_cast_fp16 = einsum(equation = var_2033_equation_0, values = (var_1833_cast_fp16, var_1994_cast_fp16))[name = tensor("op_2033_cast_fp16")]; + tensor var_2035_equation_0 = const()[name = tensor("op_2035_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2035_cast_fp16 = einsum(equation = var_2035_equation_0, values = (var_1833_cast_fp16, var_1995_cast_fp16))[name = tensor("op_2035_cast_fp16")]; + tensor var_2037_equation_0 = const()[name = tensor("op_2037_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2037_cast_fp16 = einsum(equation = var_2037_equation_0, values = (var_1837_cast_fp16, var_1996_cast_fp16))[name = tensor("op_2037_cast_fp16")]; + tensor var_2039_equation_0 = const()[name = tensor("op_2039_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2039_cast_fp16 = einsum(equation = var_2039_equation_0, values = (var_1837_cast_fp16, var_1997_cast_fp16))[name = tensor("op_2039_cast_fp16")]; + tensor var_2041_equation_0 = const()[name = tensor("op_2041_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2041_cast_fp16 = einsum(equation = var_2041_equation_0, values = (var_1837_cast_fp16, var_1998_cast_fp16))[name = tensor("op_2041_cast_fp16")]; + tensor var_2043_equation_0 = const()[name = tensor("op_2043_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2043_cast_fp16 = einsum(equation = var_2043_equation_0, values = (var_1837_cast_fp16, var_1999_cast_fp16))[name = tensor("op_2043_cast_fp16")]; + tensor var_2045_equation_0 = const()[name = tensor("op_2045_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2045_cast_fp16 = einsum(equation = var_2045_equation_0, values = (var_1841_cast_fp16, var_2000_cast_fp16))[name = tensor("op_2045_cast_fp16")]; + tensor var_2047_equation_0 = const()[name = tensor("op_2047_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2047_cast_fp16 = einsum(equation = var_2047_equation_0, values = (var_1841_cast_fp16, var_2001_cast_fp16))[name = tensor("op_2047_cast_fp16")]; + tensor var_2049_equation_0 = const()[name = tensor("op_2049_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2049_cast_fp16 = einsum(equation = var_2049_equation_0, values = (var_1841_cast_fp16, var_2002_cast_fp16))[name = tensor("op_2049_cast_fp16")]; + tensor var_2051_equation_0 = const()[name = tensor("op_2051_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2051_cast_fp16 = einsum(equation = var_2051_equation_0, values = (var_1841_cast_fp16, var_2003_cast_fp16))[name = tensor("op_2051_cast_fp16")]; + tensor var_2053_equation_0 = const()[name = tensor("op_2053_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2053_cast_fp16 = einsum(equation = var_2053_equation_0, values = (var_1845_cast_fp16, var_2004_cast_fp16))[name = tensor("op_2053_cast_fp16")]; + tensor var_2055_equation_0 = const()[name = tensor("op_2055_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2055_cast_fp16 = einsum(equation = var_2055_equation_0, values = (var_1845_cast_fp16, var_2005_cast_fp16))[name = tensor("op_2055_cast_fp16")]; + tensor var_2057_equation_0 = const()[name = tensor("op_2057_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2057_cast_fp16 = einsum(equation = var_2057_equation_0, values = (var_1845_cast_fp16, var_2006_cast_fp16))[name = tensor("op_2057_cast_fp16")]; + tensor var_2059_equation_0 = const()[name = tensor("op_2059_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2059_cast_fp16 = einsum(equation = var_2059_equation_0, values = (var_1845_cast_fp16, var_2007_cast_fp16))[name = tensor("op_2059_cast_fp16")]; + tensor var_2061_equation_0 = const()[name = tensor("op_2061_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2061_cast_fp16 = einsum(equation = var_2061_equation_0, values = (var_1849_cast_fp16, var_2008_cast_fp16))[name = tensor("op_2061_cast_fp16")]; + tensor var_2063_equation_0 = const()[name = tensor("op_2063_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2063_cast_fp16 = einsum(equation = var_2063_equation_0, values = (var_1849_cast_fp16, var_2009_cast_fp16))[name = tensor("op_2063_cast_fp16")]; + tensor var_2065_equation_0 = const()[name = tensor("op_2065_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2065_cast_fp16 = einsum(equation = var_2065_equation_0, values = (var_1849_cast_fp16, var_2010_cast_fp16))[name = tensor("op_2065_cast_fp16")]; + tensor var_2067_equation_0 = const()[name = tensor("op_2067_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2067_cast_fp16 = einsum(equation = var_2067_equation_0, values = (var_1849_cast_fp16, var_2011_cast_fp16))[name = tensor("op_2067_cast_fp16")]; + tensor var_2069_equation_0 = const()[name = tensor("op_2069_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2069_cast_fp16 = einsum(equation = var_2069_equation_0, values = (var_1853_cast_fp16, var_2012_cast_fp16))[name = tensor("op_2069_cast_fp16")]; + tensor var_2071_equation_0 = const()[name = tensor("op_2071_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2071_cast_fp16 = einsum(equation = var_2071_equation_0, values = (var_1853_cast_fp16, var_2013_cast_fp16))[name = tensor("op_2071_cast_fp16")]; + tensor var_2073_equation_0 = const()[name = tensor("op_2073_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2073_cast_fp16 = einsum(equation = var_2073_equation_0, values = (var_1853_cast_fp16, var_2014_cast_fp16))[name = tensor("op_2073_cast_fp16")]; + tensor var_2075_equation_0 = const()[name = tensor("op_2075_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2075_cast_fp16 = einsum(equation = var_2075_equation_0, values = (var_1853_cast_fp16, var_2015_cast_fp16))[name = tensor("op_2075_cast_fp16")]; + tensor var_2077_equation_0 = const()[name = tensor("op_2077_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2077_cast_fp16 = einsum(equation = var_2077_equation_0, values = (var_1857_cast_fp16, var_2016_cast_fp16))[name = tensor("op_2077_cast_fp16")]; + tensor var_2079_equation_0 = const()[name = tensor("op_2079_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2079_cast_fp16 = einsum(equation = var_2079_equation_0, values = (var_1857_cast_fp16, var_2017_cast_fp16))[name = tensor("op_2079_cast_fp16")]; + tensor var_2081_equation_0 = const()[name = tensor("op_2081_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2081_cast_fp16 = einsum(equation = var_2081_equation_0, values = (var_1857_cast_fp16, var_2018_cast_fp16))[name = tensor("op_2081_cast_fp16")]; + tensor var_2083_equation_0 = const()[name = tensor("op_2083_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2083_cast_fp16 = einsum(equation = var_2083_equation_0, values = (var_1857_cast_fp16, var_2019_cast_fp16))[name = tensor("op_2083_cast_fp16")]; + tensor var_2085_interleave_0 = const()[name = tensor("op_2085_interleave_0"), val = tensor(false)]; + tensor var_2085_cast_fp16 = concat(axis = var_1472, interleave = var_2085_interleave_0, values = (var_2021_cast_fp16, var_2023_cast_fp16, var_2025_cast_fp16, var_2027_cast_fp16))[name = tensor("op_2085_cast_fp16")]; + tensor var_2087_interleave_0 = const()[name = tensor("op_2087_interleave_0"), val = tensor(false)]; + tensor var_2087_cast_fp16 = concat(axis = var_1472, interleave = var_2087_interleave_0, values = (var_2029_cast_fp16, var_2031_cast_fp16, var_2033_cast_fp16, var_2035_cast_fp16))[name = tensor("op_2087_cast_fp16")]; + tensor var_2089_interleave_0 = const()[name = tensor("op_2089_interleave_0"), val = tensor(false)]; + tensor var_2089_cast_fp16 = concat(axis = var_1472, interleave = var_2089_interleave_0, values = (var_2037_cast_fp16, var_2039_cast_fp16, var_2041_cast_fp16, var_2043_cast_fp16))[name = tensor("op_2089_cast_fp16")]; + tensor var_2091_interleave_0 = const()[name = tensor("op_2091_interleave_0"), val = tensor(false)]; + tensor var_2091_cast_fp16 = concat(axis = var_1472, interleave = var_2091_interleave_0, values = (var_2045_cast_fp16, var_2047_cast_fp16, var_2049_cast_fp16, var_2051_cast_fp16))[name = tensor("op_2091_cast_fp16")]; + tensor var_2093_interleave_0 = const()[name = tensor("op_2093_interleave_0"), val = tensor(false)]; + tensor var_2093_cast_fp16 = concat(axis = var_1472, interleave = var_2093_interleave_0, values = (var_2053_cast_fp16, var_2055_cast_fp16, var_2057_cast_fp16, var_2059_cast_fp16))[name = tensor("op_2093_cast_fp16")]; + tensor var_2095_interleave_0 = const()[name = tensor("op_2095_interleave_0"), val = tensor(false)]; + tensor var_2095_cast_fp16 = concat(axis = var_1472, interleave = var_2095_interleave_0, values = (var_2061_cast_fp16, var_2063_cast_fp16, var_2065_cast_fp16, var_2067_cast_fp16))[name = tensor("op_2095_cast_fp16")]; + tensor var_2097_interleave_0 = const()[name = tensor("op_2097_interleave_0"), val = tensor(false)]; + tensor var_2097_cast_fp16 = concat(axis = var_1472, interleave = var_2097_interleave_0, values = (var_2069_cast_fp16, var_2071_cast_fp16, var_2073_cast_fp16, var_2075_cast_fp16))[name = tensor("op_2097_cast_fp16")]; + tensor var_2099_interleave_0 = const()[name = tensor("op_2099_interleave_0"), val = tensor(false)]; + tensor var_2099_cast_fp16 = concat(axis = var_1472, interleave = var_2099_interleave_0, values = (var_2077_cast_fp16, var_2079_cast_fp16, var_2081_cast_fp16, var_2083_cast_fp16))[name = tensor("op_2099_cast_fp16")]; + tensor input_17_interleave_0 = const()[name = tensor("input_17_interleave_0"), val = tensor(false)]; + tensor input_17_cast_fp16 = concat(axis = var_1485, interleave = input_17_interleave_0, values = (var_2085_cast_fp16, var_2087_cast_fp16, var_2089_cast_fp16, var_2091_cast_fp16, var_2093_cast_fp16, var_2095_cast_fp16, var_2097_cast_fp16, var_2099_cast_fp16))[name = tensor("input_17_cast_fp16")]; + tensor var_2104 = const()[name = tensor("op_2104"), val = tensor([1, 1])]; + tensor var_2106 = const()[name = tensor("op_2106"), val = tensor([1, 1])]; + tensor obj_11_pad_type_0 = const()[name = tensor("obj_11_pad_type_0"), val = tensor("custom")]; + tensor obj_11_pad_0 = const()[name = tensor("obj_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17546048)))]; + tensor layers_2_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18070400)))]; + tensor obj_11_cast_fp16 = conv(bias = layers_2_self_attn_o_proj_bias_to_fp16, dilations = var_2106, groups = var_1485, pad = obj_11_pad_0, pad_type = obj_11_pad_type_0, strides = var_2104, weight = layers_2_self_attn_o_proj_weight_to_fp16, x = input_17_cast_fp16)[name = tensor("obj_11_cast_fp16")]; + tensor inputs_11_cast_fp16 = add(x = inputs_9_cast_fp16, y = obj_11_cast_fp16)[name = tensor("inputs_11_cast_fp16")]; + tensor var_2112 = const()[name = tensor("op_2112"), val = tensor([1])]; + tensor channels_mean_11_cast_fp16 = reduce_mean(axes = var_2112, keep_dims = var_1486, x = inputs_11_cast_fp16)[name = tensor("channels_mean_11_cast_fp16")]; + tensor zero_mean_11_cast_fp16 = sub(x = inputs_11_cast_fp16, y = channels_mean_11_cast_fp16)[name = tensor("zero_mean_11_cast_fp16")]; + tensor zero_mean_sq_11_cast_fp16 = mul(x = zero_mean_11_cast_fp16, y = zero_mean_11_cast_fp16)[name = tensor("zero_mean_sq_11_cast_fp16")]; + tensor var_2116 = const()[name = tensor("op_2116"), val = tensor([1])]; + tensor var_2117_cast_fp16 = reduce_mean(axes = var_2116, keep_dims = var_1486, x = zero_mean_sq_11_cast_fp16)[name = tensor("op_2117_cast_fp16")]; + tensor var_2118_to_fp16 = const()[name = tensor("op_2118_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2119_cast_fp16 = add(x = var_2117_cast_fp16, y = var_2118_to_fp16)[name = tensor("op_2119_cast_fp16")]; + tensor denom_11_epsilon_0_to_fp16 = const()[name = tensor("denom_11_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_11_cast_fp16 = rsqrt(epsilon = denom_11_epsilon_0_to_fp16, x = var_2119_cast_fp16)[name = tensor("denom_11_cast_fp16")]; + tensor out_11_cast_fp16 = mul(x = zero_mean_11_cast_fp16, y = denom_11_cast_fp16)[name = tensor("out_11_cast_fp16")]; + tensor input_19_gamma_0_to_fp16 = const()[name = tensor("input_19_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18071488)))]; + tensor input_19_beta_0_to_fp16 = const()[name = tensor("input_19_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18072576)))]; + tensor input_19_epsilon_0_to_fp16 = const()[name = tensor("input_19_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_19_cast_fp16 = batch_norm(beta = input_19_beta_0_to_fp16, epsilon = input_19_epsilon_0_to_fp16, gamma = input_19_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_11_cast_fp16)[name = tensor("input_19_cast_fp16")]; + tensor var_2130 = const()[name = tensor("op_2130"), val = tensor([1, 1])]; + tensor var_2132 = const()[name = tensor("op_2132"), val = tensor([1, 1])]; + tensor input_21_pad_type_0 = const()[name = tensor("input_21_pad_type_0"), val = tensor("custom")]; + tensor input_21_pad_0 = const()[name = tensor("input_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_fc1_weight_to_fp16 = const()[name = tensor("layers_2_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18073664)))]; + tensor layers_2_fc1_bias_to_fp16 = const()[name = tensor("layers_2_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20170880)))]; + tensor input_21_cast_fp16 = conv(bias = layers_2_fc1_bias_to_fp16, dilations = var_2132, groups = var_1485, pad = input_21_pad_0, pad_type = input_21_pad_type_0, strides = var_2130, weight = layers_2_fc1_weight_to_fp16, x = input_19_cast_fp16)[name = tensor("input_21_cast_fp16")]; + tensor input_23_mode_0 = const()[name = tensor("input_23_mode_0"), val = tensor("EXACT")]; + tensor input_23_cast_fp16 = gelu(mode = input_23_mode_0, x = input_21_cast_fp16)[name = tensor("input_23_cast_fp16")]; + tensor var_2138 = const()[name = tensor("op_2138"), val = tensor([1, 1])]; + tensor var_2140 = const()[name = tensor("op_2140"), val = tensor([1, 1])]; + tensor hidden_states_9_pad_type_0 = const()[name = tensor("hidden_states_9_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_9_pad_0 = const()[name = tensor("hidden_states_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_fc2_weight_to_fp16 = const()[name = tensor("layers_2_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20175040)))]; + tensor layers_2_fc2_bias_to_fp16 = const()[name = tensor("layers_2_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22272256)))]; + tensor hidden_states_9_cast_fp16 = conv(bias = layers_2_fc2_bias_to_fp16, dilations = var_2140, groups = var_1485, pad = hidden_states_9_pad_0, pad_type = hidden_states_9_pad_type_0, strides = var_2138, weight = layers_2_fc2_weight_to_fp16, x = input_23_cast_fp16)[name = tensor("hidden_states_9_cast_fp16")]; + tensor inputs_13_cast_fp16 = add(x = inputs_11_cast_fp16, y = hidden_states_9_cast_fp16)[name = tensor("inputs_13_cast_fp16")]; + tensor var_2147 = const()[name = tensor("op_2147"), val = tensor(3)]; + tensor var_2160 = const()[name = tensor("op_2160"), val = tensor(1)]; + tensor var_2161 = const()[name = tensor("op_2161"), val = tensor(true)]; + tensor var_2171 = const()[name = tensor("op_2171"), val = tensor([1])]; + tensor channels_mean_13_cast_fp16 = reduce_mean(axes = var_2171, keep_dims = var_2161, x = inputs_13_cast_fp16)[name = tensor("channels_mean_13_cast_fp16")]; + tensor zero_mean_13_cast_fp16 = sub(x = inputs_13_cast_fp16, y = channels_mean_13_cast_fp16)[name = tensor("zero_mean_13_cast_fp16")]; + tensor zero_mean_sq_13_cast_fp16 = mul(x = zero_mean_13_cast_fp16, y = zero_mean_13_cast_fp16)[name = tensor("zero_mean_sq_13_cast_fp16")]; + tensor var_2175 = const()[name = tensor("op_2175"), val = tensor([1])]; + tensor var_2176_cast_fp16 = reduce_mean(axes = var_2175, keep_dims = var_2161, x = zero_mean_sq_13_cast_fp16)[name = tensor("op_2176_cast_fp16")]; + tensor var_2177_to_fp16 = const()[name = tensor("op_2177_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2178_cast_fp16 = add(x = var_2176_cast_fp16, y = var_2177_to_fp16)[name = tensor("op_2178_cast_fp16")]; + tensor denom_13_epsilon_0_to_fp16 = const()[name = tensor("denom_13_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_13_cast_fp16 = rsqrt(epsilon = denom_13_epsilon_0_to_fp16, x = var_2178_cast_fp16)[name = tensor("denom_13_cast_fp16")]; + tensor out_13_cast_fp16 = mul(x = zero_mean_13_cast_fp16, y = denom_13_cast_fp16)[name = tensor("out_13_cast_fp16")]; + tensor obj_13_gamma_0_to_fp16 = const()[name = tensor("obj_13_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22273344)))]; + tensor obj_13_beta_0_to_fp16 = const()[name = tensor("obj_13_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22274432)))]; + tensor obj_13_epsilon_0_to_fp16 = const()[name = tensor("obj_13_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_13_cast_fp16 = batch_norm(beta = obj_13_beta_0_to_fp16, epsilon = obj_13_epsilon_0_to_fp16, gamma = obj_13_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_13_cast_fp16)[name = tensor("obj_13_cast_fp16")]; + tensor var_2193 = const()[name = tensor("op_2193"), val = tensor([1, 1])]; + tensor var_2195 = const()[name = tensor("op_2195"), val = tensor([1, 1])]; + tensor query_7_pad_type_0 = const()[name = tensor("query_7_pad_type_0"), val = tensor("custom")]; + tensor query_7_pad_0 = const()[name = tensor("query_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22275520)))]; + tensor layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22799872)))]; + tensor query_7_cast_fp16 = conv(bias = layers_3_self_attn_q_proj_bias_to_fp16, dilations = var_2195, groups = var_2160, pad = query_7_pad_0, pad_type = query_7_pad_type_0, strides = var_2193, weight = layers_3_self_attn_q_proj_weight_to_fp16, x = obj_13_cast_fp16)[name = tensor("query_7_cast_fp16")]; + tensor var_2199 = const()[name = tensor("op_2199"), val = tensor([1, 1])]; + tensor var_2201 = const()[name = tensor("op_2201"), val = tensor([1, 1])]; + tensor key_7_pad_type_0 = const()[name = tensor("key_7_pad_type_0"), val = tensor("custom")]; + tensor key_7_pad_0 = const()[name = tensor("key_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22800960)))]; + tensor key_7_cast_fp16 = conv(dilations = var_2201, groups = var_2160, pad = key_7_pad_0, pad_type = key_7_pad_type_0, strides = var_2199, weight = layers_3_self_attn_k_proj_weight_to_fp16, x = obj_13_cast_fp16)[name = tensor("key_7_cast_fp16")]; + tensor var_2206 = const()[name = tensor("op_2206"), val = tensor([1, 1])]; + tensor var_2208 = const()[name = tensor("op_2208"), val = tensor([1, 1])]; + tensor value_7_pad_type_0 = const()[name = tensor("value_7_pad_type_0"), val = tensor("custom")]; + tensor value_7_pad_0 = const()[name = tensor("value_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23325312)))]; + tensor layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23849664)))]; + tensor value_7_cast_fp16 = conv(bias = layers_3_self_attn_v_proj_bias_to_fp16, dilations = var_2208, groups = var_2160, pad = value_7_pad_0, pad_type = value_7_pad_type_0, strides = var_2206, weight = layers_3_self_attn_v_proj_weight_to_fp16, x = obj_13_cast_fp16)[name = tensor("value_7_cast_fp16")]; + tensor var_2215_begin_0 = const()[name = tensor("op_2215_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2215_end_0 = const()[name = tensor("op_2215_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2215_end_mask_0 = const()[name = tensor("op_2215_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2215_cast_fp16 = slice_by_index(begin = var_2215_begin_0, end = var_2215_end_0, end_mask = var_2215_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_2215_cast_fp16")]; + tensor var_2219_begin_0 = const()[name = tensor("op_2219_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_2219_end_0 = const()[name = tensor("op_2219_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_2219_end_mask_0 = const()[name = tensor("op_2219_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2219_cast_fp16 = slice_by_index(begin = var_2219_begin_0, end = var_2219_end_0, end_mask = var_2219_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_2219_cast_fp16")]; + tensor var_2223_begin_0 = const()[name = tensor("op_2223_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_2223_end_0 = const()[name = tensor("op_2223_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_2223_end_mask_0 = const()[name = tensor("op_2223_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2223_cast_fp16 = slice_by_index(begin = var_2223_begin_0, end = var_2223_end_0, end_mask = var_2223_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_2223_cast_fp16")]; + tensor var_2227_begin_0 = const()[name = tensor("op_2227_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_2227_end_0 = const()[name = tensor("op_2227_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_2227_end_mask_0 = const()[name = tensor("op_2227_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2227_cast_fp16 = slice_by_index(begin = var_2227_begin_0, end = var_2227_end_0, end_mask = var_2227_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_2227_cast_fp16")]; + tensor var_2231_begin_0 = const()[name = tensor("op_2231_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_2231_end_0 = const()[name = tensor("op_2231_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_2231_end_mask_0 = const()[name = tensor("op_2231_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2231_cast_fp16 = slice_by_index(begin = var_2231_begin_0, end = var_2231_end_0, end_mask = var_2231_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_2231_cast_fp16")]; + tensor var_2235_begin_0 = const()[name = tensor("op_2235_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_2235_end_0 = const()[name = tensor("op_2235_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_2235_end_mask_0 = const()[name = tensor("op_2235_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2235_cast_fp16 = slice_by_index(begin = var_2235_begin_0, end = var_2235_end_0, end_mask = var_2235_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_2235_cast_fp16")]; + tensor var_2239_begin_0 = const()[name = tensor("op_2239_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_2239_end_0 = const()[name = tensor("op_2239_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_2239_end_mask_0 = const()[name = tensor("op_2239_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2239_cast_fp16 = slice_by_index(begin = var_2239_begin_0, end = var_2239_end_0, end_mask = var_2239_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_2239_cast_fp16")]; + tensor var_2243_begin_0 = const()[name = tensor("op_2243_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_2243_end_0 = const()[name = tensor("op_2243_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_2243_end_mask_0 = const()[name = tensor("op_2243_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2243_cast_fp16 = slice_by_index(begin = var_2243_begin_0, end = var_2243_end_0, end_mask = var_2243_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_2243_cast_fp16")]; + tensor var_2252_begin_0 = const()[name = tensor("op_2252_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2252_end_0 = const()[name = tensor("op_2252_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2252_end_mask_0 = const()[name = tensor("op_2252_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2252_cast_fp16 = slice_by_index(begin = var_2252_begin_0, end = var_2252_end_0, end_mask = var_2252_end_mask_0, x = var_2215_cast_fp16)[name = tensor("op_2252_cast_fp16")]; + tensor var_2259_begin_0 = const()[name = tensor("op_2259_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2259_end_0 = const()[name = tensor("op_2259_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2259_end_mask_0 = const()[name = tensor("op_2259_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2259_cast_fp16 = slice_by_index(begin = var_2259_begin_0, end = var_2259_end_0, end_mask = var_2259_end_mask_0, x = var_2215_cast_fp16)[name = tensor("op_2259_cast_fp16")]; + tensor var_2266_begin_0 = const()[name = tensor("op_2266_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2266_end_0 = const()[name = tensor("op_2266_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2266_end_mask_0 = const()[name = tensor("op_2266_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2266_cast_fp16 = slice_by_index(begin = var_2266_begin_0, end = var_2266_end_0, end_mask = var_2266_end_mask_0, x = var_2215_cast_fp16)[name = tensor("op_2266_cast_fp16")]; + tensor var_2273_begin_0 = const()[name = tensor("op_2273_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2273_end_0 = const()[name = tensor("op_2273_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2273_end_mask_0 = const()[name = tensor("op_2273_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2273_cast_fp16 = slice_by_index(begin = var_2273_begin_0, end = var_2273_end_0, end_mask = var_2273_end_mask_0, x = var_2215_cast_fp16)[name = tensor("op_2273_cast_fp16")]; + tensor var_2280_begin_0 = const()[name = tensor("op_2280_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2280_end_0 = const()[name = tensor("op_2280_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2280_end_mask_0 = const()[name = tensor("op_2280_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2280_cast_fp16 = slice_by_index(begin = var_2280_begin_0, end = var_2280_end_0, end_mask = var_2280_end_mask_0, x = var_2219_cast_fp16)[name = tensor("op_2280_cast_fp16")]; + tensor var_2287_begin_0 = const()[name = tensor("op_2287_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2287_end_0 = const()[name = tensor("op_2287_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2287_end_mask_0 = const()[name = tensor("op_2287_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2287_cast_fp16 = slice_by_index(begin = var_2287_begin_0, end = var_2287_end_0, end_mask = var_2287_end_mask_0, x = var_2219_cast_fp16)[name = tensor("op_2287_cast_fp16")]; + tensor var_2294_begin_0 = const()[name = tensor("op_2294_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2294_end_0 = const()[name = tensor("op_2294_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2294_end_mask_0 = const()[name = tensor("op_2294_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2294_cast_fp16 = slice_by_index(begin = var_2294_begin_0, end = var_2294_end_0, end_mask = var_2294_end_mask_0, x = var_2219_cast_fp16)[name = tensor("op_2294_cast_fp16")]; + tensor var_2301_begin_0 = const()[name = tensor("op_2301_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2301_end_0 = const()[name = tensor("op_2301_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2301_end_mask_0 = const()[name = tensor("op_2301_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2301_cast_fp16 = slice_by_index(begin = var_2301_begin_0, end = var_2301_end_0, end_mask = var_2301_end_mask_0, x = var_2219_cast_fp16)[name = tensor("op_2301_cast_fp16")]; + tensor var_2308_begin_0 = const()[name = tensor("op_2308_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2308_end_0 = const()[name = tensor("op_2308_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2308_end_mask_0 = const()[name = tensor("op_2308_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2308_cast_fp16 = slice_by_index(begin = var_2308_begin_0, end = var_2308_end_0, end_mask = var_2308_end_mask_0, x = var_2223_cast_fp16)[name = tensor("op_2308_cast_fp16")]; + tensor var_2315_begin_0 = const()[name = tensor("op_2315_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2315_end_0 = const()[name = tensor("op_2315_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2315_end_mask_0 = const()[name = tensor("op_2315_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2315_cast_fp16 = slice_by_index(begin = var_2315_begin_0, end = var_2315_end_0, end_mask = var_2315_end_mask_0, x = var_2223_cast_fp16)[name = tensor("op_2315_cast_fp16")]; + tensor var_2322_begin_0 = const()[name = tensor("op_2322_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2322_end_0 = const()[name = tensor("op_2322_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2322_end_mask_0 = const()[name = tensor("op_2322_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2322_cast_fp16 = slice_by_index(begin = var_2322_begin_0, end = var_2322_end_0, end_mask = var_2322_end_mask_0, x = var_2223_cast_fp16)[name = tensor("op_2322_cast_fp16")]; + tensor var_2329_begin_0 = const()[name = tensor("op_2329_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2329_end_0 = const()[name = tensor("op_2329_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2329_end_mask_0 = const()[name = tensor("op_2329_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2329_cast_fp16 = slice_by_index(begin = var_2329_begin_0, end = var_2329_end_0, end_mask = var_2329_end_mask_0, x = var_2223_cast_fp16)[name = tensor("op_2329_cast_fp16")]; + tensor var_2336_begin_0 = const()[name = tensor("op_2336_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2336_end_0 = const()[name = tensor("op_2336_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2336_end_mask_0 = const()[name = tensor("op_2336_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2336_cast_fp16 = slice_by_index(begin = var_2336_begin_0, end = var_2336_end_0, end_mask = var_2336_end_mask_0, x = var_2227_cast_fp16)[name = tensor("op_2336_cast_fp16")]; + tensor var_2343_begin_0 = const()[name = tensor("op_2343_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2343_end_0 = const()[name = tensor("op_2343_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2343_end_mask_0 = const()[name = tensor("op_2343_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2343_cast_fp16 = slice_by_index(begin = var_2343_begin_0, end = var_2343_end_0, end_mask = var_2343_end_mask_0, x = var_2227_cast_fp16)[name = tensor("op_2343_cast_fp16")]; + tensor var_2350_begin_0 = const()[name = tensor("op_2350_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2350_end_0 = const()[name = tensor("op_2350_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2350_end_mask_0 = const()[name = tensor("op_2350_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2350_cast_fp16 = slice_by_index(begin = var_2350_begin_0, end = var_2350_end_0, end_mask = var_2350_end_mask_0, x = var_2227_cast_fp16)[name = tensor("op_2350_cast_fp16")]; + tensor var_2357_begin_0 = const()[name = tensor("op_2357_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2357_end_0 = const()[name = tensor("op_2357_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2357_end_mask_0 = const()[name = tensor("op_2357_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2357_cast_fp16 = slice_by_index(begin = var_2357_begin_0, end = var_2357_end_0, end_mask = var_2357_end_mask_0, x = var_2227_cast_fp16)[name = tensor("op_2357_cast_fp16")]; + tensor var_2364_begin_0 = const()[name = tensor("op_2364_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2364_end_0 = const()[name = tensor("op_2364_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2364_end_mask_0 = const()[name = tensor("op_2364_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2364_cast_fp16 = slice_by_index(begin = var_2364_begin_0, end = var_2364_end_0, end_mask = var_2364_end_mask_0, x = var_2231_cast_fp16)[name = tensor("op_2364_cast_fp16")]; + tensor var_2371_begin_0 = const()[name = tensor("op_2371_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2371_end_0 = const()[name = tensor("op_2371_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2371_end_mask_0 = const()[name = tensor("op_2371_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2371_cast_fp16 = slice_by_index(begin = var_2371_begin_0, end = var_2371_end_0, end_mask = var_2371_end_mask_0, x = var_2231_cast_fp16)[name = tensor("op_2371_cast_fp16")]; + tensor var_2378_begin_0 = const()[name = tensor("op_2378_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2378_end_0 = const()[name = tensor("op_2378_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2378_end_mask_0 = const()[name = tensor("op_2378_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2378_cast_fp16 = slice_by_index(begin = var_2378_begin_0, end = var_2378_end_0, end_mask = var_2378_end_mask_0, x = var_2231_cast_fp16)[name = tensor("op_2378_cast_fp16")]; + tensor var_2385_begin_0 = const()[name = tensor("op_2385_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2385_end_0 = const()[name = tensor("op_2385_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2385_end_mask_0 = const()[name = tensor("op_2385_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2385_cast_fp16 = slice_by_index(begin = var_2385_begin_0, end = var_2385_end_0, end_mask = var_2385_end_mask_0, x = var_2231_cast_fp16)[name = tensor("op_2385_cast_fp16")]; + tensor var_2392_begin_0 = const()[name = tensor("op_2392_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2392_end_0 = const()[name = tensor("op_2392_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2392_end_mask_0 = const()[name = tensor("op_2392_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2392_cast_fp16 = slice_by_index(begin = var_2392_begin_0, end = var_2392_end_0, end_mask = var_2392_end_mask_0, x = var_2235_cast_fp16)[name = tensor("op_2392_cast_fp16")]; + tensor var_2399_begin_0 = const()[name = tensor("op_2399_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2399_end_0 = const()[name = tensor("op_2399_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2399_end_mask_0 = const()[name = tensor("op_2399_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2399_cast_fp16 = slice_by_index(begin = var_2399_begin_0, end = var_2399_end_0, end_mask = var_2399_end_mask_0, x = var_2235_cast_fp16)[name = tensor("op_2399_cast_fp16")]; + tensor var_2406_begin_0 = const()[name = tensor("op_2406_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2406_end_0 = const()[name = tensor("op_2406_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2406_end_mask_0 = const()[name = tensor("op_2406_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2406_cast_fp16 = slice_by_index(begin = var_2406_begin_0, end = var_2406_end_0, end_mask = var_2406_end_mask_0, x = var_2235_cast_fp16)[name = tensor("op_2406_cast_fp16")]; + tensor var_2413_begin_0 = const()[name = tensor("op_2413_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2413_end_0 = const()[name = tensor("op_2413_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2413_end_mask_0 = const()[name = tensor("op_2413_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2413_cast_fp16 = slice_by_index(begin = var_2413_begin_0, end = var_2413_end_0, end_mask = var_2413_end_mask_0, x = var_2235_cast_fp16)[name = tensor("op_2413_cast_fp16")]; + tensor var_2420_begin_0 = const()[name = tensor("op_2420_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2420_end_0 = const()[name = tensor("op_2420_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2420_end_mask_0 = const()[name = tensor("op_2420_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2420_cast_fp16 = slice_by_index(begin = var_2420_begin_0, end = var_2420_end_0, end_mask = var_2420_end_mask_0, x = var_2239_cast_fp16)[name = tensor("op_2420_cast_fp16")]; + tensor var_2427_begin_0 = const()[name = tensor("op_2427_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2427_end_0 = const()[name = tensor("op_2427_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2427_end_mask_0 = const()[name = tensor("op_2427_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2427_cast_fp16 = slice_by_index(begin = var_2427_begin_0, end = var_2427_end_0, end_mask = var_2427_end_mask_0, x = var_2239_cast_fp16)[name = tensor("op_2427_cast_fp16")]; + tensor var_2434_begin_0 = const()[name = tensor("op_2434_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2434_end_0 = const()[name = tensor("op_2434_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2434_end_mask_0 = const()[name = tensor("op_2434_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2434_cast_fp16 = slice_by_index(begin = var_2434_begin_0, end = var_2434_end_0, end_mask = var_2434_end_mask_0, x = var_2239_cast_fp16)[name = tensor("op_2434_cast_fp16")]; + tensor var_2441_begin_0 = const()[name = tensor("op_2441_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2441_end_0 = const()[name = tensor("op_2441_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2441_end_mask_0 = const()[name = tensor("op_2441_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2441_cast_fp16 = slice_by_index(begin = var_2441_begin_0, end = var_2441_end_0, end_mask = var_2441_end_mask_0, x = var_2239_cast_fp16)[name = tensor("op_2441_cast_fp16")]; + tensor var_2448_begin_0 = const()[name = tensor("op_2448_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2448_end_0 = const()[name = tensor("op_2448_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2448_end_mask_0 = const()[name = tensor("op_2448_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2448_cast_fp16 = slice_by_index(begin = var_2448_begin_0, end = var_2448_end_0, end_mask = var_2448_end_mask_0, x = var_2243_cast_fp16)[name = tensor("op_2448_cast_fp16")]; + tensor var_2455_begin_0 = const()[name = tensor("op_2455_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2455_end_0 = const()[name = tensor("op_2455_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2455_end_mask_0 = const()[name = tensor("op_2455_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2455_cast_fp16 = slice_by_index(begin = var_2455_begin_0, end = var_2455_end_0, end_mask = var_2455_end_mask_0, x = var_2243_cast_fp16)[name = tensor("op_2455_cast_fp16")]; + tensor var_2462_begin_0 = const()[name = tensor("op_2462_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2462_end_0 = const()[name = tensor("op_2462_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2462_end_mask_0 = const()[name = tensor("op_2462_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2462_cast_fp16 = slice_by_index(begin = var_2462_begin_0, end = var_2462_end_0, end_mask = var_2462_end_mask_0, x = var_2243_cast_fp16)[name = tensor("op_2462_cast_fp16")]; + tensor var_2469_begin_0 = const()[name = tensor("op_2469_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2469_end_0 = const()[name = tensor("op_2469_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2469_end_mask_0 = const()[name = tensor("op_2469_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2469_cast_fp16 = slice_by_index(begin = var_2469_begin_0, end = var_2469_end_0, end_mask = var_2469_end_mask_0, x = var_2243_cast_fp16)[name = tensor("op_2469_cast_fp16")]; + tensor k_7_perm_0 = const()[name = tensor("k_7_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_2474_begin_0 = const()[name = tensor("op_2474_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2474_end_0 = const()[name = tensor("op_2474_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_2474_end_mask_0 = const()[name = tensor("op_2474_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_2 = transpose(perm = k_7_perm_0, x = key_7_cast_fp16)[name = tensor("transpose_2")]; + tensor var_2474_cast_fp16 = slice_by_index(begin = var_2474_begin_0, end = var_2474_end_0, end_mask = var_2474_end_mask_0, x = transpose_2)[name = tensor("op_2474_cast_fp16")]; + tensor var_2478_begin_0 = const()[name = tensor("op_2478_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_2478_end_0 = const()[name = tensor("op_2478_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_2478_end_mask_0 = const()[name = tensor("op_2478_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2478_cast_fp16 = slice_by_index(begin = var_2478_begin_0, end = var_2478_end_0, end_mask = var_2478_end_mask_0, x = transpose_2)[name = tensor("op_2478_cast_fp16")]; + tensor var_2482_begin_0 = const()[name = tensor("op_2482_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_2482_end_0 = const()[name = tensor("op_2482_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_2482_end_mask_0 = const()[name = tensor("op_2482_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2482_cast_fp16 = slice_by_index(begin = var_2482_begin_0, end = var_2482_end_0, end_mask = var_2482_end_mask_0, x = transpose_2)[name = tensor("op_2482_cast_fp16")]; + tensor var_2486_begin_0 = const()[name = tensor("op_2486_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_2486_end_0 = const()[name = tensor("op_2486_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_2486_end_mask_0 = const()[name = tensor("op_2486_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2486_cast_fp16 = slice_by_index(begin = var_2486_begin_0, end = var_2486_end_0, end_mask = var_2486_end_mask_0, x = transpose_2)[name = tensor("op_2486_cast_fp16")]; + tensor var_2490_begin_0 = const()[name = tensor("op_2490_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_2490_end_0 = const()[name = tensor("op_2490_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_2490_end_mask_0 = const()[name = tensor("op_2490_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2490_cast_fp16 = slice_by_index(begin = var_2490_begin_0, end = var_2490_end_0, end_mask = var_2490_end_mask_0, x = transpose_2)[name = tensor("op_2490_cast_fp16")]; + tensor var_2494_begin_0 = const()[name = tensor("op_2494_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_2494_end_0 = const()[name = tensor("op_2494_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_2494_end_mask_0 = const()[name = tensor("op_2494_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2494_cast_fp16 = slice_by_index(begin = var_2494_begin_0, end = var_2494_end_0, end_mask = var_2494_end_mask_0, x = transpose_2)[name = tensor("op_2494_cast_fp16")]; + tensor var_2498_begin_0 = const()[name = tensor("op_2498_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_2498_end_0 = const()[name = tensor("op_2498_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_2498_end_mask_0 = const()[name = tensor("op_2498_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2498_cast_fp16 = slice_by_index(begin = var_2498_begin_0, end = var_2498_end_0, end_mask = var_2498_end_mask_0, x = transpose_2)[name = tensor("op_2498_cast_fp16")]; + tensor var_2502_begin_0 = const()[name = tensor("op_2502_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_2502_end_0 = const()[name = tensor("op_2502_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_2502_end_mask_0 = const()[name = tensor("op_2502_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2502_cast_fp16 = slice_by_index(begin = var_2502_begin_0, end = var_2502_end_0, end_mask = var_2502_end_mask_0, x = transpose_2)[name = tensor("op_2502_cast_fp16")]; + tensor var_2504_begin_0 = const()[name = tensor("op_2504_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2504_end_0 = const()[name = tensor("op_2504_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2504_end_mask_0 = const()[name = tensor("op_2504_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2504_cast_fp16 = slice_by_index(begin = var_2504_begin_0, end = var_2504_end_0, end_mask = var_2504_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_2504_cast_fp16")]; + tensor var_2508_begin_0 = const()[name = tensor("op_2508_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_2508_end_0 = const()[name = tensor("op_2508_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_2508_end_mask_0 = const()[name = tensor("op_2508_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2508_cast_fp16 = slice_by_index(begin = var_2508_begin_0, end = var_2508_end_0, end_mask = var_2508_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_2508_cast_fp16")]; + tensor var_2512_begin_0 = const()[name = tensor("op_2512_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_2512_end_0 = const()[name = tensor("op_2512_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_2512_end_mask_0 = const()[name = tensor("op_2512_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2512_cast_fp16 = slice_by_index(begin = var_2512_begin_0, end = var_2512_end_0, end_mask = var_2512_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_2512_cast_fp16")]; + tensor var_2516_begin_0 = const()[name = tensor("op_2516_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_2516_end_0 = const()[name = tensor("op_2516_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_2516_end_mask_0 = const()[name = tensor("op_2516_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2516_cast_fp16 = slice_by_index(begin = var_2516_begin_0, end = var_2516_end_0, end_mask = var_2516_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_2516_cast_fp16")]; + tensor var_2520_begin_0 = const()[name = tensor("op_2520_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_2520_end_0 = const()[name = tensor("op_2520_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_2520_end_mask_0 = const()[name = tensor("op_2520_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2520_cast_fp16 = slice_by_index(begin = var_2520_begin_0, end = var_2520_end_0, end_mask = var_2520_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_2520_cast_fp16")]; + tensor var_2524_begin_0 = const()[name = tensor("op_2524_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_2524_end_0 = const()[name = tensor("op_2524_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_2524_end_mask_0 = const()[name = tensor("op_2524_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2524_cast_fp16 = slice_by_index(begin = var_2524_begin_0, end = var_2524_end_0, end_mask = var_2524_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_2524_cast_fp16")]; + tensor var_2528_begin_0 = const()[name = tensor("op_2528_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_2528_end_0 = const()[name = tensor("op_2528_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_2528_end_mask_0 = const()[name = tensor("op_2528_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2528_cast_fp16 = slice_by_index(begin = var_2528_begin_0, end = var_2528_end_0, end_mask = var_2528_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_2528_cast_fp16")]; + tensor var_2532_begin_0 = const()[name = tensor("op_2532_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_2532_end_0 = const()[name = tensor("op_2532_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_2532_end_mask_0 = const()[name = tensor("op_2532_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2532_cast_fp16 = slice_by_index(begin = var_2532_begin_0, end = var_2532_end_0, end_mask = var_2532_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_2532_cast_fp16")]; + tensor var_2536_equation_0 = const()[name = tensor("op_2536_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2536_cast_fp16 = einsum(equation = var_2536_equation_0, values = (var_2474_cast_fp16, var_2252_cast_fp16))[name = tensor("op_2536_cast_fp16")]; + tensor var_2537_to_fp16 = const()[name = tensor("op_2537_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_193_cast_fp16 = mul(x = var_2536_cast_fp16, y = var_2537_to_fp16)[name = tensor("aw_chunk_193_cast_fp16")]; + tensor var_2540_equation_0 = const()[name = tensor("op_2540_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2540_cast_fp16 = einsum(equation = var_2540_equation_0, values = (var_2474_cast_fp16, var_2259_cast_fp16))[name = tensor("op_2540_cast_fp16")]; + tensor var_2541_to_fp16 = const()[name = tensor("op_2541_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_195_cast_fp16 = mul(x = var_2540_cast_fp16, y = var_2541_to_fp16)[name = tensor("aw_chunk_195_cast_fp16")]; + tensor var_2544_equation_0 = const()[name = tensor("op_2544_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2544_cast_fp16 = einsum(equation = var_2544_equation_0, values = (var_2474_cast_fp16, var_2266_cast_fp16))[name = tensor("op_2544_cast_fp16")]; + tensor var_2545_to_fp16 = const()[name = tensor("op_2545_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_197_cast_fp16 = mul(x = var_2544_cast_fp16, y = var_2545_to_fp16)[name = tensor("aw_chunk_197_cast_fp16")]; + tensor var_2548_equation_0 = const()[name = tensor("op_2548_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2548_cast_fp16 = einsum(equation = var_2548_equation_0, values = (var_2474_cast_fp16, var_2273_cast_fp16))[name = tensor("op_2548_cast_fp16")]; + tensor var_2549_to_fp16 = const()[name = tensor("op_2549_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_199_cast_fp16 = mul(x = var_2548_cast_fp16, y = var_2549_to_fp16)[name = tensor("aw_chunk_199_cast_fp16")]; + tensor var_2552_equation_0 = const()[name = tensor("op_2552_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2552_cast_fp16 = einsum(equation = var_2552_equation_0, values = (var_2478_cast_fp16, var_2280_cast_fp16))[name = tensor("op_2552_cast_fp16")]; + tensor var_2553_to_fp16 = const()[name = tensor("op_2553_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_201_cast_fp16 = mul(x = var_2552_cast_fp16, y = var_2553_to_fp16)[name = tensor("aw_chunk_201_cast_fp16")]; + tensor var_2556_equation_0 = const()[name = tensor("op_2556_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2556_cast_fp16 = einsum(equation = var_2556_equation_0, values = (var_2478_cast_fp16, var_2287_cast_fp16))[name = tensor("op_2556_cast_fp16")]; + tensor var_2557_to_fp16 = const()[name = tensor("op_2557_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_203_cast_fp16 = mul(x = var_2556_cast_fp16, y = var_2557_to_fp16)[name = tensor("aw_chunk_203_cast_fp16")]; + tensor var_2560_equation_0 = const()[name = tensor("op_2560_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2560_cast_fp16 = einsum(equation = var_2560_equation_0, values = (var_2478_cast_fp16, var_2294_cast_fp16))[name = tensor("op_2560_cast_fp16")]; + tensor var_2561_to_fp16 = const()[name = tensor("op_2561_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_205_cast_fp16 = mul(x = var_2560_cast_fp16, y = var_2561_to_fp16)[name = tensor("aw_chunk_205_cast_fp16")]; + tensor var_2564_equation_0 = const()[name = tensor("op_2564_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2564_cast_fp16 = einsum(equation = var_2564_equation_0, values = (var_2478_cast_fp16, var_2301_cast_fp16))[name = tensor("op_2564_cast_fp16")]; + tensor var_2565_to_fp16 = const()[name = tensor("op_2565_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_207_cast_fp16 = mul(x = var_2564_cast_fp16, y = var_2565_to_fp16)[name = tensor("aw_chunk_207_cast_fp16")]; + tensor var_2568_equation_0 = const()[name = tensor("op_2568_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2568_cast_fp16 = einsum(equation = var_2568_equation_0, values = (var_2482_cast_fp16, var_2308_cast_fp16))[name = tensor("op_2568_cast_fp16")]; + tensor var_2569_to_fp16 = const()[name = tensor("op_2569_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_209_cast_fp16 = mul(x = var_2568_cast_fp16, y = var_2569_to_fp16)[name = tensor("aw_chunk_209_cast_fp16")]; + tensor var_2572_equation_0 = const()[name = tensor("op_2572_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2572_cast_fp16 = einsum(equation = var_2572_equation_0, values = (var_2482_cast_fp16, var_2315_cast_fp16))[name = tensor("op_2572_cast_fp16")]; + tensor var_2573_to_fp16 = const()[name = tensor("op_2573_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_211_cast_fp16 = mul(x = var_2572_cast_fp16, y = var_2573_to_fp16)[name = tensor("aw_chunk_211_cast_fp16")]; + tensor var_2576_equation_0 = const()[name = tensor("op_2576_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2576_cast_fp16 = einsum(equation = var_2576_equation_0, values = (var_2482_cast_fp16, var_2322_cast_fp16))[name = tensor("op_2576_cast_fp16")]; + tensor var_2577_to_fp16 = const()[name = tensor("op_2577_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_213_cast_fp16 = mul(x = var_2576_cast_fp16, y = var_2577_to_fp16)[name = tensor("aw_chunk_213_cast_fp16")]; + tensor var_2580_equation_0 = const()[name = tensor("op_2580_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2580_cast_fp16 = einsum(equation = var_2580_equation_0, values = (var_2482_cast_fp16, var_2329_cast_fp16))[name = tensor("op_2580_cast_fp16")]; + tensor var_2581_to_fp16 = const()[name = tensor("op_2581_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_215_cast_fp16 = mul(x = var_2580_cast_fp16, y = var_2581_to_fp16)[name = tensor("aw_chunk_215_cast_fp16")]; + tensor var_2584_equation_0 = const()[name = tensor("op_2584_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2584_cast_fp16 = einsum(equation = var_2584_equation_0, values = (var_2486_cast_fp16, var_2336_cast_fp16))[name = tensor("op_2584_cast_fp16")]; + tensor var_2585_to_fp16 = const()[name = tensor("op_2585_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_217_cast_fp16 = mul(x = var_2584_cast_fp16, y = var_2585_to_fp16)[name = tensor("aw_chunk_217_cast_fp16")]; + tensor var_2588_equation_0 = const()[name = tensor("op_2588_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2588_cast_fp16 = einsum(equation = var_2588_equation_0, values = (var_2486_cast_fp16, var_2343_cast_fp16))[name = tensor("op_2588_cast_fp16")]; + tensor var_2589_to_fp16 = const()[name = tensor("op_2589_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_219_cast_fp16 = mul(x = var_2588_cast_fp16, y = var_2589_to_fp16)[name = tensor("aw_chunk_219_cast_fp16")]; + tensor var_2592_equation_0 = const()[name = tensor("op_2592_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2592_cast_fp16 = einsum(equation = var_2592_equation_0, values = (var_2486_cast_fp16, var_2350_cast_fp16))[name = tensor("op_2592_cast_fp16")]; + tensor var_2593_to_fp16 = const()[name = tensor("op_2593_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_221_cast_fp16 = mul(x = var_2592_cast_fp16, y = var_2593_to_fp16)[name = tensor("aw_chunk_221_cast_fp16")]; + tensor var_2596_equation_0 = const()[name = tensor("op_2596_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2596_cast_fp16 = einsum(equation = var_2596_equation_0, values = (var_2486_cast_fp16, var_2357_cast_fp16))[name = tensor("op_2596_cast_fp16")]; + tensor var_2597_to_fp16 = const()[name = tensor("op_2597_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_223_cast_fp16 = mul(x = var_2596_cast_fp16, y = var_2597_to_fp16)[name = tensor("aw_chunk_223_cast_fp16")]; + tensor var_2600_equation_0 = const()[name = tensor("op_2600_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2600_cast_fp16 = einsum(equation = var_2600_equation_0, values = (var_2490_cast_fp16, var_2364_cast_fp16))[name = tensor("op_2600_cast_fp16")]; + tensor var_2601_to_fp16 = const()[name = tensor("op_2601_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_225_cast_fp16 = mul(x = var_2600_cast_fp16, y = var_2601_to_fp16)[name = tensor("aw_chunk_225_cast_fp16")]; + tensor var_2604_equation_0 = const()[name = tensor("op_2604_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2604_cast_fp16 = einsum(equation = var_2604_equation_0, values = (var_2490_cast_fp16, var_2371_cast_fp16))[name = tensor("op_2604_cast_fp16")]; + tensor var_2605_to_fp16 = const()[name = tensor("op_2605_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_227_cast_fp16 = mul(x = var_2604_cast_fp16, y = var_2605_to_fp16)[name = tensor("aw_chunk_227_cast_fp16")]; + tensor var_2608_equation_0 = const()[name = tensor("op_2608_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2608_cast_fp16 = einsum(equation = var_2608_equation_0, values = (var_2490_cast_fp16, var_2378_cast_fp16))[name = tensor("op_2608_cast_fp16")]; + tensor var_2609_to_fp16 = const()[name = tensor("op_2609_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_229_cast_fp16 = mul(x = var_2608_cast_fp16, y = var_2609_to_fp16)[name = tensor("aw_chunk_229_cast_fp16")]; + tensor var_2612_equation_0 = const()[name = tensor("op_2612_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2612_cast_fp16 = einsum(equation = var_2612_equation_0, values = (var_2490_cast_fp16, var_2385_cast_fp16))[name = tensor("op_2612_cast_fp16")]; + tensor var_2613_to_fp16 = const()[name = tensor("op_2613_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_231_cast_fp16 = mul(x = var_2612_cast_fp16, y = var_2613_to_fp16)[name = tensor("aw_chunk_231_cast_fp16")]; + tensor var_2616_equation_0 = const()[name = tensor("op_2616_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2616_cast_fp16 = einsum(equation = var_2616_equation_0, values = (var_2494_cast_fp16, var_2392_cast_fp16))[name = tensor("op_2616_cast_fp16")]; + tensor var_2617_to_fp16 = const()[name = tensor("op_2617_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_233_cast_fp16 = mul(x = var_2616_cast_fp16, y = var_2617_to_fp16)[name = tensor("aw_chunk_233_cast_fp16")]; + tensor var_2620_equation_0 = const()[name = tensor("op_2620_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2620_cast_fp16 = einsum(equation = var_2620_equation_0, values = (var_2494_cast_fp16, var_2399_cast_fp16))[name = tensor("op_2620_cast_fp16")]; + tensor var_2621_to_fp16 = const()[name = tensor("op_2621_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_235_cast_fp16 = mul(x = var_2620_cast_fp16, y = var_2621_to_fp16)[name = tensor("aw_chunk_235_cast_fp16")]; + tensor var_2624_equation_0 = const()[name = tensor("op_2624_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2624_cast_fp16 = einsum(equation = var_2624_equation_0, values = (var_2494_cast_fp16, var_2406_cast_fp16))[name = tensor("op_2624_cast_fp16")]; + tensor var_2625_to_fp16 = const()[name = tensor("op_2625_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_237_cast_fp16 = mul(x = var_2624_cast_fp16, y = var_2625_to_fp16)[name = tensor("aw_chunk_237_cast_fp16")]; + tensor var_2628_equation_0 = const()[name = tensor("op_2628_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2628_cast_fp16 = einsum(equation = var_2628_equation_0, values = (var_2494_cast_fp16, var_2413_cast_fp16))[name = tensor("op_2628_cast_fp16")]; + tensor var_2629_to_fp16 = const()[name = tensor("op_2629_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_239_cast_fp16 = mul(x = var_2628_cast_fp16, y = var_2629_to_fp16)[name = tensor("aw_chunk_239_cast_fp16")]; + tensor var_2632_equation_0 = const()[name = tensor("op_2632_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2632_cast_fp16 = einsum(equation = var_2632_equation_0, values = (var_2498_cast_fp16, var_2420_cast_fp16))[name = tensor("op_2632_cast_fp16")]; + tensor var_2633_to_fp16 = const()[name = tensor("op_2633_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_241_cast_fp16 = mul(x = var_2632_cast_fp16, y = var_2633_to_fp16)[name = tensor("aw_chunk_241_cast_fp16")]; + tensor var_2636_equation_0 = const()[name = tensor("op_2636_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2636_cast_fp16 = einsum(equation = var_2636_equation_0, values = (var_2498_cast_fp16, var_2427_cast_fp16))[name = tensor("op_2636_cast_fp16")]; + tensor var_2637_to_fp16 = const()[name = tensor("op_2637_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_243_cast_fp16 = mul(x = var_2636_cast_fp16, y = var_2637_to_fp16)[name = tensor("aw_chunk_243_cast_fp16")]; + tensor var_2640_equation_0 = const()[name = tensor("op_2640_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2640_cast_fp16 = einsum(equation = var_2640_equation_0, values = (var_2498_cast_fp16, var_2434_cast_fp16))[name = tensor("op_2640_cast_fp16")]; + tensor var_2641_to_fp16 = const()[name = tensor("op_2641_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_245_cast_fp16 = mul(x = var_2640_cast_fp16, y = var_2641_to_fp16)[name = tensor("aw_chunk_245_cast_fp16")]; + tensor var_2644_equation_0 = const()[name = tensor("op_2644_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2644_cast_fp16 = einsum(equation = var_2644_equation_0, values = (var_2498_cast_fp16, var_2441_cast_fp16))[name = tensor("op_2644_cast_fp16")]; + tensor var_2645_to_fp16 = const()[name = tensor("op_2645_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_247_cast_fp16 = mul(x = var_2644_cast_fp16, y = var_2645_to_fp16)[name = tensor("aw_chunk_247_cast_fp16")]; + tensor var_2648_equation_0 = const()[name = tensor("op_2648_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2648_cast_fp16 = einsum(equation = var_2648_equation_0, values = (var_2502_cast_fp16, var_2448_cast_fp16))[name = tensor("op_2648_cast_fp16")]; + tensor var_2649_to_fp16 = const()[name = tensor("op_2649_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_249_cast_fp16 = mul(x = var_2648_cast_fp16, y = var_2649_to_fp16)[name = tensor("aw_chunk_249_cast_fp16")]; + tensor var_2652_equation_0 = const()[name = tensor("op_2652_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2652_cast_fp16 = einsum(equation = var_2652_equation_0, values = (var_2502_cast_fp16, var_2455_cast_fp16))[name = tensor("op_2652_cast_fp16")]; + tensor var_2653_to_fp16 = const()[name = tensor("op_2653_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_251_cast_fp16 = mul(x = var_2652_cast_fp16, y = var_2653_to_fp16)[name = tensor("aw_chunk_251_cast_fp16")]; + tensor var_2656_equation_0 = const()[name = tensor("op_2656_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2656_cast_fp16 = einsum(equation = var_2656_equation_0, values = (var_2502_cast_fp16, var_2462_cast_fp16))[name = tensor("op_2656_cast_fp16")]; + tensor var_2657_to_fp16 = const()[name = tensor("op_2657_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_253_cast_fp16 = mul(x = var_2656_cast_fp16, y = var_2657_to_fp16)[name = tensor("aw_chunk_253_cast_fp16")]; + tensor var_2660_equation_0 = const()[name = tensor("op_2660_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2660_cast_fp16 = einsum(equation = var_2660_equation_0, values = (var_2502_cast_fp16, var_2469_cast_fp16))[name = tensor("op_2660_cast_fp16")]; + tensor var_2661_to_fp16 = const()[name = tensor("op_2661_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_255_cast_fp16 = mul(x = var_2660_cast_fp16, y = var_2661_to_fp16)[name = tensor("aw_chunk_255_cast_fp16")]; + tensor var_2663_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_193_cast_fp16)[name = tensor("op_2663_cast_fp16")]; + tensor var_2664_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_195_cast_fp16)[name = tensor("op_2664_cast_fp16")]; + tensor var_2665_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_197_cast_fp16)[name = tensor("op_2665_cast_fp16")]; + tensor var_2666_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_199_cast_fp16)[name = tensor("op_2666_cast_fp16")]; + tensor var_2667_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_201_cast_fp16)[name = tensor("op_2667_cast_fp16")]; + tensor var_2668_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_203_cast_fp16)[name = tensor("op_2668_cast_fp16")]; + tensor var_2669_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_205_cast_fp16)[name = tensor("op_2669_cast_fp16")]; + tensor var_2670_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_207_cast_fp16)[name = tensor("op_2670_cast_fp16")]; + tensor var_2671_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_209_cast_fp16)[name = tensor("op_2671_cast_fp16")]; + tensor var_2672_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_211_cast_fp16)[name = tensor("op_2672_cast_fp16")]; + tensor var_2673_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_213_cast_fp16)[name = tensor("op_2673_cast_fp16")]; + tensor var_2674_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_215_cast_fp16)[name = tensor("op_2674_cast_fp16")]; + tensor var_2675_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_217_cast_fp16)[name = tensor("op_2675_cast_fp16")]; + tensor var_2676_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_219_cast_fp16)[name = tensor("op_2676_cast_fp16")]; + tensor var_2677_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_221_cast_fp16)[name = tensor("op_2677_cast_fp16")]; + tensor var_2678_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_223_cast_fp16)[name = tensor("op_2678_cast_fp16")]; + tensor var_2679_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_225_cast_fp16)[name = tensor("op_2679_cast_fp16")]; + tensor var_2680_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_227_cast_fp16)[name = tensor("op_2680_cast_fp16")]; + tensor var_2681_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_229_cast_fp16)[name = tensor("op_2681_cast_fp16")]; + tensor var_2682_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_231_cast_fp16)[name = tensor("op_2682_cast_fp16")]; + tensor var_2683_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_233_cast_fp16)[name = tensor("op_2683_cast_fp16")]; + tensor var_2684_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_235_cast_fp16)[name = tensor("op_2684_cast_fp16")]; + tensor var_2685_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_237_cast_fp16)[name = tensor("op_2685_cast_fp16")]; + tensor var_2686_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_239_cast_fp16)[name = tensor("op_2686_cast_fp16")]; + tensor var_2687_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_241_cast_fp16)[name = tensor("op_2687_cast_fp16")]; + tensor var_2688_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_243_cast_fp16)[name = tensor("op_2688_cast_fp16")]; + tensor var_2689_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_245_cast_fp16)[name = tensor("op_2689_cast_fp16")]; + tensor var_2690_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_247_cast_fp16)[name = tensor("op_2690_cast_fp16")]; + tensor var_2691_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_249_cast_fp16)[name = tensor("op_2691_cast_fp16")]; + tensor var_2692_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_251_cast_fp16)[name = tensor("op_2692_cast_fp16")]; + tensor var_2693_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_253_cast_fp16)[name = tensor("op_2693_cast_fp16")]; + tensor var_2694_cast_fp16 = softmax(axis = var_2160, x = aw_chunk_255_cast_fp16)[name = tensor("op_2694_cast_fp16")]; + tensor var_2696_equation_0 = const()[name = tensor("op_2696_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2696_cast_fp16 = einsum(equation = var_2696_equation_0, values = (var_2504_cast_fp16, var_2663_cast_fp16))[name = tensor("op_2696_cast_fp16")]; + tensor var_2698_equation_0 = const()[name = tensor("op_2698_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2698_cast_fp16 = einsum(equation = var_2698_equation_0, values = (var_2504_cast_fp16, var_2664_cast_fp16))[name = tensor("op_2698_cast_fp16")]; + tensor var_2700_equation_0 = const()[name = tensor("op_2700_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2700_cast_fp16 = einsum(equation = var_2700_equation_0, values = (var_2504_cast_fp16, var_2665_cast_fp16))[name = tensor("op_2700_cast_fp16")]; + tensor var_2702_equation_0 = const()[name = tensor("op_2702_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2702_cast_fp16 = einsum(equation = var_2702_equation_0, values = (var_2504_cast_fp16, var_2666_cast_fp16))[name = tensor("op_2702_cast_fp16")]; + tensor var_2704_equation_0 = const()[name = tensor("op_2704_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2704_cast_fp16 = einsum(equation = var_2704_equation_0, values = (var_2508_cast_fp16, var_2667_cast_fp16))[name = tensor("op_2704_cast_fp16")]; + tensor var_2706_equation_0 = const()[name = tensor("op_2706_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2706_cast_fp16 = einsum(equation = var_2706_equation_0, values = (var_2508_cast_fp16, var_2668_cast_fp16))[name = tensor("op_2706_cast_fp16")]; + tensor var_2708_equation_0 = const()[name = tensor("op_2708_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2708_cast_fp16 = einsum(equation = var_2708_equation_0, values = (var_2508_cast_fp16, var_2669_cast_fp16))[name = tensor("op_2708_cast_fp16")]; + tensor var_2710_equation_0 = const()[name = tensor("op_2710_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2710_cast_fp16 = einsum(equation = var_2710_equation_0, values = (var_2508_cast_fp16, var_2670_cast_fp16))[name = tensor("op_2710_cast_fp16")]; + tensor var_2712_equation_0 = const()[name = tensor("op_2712_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2712_cast_fp16 = einsum(equation = var_2712_equation_0, values = (var_2512_cast_fp16, var_2671_cast_fp16))[name = tensor("op_2712_cast_fp16")]; + tensor var_2714_equation_0 = const()[name = tensor("op_2714_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2714_cast_fp16 = einsum(equation = var_2714_equation_0, values = (var_2512_cast_fp16, var_2672_cast_fp16))[name = tensor("op_2714_cast_fp16")]; + tensor var_2716_equation_0 = const()[name = tensor("op_2716_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2716_cast_fp16 = einsum(equation = var_2716_equation_0, values = (var_2512_cast_fp16, var_2673_cast_fp16))[name = tensor("op_2716_cast_fp16")]; + tensor var_2718_equation_0 = const()[name = tensor("op_2718_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2718_cast_fp16 = einsum(equation = var_2718_equation_0, values = (var_2512_cast_fp16, var_2674_cast_fp16))[name = tensor("op_2718_cast_fp16")]; + tensor var_2720_equation_0 = const()[name = tensor("op_2720_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2720_cast_fp16 = einsum(equation = var_2720_equation_0, values = (var_2516_cast_fp16, var_2675_cast_fp16))[name = tensor("op_2720_cast_fp16")]; + tensor var_2722_equation_0 = const()[name = tensor("op_2722_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2722_cast_fp16 = einsum(equation = var_2722_equation_0, values = (var_2516_cast_fp16, var_2676_cast_fp16))[name = tensor("op_2722_cast_fp16")]; + tensor var_2724_equation_0 = const()[name = tensor("op_2724_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2724_cast_fp16 = einsum(equation = var_2724_equation_0, values = (var_2516_cast_fp16, var_2677_cast_fp16))[name = tensor("op_2724_cast_fp16")]; + tensor var_2726_equation_0 = const()[name = tensor("op_2726_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2726_cast_fp16 = einsum(equation = var_2726_equation_0, values = (var_2516_cast_fp16, var_2678_cast_fp16))[name = tensor("op_2726_cast_fp16")]; + tensor var_2728_equation_0 = const()[name = tensor("op_2728_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2728_cast_fp16 = einsum(equation = var_2728_equation_0, values = (var_2520_cast_fp16, var_2679_cast_fp16))[name = tensor("op_2728_cast_fp16")]; + tensor var_2730_equation_0 = const()[name = tensor("op_2730_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2730_cast_fp16 = einsum(equation = var_2730_equation_0, values = (var_2520_cast_fp16, var_2680_cast_fp16))[name = tensor("op_2730_cast_fp16")]; + tensor var_2732_equation_0 = const()[name = tensor("op_2732_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2732_cast_fp16 = einsum(equation = var_2732_equation_0, values = (var_2520_cast_fp16, var_2681_cast_fp16))[name = tensor("op_2732_cast_fp16")]; + tensor var_2734_equation_0 = const()[name = tensor("op_2734_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2734_cast_fp16 = einsum(equation = var_2734_equation_0, values = (var_2520_cast_fp16, var_2682_cast_fp16))[name = tensor("op_2734_cast_fp16")]; + tensor var_2736_equation_0 = const()[name = tensor("op_2736_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2736_cast_fp16 = einsum(equation = var_2736_equation_0, values = (var_2524_cast_fp16, var_2683_cast_fp16))[name = tensor("op_2736_cast_fp16")]; + tensor var_2738_equation_0 = const()[name = tensor("op_2738_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2738_cast_fp16 = einsum(equation = var_2738_equation_0, values = (var_2524_cast_fp16, var_2684_cast_fp16))[name = tensor("op_2738_cast_fp16")]; + tensor var_2740_equation_0 = const()[name = tensor("op_2740_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2740_cast_fp16 = einsum(equation = var_2740_equation_0, values = (var_2524_cast_fp16, var_2685_cast_fp16))[name = tensor("op_2740_cast_fp16")]; + tensor var_2742_equation_0 = const()[name = tensor("op_2742_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2742_cast_fp16 = einsum(equation = var_2742_equation_0, values = (var_2524_cast_fp16, var_2686_cast_fp16))[name = tensor("op_2742_cast_fp16")]; + tensor var_2744_equation_0 = const()[name = tensor("op_2744_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2744_cast_fp16 = einsum(equation = var_2744_equation_0, values = (var_2528_cast_fp16, var_2687_cast_fp16))[name = tensor("op_2744_cast_fp16")]; + tensor var_2746_equation_0 = const()[name = tensor("op_2746_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2746_cast_fp16 = einsum(equation = var_2746_equation_0, values = (var_2528_cast_fp16, var_2688_cast_fp16))[name = tensor("op_2746_cast_fp16")]; + tensor var_2748_equation_0 = const()[name = tensor("op_2748_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2748_cast_fp16 = einsum(equation = var_2748_equation_0, values = (var_2528_cast_fp16, var_2689_cast_fp16))[name = tensor("op_2748_cast_fp16")]; + tensor var_2750_equation_0 = const()[name = tensor("op_2750_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2750_cast_fp16 = einsum(equation = var_2750_equation_0, values = (var_2528_cast_fp16, var_2690_cast_fp16))[name = tensor("op_2750_cast_fp16")]; + tensor var_2752_equation_0 = const()[name = tensor("op_2752_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2752_cast_fp16 = einsum(equation = var_2752_equation_0, values = (var_2532_cast_fp16, var_2691_cast_fp16))[name = tensor("op_2752_cast_fp16")]; + tensor var_2754_equation_0 = const()[name = tensor("op_2754_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2754_cast_fp16 = einsum(equation = var_2754_equation_0, values = (var_2532_cast_fp16, var_2692_cast_fp16))[name = tensor("op_2754_cast_fp16")]; + tensor var_2756_equation_0 = const()[name = tensor("op_2756_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2756_cast_fp16 = einsum(equation = var_2756_equation_0, values = (var_2532_cast_fp16, var_2693_cast_fp16))[name = tensor("op_2756_cast_fp16")]; + tensor var_2758_equation_0 = const()[name = tensor("op_2758_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2758_cast_fp16 = einsum(equation = var_2758_equation_0, values = (var_2532_cast_fp16, var_2694_cast_fp16))[name = tensor("op_2758_cast_fp16")]; + tensor var_2760_interleave_0 = const()[name = tensor("op_2760_interleave_0"), val = tensor(false)]; + tensor var_2760_cast_fp16 = concat(axis = var_2147, interleave = var_2760_interleave_0, values = (var_2696_cast_fp16, var_2698_cast_fp16, var_2700_cast_fp16, var_2702_cast_fp16))[name = tensor("op_2760_cast_fp16")]; + tensor var_2762_interleave_0 = const()[name = tensor("op_2762_interleave_0"), val = tensor(false)]; + tensor var_2762_cast_fp16 = concat(axis = var_2147, interleave = var_2762_interleave_0, values = (var_2704_cast_fp16, var_2706_cast_fp16, var_2708_cast_fp16, var_2710_cast_fp16))[name = tensor("op_2762_cast_fp16")]; + tensor var_2764_interleave_0 = const()[name = tensor("op_2764_interleave_0"), val = tensor(false)]; + tensor var_2764_cast_fp16 = concat(axis = var_2147, interleave = var_2764_interleave_0, values = (var_2712_cast_fp16, var_2714_cast_fp16, var_2716_cast_fp16, var_2718_cast_fp16))[name = tensor("op_2764_cast_fp16")]; + tensor var_2766_interleave_0 = const()[name = tensor("op_2766_interleave_0"), val = tensor(false)]; + tensor var_2766_cast_fp16 = concat(axis = var_2147, interleave = var_2766_interleave_0, values = (var_2720_cast_fp16, var_2722_cast_fp16, var_2724_cast_fp16, var_2726_cast_fp16))[name = tensor("op_2766_cast_fp16")]; + tensor var_2768_interleave_0 = const()[name = tensor("op_2768_interleave_0"), val = tensor(false)]; + tensor var_2768_cast_fp16 = concat(axis = var_2147, interleave = var_2768_interleave_0, values = (var_2728_cast_fp16, var_2730_cast_fp16, var_2732_cast_fp16, var_2734_cast_fp16))[name = tensor("op_2768_cast_fp16")]; + tensor var_2770_interleave_0 = const()[name = tensor("op_2770_interleave_0"), val = tensor(false)]; + tensor var_2770_cast_fp16 = concat(axis = var_2147, interleave = var_2770_interleave_0, values = (var_2736_cast_fp16, var_2738_cast_fp16, var_2740_cast_fp16, var_2742_cast_fp16))[name = tensor("op_2770_cast_fp16")]; + tensor var_2772_interleave_0 = const()[name = tensor("op_2772_interleave_0"), val = tensor(false)]; + tensor var_2772_cast_fp16 = concat(axis = var_2147, interleave = var_2772_interleave_0, values = (var_2744_cast_fp16, var_2746_cast_fp16, var_2748_cast_fp16, var_2750_cast_fp16))[name = tensor("op_2772_cast_fp16")]; + tensor var_2774_interleave_0 = const()[name = tensor("op_2774_interleave_0"), val = tensor(false)]; + tensor var_2774_cast_fp16 = concat(axis = var_2147, interleave = var_2774_interleave_0, values = (var_2752_cast_fp16, var_2754_cast_fp16, var_2756_cast_fp16, var_2758_cast_fp16))[name = tensor("op_2774_cast_fp16")]; + tensor input_25_interleave_0 = const()[name = tensor("input_25_interleave_0"), val = tensor(false)]; + tensor input_25_cast_fp16 = concat(axis = var_2160, interleave = input_25_interleave_0, values = (var_2760_cast_fp16, var_2762_cast_fp16, var_2764_cast_fp16, var_2766_cast_fp16, var_2768_cast_fp16, var_2770_cast_fp16, var_2772_cast_fp16, var_2774_cast_fp16))[name = tensor("input_25_cast_fp16")]; + tensor var_2779 = const()[name = tensor("op_2779"), val = tensor([1, 1])]; + tensor var_2781 = const()[name = tensor("op_2781"), val = tensor([1, 1])]; + tensor obj_15_pad_type_0 = const()[name = tensor("obj_15_pad_type_0"), val = tensor("custom")]; + tensor obj_15_pad_0 = const()[name = tensor("obj_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23850752)))]; + tensor layers_3_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24375104)))]; + tensor obj_15_cast_fp16 = conv(bias = layers_3_self_attn_o_proj_bias_to_fp16, dilations = var_2781, groups = var_2160, pad = obj_15_pad_0, pad_type = obj_15_pad_type_0, strides = var_2779, weight = layers_3_self_attn_o_proj_weight_to_fp16, x = input_25_cast_fp16)[name = tensor("obj_15_cast_fp16")]; + tensor inputs_15_cast_fp16 = add(x = inputs_13_cast_fp16, y = obj_15_cast_fp16)[name = tensor("inputs_15_cast_fp16")]; + tensor var_2787 = const()[name = tensor("op_2787"), val = tensor([1])]; + tensor channels_mean_15_cast_fp16 = reduce_mean(axes = var_2787, keep_dims = var_2161, x = inputs_15_cast_fp16)[name = tensor("channels_mean_15_cast_fp16")]; + tensor zero_mean_15_cast_fp16 = sub(x = inputs_15_cast_fp16, y = channels_mean_15_cast_fp16)[name = tensor("zero_mean_15_cast_fp16")]; + tensor zero_mean_sq_15_cast_fp16 = mul(x = zero_mean_15_cast_fp16, y = zero_mean_15_cast_fp16)[name = tensor("zero_mean_sq_15_cast_fp16")]; + tensor var_2791 = const()[name = tensor("op_2791"), val = tensor([1])]; + tensor var_2792_cast_fp16 = reduce_mean(axes = var_2791, keep_dims = var_2161, x = zero_mean_sq_15_cast_fp16)[name = tensor("op_2792_cast_fp16")]; + tensor var_2793_to_fp16 = const()[name = tensor("op_2793_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2794_cast_fp16 = add(x = var_2792_cast_fp16, y = var_2793_to_fp16)[name = tensor("op_2794_cast_fp16")]; + tensor denom_15_epsilon_0_to_fp16 = const()[name = tensor("denom_15_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_15_cast_fp16 = rsqrt(epsilon = denom_15_epsilon_0_to_fp16, x = var_2794_cast_fp16)[name = tensor("denom_15_cast_fp16")]; + tensor out_15_cast_fp16 = mul(x = zero_mean_15_cast_fp16, y = denom_15_cast_fp16)[name = tensor("out_15_cast_fp16")]; + tensor input_27_gamma_0_to_fp16 = const()[name = tensor("input_27_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24376192)))]; + tensor input_27_beta_0_to_fp16 = const()[name = tensor("input_27_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24377280)))]; + tensor input_27_epsilon_0_to_fp16 = const()[name = tensor("input_27_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_27_cast_fp16 = batch_norm(beta = input_27_beta_0_to_fp16, epsilon = input_27_epsilon_0_to_fp16, gamma = input_27_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_15_cast_fp16)[name = tensor("input_27_cast_fp16")]; + tensor var_2805 = const()[name = tensor("op_2805"), val = tensor([1, 1])]; + tensor var_2807 = const()[name = tensor("op_2807"), val = tensor([1, 1])]; + tensor input_29_pad_type_0 = const()[name = tensor("input_29_pad_type_0"), val = tensor("custom")]; + tensor input_29_pad_0 = const()[name = tensor("input_29_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_fc1_weight_to_fp16 = const()[name = tensor("layers_3_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24378368)))]; + tensor layers_3_fc1_bias_to_fp16 = const()[name = tensor("layers_3_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26475584)))]; + tensor input_29_cast_fp16 = conv(bias = layers_3_fc1_bias_to_fp16, dilations = var_2807, groups = var_2160, pad = input_29_pad_0, pad_type = input_29_pad_type_0, strides = var_2805, weight = layers_3_fc1_weight_to_fp16, x = input_27_cast_fp16)[name = tensor("input_29_cast_fp16")]; + tensor input_31_mode_0 = const()[name = tensor("input_31_mode_0"), val = tensor("EXACT")]; + tensor input_31_cast_fp16 = gelu(mode = input_31_mode_0, x = input_29_cast_fp16)[name = tensor("input_31_cast_fp16")]; + tensor var_2813 = const()[name = tensor("op_2813"), val = tensor([1, 1])]; + tensor var_2815 = const()[name = tensor("op_2815"), val = tensor([1, 1])]; + tensor hidden_states_11_pad_type_0 = const()[name = tensor("hidden_states_11_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_11_pad_0 = const()[name = tensor("hidden_states_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_fc2_weight_to_fp16 = const()[name = tensor("layers_3_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26479744)))]; + tensor layers_3_fc2_bias_to_fp16 = const()[name = tensor("layers_3_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(28576960)))]; + tensor hidden_states_11_cast_fp16 = conv(bias = layers_3_fc2_bias_to_fp16, dilations = var_2815, groups = var_2160, pad = hidden_states_11_pad_0, pad_type = hidden_states_11_pad_type_0, strides = var_2813, weight = layers_3_fc2_weight_to_fp16, x = input_31_cast_fp16)[name = tensor("hidden_states_11_cast_fp16")]; + tensor inputs_17_cast_fp16 = add(x = inputs_15_cast_fp16, y = hidden_states_11_cast_fp16)[name = tensor("inputs_17_cast_fp16")]; + tensor var_2822 = const()[name = tensor("op_2822"), val = tensor(3)]; + tensor var_2835 = const()[name = tensor("op_2835"), val = tensor(1)]; + tensor var_2836 = const()[name = tensor("op_2836"), val = tensor(true)]; + tensor var_2846 = const()[name = tensor("op_2846"), val = tensor([1])]; + tensor channels_mean_17_cast_fp16 = reduce_mean(axes = var_2846, keep_dims = var_2836, x = inputs_17_cast_fp16)[name = tensor("channels_mean_17_cast_fp16")]; + tensor zero_mean_17_cast_fp16 = sub(x = inputs_17_cast_fp16, y = channels_mean_17_cast_fp16)[name = tensor("zero_mean_17_cast_fp16")]; + tensor zero_mean_sq_17_cast_fp16 = mul(x = zero_mean_17_cast_fp16, y = zero_mean_17_cast_fp16)[name = tensor("zero_mean_sq_17_cast_fp16")]; + tensor var_2850 = const()[name = tensor("op_2850"), val = tensor([1])]; + tensor var_2851_cast_fp16 = reduce_mean(axes = var_2850, keep_dims = var_2836, x = zero_mean_sq_17_cast_fp16)[name = tensor("op_2851_cast_fp16")]; + tensor var_2852_to_fp16 = const()[name = tensor("op_2852_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2853_cast_fp16 = add(x = var_2851_cast_fp16, y = var_2852_to_fp16)[name = tensor("op_2853_cast_fp16")]; + tensor denom_17_epsilon_0_to_fp16 = const()[name = tensor("denom_17_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_17_cast_fp16 = rsqrt(epsilon = denom_17_epsilon_0_to_fp16, x = var_2853_cast_fp16)[name = tensor("denom_17_cast_fp16")]; + tensor out_17_cast_fp16 = mul(x = zero_mean_17_cast_fp16, y = denom_17_cast_fp16)[name = tensor("out_17_cast_fp16")]; + tensor obj_17_gamma_0_to_fp16 = const()[name = tensor("obj_17_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(28578048)))]; + tensor obj_17_beta_0_to_fp16 = const()[name = tensor("obj_17_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(28579136)))]; + tensor obj_17_epsilon_0_to_fp16 = const()[name = tensor("obj_17_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_17_cast_fp16 = batch_norm(beta = obj_17_beta_0_to_fp16, epsilon = obj_17_epsilon_0_to_fp16, gamma = obj_17_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_17_cast_fp16)[name = tensor("obj_17_cast_fp16")]; + tensor var_2868 = const()[name = tensor("op_2868"), val = tensor([1, 1])]; + tensor var_2870 = const()[name = tensor("op_2870"), val = tensor([1, 1])]; + tensor query_9_pad_type_0 = const()[name = tensor("query_9_pad_type_0"), val = tensor("custom")]; + tensor query_9_pad_0 = const()[name = tensor("query_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(28580224)))]; + tensor layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29104576)))]; + tensor query_9_cast_fp16 = conv(bias = layers_4_self_attn_q_proj_bias_to_fp16, dilations = var_2870, groups = var_2835, pad = query_9_pad_0, pad_type = query_9_pad_type_0, strides = var_2868, weight = layers_4_self_attn_q_proj_weight_to_fp16, x = obj_17_cast_fp16)[name = tensor("query_9_cast_fp16")]; + tensor var_2874 = const()[name = tensor("op_2874"), val = tensor([1, 1])]; + tensor var_2876 = const()[name = tensor("op_2876"), val = tensor([1, 1])]; + tensor key_9_pad_type_0 = const()[name = tensor("key_9_pad_type_0"), val = tensor("custom")]; + tensor key_9_pad_0 = const()[name = tensor("key_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29105664)))]; + tensor key_9_cast_fp16 = conv(dilations = var_2876, groups = var_2835, pad = key_9_pad_0, pad_type = key_9_pad_type_0, strides = var_2874, weight = layers_4_self_attn_k_proj_weight_to_fp16, x = obj_17_cast_fp16)[name = tensor("key_9_cast_fp16")]; + tensor var_2881 = const()[name = tensor("op_2881"), val = tensor([1, 1])]; + tensor var_2883 = const()[name = tensor("op_2883"), val = tensor([1, 1])]; + tensor value_9_pad_type_0 = const()[name = tensor("value_9_pad_type_0"), val = tensor("custom")]; + tensor value_9_pad_0 = const()[name = tensor("value_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29630016)))]; + tensor layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30154368)))]; + tensor value_9_cast_fp16 = conv(bias = layers_4_self_attn_v_proj_bias_to_fp16, dilations = var_2883, groups = var_2835, pad = value_9_pad_0, pad_type = value_9_pad_type_0, strides = var_2881, weight = layers_4_self_attn_v_proj_weight_to_fp16, x = obj_17_cast_fp16)[name = tensor("value_9_cast_fp16")]; + tensor var_2890_begin_0 = const()[name = tensor("op_2890_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2890_end_0 = const()[name = tensor("op_2890_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2890_end_mask_0 = const()[name = tensor("op_2890_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2890_cast_fp16 = slice_by_index(begin = var_2890_begin_0, end = var_2890_end_0, end_mask = var_2890_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_2890_cast_fp16")]; + tensor var_2894_begin_0 = const()[name = tensor("op_2894_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_2894_end_0 = const()[name = tensor("op_2894_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_2894_end_mask_0 = const()[name = tensor("op_2894_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2894_cast_fp16 = slice_by_index(begin = var_2894_begin_0, end = var_2894_end_0, end_mask = var_2894_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_2894_cast_fp16")]; + tensor var_2898_begin_0 = const()[name = tensor("op_2898_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_2898_end_0 = const()[name = tensor("op_2898_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_2898_end_mask_0 = const()[name = tensor("op_2898_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2898_cast_fp16 = slice_by_index(begin = var_2898_begin_0, end = var_2898_end_0, end_mask = var_2898_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_2898_cast_fp16")]; + tensor var_2902_begin_0 = const()[name = tensor("op_2902_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_2902_end_0 = const()[name = tensor("op_2902_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_2902_end_mask_0 = const()[name = tensor("op_2902_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2902_cast_fp16 = slice_by_index(begin = var_2902_begin_0, end = var_2902_end_0, end_mask = var_2902_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_2902_cast_fp16")]; + tensor var_2906_begin_0 = const()[name = tensor("op_2906_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_2906_end_0 = const()[name = tensor("op_2906_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_2906_end_mask_0 = const()[name = tensor("op_2906_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2906_cast_fp16 = slice_by_index(begin = var_2906_begin_0, end = var_2906_end_0, end_mask = var_2906_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_2906_cast_fp16")]; + tensor var_2910_begin_0 = const()[name = tensor("op_2910_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_2910_end_0 = const()[name = tensor("op_2910_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_2910_end_mask_0 = const()[name = tensor("op_2910_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2910_cast_fp16 = slice_by_index(begin = var_2910_begin_0, end = var_2910_end_0, end_mask = var_2910_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_2910_cast_fp16")]; + tensor var_2914_begin_0 = const()[name = tensor("op_2914_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_2914_end_0 = const()[name = tensor("op_2914_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_2914_end_mask_0 = const()[name = tensor("op_2914_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2914_cast_fp16 = slice_by_index(begin = var_2914_begin_0, end = var_2914_end_0, end_mask = var_2914_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_2914_cast_fp16")]; + tensor var_2918_begin_0 = const()[name = tensor("op_2918_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_2918_end_0 = const()[name = tensor("op_2918_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_2918_end_mask_0 = const()[name = tensor("op_2918_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2918_cast_fp16 = slice_by_index(begin = var_2918_begin_0, end = var_2918_end_0, end_mask = var_2918_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_2918_cast_fp16")]; + tensor var_2927_begin_0 = const()[name = tensor("op_2927_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2927_end_0 = const()[name = tensor("op_2927_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2927_end_mask_0 = const()[name = tensor("op_2927_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2927_cast_fp16 = slice_by_index(begin = var_2927_begin_0, end = var_2927_end_0, end_mask = var_2927_end_mask_0, x = var_2890_cast_fp16)[name = tensor("op_2927_cast_fp16")]; + tensor var_2934_begin_0 = const()[name = tensor("op_2934_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2934_end_0 = const()[name = tensor("op_2934_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2934_end_mask_0 = const()[name = tensor("op_2934_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2934_cast_fp16 = slice_by_index(begin = var_2934_begin_0, end = var_2934_end_0, end_mask = var_2934_end_mask_0, x = var_2890_cast_fp16)[name = tensor("op_2934_cast_fp16")]; + tensor var_2941_begin_0 = const()[name = tensor("op_2941_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2941_end_0 = const()[name = tensor("op_2941_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2941_end_mask_0 = const()[name = tensor("op_2941_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2941_cast_fp16 = slice_by_index(begin = var_2941_begin_0, end = var_2941_end_0, end_mask = var_2941_end_mask_0, x = var_2890_cast_fp16)[name = tensor("op_2941_cast_fp16")]; + tensor var_2948_begin_0 = const()[name = tensor("op_2948_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2948_end_0 = const()[name = tensor("op_2948_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2948_end_mask_0 = const()[name = tensor("op_2948_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2948_cast_fp16 = slice_by_index(begin = var_2948_begin_0, end = var_2948_end_0, end_mask = var_2948_end_mask_0, x = var_2890_cast_fp16)[name = tensor("op_2948_cast_fp16")]; + tensor var_2955_begin_0 = const()[name = tensor("op_2955_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2955_end_0 = const()[name = tensor("op_2955_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2955_end_mask_0 = const()[name = tensor("op_2955_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2955_cast_fp16 = slice_by_index(begin = var_2955_begin_0, end = var_2955_end_0, end_mask = var_2955_end_mask_0, x = var_2894_cast_fp16)[name = tensor("op_2955_cast_fp16")]; + tensor var_2962_begin_0 = const()[name = tensor("op_2962_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2962_end_0 = const()[name = tensor("op_2962_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2962_end_mask_0 = const()[name = tensor("op_2962_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2962_cast_fp16 = slice_by_index(begin = var_2962_begin_0, end = var_2962_end_0, end_mask = var_2962_end_mask_0, x = var_2894_cast_fp16)[name = tensor("op_2962_cast_fp16")]; + tensor var_2969_begin_0 = const()[name = tensor("op_2969_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2969_end_0 = const()[name = tensor("op_2969_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2969_end_mask_0 = const()[name = tensor("op_2969_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2969_cast_fp16 = slice_by_index(begin = var_2969_begin_0, end = var_2969_end_0, end_mask = var_2969_end_mask_0, x = var_2894_cast_fp16)[name = tensor("op_2969_cast_fp16")]; + tensor var_2976_begin_0 = const()[name = tensor("op_2976_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2976_end_0 = const()[name = tensor("op_2976_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2976_end_mask_0 = const()[name = tensor("op_2976_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2976_cast_fp16 = slice_by_index(begin = var_2976_begin_0, end = var_2976_end_0, end_mask = var_2976_end_mask_0, x = var_2894_cast_fp16)[name = tensor("op_2976_cast_fp16")]; + tensor var_2983_begin_0 = const()[name = tensor("op_2983_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2983_end_0 = const()[name = tensor("op_2983_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2983_end_mask_0 = const()[name = tensor("op_2983_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2983_cast_fp16 = slice_by_index(begin = var_2983_begin_0, end = var_2983_end_0, end_mask = var_2983_end_mask_0, x = var_2898_cast_fp16)[name = tensor("op_2983_cast_fp16")]; + tensor var_2990_begin_0 = const()[name = tensor("op_2990_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2990_end_0 = const()[name = tensor("op_2990_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2990_end_mask_0 = const()[name = tensor("op_2990_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2990_cast_fp16 = slice_by_index(begin = var_2990_begin_0, end = var_2990_end_0, end_mask = var_2990_end_mask_0, x = var_2898_cast_fp16)[name = tensor("op_2990_cast_fp16")]; + tensor var_2997_begin_0 = const()[name = tensor("op_2997_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2997_end_0 = const()[name = tensor("op_2997_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2997_end_mask_0 = const()[name = tensor("op_2997_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2997_cast_fp16 = slice_by_index(begin = var_2997_begin_0, end = var_2997_end_0, end_mask = var_2997_end_mask_0, x = var_2898_cast_fp16)[name = tensor("op_2997_cast_fp16")]; + tensor var_3004_begin_0 = const()[name = tensor("op_3004_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3004_end_0 = const()[name = tensor("op_3004_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3004_end_mask_0 = const()[name = tensor("op_3004_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3004_cast_fp16 = slice_by_index(begin = var_3004_begin_0, end = var_3004_end_0, end_mask = var_3004_end_mask_0, x = var_2898_cast_fp16)[name = tensor("op_3004_cast_fp16")]; + tensor var_3011_begin_0 = const()[name = tensor("op_3011_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3011_end_0 = const()[name = tensor("op_3011_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3011_end_mask_0 = const()[name = tensor("op_3011_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3011_cast_fp16 = slice_by_index(begin = var_3011_begin_0, end = var_3011_end_0, end_mask = var_3011_end_mask_0, x = var_2902_cast_fp16)[name = tensor("op_3011_cast_fp16")]; + tensor var_3018_begin_0 = const()[name = tensor("op_3018_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3018_end_0 = const()[name = tensor("op_3018_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3018_end_mask_0 = const()[name = tensor("op_3018_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3018_cast_fp16 = slice_by_index(begin = var_3018_begin_0, end = var_3018_end_0, end_mask = var_3018_end_mask_0, x = var_2902_cast_fp16)[name = tensor("op_3018_cast_fp16")]; + tensor var_3025_begin_0 = const()[name = tensor("op_3025_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3025_end_0 = const()[name = tensor("op_3025_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3025_end_mask_0 = const()[name = tensor("op_3025_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3025_cast_fp16 = slice_by_index(begin = var_3025_begin_0, end = var_3025_end_0, end_mask = var_3025_end_mask_0, x = var_2902_cast_fp16)[name = tensor("op_3025_cast_fp16")]; + tensor var_3032_begin_0 = const()[name = tensor("op_3032_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3032_end_0 = const()[name = tensor("op_3032_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3032_end_mask_0 = const()[name = tensor("op_3032_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3032_cast_fp16 = slice_by_index(begin = var_3032_begin_0, end = var_3032_end_0, end_mask = var_3032_end_mask_0, x = var_2902_cast_fp16)[name = tensor("op_3032_cast_fp16")]; + tensor var_3039_begin_0 = const()[name = tensor("op_3039_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3039_end_0 = const()[name = tensor("op_3039_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3039_end_mask_0 = const()[name = tensor("op_3039_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3039_cast_fp16 = slice_by_index(begin = var_3039_begin_0, end = var_3039_end_0, end_mask = var_3039_end_mask_0, x = var_2906_cast_fp16)[name = tensor("op_3039_cast_fp16")]; + tensor var_3046_begin_0 = const()[name = tensor("op_3046_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3046_end_0 = const()[name = tensor("op_3046_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3046_end_mask_0 = const()[name = tensor("op_3046_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3046_cast_fp16 = slice_by_index(begin = var_3046_begin_0, end = var_3046_end_0, end_mask = var_3046_end_mask_0, x = var_2906_cast_fp16)[name = tensor("op_3046_cast_fp16")]; + tensor var_3053_begin_0 = const()[name = tensor("op_3053_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3053_end_0 = const()[name = tensor("op_3053_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3053_end_mask_0 = const()[name = tensor("op_3053_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3053_cast_fp16 = slice_by_index(begin = var_3053_begin_0, end = var_3053_end_0, end_mask = var_3053_end_mask_0, x = var_2906_cast_fp16)[name = tensor("op_3053_cast_fp16")]; + tensor var_3060_begin_0 = const()[name = tensor("op_3060_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3060_end_0 = const()[name = tensor("op_3060_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3060_end_mask_0 = const()[name = tensor("op_3060_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3060_cast_fp16 = slice_by_index(begin = var_3060_begin_0, end = var_3060_end_0, end_mask = var_3060_end_mask_0, x = var_2906_cast_fp16)[name = tensor("op_3060_cast_fp16")]; + tensor var_3067_begin_0 = const()[name = tensor("op_3067_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3067_end_0 = const()[name = tensor("op_3067_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3067_end_mask_0 = const()[name = tensor("op_3067_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3067_cast_fp16 = slice_by_index(begin = var_3067_begin_0, end = var_3067_end_0, end_mask = var_3067_end_mask_0, x = var_2910_cast_fp16)[name = tensor("op_3067_cast_fp16")]; + tensor var_3074_begin_0 = const()[name = tensor("op_3074_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3074_end_0 = const()[name = tensor("op_3074_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3074_end_mask_0 = const()[name = tensor("op_3074_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3074_cast_fp16 = slice_by_index(begin = var_3074_begin_0, end = var_3074_end_0, end_mask = var_3074_end_mask_0, x = var_2910_cast_fp16)[name = tensor("op_3074_cast_fp16")]; + tensor var_3081_begin_0 = const()[name = tensor("op_3081_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3081_end_0 = const()[name = tensor("op_3081_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3081_end_mask_0 = const()[name = tensor("op_3081_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3081_cast_fp16 = slice_by_index(begin = var_3081_begin_0, end = var_3081_end_0, end_mask = var_3081_end_mask_0, x = var_2910_cast_fp16)[name = tensor("op_3081_cast_fp16")]; + tensor var_3088_begin_0 = const()[name = tensor("op_3088_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3088_end_0 = const()[name = tensor("op_3088_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3088_end_mask_0 = const()[name = tensor("op_3088_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3088_cast_fp16 = slice_by_index(begin = var_3088_begin_0, end = var_3088_end_0, end_mask = var_3088_end_mask_0, x = var_2910_cast_fp16)[name = tensor("op_3088_cast_fp16")]; + tensor var_3095_begin_0 = const()[name = tensor("op_3095_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3095_end_0 = const()[name = tensor("op_3095_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3095_end_mask_0 = const()[name = tensor("op_3095_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3095_cast_fp16 = slice_by_index(begin = var_3095_begin_0, end = var_3095_end_0, end_mask = var_3095_end_mask_0, x = var_2914_cast_fp16)[name = tensor("op_3095_cast_fp16")]; + tensor var_3102_begin_0 = const()[name = tensor("op_3102_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3102_end_0 = const()[name = tensor("op_3102_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3102_end_mask_0 = const()[name = tensor("op_3102_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3102_cast_fp16 = slice_by_index(begin = var_3102_begin_0, end = var_3102_end_0, end_mask = var_3102_end_mask_0, x = var_2914_cast_fp16)[name = tensor("op_3102_cast_fp16")]; + tensor var_3109_begin_0 = const()[name = tensor("op_3109_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3109_end_0 = const()[name = tensor("op_3109_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3109_end_mask_0 = const()[name = tensor("op_3109_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3109_cast_fp16 = slice_by_index(begin = var_3109_begin_0, end = var_3109_end_0, end_mask = var_3109_end_mask_0, x = var_2914_cast_fp16)[name = tensor("op_3109_cast_fp16")]; + tensor var_3116_begin_0 = const()[name = tensor("op_3116_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3116_end_0 = const()[name = tensor("op_3116_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3116_end_mask_0 = const()[name = tensor("op_3116_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3116_cast_fp16 = slice_by_index(begin = var_3116_begin_0, end = var_3116_end_0, end_mask = var_3116_end_mask_0, x = var_2914_cast_fp16)[name = tensor("op_3116_cast_fp16")]; + tensor var_3123_begin_0 = const()[name = tensor("op_3123_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3123_end_0 = const()[name = tensor("op_3123_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3123_end_mask_0 = const()[name = tensor("op_3123_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3123_cast_fp16 = slice_by_index(begin = var_3123_begin_0, end = var_3123_end_0, end_mask = var_3123_end_mask_0, x = var_2918_cast_fp16)[name = tensor("op_3123_cast_fp16")]; + tensor var_3130_begin_0 = const()[name = tensor("op_3130_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3130_end_0 = const()[name = tensor("op_3130_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3130_end_mask_0 = const()[name = tensor("op_3130_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3130_cast_fp16 = slice_by_index(begin = var_3130_begin_0, end = var_3130_end_0, end_mask = var_3130_end_mask_0, x = var_2918_cast_fp16)[name = tensor("op_3130_cast_fp16")]; + tensor var_3137_begin_0 = const()[name = tensor("op_3137_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3137_end_0 = const()[name = tensor("op_3137_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3137_end_mask_0 = const()[name = tensor("op_3137_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3137_cast_fp16 = slice_by_index(begin = var_3137_begin_0, end = var_3137_end_0, end_mask = var_3137_end_mask_0, x = var_2918_cast_fp16)[name = tensor("op_3137_cast_fp16")]; + tensor var_3144_begin_0 = const()[name = tensor("op_3144_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3144_end_0 = const()[name = tensor("op_3144_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3144_end_mask_0 = const()[name = tensor("op_3144_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3144_cast_fp16 = slice_by_index(begin = var_3144_begin_0, end = var_3144_end_0, end_mask = var_3144_end_mask_0, x = var_2918_cast_fp16)[name = tensor("op_3144_cast_fp16")]; + tensor k_9_perm_0 = const()[name = tensor("k_9_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_3149_begin_0 = const()[name = tensor("op_3149_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3149_end_0 = const()[name = tensor("op_3149_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_3149_end_mask_0 = const()[name = tensor("op_3149_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_1 = transpose(perm = k_9_perm_0, x = key_9_cast_fp16)[name = tensor("transpose_1")]; + tensor var_3149_cast_fp16 = slice_by_index(begin = var_3149_begin_0, end = var_3149_end_0, end_mask = var_3149_end_mask_0, x = transpose_1)[name = tensor("op_3149_cast_fp16")]; + tensor var_3153_begin_0 = const()[name = tensor("op_3153_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_3153_end_0 = const()[name = tensor("op_3153_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_3153_end_mask_0 = const()[name = tensor("op_3153_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3153_cast_fp16 = slice_by_index(begin = var_3153_begin_0, end = var_3153_end_0, end_mask = var_3153_end_mask_0, x = transpose_1)[name = tensor("op_3153_cast_fp16")]; + tensor var_3157_begin_0 = const()[name = tensor("op_3157_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_3157_end_0 = const()[name = tensor("op_3157_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_3157_end_mask_0 = const()[name = tensor("op_3157_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3157_cast_fp16 = slice_by_index(begin = var_3157_begin_0, end = var_3157_end_0, end_mask = var_3157_end_mask_0, x = transpose_1)[name = tensor("op_3157_cast_fp16")]; + tensor var_3161_begin_0 = const()[name = tensor("op_3161_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_3161_end_0 = const()[name = tensor("op_3161_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_3161_end_mask_0 = const()[name = tensor("op_3161_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3161_cast_fp16 = slice_by_index(begin = var_3161_begin_0, end = var_3161_end_0, end_mask = var_3161_end_mask_0, x = transpose_1)[name = tensor("op_3161_cast_fp16")]; + tensor var_3165_begin_0 = const()[name = tensor("op_3165_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_3165_end_0 = const()[name = tensor("op_3165_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_3165_end_mask_0 = const()[name = tensor("op_3165_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3165_cast_fp16 = slice_by_index(begin = var_3165_begin_0, end = var_3165_end_0, end_mask = var_3165_end_mask_0, x = transpose_1)[name = tensor("op_3165_cast_fp16")]; + tensor var_3169_begin_0 = const()[name = tensor("op_3169_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_3169_end_0 = const()[name = tensor("op_3169_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_3169_end_mask_0 = const()[name = tensor("op_3169_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3169_cast_fp16 = slice_by_index(begin = var_3169_begin_0, end = var_3169_end_0, end_mask = var_3169_end_mask_0, x = transpose_1)[name = tensor("op_3169_cast_fp16")]; + tensor var_3173_begin_0 = const()[name = tensor("op_3173_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_3173_end_0 = const()[name = tensor("op_3173_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_3173_end_mask_0 = const()[name = tensor("op_3173_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3173_cast_fp16 = slice_by_index(begin = var_3173_begin_0, end = var_3173_end_0, end_mask = var_3173_end_mask_0, x = transpose_1)[name = tensor("op_3173_cast_fp16")]; + tensor var_3177_begin_0 = const()[name = tensor("op_3177_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_3177_end_0 = const()[name = tensor("op_3177_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_3177_end_mask_0 = const()[name = tensor("op_3177_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3177_cast_fp16 = slice_by_index(begin = var_3177_begin_0, end = var_3177_end_0, end_mask = var_3177_end_mask_0, x = transpose_1)[name = tensor("op_3177_cast_fp16")]; + tensor var_3179_begin_0 = const()[name = tensor("op_3179_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3179_end_0 = const()[name = tensor("op_3179_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3179_end_mask_0 = const()[name = tensor("op_3179_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3179_cast_fp16 = slice_by_index(begin = var_3179_begin_0, end = var_3179_end_0, end_mask = var_3179_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_3179_cast_fp16")]; + tensor var_3183_begin_0 = const()[name = tensor("op_3183_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_3183_end_0 = const()[name = tensor("op_3183_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_3183_end_mask_0 = const()[name = tensor("op_3183_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3183_cast_fp16 = slice_by_index(begin = var_3183_begin_0, end = var_3183_end_0, end_mask = var_3183_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_3183_cast_fp16")]; + tensor var_3187_begin_0 = const()[name = tensor("op_3187_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_3187_end_0 = const()[name = tensor("op_3187_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_3187_end_mask_0 = const()[name = tensor("op_3187_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3187_cast_fp16 = slice_by_index(begin = var_3187_begin_0, end = var_3187_end_0, end_mask = var_3187_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_3187_cast_fp16")]; + tensor var_3191_begin_0 = const()[name = tensor("op_3191_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_3191_end_0 = const()[name = tensor("op_3191_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_3191_end_mask_0 = const()[name = tensor("op_3191_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3191_cast_fp16 = slice_by_index(begin = var_3191_begin_0, end = var_3191_end_0, end_mask = var_3191_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_3191_cast_fp16")]; + tensor var_3195_begin_0 = const()[name = tensor("op_3195_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_3195_end_0 = const()[name = tensor("op_3195_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_3195_end_mask_0 = const()[name = tensor("op_3195_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3195_cast_fp16 = slice_by_index(begin = var_3195_begin_0, end = var_3195_end_0, end_mask = var_3195_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_3195_cast_fp16")]; + tensor var_3199_begin_0 = const()[name = tensor("op_3199_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_3199_end_0 = const()[name = tensor("op_3199_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_3199_end_mask_0 = const()[name = tensor("op_3199_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3199_cast_fp16 = slice_by_index(begin = var_3199_begin_0, end = var_3199_end_0, end_mask = var_3199_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_3199_cast_fp16")]; + tensor var_3203_begin_0 = const()[name = tensor("op_3203_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_3203_end_0 = const()[name = tensor("op_3203_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_3203_end_mask_0 = const()[name = tensor("op_3203_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3203_cast_fp16 = slice_by_index(begin = var_3203_begin_0, end = var_3203_end_0, end_mask = var_3203_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_3203_cast_fp16")]; + tensor var_3207_begin_0 = const()[name = tensor("op_3207_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_3207_end_0 = const()[name = tensor("op_3207_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_3207_end_mask_0 = const()[name = tensor("op_3207_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3207_cast_fp16 = slice_by_index(begin = var_3207_begin_0, end = var_3207_end_0, end_mask = var_3207_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_3207_cast_fp16")]; + tensor var_3211_equation_0 = const()[name = tensor("op_3211_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3211_cast_fp16 = einsum(equation = var_3211_equation_0, values = (var_3149_cast_fp16, var_2927_cast_fp16))[name = tensor("op_3211_cast_fp16")]; + tensor var_3212_to_fp16 = const()[name = tensor("op_3212_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_257_cast_fp16 = mul(x = var_3211_cast_fp16, y = var_3212_to_fp16)[name = tensor("aw_chunk_257_cast_fp16")]; + tensor var_3215_equation_0 = const()[name = tensor("op_3215_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3215_cast_fp16 = einsum(equation = var_3215_equation_0, values = (var_3149_cast_fp16, var_2934_cast_fp16))[name = tensor("op_3215_cast_fp16")]; + tensor var_3216_to_fp16 = const()[name = tensor("op_3216_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_259_cast_fp16 = mul(x = var_3215_cast_fp16, y = var_3216_to_fp16)[name = tensor("aw_chunk_259_cast_fp16")]; + tensor var_3219_equation_0 = const()[name = tensor("op_3219_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3219_cast_fp16 = einsum(equation = var_3219_equation_0, values = (var_3149_cast_fp16, var_2941_cast_fp16))[name = tensor("op_3219_cast_fp16")]; + tensor var_3220_to_fp16 = const()[name = tensor("op_3220_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_261_cast_fp16 = mul(x = var_3219_cast_fp16, y = var_3220_to_fp16)[name = tensor("aw_chunk_261_cast_fp16")]; + tensor var_3223_equation_0 = const()[name = tensor("op_3223_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3223_cast_fp16 = einsum(equation = var_3223_equation_0, values = (var_3149_cast_fp16, var_2948_cast_fp16))[name = tensor("op_3223_cast_fp16")]; + tensor var_3224_to_fp16 = const()[name = tensor("op_3224_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_263_cast_fp16 = mul(x = var_3223_cast_fp16, y = var_3224_to_fp16)[name = tensor("aw_chunk_263_cast_fp16")]; + tensor var_3227_equation_0 = const()[name = tensor("op_3227_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3227_cast_fp16 = einsum(equation = var_3227_equation_0, values = (var_3153_cast_fp16, var_2955_cast_fp16))[name = tensor("op_3227_cast_fp16")]; + tensor var_3228_to_fp16 = const()[name = tensor("op_3228_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_265_cast_fp16 = mul(x = var_3227_cast_fp16, y = var_3228_to_fp16)[name = tensor("aw_chunk_265_cast_fp16")]; + tensor var_3231_equation_0 = const()[name = tensor("op_3231_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3231_cast_fp16 = einsum(equation = var_3231_equation_0, values = (var_3153_cast_fp16, var_2962_cast_fp16))[name = tensor("op_3231_cast_fp16")]; + tensor var_3232_to_fp16 = const()[name = tensor("op_3232_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_267_cast_fp16 = mul(x = var_3231_cast_fp16, y = var_3232_to_fp16)[name = tensor("aw_chunk_267_cast_fp16")]; + tensor var_3235_equation_0 = const()[name = tensor("op_3235_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3235_cast_fp16 = einsum(equation = var_3235_equation_0, values = (var_3153_cast_fp16, var_2969_cast_fp16))[name = tensor("op_3235_cast_fp16")]; + tensor var_3236_to_fp16 = const()[name = tensor("op_3236_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_269_cast_fp16 = mul(x = var_3235_cast_fp16, y = var_3236_to_fp16)[name = tensor("aw_chunk_269_cast_fp16")]; + tensor var_3239_equation_0 = const()[name = tensor("op_3239_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3239_cast_fp16 = einsum(equation = var_3239_equation_0, values = (var_3153_cast_fp16, var_2976_cast_fp16))[name = tensor("op_3239_cast_fp16")]; + tensor var_3240_to_fp16 = const()[name = tensor("op_3240_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_271_cast_fp16 = mul(x = var_3239_cast_fp16, y = var_3240_to_fp16)[name = tensor("aw_chunk_271_cast_fp16")]; + tensor var_3243_equation_0 = const()[name = tensor("op_3243_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3243_cast_fp16 = einsum(equation = var_3243_equation_0, values = (var_3157_cast_fp16, var_2983_cast_fp16))[name = tensor("op_3243_cast_fp16")]; + tensor var_3244_to_fp16 = const()[name = tensor("op_3244_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_273_cast_fp16 = mul(x = var_3243_cast_fp16, y = var_3244_to_fp16)[name = tensor("aw_chunk_273_cast_fp16")]; + tensor var_3247_equation_0 = const()[name = tensor("op_3247_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3247_cast_fp16 = einsum(equation = var_3247_equation_0, values = (var_3157_cast_fp16, var_2990_cast_fp16))[name = tensor("op_3247_cast_fp16")]; + tensor var_3248_to_fp16 = const()[name = tensor("op_3248_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_275_cast_fp16 = mul(x = var_3247_cast_fp16, y = var_3248_to_fp16)[name = tensor("aw_chunk_275_cast_fp16")]; + tensor var_3251_equation_0 = const()[name = tensor("op_3251_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3251_cast_fp16 = einsum(equation = var_3251_equation_0, values = (var_3157_cast_fp16, var_2997_cast_fp16))[name = tensor("op_3251_cast_fp16")]; + tensor var_3252_to_fp16 = const()[name = tensor("op_3252_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_277_cast_fp16 = mul(x = var_3251_cast_fp16, y = var_3252_to_fp16)[name = tensor("aw_chunk_277_cast_fp16")]; + tensor var_3255_equation_0 = const()[name = tensor("op_3255_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3255_cast_fp16 = einsum(equation = var_3255_equation_0, values = (var_3157_cast_fp16, var_3004_cast_fp16))[name = tensor("op_3255_cast_fp16")]; + tensor var_3256_to_fp16 = const()[name = tensor("op_3256_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_279_cast_fp16 = mul(x = var_3255_cast_fp16, y = var_3256_to_fp16)[name = tensor("aw_chunk_279_cast_fp16")]; + tensor var_3259_equation_0 = const()[name = tensor("op_3259_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3259_cast_fp16 = einsum(equation = var_3259_equation_0, values = (var_3161_cast_fp16, var_3011_cast_fp16))[name = tensor("op_3259_cast_fp16")]; + tensor var_3260_to_fp16 = const()[name = tensor("op_3260_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_281_cast_fp16 = mul(x = var_3259_cast_fp16, y = var_3260_to_fp16)[name = tensor("aw_chunk_281_cast_fp16")]; + tensor var_3263_equation_0 = const()[name = tensor("op_3263_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3263_cast_fp16 = einsum(equation = var_3263_equation_0, values = (var_3161_cast_fp16, var_3018_cast_fp16))[name = tensor("op_3263_cast_fp16")]; + tensor var_3264_to_fp16 = const()[name = tensor("op_3264_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_283_cast_fp16 = mul(x = var_3263_cast_fp16, y = var_3264_to_fp16)[name = tensor("aw_chunk_283_cast_fp16")]; + tensor var_3267_equation_0 = const()[name = tensor("op_3267_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3267_cast_fp16 = einsum(equation = var_3267_equation_0, values = (var_3161_cast_fp16, var_3025_cast_fp16))[name = tensor("op_3267_cast_fp16")]; + tensor var_3268_to_fp16 = const()[name = tensor("op_3268_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_285_cast_fp16 = mul(x = var_3267_cast_fp16, y = var_3268_to_fp16)[name = tensor("aw_chunk_285_cast_fp16")]; + tensor var_3271_equation_0 = const()[name = tensor("op_3271_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3271_cast_fp16 = einsum(equation = var_3271_equation_0, values = (var_3161_cast_fp16, var_3032_cast_fp16))[name = tensor("op_3271_cast_fp16")]; + tensor var_3272_to_fp16 = const()[name = tensor("op_3272_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_287_cast_fp16 = mul(x = var_3271_cast_fp16, y = var_3272_to_fp16)[name = tensor("aw_chunk_287_cast_fp16")]; + tensor var_3275_equation_0 = const()[name = tensor("op_3275_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3275_cast_fp16 = einsum(equation = var_3275_equation_0, values = (var_3165_cast_fp16, var_3039_cast_fp16))[name = tensor("op_3275_cast_fp16")]; + tensor var_3276_to_fp16 = const()[name = tensor("op_3276_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_289_cast_fp16 = mul(x = var_3275_cast_fp16, y = var_3276_to_fp16)[name = tensor("aw_chunk_289_cast_fp16")]; + tensor var_3279_equation_0 = const()[name = tensor("op_3279_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3279_cast_fp16 = einsum(equation = var_3279_equation_0, values = (var_3165_cast_fp16, var_3046_cast_fp16))[name = tensor("op_3279_cast_fp16")]; + tensor var_3280_to_fp16 = const()[name = tensor("op_3280_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_291_cast_fp16 = mul(x = var_3279_cast_fp16, y = var_3280_to_fp16)[name = tensor("aw_chunk_291_cast_fp16")]; + tensor var_3283_equation_0 = const()[name = tensor("op_3283_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3283_cast_fp16 = einsum(equation = var_3283_equation_0, values = (var_3165_cast_fp16, var_3053_cast_fp16))[name = tensor("op_3283_cast_fp16")]; + tensor var_3284_to_fp16 = const()[name = tensor("op_3284_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_293_cast_fp16 = mul(x = var_3283_cast_fp16, y = var_3284_to_fp16)[name = tensor("aw_chunk_293_cast_fp16")]; + tensor var_3287_equation_0 = const()[name = tensor("op_3287_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3287_cast_fp16 = einsum(equation = var_3287_equation_0, values = (var_3165_cast_fp16, var_3060_cast_fp16))[name = tensor("op_3287_cast_fp16")]; + tensor var_3288_to_fp16 = const()[name = tensor("op_3288_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_295_cast_fp16 = mul(x = var_3287_cast_fp16, y = var_3288_to_fp16)[name = tensor("aw_chunk_295_cast_fp16")]; + tensor var_3291_equation_0 = const()[name = tensor("op_3291_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3291_cast_fp16 = einsum(equation = var_3291_equation_0, values = (var_3169_cast_fp16, var_3067_cast_fp16))[name = tensor("op_3291_cast_fp16")]; + tensor var_3292_to_fp16 = const()[name = tensor("op_3292_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_297_cast_fp16 = mul(x = var_3291_cast_fp16, y = var_3292_to_fp16)[name = tensor("aw_chunk_297_cast_fp16")]; + tensor var_3295_equation_0 = const()[name = tensor("op_3295_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3295_cast_fp16 = einsum(equation = var_3295_equation_0, values = (var_3169_cast_fp16, var_3074_cast_fp16))[name = tensor("op_3295_cast_fp16")]; + tensor var_3296_to_fp16 = const()[name = tensor("op_3296_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_299_cast_fp16 = mul(x = var_3295_cast_fp16, y = var_3296_to_fp16)[name = tensor("aw_chunk_299_cast_fp16")]; + tensor var_3299_equation_0 = const()[name = tensor("op_3299_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3299_cast_fp16 = einsum(equation = var_3299_equation_0, values = (var_3169_cast_fp16, var_3081_cast_fp16))[name = tensor("op_3299_cast_fp16")]; + tensor var_3300_to_fp16 = const()[name = tensor("op_3300_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_301_cast_fp16 = mul(x = var_3299_cast_fp16, y = var_3300_to_fp16)[name = tensor("aw_chunk_301_cast_fp16")]; + tensor var_3303_equation_0 = const()[name = tensor("op_3303_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3303_cast_fp16 = einsum(equation = var_3303_equation_0, values = (var_3169_cast_fp16, var_3088_cast_fp16))[name = tensor("op_3303_cast_fp16")]; + tensor var_3304_to_fp16 = const()[name = tensor("op_3304_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_303_cast_fp16 = mul(x = var_3303_cast_fp16, y = var_3304_to_fp16)[name = tensor("aw_chunk_303_cast_fp16")]; + tensor var_3307_equation_0 = const()[name = tensor("op_3307_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3307_cast_fp16 = einsum(equation = var_3307_equation_0, values = (var_3173_cast_fp16, var_3095_cast_fp16))[name = tensor("op_3307_cast_fp16")]; + tensor var_3308_to_fp16 = const()[name = tensor("op_3308_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_305_cast_fp16 = mul(x = var_3307_cast_fp16, y = var_3308_to_fp16)[name = tensor("aw_chunk_305_cast_fp16")]; + tensor var_3311_equation_0 = const()[name = tensor("op_3311_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3311_cast_fp16 = einsum(equation = var_3311_equation_0, values = (var_3173_cast_fp16, var_3102_cast_fp16))[name = tensor("op_3311_cast_fp16")]; + tensor var_3312_to_fp16 = const()[name = tensor("op_3312_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_307_cast_fp16 = mul(x = var_3311_cast_fp16, y = var_3312_to_fp16)[name = tensor("aw_chunk_307_cast_fp16")]; + tensor var_3315_equation_0 = const()[name = tensor("op_3315_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3315_cast_fp16 = einsum(equation = var_3315_equation_0, values = (var_3173_cast_fp16, var_3109_cast_fp16))[name = tensor("op_3315_cast_fp16")]; + tensor var_3316_to_fp16 = const()[name = tensor("op_3316_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_309_cast_fp16 = mul(x = var_3315_cast_fp16, y = var_3316_to_fp16)[name = tensor("aw_chunk_309_cast_fp16")]; + tensor var_3319_equation_0 = const()[name = tensor("op_3319_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3319_cast_fp16 = einsum(equation = var_3319_equation_0, values = (var_3173_cast_fp16, var_3116_cast_fp16))[name = tensor("op_3319_cast_fp16")]; + tensor var_3320_to_fp16 = const()[name = tensor("op_3320_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_311_cast_fp16 = mul(x = var_3319_cast_fp16, y = var_3320_to_fp16)[name = tensor("aw_chunk_311_cast_fp16")]; + tensor var_3323_equation_0 = const()[name = tensor("op_3323_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3323_cast_fp16 = einsum(equation = var_3323_equation_0, values = (var_3177_cast_fp16, var_3123_cast_fp16))[name = tensor("op_3323_cast_fp16")]; + tensor var_3324_to_fp16 = const()[name = tensor("op_3324_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_313_cast_fp16 = mul(x = var_3323_cast_fp16, y = var_3324_to_fp16)[name = tensor("aw_chunk_313_cast_fp16")]; + tensor var_3327_equation_0 = const()[name = tensor("op_3327_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3327_cast_fp16 = einsum(equation = var_3327_equation_0, values = (var_3177_cast_fp16, var_3130_cast_fp16))[name = tensor("op_3327_cast_fp16")]; + tensor var_3328_to_fp16 = const()[name = tensor("op_3328_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_315_cast_fp16 = mul(x = var_3327_cast_fp16, y = var_3328_to_fp16)[name = tensor("aw_chunk_315_cast_fp16")]; + tensor var_3331_equation_0 = const()[name = tensor("op_3331_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3331_cast_fp16 = einsum(equation = var_3331_equation_0, values = (var_3177_cast_fp16, var_3137_cast_fp16))[name = tensor("op_3331_cast_fp16")]; + tensor var_3332_to_fp16 = const()[name = tensor("op_3332_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_317_cast_fp16 = mul(x = var_3331_cast_fp16, y = var_3332_to_fp16)[name = tensor("aw_chunk_317_cast_fp16")]; + tensor var_3335_equation_0 = const()[name = tensor("op_3335_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3335_cast_fp16 = einsum(equation = var_3335_equation_0, values = (var_3177_cast_fp16, var_3144_cast_fp16))[name = tensor("op_3335_cast_fp16")]; + tensor var_3336_to_fp16 = const()[name = tensor("op_3336_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_319_cast_fp16 = mul(x = var_3335_cast_fp16, y = var_3336_to_fp16)[name = tensor("aw_chunk_319_cast_fp16")]; + tensor var_3338_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_257_cast_fp16)[name = tensor("op_3338_cast_fp16")]; + tensor var_3339_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_259_cast_fp16)[name = tensor("op_3339_cast_fp16")]; + tensor var_3340_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_261_cast_fp16)[name = tensor("op_3340_cast_fp16")]; + tensor var_3341_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_263_cast_fp16)[name = tensor("op_3341_cast_fp16")]; + tensor var_3342_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_265_cast_fp16)[name = tensor("op_3342_cast_fp16")]; + tensor var_3343_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_267_cast_fp16)[name = tensor("op_3343_cast_fp16")]; + tensor var_3344_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_269_cast_fp16)[name = tensor("op_3344_cast_fp16")]; + tensor var_3345_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_271_cast_fp16)[name = tensor("op_3345_cast_fp16")]; + tensor var_3346_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_273_cast_fp16)[name = tensor("op_3346_cast_fp16")]; + tensor var_3347_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_275_cast_fp16)[name = tensor("op_3347_cast_fp16")]; + tensor var_3348_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_277_cast_fp16)[name = tensor("op_3348_cast_fp16")]; + tensor var_3349_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_279_cast_fp16)[name = tensor("op_3349_cast_fp16")]; + tensor var_3350_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_281_cast_fp16)[name = tensor("op_3350_cast_fp16")]; + tensor var_3351_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_283_cast_fp16)[name = tensor("op_3351_cast_fp16")]; + tensor var_3352_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_285_cast_fp16)[name = tensor("op_3352_cast_fp16")]; + tensor var_3353_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_287_cast_fp16)[name = tensor("op_3353_cast_fp16")]; + tensor var_3354_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_289_cast_fp16)[name = tensor("op_3354_cast_fp16")]; + tensor var_3355_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_291_cast_fp16)[name = tensor("op_3355_cast_fp16")]; + tensor var_3356_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_293_cast_fp16)[name = tensor("op_3356_cast_fp16")]; + tensor var_3357_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_295_cast_fp16)[name = tensor("op_3357_cast_fp16")]; + tensor var_3358_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_297_cast_fp16)[name = tensor("op_3358_cast_fp16")]; + tensor var_3359_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_299_cast_fp16)[name = tensor("op_3359_cast_fp16")]; + tensor var_3360_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_301_cast_fp16)[name = tensor("op_3360_cast_fp16")]; + tensor var_3361_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_303_cast_fp16)[name = tensor("op_3361_cast_fp16")]; + tensor var_3362_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_305_cast_fp16)[name = tensor("op_3362_cast_fp16")]; + tensor var_3363_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_307_cast_fp16)[name = tensor("op_3363_cast_fp16")]; + tensor var_3364_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_309_cast_fp16)[name = tensor("op_3364_cast_fp16")]; + tensor var_3365_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_311_cast_fp16)[name = tensor("op_3365_cast_fp16")]; + tensor var_3366_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_313_cast_fp16)[name = tensor("op_3366_cast_fp16")]; + tensor var_3367_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_315_cast_fp16)[name = tensor("op_3367_cast_fp16")]; + tensor var_3368_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_317_cast_fp16)[name = tensor("op_3368_cast_fp16")]; + tensor var_3369_cast_fp16 = softmax(axis = var_2835, x = aw_chunk_319_cast_fp16)[name = tensor("op_3369_cast_fp16")]; + tensor var_3371_equation_0 = const()[name = tensor("op_3371_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3371_cast_fp16 = einsum(equation = var_3371_equation_0, values = (var_3179_cast_fp16, var_3338_cast_fp16))[name = tensor("op_3371_cast_fp16")]; + tensor var_3373_equation_0 = const()[name = tensor("op_3373_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3373_cast_fp16 = einsum(equation = var_3373_equation_0, values = (var_3179_cast_fp16, var_3339_cast_fp16))[name = tensor("op_3373_cast_fp16")]; + tensor var_3375_equation_0 = const()[name = tensor("op_3375_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3375_cast_fp16 = einsum(equation = var_3375_equation_0, values = (var_3179_cast_fp16, var_3340_cast_fp16))[name = tensor("op_3375_cast_fp16")]; + tensor var_3377_equation_0 = const()[name = tensor("op_3377_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3377_cast_fp16 = einsum(equation = var_3377_equation_0, values = (var_3179_cast_fp16, var_3341_cast_fp16))[name = tensor("op_3377_cast_fp16")]; + tensor var_3379_equation_0 = const()[name = tensor("op_3379_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3379_cast_fp16 = einsum(equation = var_3379_equation_0, values = (var_3183_cast_fp16, var_3342_cast_fp16))[name = tensor("op_3379_cast_fp16")]; + tensor var_3381_equation_0 = const()[name = tensor("op_3381_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3381_cast_fp16 = einsum(equation = var_3381_equation_0, values = (var_3183_cast_fp16, var_3343_cast_fp16))[name = tensor("op_3381_cast_fp16")]; + tensor var_3383_equation_0 = const()[name = tensor("op_3383_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3383_cast_fp16 = einsum(equation = var_3383_equation_0, values = (var_3183_cast_fp16, var_3344_cast_fp16))[name = tensor("op_3383_cast_fp16")]; + tensor var_3385_equation_0 = const()[name = tensor("op_3385_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3385_cast_fp16 = einsum(equation = var_3385_equation_0, values = (var_3183_cast_fp16, var_3345_cast_fp16))[name = tensor("op_3385_cast_fp16")]; + tensor var_3387_equation_0 = const()[name = tensor("op_3387_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3387_cast_fp16 = einsum(equation = var_3387_equation_0, values = (var_3187_cast_fp16, var_3346_cast_fp16))[name = tensor("op_3387_cast_fp16")]; + tensor var_3389_equation_0 = const()[name = tensor("op_3389_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3389_cast_fp16 = einsum(equation = var_3389_equation_0, values = (var_3187_cast_fp16, var_3347_cast_fp16))[name = tensor("op_3389_cast_fp16")]; + tensor var_3391_equation_0 = const()[name = tensor("op_3391_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3391_cast_fp16 = einsum(equation = var_3391_equation_0, values = (var_3187_cast_fp16, var_3348_cast_fp16))[name = tensor("op_3391_cast_fp16")]; + tensor var_3393_equation_0 = const()[name = tensor("op_3393_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3393_cast_fp16 = einsum(equation = var_3393_equation_0, values = (var_3187_cast_fp16, var_3349_cast_fp16))[name = tensor("op_3393_cast_fp16")]; + tensor var_3395_equation_0 = const()[name = tensor("op_3395_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3395_cast_fp16 = einsum(equation = var_3395_equation_0, values = (var_3191_cast_fp16, var_3350_cast_fp16))[name = tensor("op_3395_cast_fp16")]; + tensor var_3397_equation_0 = const()[name = tensor("op_3397_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3397_cast_fp16 = einsum(equation = var_3397_equation_0, values = (var_3191_cast_fp16, var_3351_cast_fp16))[name = tensor("op_3397_cast_fp16")]; + tensor var_3399_equation_0 = const()[name = tensor("op_3399_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3399_cast_fp16 = einsum(equation = var_3399_equation_0, values = (var_3191_cast_fp16, var_3352_cast_fp16))[name = tensor("op_3399_cast_fp16")]; + tensor var_3401_equation_0 = const()[name = tensor("op_3401_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3401_cast_fp16 = einsum(equation = var_3401_equation_0, values = (var_3191_cast_fp16, var_3353_cast_fp16))[name = tensor("op_3401_cast_fp16")]; + tensor var_3403_equation_0 = const()[name = tensor("op_3403_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3403_cast_fp16 = einsum(equation = var_3403_equation_0, values = (var_3195_cast_fp16, var_3354_cast_fp16))[name = tensor("op_3403_cast_fp16")]; + tensor var_3405_equation_0 = const()[name = tensor("op_3405_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3405_cast_fp16 = einsum(equation = var_3405_equation_0, values = (var_3195_cast_fp16, var_3355_cast_fp16))[name = tensor("op_3405_cast_fp16")]; + tensor var_3407_equation_0 = const()[name = tensor("op_3407_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3407_cast_fp16 = einsum(equation = var_3407_equation_0, values = (var_3195_cast_fp16, var_3356_cast_fp16))[name = tensor("op_3407_cast_fp16")]; + tensor var_3409_equation_0 = const()[name = tensor("op_3409_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3409_cast_fp16 = einsum(equation = var_3409_equation_0, values = (var_3195_cast_fp16, var_3357_cast_fp16))[name = tensor("op_3409_cast_fp16")]; + tensor var_3411_equation_0 = const()[name = tensor("op_3411_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3411_cast_fp16 = einsum(equation = var_3411_equation_0, values = (var_3199_cast_fp16, var_3358_cast_fp16))[name = tensor("op_3411_cast_fp16")]; + tensor var_3413_equation_0 = const()[name = tensor("op_3413_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3413_cast_fp16 = einsum(equation = var_3413_equation_0, values = (var_3199_cast_fp16, var_3359_cast_fp16))[name = tensor("op_3413_cast_fp16")]; + tensor var_3415_equation_0 = const()[name = tensor("op_3415_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3415_cast_fp16 = einsum(equation = var_3415_equation_0, values = (var_3199_cast_fp16, var_3360_cast_fp16))[name = tensor("op_3415_cast_fp16")]; + tensor var_3417_equation_0 = const()[name = tensor("op_3417_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3417_cast_fp16 = einsum(equation = var_3417_equation_0, values = (var_3199_cast_fp16, var_3361_cast_fp16))[name = tensor("op_3417_cast_fp16")]; + tensor var_3419_equation_0 = const()[name = tensor("op_3419_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3419_cast_fp16 = einsum(equation = var_3419_equation_0, values = (var_3203_cast_fp16, var_3362_cast_fp16))[name = tensor("op_3419_cast_fp16")]; + tensor var_3421_equation_0 = const()[name = tensor("op_3421_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3421_cast_fp16 = einsum(equation = var_3421_equation_0, values = (var_3203_cast_fp16, var_3363_cast_fp16))[name = tensor("op_3421_cast_fp16")]; + tensor var_3423_equation_0 = const()[name = tensor("op_3423_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3423_cast_fp16 = einsum(equation = var_3423_equation_0, values = (var_3203_cast_fp16, var_3364_cast_fp16))[name = tensor("op_3423_cast_fp16")]; + tensor var_3425_equation_0 = const()[name = tensor("op_3425_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3425_cast_fp16 = einsum(equation = var_3425_equation_0, values = (var_3203_cast_fp16, var_3365_cast_fp16))[name = tensor("op_3425_cast_fp16")]; + tensor var_3427_equation_0 = const()[name = tensor("op_3427_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3427_cast_fp16 = einsum(equation = var_3427_equation_0, values = (var_3207_cast_fp16, var_3366_cast_fp16))[name = tensor("op_3427_cast_fp16")]; + tensor var_3429_equation_0 = const()[name = tensor("op_3429_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3429_cast_fp16 = einsum(equation = var_3429_equation_0, values = (var_3207_cast_fp16, var_3367_cast_fp16))[name = tensor("op_3429_cast_fp16")]; + tensor var_3431_equation_0 = const()[name = tensor("op_3431_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3431_cast_fp16 = einsum(equation = var_3431_equation_0, values = (var_3207_cast_fp16, var_3368_cast_fp16))[name = tensor("op_3431_cast_fp16")]; + tensor var_3433_equation_0 = const()[name = tensor("op_3433_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3433_cast_fp16 = einsum(equation = var_3433_equation_0, values = (var_3207_cast_fp16, var_3369_cast_fp16))[name = tensor("op_3433_cast_fp16")]; + tensor var_3435_interleave_0 = const()[name = tensor("op_3435_interleave_0"), val = tensor(false)]; + tensor var_3435_cast_fp16 = concat(axis = var_2822, interleave = var_3435_interleave_0, values = (var_3371_cast_fp16, var_3373_cast_fp16, var_3375_cast_fp16, var_3377_cast_fp16))[name = tensor("op_3435_cast_fp16")]; + tensor var_3437_interleave_0 = const()[name = tensor("op_3437_interleave_0"), val = tensor(false)]; + tensor var_3437_cast_fp16 = concat(axis = var_2822, interleave = var_3437_interleave_0, values = (var_3379_cast_fp16, var_3381_cast_fp16, var_3383_cast_fp16, var_3385_cast_fp16))[name = tensor("op_3437_cast_fp16")]; + tensor var_3439_interleave_0 = const()[name = tensor("op_3439_interleave_0"), val = tensor(false)]; + tensor var_3439_cast_fp16 = concat(axis = var_2822, interleave = var_3439_interleave_0, values = (var_3387_cast_fp16, var_3389_cast_fp16, var_3391_cast_fp16, var_3393_cast_fp16))[name = tensor("op_3439_cast_fp16")]; + tensor var_3441_interleave_0 = const()[name = tensor("op_3441_interleave_0"), val = tensor(false)]; + tensor var_3441_cast_fp16 = concat(axis = var_2822, interleave = var_3441_interleave_0, values = (var_3395_cast_fp16, var_3397_cast_fp16, var_3399_cast_fp16, var_3401_cast_fp16))[name = tensor("op_3441_cast_fp16")]; + tensor var_3443_interleave_0 = const()[name = tensor("op_3443_interleave_0"), val = tensor(false)]; + tensor var_3443_cast_fp16 = concat(axis = var_2822, interleave = var_3443_interleave_0, values = (var_3403_cast_fp16, var_3405_cast_fp16, var_3407_cast_fp16, var_3409_cast_fp16))[name = tensor("op_3443_cast_fp16")]; + tensor var_3445_interleave_0 = const()[name = tensor("op_3445_interleave_0"), val = tensor(false)]; + tensor var_3445_cast_fp16 = concat(axis = var_2822, interleave = var_3445_interleave_0, values = (var_3411_cast_fp16, var_3413_cast_fp16, var_3415_cast_fp16, var_3417_cast_fp16))[name = tensor("op_3445_cast_fp16")]; + tensor var_3447_interleave_0 = const()[name = tensor("op_3447_interleave_0"), val = tensor(false)]; + tensor var_3447_cast_fp16 = concat(axis = var_2822, interleave = var_3447_interleave_0, values = (var_3419_cast_fp16, var_3421_cast_fp16, var_3423_cast_fp16, var_3425_cast_fp16))[name = tensor("op_3447_cast_fp16")]; + tensor var_3449_interleave_0 = const()[name = tensor("op_3449_interleave_0"), val = tensor(false)]; + tensor var_3449_cast_fp16 = concat(axis = var_2822, interleave = var_3449_interleave_0, values = (var_3427_cast_fp16, var_3429_cast_fp16, var_3431_cast_fp16, var_3433_cast_fp16))[name = tensor("op_3449_cast_fp16")]; + tensor input_33_interleave_0 = const()[name = tensor("input_33_interleave_0"), val = tensor(false)]; + tensor input_33_cast_fp16 = concat(axis = var_2835, interleave = input_33_interleave_0, values = (var_3435_cast_fp16, var_3437_cast_fp16, var_3439_cast_fp16, var_3441_cast_fp16, var_3443_cast_fp16, var_3445_cast_fp16, var_3447_cast_fp16, var_3449_cast_fp16))[name = tensor("input_33_cast_fp16")]; + tensor var_3454 = const()[name = tensor("op_3454"), val = tensor([1, 1])]; + tensor var_3456 = const()[name = tensor("op_3456"), val = tensor([1, 1])]; + tensor obj_19_pad_type_0 = const()[name = tensor("obj_19_pad_type_0"), val = tensor("custom")]; + tensor obj_19_pad_0 = const()[name = tensor("obj_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30155456)))]; + tensor layers_4_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30679808)))]; + tensor obj_19_cast_fp16 = conv(bias = layers_4_self_attn_o_proj_bias_to_fp16, dilations = var_3456, groups = var_2835, pad = obj_19_pad_0, pad_type = obj_19_pad_type_0, strides = var_3454, weight = layers_4_self_attn_o_proj_weight_to_fp16, x = input_33_cast_fp16)[name = tensor("obj_19_cast_fp16")]; + tensor inputs_19_cast_fp16 = add(x = inputs_17_cast_fp16, y = obj_19_cast_fp16)[name = tensor("inputs_19_cast_fp16")]; + tensor var_3462 = const()[name = tensor("op_3462"), val = tensor([1])]; + tensor channels_mean_19_cast_fp16 = reduce_mean(axes = var_3462, keep_dims = var_2836, x = inputs_19_cast_fp16)[name = tensor("channels_mean_19_cast_fp16")]; + tensor zero_mean_19_cast_fp16 = sub(x = inputs_19_cast_fp16, y = channels_mean_19_cast_fp16)[name = tensor("zero_mean_19_cast_fp16")]; + tensor zero_mean_sq_19_cast_fp16 = mul(x = zero_mean_19_cast_fp16, y = zero_mean_19_cast_fp16)[name = tensor("zero_mean_sq_19_cast_fp16")]; + tensor var_3466 = const()[name = tensor("op_3466"), val = tensor([1])]; + tensor var_3467_cast_fp16 = reduce_mean(axes = var_3466, keep_dims = var_2836, x = zero_mean_sq_19_cast_fp16)[name = tensor("op_3467_cast_fp16")]; + tensor var_3468_to_fp16 = const()[name = tensor("op_3468_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_3469_cast_fp16 = add(x = var_3467_cast_fp16, y = var_3468_to_fp16)[name = tensor("op_3469_cast_fp16")]; + tensor denom_19_epsilon_0_to_fp16 = const()[name = tensor("denom_19_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_19_cast_fp16 = rsqrt(epsilon = denom_19_epsilon_0_to_fp16, x = var_3469_cast_fp16)[name = tensor("denom_19_cast_fp16")]; + tensor out_19_cast_fp16 = mul(x = zero_mean_19_cast_fp16, y = denom_19_cast_fp16)[name = tensor("out_19_cast_fp16")]; + tensor input_35_gamma_0_to_fp16 = const()[name = tensor("input_35_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30680896)))]; + tensor input_35_beta_0_to_fp16 = const()[name = tensor("input_35_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30681984)))]; + tensor input_35_epsilon_0_to_fp16 = const()[name = tensor("input_35_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_35_cast_fp16 = batch_norm(beta = input_35_beta_0_to_fp16, epsilon = input_35_epsilon_0_to_fp16, gamma = input_35_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_19_cast_fp16)[name = tensor("input_35_cast_fp16")]; + tensor var_3480 = const()[name = tensor("op_3480"), val = tensor([1, 1])]; + tensor var_3482 = const()[name = tensor("op_3482"), val = tensor([1, 1])]; + tensor input_37_pad_type_0 = const()[name = tensor("input_37_pad_type_0"), val = tensor("custom")]; + tensor input_37_pad_0 = const()[name = tensor("input_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_fc1_weight_to_fp16 = const()[name = tensor("layers_4_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30683072)))]; + tensor layers_4_fc1_bias_to_fp16 = const()[name = tensor("layers_4_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32780288)))]; + tensor input_37_cast_fp16 = conv(bias = layers_4_fc1_bias_to_fp16, dilations = var_3482, groups = var_2835, pad = input_37_pad_0, pad_type = input_37_pad_type_0, strides = var_3480, weight = layers_4_fc1_weight_to_fp16, x = input_35_cast_fp16)[name = tensor("input_37_cast_fp16")]; + tensor input_39_mode_0 = const()[name = tensor("input_39_mode_0"), val = tensor("EXACT")]; + tensor input_39_cast_fp16 = gelu(mode = input_39_mode_0, x = input_37_cast_fp16)[name = tensor("input_39_cast_fp16")]; + tensor var_3488 = const()[name = tensor("op_3488"), val = tensor([1, 1])]; + tensor var_3490 = const()[name = tensor("op_3490"), val = tensor([1, 1])]; + tensor hidden_states_13_pad_type_0 = const()[name = tensor("hidden_states_13_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_13_pad_0 = const()[name = tensor("hidden_states_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_fc2_weight_to_fp16 = const()[name = tensor("layers_4_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32784448)))]; + tensor layers_4_fc2_bias_to_fp16 = const()[name = tensor("layers_4_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(34881664)))]; + tensor hidden_states_13_cast_fp16 = conv(bias = layers_4_fc2_bias_to_fp16, dilations = var_3490, groups = var_2835, pad = hidden_states_13_pad_0, pad_type = hidden_states_13_pad_type_0, strides = var_3488, weight = layers_4_fc2_weight_to_fp16, x = input_39_cast_fp16)[name = tensor("hidden_states_13_cast_fp16")]; + tensor inputs_21_cast_fp16 = add(x = inputs_19_cast_fp16, y = hidden_states_13_cast_fp16)[name = tensor("inputs_21_cast_fp16")]; + tensor var_3497 = const()[name = tensor("op_3497"), val = tensor(3)]; + tensor var_3510 = const()[name = tensor("op_3510"), val = tensor(1)]; + tensor var_3511 = const()[name = tensor("op_3511"), val = tensor(true)]; + tensor var_3521 = const()[name = tensor("op_3521"), val = tensor([1])]; + tensor channels_mean_21_cast_fp16 = reduce_mean(axes = var_3521, keep_dims = var_3511, x = inputs_21_cast_fp16)[name = tensor("channels_mean_21_cast_fp16")]; + tensor zero_mean_21_cast_fp16 = sub(x = inputs_21_cast_fp16, y = channels_mean_21_cast_fp16)[name = tensor("zero_mean_21_cast_fp16")]; + tensor zero_mean_sq_21_cast_fp16 = mul(x = zero_mean_21_cast_fp16, y = zero_mean_21_cast_fp16)[name = tensor("zero_mean_sq_21_cast_fp16")]; + tensor var_3525 = const()[name = tensor("op_3525"), val = tensor([1])]; + tensor var_3526_cast_fp16 = reduce_mean(axes = var_3525, keep_dims = var_3511, x = zero_mean_sq_21_cast_fp16)[name = tensor("op_3526_cast_fp16")]; + tensor var_3527_to_fp16 = const()[name = tensor("op_3527_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_3528_cast_fp16 = add(x = var_3526_cast_fp16, y = var_3527_to_fp16)[name = tensor("op_3528_cast_fp16")]; + tensor denom_21_epsilon_0_to_fp16 = const()[name = tensor("denom_21_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_21_cast_fp16 = rsqrt(epsilon = denom_21_epsilon_0_to_fp16, x = var_3528_cast_fp16)[name = tensor("denom_21_cast_fp16")]; + tensor out_21_cast_fp16 = mul(x = zero_mean_21_cast_fp16, y = denom_21_cast_fp16)[name = tensor("out_21_cast_fp16")]; + tensor obj_21_gamma_0_to_fp16 = const()[name = tensor("obj_21_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(34882752)))]; + tensor obj_21_beta_0_to_fp16 = const()[name = tensor("obj_21_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(34883840)))]; + tensor obj_21_epsilon_0_to_fp16 = const()[name = tensor("obj_21_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_21_cast_fp16 = batch_norm(beta = obj_21_beta_0_to_fp16, epsilon = obj_21_epsilon_0_to_fp16, gamma = obj_21_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_21_cast_fp16)[name = tensor("obj_21_cast_fp16")]; + tensor var_3543 = const()[name = tensor("op_3543"), val = tensor([1, 1])]; + tensor var_3545 = const()[name = tensor("op_3545"), val = tensor([1, 1])]; + tensor query_pad_type_0 = const()[name = tensor("query_pad_type_0"), val = tensor("custom")]; + tensor query_pad_0 = const()[name = tensor("query_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(34884928)))]; + tensor layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35409280)))]; + tensor query_cast_fp16 = conv(bias = layers_5_self_attn_q_proj_bias_to_fp16, dilations = var_3545, groups = var_3510, pad = query_pad_0, pad_type = query_pad_type_0, strides = var_3543, weight = layers_5_self_attn_q_proj_weight_to_fp16, x = obj_21_cast_fp16)[name = tensor("query_cast_fp16")]; + tensor var_3549 = const()[name = tensor("op_3549"), val = tensor([1, 1])]; + tensor var_3551 = const()[name = tensor("op_3551"), val = tensor([1, 1])]; + tensor key_pad_type_0 = const()[name = tensor("key_pad_type_0"), val = tensor("custom")]; + tensor key_pad_0 = const()[name = tensor("key_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35410368)))]; + tensor key_cast_fp16 = conv(dilations = var_3551, groups = var_3510, pad = key_pad_0, pad_type = key_pad_type_0, strides = var_3549, weight = layers_5_self_attn_k_proj_weight_to_fp16, x = obj_21_cast_fp16)[name = tensor("key_cast_fp16")]; + tensor var_3556 = const()[name = tensor("op_3556"), val = tensor([1, 1])]; + tensor var_3558 = const()[name = tensor("op_3558"), val = tensor([1, 1])]; + tensor value_pad_type_0 = const()[name = tensor("value_pad_type_0"), val = tensor("custom")]; + tensor value_pad_0 = const()[name = tensor("value_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35934720)))]; + tensor layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36459072)))]; + tensor value_cast_fp16 = conv(bias = layers_5_self_attn_v_proj_bias_to_fp16, dilations = var_3558, groups = var_3510, pad = value_pad_0, pad_type = value_pad_type_0, strides = var_3556, weight = layers_5_self_attn_v_proj_weight_to_fp16, x = obj_21_cast_fp16)[name = tensor("value_cast_fp16")]; + tensor var_3565_begin_0 = const()[name = tensor("op_3565_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3565_end_0 = const()[name = tensor("op_3565_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3565_end_mask_0 = const()[name = tensor("op_3565_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3565_cast_fp16 = slice_by_index(begin = var_3565_begin_0, end = var_3565_end_0, end_mask = var_3565_end_mask_0, x = query_cast_fp16)[name = tensor("op_3565_cast_fp16")]; + tensor var_3569_begin_0 = const()[name = tensor("op_3569_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_3569_end_0 = const()[name = tensor("op_3569_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_3569_end_mask_0 = const()[name = tensor("op_3569_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3569_cast_fp16 = slice_by_index(begin = var_3569_begin_0, end = var_3569_end_0, end_mask = var_3569_end_mask_0, x = query_cast_fp16)[name = tensor("op_3569_cast_fp16")]; + tensor var_3573_begin_0 = const()[name = tensor("op_3573_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_3573_end_0 = const()[name = tensor("op_3573_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_3573_end_mask_0 = const()[name = tensor("op_3573_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3573_cast_fp16 = slice_by_index(begin = var_3573_begin_0, end = var_3573_end_0, end_mask = var_3573_end_mask_0, x = query_cast_fp16)[name = tensor("op_3573_cast_fp16")]; + tensor var_3577_begin_0 = const()[name = tensor("op_3577_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_3577_end_0 = const()[name = tensor("op_3577_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_3577_end_mask_0 = const()[name = tensor("op_3577_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3577_cast_fp16 = slice_by_index(begin = var_3577_begin_0, end = var_3577_end_0, end_mask = var_3577_end_mask_0, x = query_cast_fp16)[name = tensor("op_3577_cast_fp16")]; + tensor var_3581_begin_0 = const()[name = tensor("op_3581_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_3581_end_0 = const()[name = tensor("op_3581_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_3581_end_mask_0 = const()[name = tensor("op_3581_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3581_cast_fp16 = slice_by_index(begin = var_3581_begin_0, end = var_3581_end_0, end_mask = var_3581_end_mask_0, x = query_cast_fp16)[name = tensor("op_3581_cast_fp16")]; + tensor var_3585_begin_0 = const()[name = tensor("op_3585_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_3585_end_0 = const()[name = tensor("op_3585_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_3585_end_mask_0 = const()[name = tensor("op_3585_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3585_cast_fp16 = slice_by_index(begin = var_3585_begin_0, end = var_3585_end_0, end_mask = var_3585_end_mask_0, x = query_cast_fp16)[name = tensor("op_3585_cast_fp16")]; + tensor var_3589_begin_0 = const()[name = tensor("op_3589_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_3589_end_0 = const()[name = tensor("op_3589_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_3589_end_mask_0 = const()[name = tensor("op_3589_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3589_cast_fp16 = slice_by_index(begin = var_3589_begin_0, end = var_3589_end_0, end_mask = var_3589_end_mask_0, x = query_cast_fp16)[name = tensor("op_3589_cast_fp16")]; + tensor var_3593_begin_0 = const()[name = tensor("op_3593_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_3593_end_0 = const()[name = tensor("op_3593_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_3593_end_mask_0 = const()[name = tensor("op_3593_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3593_cast_fp16 = slice_by_index(begin = var_3593_begin_0, end = var_3593_end_0, end_mask = var_3593_end_mask_0, x = query_cast_fp16)[name = tensor("op_3593_cast_fp16")]; + tensor var_3602_begin_0 = const()[name = tensor("op_3602_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3602_end_0 = const()[name = tensor("op_3602_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3602_end_mask_0 = const()[name = tensor("op_3602_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3602_cast_fp16 = slice_by_index(begin = var_3602_begin_0, end = var_3602_end_0, end_mask = var_3602_end_mask_0, x = var_3565_cast_fp16)[name = tensor("op_3602_cast_fp16")]; + tensor var_3609_begin_0 = const()[name = tensor("op_3609_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3609_end_0 = const()[name = tensor("op_3609_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3609_end_mask_0 = const()[name = tensor("op_3609_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3609_cast_fp16 = slice_by_index(begin = var_3609_begin_0, end = var_3609_end_0, end_mask = var_3609_end_mask_0, x = var_3565_cast_fp16)[name = tensor("op_3609_cast_fp16")]; + tensor var_3616_begin_0 = const()[name = tensor("op_3616_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3616_end_0 = const()[name = tensor("op_3616_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3616_end_mask_0 = const()[name = tensor("op_3616_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3616_cast_fp16 = slice_by_index(begin = var_3616_begin_0, end = var_3616_end_0, end_mask = var_3616_end_mask_0, x = var_3565_cast_fp16)[name = tensor("op_3616_cast_fp16")]; + tensor var_3623_begin_0 = const()[name = tensor("op_3623_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3623_end_0 = const()[name = tensor("op_3623_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3623_end_mask_0 = const()[name = tensor("op_3623_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3623_cast_fp16 = slice_by_index(begin = var_3623_begin_0, end = var_3623_end_0, end_mask = var_3623_end_mask_0, x = var_3565_cast_fp16)[name = tensor("op_3623_cast_fp16")]; + tensor var_3630_begin_0 = const()[name = tensor("op_3630_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3630_end_0 = const()[name = tensor("op_3630_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3630_end_mask_0 = const()[name = tensor("op_3630_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3630_cast_fp16 = slice_by_index(begin = var_3630_begin_0, end = var_3630_end_0, end_mask = var_3630_end_mask_0, x = var_3569_cast_fp16)[name = tensor("op_3630_cast_fp16")]; + tensor var_3637_begin_0 = const()[name = tensor("op_3637_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3637_end_0 = const()[name = tensor("op_3637_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3637_end_mask_0 = const()[name = tensor("op_3637_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3637_cast_fp16 = slice_by_index(begin = var_3637_begin_0, end = var_3637_end_0, end_mask = var_3637_end_mask_0, x = var_3569_cast_fp16)[name = tensor("op_3637_cast_fp16")]; + tensor var_3644_begin_0 = const()[name = tensor("op_3644_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3644_end_0 = const()[name = tensor("op_3644_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3644_end_mask_0 = const()[name = tensor("op_3644_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3644_cast_fp16 = slice_by_index(begin = var_3644_begin_0, end = var_3644_end_0, end_mask = var_3644_end_mask_0, x = var_3569_cast_fp16)[name = tensor("op_3644_cast_fp16")]; + tensor var_3651_begin_0 = const()[name = tensor("op_3651_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3651_end_0 = const()[name = tensor("op_3651_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3651_end_mask_0 = const()[name = tensor("op_3651_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3651_cast_fp16 = slice_by_index(begin = var_3651_begin_0, end = var_3651_end_0, end_mask = var_3651_end_mask_0, x = var_3569_cast_fp16)[name = tensor("op_3651_cast_fp16")]; + tensor var_3658_begin_0 = const()[name = tensor("op_3658_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3658_end_0 = const()[name = tensor("op_3658_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3658_end_mask_0 = const()[name = tensor("op_3658_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3658_cast_fp16 = slice_by_index(begin = var_3658_begin_0, end = var_3658_end_0, end_mask = var_3658_end_mask_0, x = var_3573_cast_fp16)[name = tensor("op_3658_cast_fp16")]; + tensor var_3665_begin_0 = const()[name = tensor("op_3665_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3665_end_0 = const()[name = tensor("op_3665_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3665_end_mask_0 = const()[name = tensor("op_3665_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3665_cast_fp16 = slice_by_index(begin = var_3665_begin_0, end = var_3665_end_0, end_mask = var_3665_end_mask_0, x = var_3573_cast_fp16)[name = tensor("op_3665_cast_fp16")]; + tensor var_3672_begin_0 = const()[name = tensor("op_3672_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3672_end_0 = const()[name = tensor("op_3672_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3672_end_mask_0 = const()[name = tensor("op_3672_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3672_cast_fp16 = slice_by_index(begin = var_3672_begin_0, end = var_3672_end_0, end_mask = var_3672_end_mask_0, x = var_3573_cast_fp16)[name = tensor("op_3672_cast_fp16")]; + tensor var_3679_begin_0 = const()[name = tensor("op_3679_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3679_end_0 = const()[name = tensor("op_3679_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3679_end_mask_0 = const()[name = tensor("op_3679_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3679_cast_fp16 = slice_by_index(begin = var_3679_begin_0, end = var_3679_end_0, end_mask = var_3679_end_mask_0, x = var_3573_cast_fp16)[name = tensor("op_3679_cast_fp16")]; + tensor var_3686_begin_0 = const()[name = tensor("op_3686_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3686_end_0 = const()[name = tensor("op_3686_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3686_end_mask_0 = const()[name = tensor("op_3686_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3686_cast_fp16 = slice_by_index(begin = var_3686_begin_0, end = var_3686_end_0, end_mask = var_3686_end_mask_0, x = var_3577_cast_fp16)[name = tensor("op_3686_cast_fp16")]; + tensor var_3693_begin_0 = const()[name = tensor("op_3693_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3693_end_0 = const()[name = tensor("op_3693_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3693_end_mask_0 = const()[name = tensor("op_3693_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3693_cast_fp16 = slice_by_index(begin = var_3693_begin_0, end = var_3693_end_0, end_mask = var_3693_end_mask_0, x = var_3577_cast_fp16)[name = tensor("op_3693_cast_fp16")]; + tensor var_3700_begin_0 = const()[name = tensor("op_3700_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3700_end_0 = const()[name = tensor("op_3700_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3700_end_mask_0 = const()[name = tensor("op_3700_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3700_cast_fp16 = slice_by_index(begin = var_3700_begin_0, end = var_3700_end_0, end_mask = var_3700_end_mask_0, x = var_3577_cast_fp16)[name = tensor("op_3700_cast_fp16")]; + tensor var_3707_begin_0 = const()[name = tensor("op_3707_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3707_end_0 = const()[name = tensor("op_3707_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3707_end_mask_0 = const()[name = tensor("op_3707_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3707_cast_fp16 = slice_by_index(begin = var_3707_begin_0, end = var_3707_end_0, end_mask = var_3707_end_mask_0, x = var_3577_cast_fp16)[name = tensor("op_3707_cast_fp16")]; + tensor var_3714_begin_0 = const()[name = tensor("op_3714_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3714_end_0 = const()[name = tensor("op_3714_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3714_end_mask_0 = const()[name = tensor("op_3714_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3714_cast_fp16 = slice_by_index(begin = var_3714_begin_0, end = var_3714_end_0, end_mask = var_3714_end_mask_0, x = var_3581_cast_fp16)[name = tensor("op_3714_cast_fp16")]; + tensor var_3721_begin_0 = const()[name = tensor("op_3721_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3721_end_0 = const()[name = tensor("op_3721_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3721_end_mask_0 = const()[name = tensor("op_3721_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3721_cast_fp16 = slice_by_index(begin = var_3721_begin_0, end = var_3721_end_0, end_mask = var_3721_end_mask_0, x = var_3581_cast_fp16)[name = tensor("op_3721_cast_fp16")]; + tensor var_3728_begin_0 = const()[name = tensor("op_3728_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3728_end_0 = const()[name = tensor("op_3728_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3728_end_mask_0 = const()[name = tensor("op_3728_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3728_cast_fp16 = slice_by_index(begin = var_3728_begin_0, end = var_3728_end_0, end_mask = var_3728_end_mask_0, x = var_3581_cast_fp16)[name = tensor("op_3728_cast_fp16")]; + tensor var_3735_begin_0 = const()[name = tensor("op_3735_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3735_end_0 = const()[name = tensor("op_3735_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3735_end_mask_0 = const()[name = tensor("op_3735_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3735_cast_fp16 = slice_by_index(begin = var_3735_begin_0, end = var_3735_end_0, end_mask = var_3735_end_mask_0, x = var_3581_cast_fp16)[name = tensor("op_3735_cast_fp16")]; + tensor var_3742_begin_0 = const()[name = tensor("op_3742_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3742_end_0 = const()[name = tensor("op_3742_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3742_end_mask_0 = const()[name = tensor("op_3742_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3742_cast_fp16 = slice_by_index(begin = var_3742_begin_0, end = var_3742_end_0, end_mask = var_3742_end_mask_0, x = var_3585_cast_fp16)[name = tensor("op_3742_cast_fp16")]; + tensor var_3749_begin_0 = const()[name = tensor("op_3749_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3749_end_0 = const()[name = tensor("op_3749_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3749_end_mask_0 = const()[name = tensor("op_3749_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3749_cast_fp16 = slice_by_index(begin = var_3749_begin_0, end = var_3749_end_0, end_mask = var_3749_end_mask_0, x = var_3585_cast_fp16)[name = tensor("op_3749_cast_fp16")]; + tensor var_3756_begin_0 = const()[name = tensor("op_3756_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3756_end_0 = const()[name = tensor("op_3756_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3756_end_mask_0 = const()[name = tensor("op_3756_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3756_cast_fp16 = slice_by_index(begin = var_3756_begin_0, end = var_3756_end_0, end_mask = var_3756_end_mask_0, x = var_3585_cast_fp16)[name = tensor("op_3756_cast_fp16")]; + tensor var_3763_begin_0 = const()[name = tensor("op_3763_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3763_end_0 = const()[name = tensor("op_3763_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3763_end_mask_0 = const()[name = tensor("op_3763_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3763_cast_fp16 = slice_by_index(begin = var_3763_begin_0, end = var_3763_end_0, end_mask = var_3763_end_mask_0, x = var_3585_cast_fp16)[name = tensor("op_3763_cast_fp16")]; + tensor var_3770_begin_0 = const()[name = tensor("op_3770_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3770_end_0 = const()[name = tensor("op_3770_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3770_end_mask_0 = const()[name = tensor("op_3770_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3770_cast_fp16 = slice_by_index(begin = var_3770_begin_0, end = var_3770_end_0, end_mask = var_3770_end_mask_0, x = var_3589_cast_fp16)[name = tensor("op_3770_cast_fp16")]; + tensor var_3777_begin_0 = const()[name = tensor("op_3777_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3777_end_0 = const()[name = tensor("op_3777_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3777_end_mask_0 = const()[name = tensor("op_3777_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3777_cast_fp16 = slice_by_index(begin = var_3777_begin_0, end = var_3777_end_0, end_mask = var_3777_end_mask_0, x = var_3589_cast_fp16)[name = tensor("op_3777_cast_fp16")]; + tensor var_3784_begin_0 = const()[name = tensor("op_3784_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3784_end_0 = const()[name = tensor("op_3784_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3784_end_mask_0 = const()[name = tensor("op_3784_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3784_cast_fp16 = slice_by_index(begin = var_3784_begin_0, end = var_3784_end_0, end_mask = var_3784_end_mask_0, x = var_3589_cast_fp16)[name = tensor("op_3784_cast_fp16")]; + tensor var_3791_begin_0 = const()[name = tensor("op_3791_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3791_end_0 = const()[name = tensor("op_3791_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3791_end_mask_0 = const()[name = tensor("op_3791_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3791_cast_fp16 = slice_by_index(begin = var_3791_begin_0, end = var_3791_end_0, end_mask = var_3791_end_mask_0, x = var_3589_cast_fp16)[name = tensor("op_3791_cast_fp16")]; + tensor var_3798_begin_0 = const()[name = tensor("op_3798_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3798_end_0 = const()[name = tensor("op_3798_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3798_end_mask_0 = const()[name = tensor("op_3798_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3798_cast_fp16 = slice_by_index(begin = var_3798_begin_0, end = var_3798_end_0, end_mask = var_3798_end_mask_0, x = var_3593_cast_fp16)[name = tensor("op_3798_cast_fp16")]; + tensor var_3805_begin_0 = const()[name = tensor("op_3805_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3805_end_0 = const()[name = tensor("op_3805_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3805_end_mask_0 = const()[name = tensor("op_3805_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3805_cast_fp16 = slice_by_index(begin = var_3805_begin_0, end = var_3805_end_0, end_mask = var_3805_end_mask_0, x = var_3593_cast_fp16)[name = tensor("op_3805_cast_fp16")]; + tensor var_3812_begin_0 = const()[name = tensor("op_3812_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3812_end_0 = const()[name = tensor("op_3812_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3812_end_mask_0 = const()[name = tensor("op_3812_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3812_cast_fp16 = slice_by_index(begin = var_3812_begin_0, end = var_3812_end_0, end_mask = var_3812_end_mask_0, x = var_3593_cast_fp16)[name = tensor("op_3812_cast_fp16")]; + tensor var_3819_begin_0 = const()[name = tensor("op_3819_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3819_end_0 = const()[name = tensor("op_3819_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3819_end_mask_0 = const()[name = tensor("op_3819_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3819_cast_fp16 = slice_by_index(begin = var_3819_begin_0, end = var_3819_end_0, end_mask = var_3819_end_mask_0, x = var_3593_cast_fp16)[name = tensor("op_3819_cast_fp16")]; + tensor k_perm_0 = const()[name = tensor("k_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_3824_begin_0 = const()[name = tensor("op_3824_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3824_end_0 = const()[name = tensor("op_3824_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_3824_end_mask_0 = const()[name = tensor("op_3824_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_0 = transpose(perm = k_perm_0, x = key_cast_fp16)[name = tensor("transpose_0")]; + tensor var_3824_cast_fp16 = slice_by_index(begin = var_3824_begin_0, end = var_3824_end_0, end_mask = var_3824_end_mask_0, x = transpose_0)[name = tensor("op_3824_cast_fp16")]; + tensor var_3828_begin_0 = const()[name = tensor("op_3828_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_3828_end_0 = const()[name = tensor("op_3828_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_3828_end_mask_0 = const()[name = tensor("op_3828_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3828_cast_fp16 = slice_by_index(begin = var_3828_begin_0, end = var_3828_end_0, end_mask = var_3828_end_mask_0, x = transpose_0)[name = tensor("op_3828_cast_fp16")]; + tensor var_3832_begin_0 = const()[name = tensor("op_3832_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_3832_end_0 = const()[name = tensor("op_3832_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_3832_end_mask_0 = const()[name = tensor("op_3832_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3832_cast_fp16 = slice_by_index(begin = var_3832_begin_0, end = var_3832_end_0, end_mask = var_3832_end_mask_0, x = transpose_0)[name = tensor("op_3832_cast_fp16")]; + tensor var_3836_begin_0 = const()[name = tensor("op_3836_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_3836_end_0 = const()[name = tensor("op_3836_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_3836_end_mask_0 = const()[name = tensor("op_3836_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3836_cast_fp16 = slice_by_index(begin = var_3836_begin_0, end = var_3836_end_0, end_mask = var_3836_end_mask_0, x = transpose_0)[name = tensor("op_3836_cast_fp16")]; + tensor var_3840_begin_0 = const()[name = tensor("op_3840_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_3840_end_0 = const()[name = tensor("op_3840_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_3840_end_mask_0 = const()[name = tensor("op_3840_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3840_cast_fp16 = slice_by_index(begin = var_3840_begin_0, end = var_3840_end_0, end_mask = var_3840_end_mask_0, x = transpose_0)[name = tensor("op_3840_cast_fp16")]; + tensor var_3844_begin_0 = const()[name = tensor("op_3844_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_3844_end_0 = const()[name = tensor("op_3844_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_3844_end_mask_0 = const()[name = tensor("op_3844_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3844_cast_fp16 = slice_by_index(begin = var_3844_begin_0, end = var_3844_end_0, end_mask = var_3844_end_mask_0, x = transpose_0)[name = tensor("op_3844_cast_fp16")]; + tensor var_3848_begin_0 = const()[name = tensor("op_3848_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_3848_end_0 = const()[name = tensor("op_3848_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_3848_end_mask_0 = const()[name = tensor("op_3848_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3848_cast_fp16 = slice_by_index(begin = var_3848_begin_0, end = var_3848_end_0, end_mask = var_3848_end_mask_0, x = transpose_0)[name = tensor("op_3848_cast_fp16")]; + tensor var_3852_begin_0 = const()[name = tensor("op_3852_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_3852_end_0 = const()[name = tensor("op_3852_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_3852_end_mask_0 = const()[name = tensor("op_3852_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3852_cast_fp16 = slice_by_index(begin = var_3852_begin_0, end = var_3852_end_0, end_mask = var_3852_end_mask_0, x = transpose_0)[name = tensor("op_3852_cast_fp16")]; + tensor var_3854_begin_0 = const()[name = tensor("op_3854_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3854_end_0 = const()[name = tensor("op_3854_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3854_end_mask_0 = const()[name = tensor("op_3854_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3854_cast_fp16 = slice_by_index(begin = var_3854_begin_0, end = var_3854_end_0, end_mask = var_3854_end_mask_0, x = value_cast_fp16)[name = tensor("op_3854_cast_fp16")]; + tensor var_3858_begin_0 = const()[name = tensor("op_3858_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_3858_end_0 = const()[name = tensor("op_3858_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_3858_end_mask_0 = const()[name = tensor("op_3858_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3858_cast_fp16 = slice_by_index(begin = var_3858_begin_0, end = var_3858_end_0, end_mask = var_3858_end_mask_0, x = value_cast_fp16)[name = tensor("op_3858_cast_fp16")]; + tensor var_3862_begin_0 = const()[name = tensor("op_3862_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_3862_end_0 = const()[name = tensor("op_3862_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_3862_end_mask_0 = const()[name = tensor("op_3862_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3862_cast_fp16 = slice_by_index(begin = var_3862_begin_0, end = var_3862_end_0, end_mask = var_3862_end_mask_0, x = value_cast_fp16)[name = tensor("op_3862_cast_fp16")]; + tensor var_3866_begin_0 = const()[name = tensor("op_3866_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_3866_end_0 = const()[name = tensor("op_3866_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_3866_end_mask_0 = const()[name = tensor("op_3866_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3866_cast_fp16 = slice_by_index(begin = var_3866_begin_0, end = var_3866_end_0, end_mask = var_3866_end_mask_0, x = value_cast_fp16)[name = tensor("op_3866_cast_fp16")]; + tensor var_3870_begin_0 = const()[name = tensor("op_3870_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_3870_end_0 = const()[name = tensor("op_3870_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_3870_end_mask_0 = const()[name = tensor("op_3870_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3870_cast_fp16 = slice_by_index(begin = var_3870_begin_0, end = var_3870_end_0, end_mask = var_3870_end_mask_0, x = value_cast_fp16)[name = tensor("op_3870_cast_fp16")]; + tensor var_3874_begin_0 = const()[name = tensor("op_3874_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_3874_end_0 = const()[name = tensor("op_3874_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_3874_end_mask_0 = const()[name = tensor("op_3874_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3874_cast_fp16 = slice_by_index(begin = var_3874_begin_0, end = var_3874_end_0, end_mask = var_3874_end_mask_0, x = value_cast_fp16)[name = tensor("op_3874_cast_fp16")]; + tensor var_3878_begin_0 = const()[name = tensor("op_3878_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_3878_end_0 = const()[name = tensor("op_3878_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_3878_end_mask_0 = const()[name = tensor("op_3878_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3878_cast_fp16 = slice_by_index(begin = var_3878_begin_0, end = var_3878_end_0, end_mask = var_3878_end_mask_0, x = value_cast_fp16)[name = tensor("op_3878_cast_fp16")]; + tensor var_3882_begin_0 = const()[name = tensor("op_3882_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_3882_end_0 = const()[name = tensor("op_3882_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_3882_end_mask_0 = const()[name = tensor("op_3882_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3882_cast_fp16 = slice_by_index(begin = var_3882_begin_0, end = var_3882_end_0, end_mask = var_3882_end_mask_0, x = value_cast_fp16)[name = tensor("op_3882_cast_fp16")]; + tensor var_3886_equation_0 = const()[name = tensor("op_3886_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3886_cast_fp16 = einsum(equation = var_3886_equation_0, values = (var_3824_cast_fp16, var_3602_cast_fp16))[name = tensor("op_3886_cast_fp16")]; + tensor var_3887_to_fp16 = const()[name = tensor("op_3887_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_321_cast_fp16 = mul(x = var_3886_cast_fp16, y = var_3887_to_fp16)[name = tensor("aw_chunk_321_cast_fp16")]; + tensor var_3890_equation_0 = const()[name = tensor("op_3890_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3890_cast_fp16 = einsum(equation = var_3890_equation_0, values = (var_3824_cast_fp16, var_3609_cast_fp16))[name = tensor("op_3890_cast_fp16")]; + tensor var_3891_to_fp16 = const()[name = tensor("op_3891_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_323_cast_fp16 = mul(x = var_3890_cast_fp16, y = var_3891_to_fp16)[name = tensor("aw_chunk_323_cast_fp16")]; + tensor var_3894_equation_0 = const()[name = tensor("op_3894_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3894_cast_fp16 = einsum(equation = var_3894_equation_0, values = (var_3824_cast_fp16, var_3616_cast_fp16))[name = tensor("op_3894_cast_fp16")]; + tensor var_3895_to_fp16 = const()[name = tensor("op_3895_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_325_cast_fp16 = mul(x = var_3894_cast_fp16, y = var_3895_to_fp16)[name = tensor("aw_chunk_325_cast_fp16")]; + tensor var_3898_equation_0 = const()[name = tensor("op_3898_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3898_cast_fp16 = einsum(equation = var_3898_equation_0, values = (var_3824_cast_fp16, var_3623_cast_fp16))[name = tensor("op_3898_cast_fp16")]; + tensor var_3899_to_fp16 = const()[name = tensor("op_3899_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_327_cast_fp16 = mul(x = var_3898_cast_fp16, y = var_3899_to_fp16)[name = tensor("aw_chunk_327_cast_fp16")]; + tensor var_3902_equation_0 = const()[name = tensor("op_3902_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3902_cast_fp16 = einsum(equation = var_3902_equation_0, values = (var_3828_cast_fp16, var_3630_cast_fp16))[name = tensor("op_3902_cast_fp16")]; + tensor var_3903_to_fp16 = const()[name = tensor("op_3903_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_329_cast_fp16 = mul(x = var_3902_cast_fp16, y = var_3903_to_fp16)[name = tensor("aw_chunk_329_cast_fp16")]; + tensor var_3906_equation_0 = const()[name = tensor("op_3906_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3906_cast_fp16 = einsum(equation = var_3906_equation_0, values = (var_3828_cast_fp16, var_3637_cast_fp16))[name = tensor("op_3906_cast_fp16")]; + tensor var_3907_to_fp16 = const()[name = tensor("op_3907_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_331_cast_fp16 = mul(x = var_3906_cast_fp16, y = var_3907_to_fp16)[name = tensor("aw_chunk_331_cast_fp16")]; + tensor var_3910_equation_0 = const()[name = tensor("op_3910_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3910_cast_fp16 = einsum(equation = var_3910_equation_0, values = (var_3828_cast_fp16, var_3644_cast_fp16))[name = tensor("op_3910_cast_fp16")]; + tensor var_3911_to_fp16 = const()[name = tensor("op_3911_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_333_cast_fp16 = mul(x = var_3910_cast_fp16, y = var_3911_to_fp16)[name = tensor("aw_chunk_333_cast_fp16")]; + tensor var_3914_equation_0 = const()[name = tensor("op_3914_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3914_cast_fp16 = einsum(equation = var_3914_equation_0, values = (var_3828_cast_fp16, var_3651_cast_fp16))[name = tensor("op_3914_cast_fp16")]; + tensor var_3915_to_fp16 = const()[name = tensor("op_3915_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_335_cast_fp16 = mul(x = var_3914_cast_fp16, y = var_3915_to_fp16)[name = tensor("aw_chunk_335_cast_fp16")]; + tensor var_3918_equation_0 = const()[name = tensor("op_3918_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3918_cast_fp16 = einsum(equation = var_3918_equation_0, values = (var_3832_cast_fp16, var_3658_cast_fp16))[name = tensor("op_3918_cast_fp16")]; + tensor var_3919_to_fp16 = const()[name = tensor("op_3919_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_337_cast_fp16 = mul(x = var_3918_cast_fp16, y = var_3919_to_fp16)[name = tensor("aw_chunk_337_cast_fp16")]; + tensor var_3922_equation_0 = const()[name = tensor("op_3922_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3922_cast_fp16 = einsum(equation = var_3922_equation_0, values = (var_3832_cast_fp16, var_3665_cast_fp16))[name = tensor("op_3922_cast_fp16")]; + tensor var_3923_to_fp16 = const()[name = tensor("op_3923_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_339_cast_fp16 = mul(x = var_3922_cast_fp16, y = var_3923_to_fp16)[name = tensor("aw_chunk_339_cast_fp16")]; + tensor var_3926_equation_0 = const()[name = tensor("op_3926_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3926_cast_fp16 = einsum(equation = var_3926_equation_0, values = (var_3832_cast_fp16, var_3672_cast_fp16))[name = tensor("op_3926_cast_fp16")]; + tensor var_3927_to_fp16 = const()[name = tensor("op_3927_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_341_cast_fp16 = mul(x = var_3926_cast_fp16, y = var_3927_to_fp16)[name = tensor("aw_chunk_341_cast_fp16")]; + tensor var_3930_equation_0 = const()[name = tensor("op_3930_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3930_cast_fp16 = einsum(equation = var_3930_equation_0, values = (var_3832_cast_fp16, var_3679_cast_fp16))[name = tensor("op_3930_cast_fp16")]; + tensor var_3931_to_fp16 = const()[name = tensor("op_3931_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_343_cast_fp16 = mul(x = var_3930_cast_fp16, y = var_3931_to_fp16)[name = tensor("aw_chunk_343_cast_fp16")]; + tensor var_3934_equation_0 = const()[name = tensor("op_3934_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3934_cast_fp16 = einsum(equation = var_3934_equation_0, values = (var_3836_cast_fp16, var_3686_cast_fp16))[name = tensor("op_3934_cast_fp16")]; + tensor var_3935_to_fp16 = const()[name = tensor("op_3935_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_345_cast_fp16 = mul(x = var_3934_cast_fp16, y = var_3935_to_fp16)[name = tensor("aw_chunk_345_cast_fp16")]; + tensor var_3938_equation_0 = const()[name = tensor("op_3938_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3938_cast_fp16 = einsum(equation = var_3938_equation_0, values = (var_3836_cast_fp16, var_3693_cast_fp16))[name = tensor("op_3938_cast_fp16")]; + tensor var_3939_to_fp16 = const()[name = tensor("op_3939_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_347_cast_fp16 = mul(x = var_3938_cast_fp16, y = var_3939_to_fp16)[name = tensor("aw_chunk_347_cast_fp16")]; + tensor var_3942_equation_0 = const()[name = tensor("op_3942_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3942_cast_fp16 = einsum(equation = var_3942_equation_0, values = (var_3836_cast_fp16, var_3700_cast_fp16))[name = tensor("op_3942_cast_fp16")]; + tensor var_3943_to_fp16 = const()[name = tensor("op_3943_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_349_cast_fp16 = mul(x = var_3942_cast_fp16, y = var_3943_to_fp16)[name = tensor("aw_chunk_349_cast_fp16")]; + tensor var_3946_equation_0 = const()[name = tensor("op_3946_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3946_cast_fp16 = einsum(equation = var_3946_equation_0, values = (var_3836_cast_fp16, var_3707_cast_fp16))[name = tensor("op_3946_cast_fp16")]; + tensor var_3947_to_fp16 = const()[name = tensor("op_3947_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_351_cast_fp16 = mul(x = var_3946_cast_fp16, y = var_3947_to_fp16)[name = tensor("aw_chunk_351_cast_fp16")]; + tensor var_3950_equation_0 = const()[name = tensor("op_3950_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3950_cast_fp16 = einsum(equation = var_3950_equation_0, values = (var_3840_cast_fp16, var_3714_cast_fp16))[name = tensor("op_3950_cast_fp16")]; + tensor var_3951_to_fp16 = const()[name = tensor("op_3951_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_353_cast_fp16 = mul(x = var_3950_cast_fp16, y = var_3951_to_fp16)[name = tensor("aw_chunk_353_cast_fp16")]; + tensor var_3954_equation_0 = const()[name = tensor("op_3954_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3954_cast_fp16 = einsum(equation = var_3954_equation_0, values = (var_3840_cast_fp16, var_3721_cast_fp16))[name = tensor("op_3954_cast_fp16")]; + tensor var_3955_to_fp16 = const()[name = tensor("op_3955_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_355_cast_fp16 = mul(x = var_3954_cast_fp16, y = var_3955_to_fp16)[name = tensor("aw_chunk_355_cast_fp16")]; + tensor var_3958_equation_0 = const()[name = tensor("op_3958_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3958_cast_fp16 = einsum(equation = var_3958_equation_0, values = (var_3840_cast_fp16, var_3728_cast_fp16))[name = tensor("op_3958_cast_fp16")]; + tensor var_3959_to_fp16 = const()[name = tensor("op_3959_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_357_cast_fp16 = mul(x = var_3958_cast_fp16, y = var_3959_to_fp16)[name = tensor("aw_chunk_357_cast_fp16")]; + tensor var_3962_equation_0 = const()[name = tensor("op_3962_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3962_cast_fp16 = einsum(equation = var_3962_equation_0, values = (var_3840_cast_fp16, var_3735_cast_fp16))[name = tensor("op_3962_cast_fp16")]; + tensor var_3963_to_fp16 = const()[name = tensor("op_3963_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_359_cast_fp16 = mul(x = var_3962_cast_fp16, y = var_3963_to_fp16)[name = tensor("aw_chunk_359_cast_fp16")]; + tensor var_3966_equation_0 = const()[name = tensor("op_3966_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3966_cast_fp16 = einsum(equation = var_3966_equation_0, values = (var_3844_cast_fp16, var_3742_cast_fp16))[name = tensor("op_3966_cast_fp16")]; + tensor var_3967_to_fp16 = const()[name = tensor("op_3967_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_361_cast_fp16 = mul(x = var_3966_cast_fp16, y = var_3967_to_fp16)[name = tensor("aw_chunk_361_cast_fp16")]; + tensor var_3970_equation_0 = const()[name = tensor("op_3970_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3970_cast_fp16 = einsum(equation = var_3970_equation_0, values = (var_3844_cast_fp16, var_3749_cast_fp16))[name = tensor("op_3970_cast_fp16")]; + tensor var_3971_to_fp16 = const()[name = tensor("op_3971_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_363_cast_fp16 = mul(x = var_3970_cast_fp16, y = var_3971_to_fp16)[name = tensor("aw_chunk_363_cast_fp16")]; + tensor var_3974_equation_0 = const()[name = tensor("op_3974_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3974_cast_fp16 = einsum(equation = var_3974_equation_0, values = (var_3844_cast_fp16, var_3756_cast_fp16))[name = tensor("op_3974_cast_fp16")]; + tensor var_3975_to_fp16 = const()[name = tensor("op_3975_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_365_cast_fp16 = mul(x = var_3974_cast_fp16, y = var_3975_to_fp16)[name = tensor("aw_chunk_365_cast_fp16")]; + tensor var_3978_equation_0 = const()[name = tensor("op_3978_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3978_cast_fp16 = einsum(equation = var_3978_equation_0, values = (var_3844_cast_fp16, var_3763_cast_fp16))[name = tensor("op_3978_cast_fp16")]; + tensor var_3979_to_fp16 = const()[name = tensor("op_3979_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_367_cast_fp16 = mul(x = var_3978_cast_fp16, y = var_3979_to_fp16)[name = tensor("aw_chunk_367_cast_fp16")]; + tensor var_3982_equation_0 = const()[name = tensor("op_3982_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3982_cast_fp16 = einsum(equation = var_3982_equation_0, values = (var_3848_cast_fp16, var_3770_cast_fp16))[name = tensor("op_3982_cast_fp16")]; + tensor var_3983_to_fp16 = const()[name = tensor("op_3983_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_369_cast_fp16 = mul(x = var_3982_cast_fp16, y = var_3983_to_fp16)[name = tensor("aw_chunk_369_cast_fp16")]; + tensor var_3986_equation_0 = const()[name = tensor("op_3986_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3986_cast_fp16 = einsum(equation = var_3986_equation_0, values = (var_3848_cast_fp16, var_3777_cast_fp16))[name = tensor("op_3986_cast_fp16")]; + tensor var_3987_to_fp16 = const()[name = tensor("op_3987_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_371_cast_fp16 = mul(x = var_3986_cast_fp16, y = var_3987_to_fp16)[name = tensor("aw_chunk_371_cast_fp16")]; + tensor var_3990_equation_0 = const()[name = tensor("op_3990_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3990_cast_fp16 = einsum(equation = var_3990_equation_0, values = (var_3848_cast_fp16, var_3784_cast_fp16))[name = tensor("op_3990_cast_fp16")]; + tensor var_3991_to_fp16 = const()[name = tensor("op_3991_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_373_cast_fp16 = mul(x = var_3990_cast_fp16, y = var_3991_to_fp16)[name = tensor("aw_chunk_373_cast_fp16")]; + tensor var_3994_equation_0 = const()[name = tensor("op_3994_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3994_cast_fp16 = einsum(equation = var_3994_equation_0, values = (var_3848_cast_fp16, var_3791_cast_fp16))[name = tensor("op_3994_cast_fp16")]; + tensor var_3995_to_fp16 = const()[name = tensor("op_3995_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_375_cast_fp16 = mul(x = var_3994_cast_fp16, y = var_3995_to_fp16)[name = tensor("aw_chunk_375_cast_fp16")]; + tensor var_3998_equation_0 = const()[name = tensor("op_3998_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3998_cast_fp16 = einsum(equation = var_3998_equation_0, values = (var_3852_cast_fp16, var_3798_cast_fp16))[name = tensor("op_3998_cast_fp16")]; + tensor var_3999_to_fp16 = const()[name = tensor("op_3999_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_377_cast_fp16 = mul(x = var_3998_cast_fp16, y = var_3999_to_fp16)[name = tensor("aw_chunk_377_cast_fp16")]; + tensor var_4002_equation_0 = const()[name = tensor("op_4002_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4002_cast_fp16 = einsum(equation = var_4002_equation_0, values = (var_3852_cast_fp16, var_3805_cast_fp16))[name = tensor("op_4002_cast_fp16")]; + tensor var_4003_to_fp16 = const()[name = tensor("op_4003_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_379_cast_fp16 = mul(x = var_4002_cast_fp16, y = var_4003_to_fp16)[name = tensor("aw_chunk_379_cast_fp16")]; + tensor var_4006_equation_0 = const()[name = tensor("op_4006_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4006_cast_fp16 = einsum(equation = var_4006_equation_0, values = (var_3852_cast_fp16, var_3812_cast_fp16))[name = tensor("op_4006_cast_fp16")]; + tensor var_4007_to_fp16 = const()[name = tensor("op_4007_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_381_cast_fp16 = mul(x = var_4006_cast_fp16, y = var_4007_to_fp16)[name = tensor("aw_chunk_381_cast_fp16")]; + tensor var_4010_equation_0 = const()[name = tensor("op_4010_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4010_cast_fp16 = einsum(equation = var_4010_equation_0, values = (var_3852_cast_fp16, var_3819_cast_fp16))[name = tensor("op_4010_cast_fp16")]; + tensor var_4011_to_fp16 = const()[name = tensor("op_4011_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_cast_fp16 = mul(x = var_4010_cast_fp16, y = var_4011_to_fp16)[name = tensor("aw_chunk_cast_fp16")]; + tensor var_4013_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_321_cast_fp16)[name = tensor("op_4013_cast_fp16")]; + tensor var_4014_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_323_cast_fp16)[name = tensor("op_4014_cast_fp16")]; + tensor var_4015_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_325_cast_fp16)[name = tensor("op_4015_cast_fp16")]; + tensor var_4016_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_327_cast_fp16)[name = tensor("op_4016_cast_fp16")]; + tensor var_4017_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_329_cast_fp16)[name = tensor("op_4017_cast_fp16")]; + tensor var_4018_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_331_cast_fp16)[name = tensor("op_4018_cast_fp16")]; + tensor var_4019_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_333_cast_fp16)[name = tensor("op_4019_cast_fp16")]; + tensor var_4020_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_335_cast_fp16)[name = tensor("op_4020_cast_fp16")]; + tensor var_4021_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_337_cast_fp16)[name = tensor("op_4021_cast_fp16")]; + tensor var_4022_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_339_cast_fp16)[name = tensor("op_4022_cast_fp16")]; + tensor var_4023_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_341_cast_fp16)[name = tensor("op_4023_cast_fp16")]; + tensor var_4024_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_343_cast_fp16)[name = tensor("op_4024_cast_fp16")]; + tensor var_4025_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_345_cast_fp16)[name = tensor("op_4025_cast_fp16")]; + tensor var_4026_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_347_cast_fp16)[name = tensor("op_4026_cast_fp16")]; + tensor var_4027_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_349_cast_fp16)[name = tensor("op_4027_cast_fp16")]; + tensor var_4028_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_351_cast_fp16)[name = tensor("op_4028_cast_fp16")]; + tensor var_4029_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_353_cast_fp16)[name = tensor("op_4029_cast_fp16")]; + tensor var_4030_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_355_cast_fp16)[name = tensor("op_4030_cast_fp16")]; + tensor var_4031_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_357_cast_fp16)[name = tensor("op_4031_cast_fp16")]; + tensor var_4032_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_359_cast_fp16)[name = tensor("op_4032_cast_fp16")]; + tensor var_4033_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_361_cast_fp16)[name = tensor("op_4033_cast_fp16")]; + tensor var_4034_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_363_cast_fp16)[name = tensor("op_4034_cast_fp16")]; + tensor var_4035_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_365_cast_fp16)[name = tensor("op_4035_cast_fp16")]; + tensor var_4036_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_367_cast_fp16)[name = tensor("op_4036_cast_fp16")]; + tensor var_4037_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_369_cast_fp16)[name = tensor("op_4037_cast_fp16")]; + tensor var_4038_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_371_cast_fp16)[name = tensor("op_4038_cast_fp16")]; + tensor var_4039_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_373_cast_fp16)[name = tensor("op_4039_cast_fp16")]; + tensor var_4040_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_375_cast_fp16)[name = tensor("op_4040_cast_fp16")]; + tensor var_4041_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_377_cast_fp16)[name = tensor("op_4041_cast_fp16")]; + tensor var_4042_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_379_cast_fp16)[name = tensor("op_4042_cast_fp16")]; + tensor var_4043_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_381_cast_fp16)[name = tensor("op_4043_cast_fp16")]; + tensor var_4044_cast_fp16 = softmax(axis = var_3510, x = aw_chunk_cast_fp16)[name = tensor("op_4044_cast_fp16")]; + tensor var_4046_equation_0 = const()[name = tensor("op_4046_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4046_cast_fp16 = einsum(equation = var_4046_equation_0, values = (var_3854_cast_fp16, var_4013_cast_fp16))[name = tensor("op_4046_cast_fp16")]; + tensor var_4048_equation_0 = const()[name = tensor("op_4048_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4048_cast_fp16 = einsum(equation = var_4048_equation_0, values = (var_3854_cast_fp16, var_4014_cast_fp16))[name = tensor("op_4048_cast_fp16")]; + tensor var_4050_equation_0 = const()[name = tensor("op_4050_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4050_cast_fp16 = einsum(equation = var_4050_equation_0, values = (var_3854_cast_fp16, var_4015_cast_fp16))[name = tensor("op_4050_cast_fp16")]; + tensor var_4052_equation_0 = const()[name = tensor("op_4052_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4052_cast_fp16 = einsum(equation = var_4052_equation_0, values = (var_3854_cast_fp16, var_4016_cast_fp16))[name = tensor("op_4052_cast_fp16")]; + tensor var_4054_equation_0 = const()[name = tensor("op_4054_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4054_cast_fp16 = einsum(equation = var_4054_equation_0, values = (var_3858_cast_fp16, var_4017_cast_fp16))[name = tensor("op_4054_cast_fp16")]; + tensor var_4056_equation_0 = const()[name = tensor("op_4056_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4056_cast_fp16 = einsum(equation = var_4056_equation_0, values = (var_3858_cast_fp16, var_4018_cast_fp16))[name = tensor("op_4056_cast_fp16")]; + tensor var_4058_equation_0 = const()[name = tensor("op_4058_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4058_cast_fp16 = einsum(equation = var_4058_equation_0, values = (var_3858_cast_fp16, var_4019_cast_fp16))[name = tensor("op_4058_cast_fp16")]; + tensor var_4060_equation_0 = const()[name = tensor("op_4060_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4060_cast_fp16 = einsum(equation = var_4060_equation_0, values = (var_3858_cast_fp16, var_4020_cast_fp16))[name = tensor("op_4060_cast_fp16")]; + tensor var_4062_equation_0 = const()[name = tensor("op_4062_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4062_cast_fp16 = einsum(equation = var_4062_equation_0, values = (var_3862_cast_fp16, var_4021_cast_fp16))[name = tensor("op_4062_cast_fp16")]; + tensor var_4064_equation_0 = const()[name = tensor("op_4064_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4064_cast_fp16 = einsum(equation = var_4064_equation_0, values = (var_3862_cast_fp16, var_4022_cast_fp16))[name = tensor("op_4064_cast_fp16")]; + tensor var_4066_equation_0 = const()[name = tensor("op_4066_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4066_cast_fp16 = einsum(equation = var_4066_equation_0, values = (var_3862_cast_fp16, var_4023_cast_fp16))[name = tensor("op_4066_cast_fp16")]; + tensor var_4068_equation_0 = const()[name = tensor("op_4068_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4068_cast_fp16 = einsum(equation = var_4068_equation_0, values = (var_3862_cast_fp16, var_4024_cast_fp16))[name = tensor("op_4068_cast_fp16")]; + tensor var_4070_equation_0 = const()[name = tensor("op_4070_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4070_cast_fp16 = einsum(equation = var_4070_equation_0, values = (var_3866_cast_fp16, var_4025_cast_fp16))[name = tensor("op_4070_cast_fp16")]; + tensor var_4072_equation_0 = const()[name = tensor("op_4072_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4072_cast_fp16 = einsum(equation = var_4072_equation_0, values = (var_3866_cast_fp16, var_4026_cast_fp16))[name = tensor("op_4072_cast_fp16")]; + tensor var_4074_equation_0 = const()[name = tensor("op_4074_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4074_cast_fp16 = einsum(equation = var_4074_equation_0, values = (var_3866_cast_fp16, var_4027_cast_fp16))[name = tensor("op_4074_cast_fp16")]; + tensor var_4076_equation_0 = const()[name = tensor("op_4076_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4076_cast_fp16 = einsum(equation = var_4076_equation_0, values = (var_3866_cast_fp16, var_4028_cast_fp16))[name = tensor("op_4076_cast_fp16")]; + tensor var_4078_equation_0 = const()[name = tensor("op_4078_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4078_cast_fp16 = einsum(equation = var_4078_equation_0, values = (var_3870_cast_fp16, var_4029_cast_fp16))[name = tensor("op_4078_cast_fp16")]; + tensor var_4080_equation_0 = const()[name = tensor("op_4080_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4080_cast_fp16 = einsum(equation = var_4080_equation_0, values = (var_3870_cast_fp16, var_4030_cast_fp16))[name = tensor("op_4080_cast_fp16")]; + tensor var_4082_equation_0 = const()[name = tensor("op_4082_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4082_cast_fp16 = einsum(equation = var_4082_equation_0, values = (var_3870_cast_fp16, var_4031_cast_fp16))[name = tensor("op_4082_cast_fp16")]; + tensor var_4084_equation_0 = const()[name = tensor("op_4084_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4084_cast_fp16 = einsum(equation = var_4084_equation_0, values = (var_3870_cast_fp16, var_4032_cast_fp16))[name = tensor("op_4084_cast_fp16")]; + tensor var_4086_equation_0 = const()[name = tensor("op_4086_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4086_cast_fp16 = einsum(equation = var_4086_equation_0, values = (var_3874_cast_fp16, var_4033_cast_fp16))[name = tensor("op_4086_cast_fp16")]; + tensor var_4088_equation_0 = const()[name = tensor("op_4088_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4088_cast_fp16 = einsum(equation = var_4088_equation_0, values = (var_3874_cast_fp16, var_4034_cast_fp16))[name = tensor("op_4088_cast_fp16")]; + tensor var_4090_equation_0 = const()[name = tensor("op_4090_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4090_cast_fp16 = einsum(equation = var_4090_equation_0, values = (var_3874_cast_fp16, var_4035_cast_fp16))[name = tensor("op_4090_cast_fp16")]; + tensor var_4092_equation_0 = const()[name = tensor("op_4092_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4092_cast_fp16 = einsum(equation = var_4092_equation_0, values = (var_3874_cast_fp16, var_4036_cast_fp16))[name = tensor("op_4092_cast_fp16")]; + tensor var_4094_equation_0 = const()[name = tensor("op_4094_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4094_cast_fp16 = einsum(equation = var_4094_equation_0, values = (var_3878_cast_fp16, var_4037_cast_fp16))[name = tensor("op_4094_cast_fp16")]; + tensor var_4096_equation_0 = const()[name = tensor("op_4096_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4096_cast_fp16 = einsum(equation = var_4096_equation_0, values = (var_3878_cast_fp16, var_4038_cast_fp16))[name = tensor("op_4096_cast_fp16")]; + tensor var_4098_equation_0 = const()[name = tensor("op_4098_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4098_cast_fp16 = einsum(equation = var_4098_equation_0, values = (var_3878_cast_fp16, var_4039_cast_fp16))[name = tensor("op_4098_cast_fp16")]; + tensor var_4100_equation_0 = const()[name = tensor("op_4100_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4100_cast_fp16 = einsum(equation = var_4100_equation_0, values = (var_3878_cast_fp16, var_4040_cast_fp16))[name = tensor("op_4100_cast_fp16")]; + tensor var_4102_equation_0 = const()[name = tensor("op_4102_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4102_cast_fp16 = einsum(equation = var_4102_equation_0, values = (var_3882_cast_fp16, var_4041_cast_fp16))[name = tensor("op_4102_cast_fp16")]; + tensor var_4104_equation_0 = const()[name = tensor("op_4104_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4104_cast_fp16 = einsum(equation = var_4104_equation_0, values = (var_3882_cast_fp16, var_4042_cast_fp16))[name = tensor("op_4104_cast_fp16")]; + tensor var_4106_equation_0 = const()[name = tensor("op_4106_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4106_cast_fp16 = einsum(equation = var_4106_equation_0, values = (var_3882_cast_fp16, var_4043_cast_fp16))[name = tensor("op_4106_cast_fp16")]; + tensor var_4108_equation_0 = const()[name = tensor("op_4108_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4108_cast_fp16 = einsum(equation = var_4108_equation_0, values = (var_3882_cast_fp16, var_4044_cast_fp16))[name = tensor("op_4108_cast_fp16")]; + tensor var_4110_interleave_0 = const()[name = tensor("op_4110_interleave_0"), val = tensor(false)]; + tensor var_4110_cast_fp16 = concat(axis = var_3497, interleave = var_4110_interleave_0, values = (var_4046_cast_fp16, var_4048_cast_fp16, var_4050_cast_fp16, var_4052_cast_fp16))[name = tensor("op_4110_cast_fp16")]; + tensor var_4112_interleave_0 = const()[name = tensor("op_4112_interleave_0"), val = tensor(false)]; + tensor var_4112_cast_fp16 = concat(axis = var_3497, interleave = var_4112_interleave_0, values = (var_4054_cast_fp16, var_4056_cast_fp16, var_4058_cast_fp16, var_4060_cast_fp16))[name = tensor("op_4112_cast_fp16")]; + tensor var_4114_interleave_0 = const()[name = tensor("op_4114_interleave_0"), val = tensor(false)]; + tensor var_4114_cast_fp16 = concat(axis = var_3497, interleave = var_4114_interleave_0, values = (var_4062_cast_fp16, var_4064_cast_fp16, var_4066_cast_fp16, var_4068_cast_fp16))[name = tensor("op_4114_cast_fp16")]; + tensor var_4116_interleave_0 = const()[name = tensor("op_4116_interleave_0"), val = tensor(false)]; + tensor var_4116_cast_fp16 = concat(axis = var_3497, interleave = var_4116_interleave_0, values = (var_4070_cast_fp16, var_4072_cast_fp16, var_4074_cast_fp16, var_4076_cast_fp16))[name = tensor("op_4116_cast_fp16")]; + tensor var_4118_interleave_0 = const()[name = tensor("op_4118_interleave_0"), val = tensor(false)]; + tensor var_4118_cast_fp16 = concat(axis = var_3497, interleave = var_4118_interleave_0, values = (var_4078_cast_fp16, var_4080_cast_fp16, var_4082_cast_fp16, var_4084_cast_fp16))[name = tensor("op_4118_cast_fp16")]; + tensor var_4120_interleave_0 = const()[name = tensor("op_4120_interleave_0"), val = tensor(false)]; + tensor var_4120_cast_fp16 = concat(axis = var_3497, interleave = var_4120_interleave_0, values = (var_4086_cast_fp16, var_4088_cast_fp16, var_4090_cast_fp16, var_4092_cast_fp16))[name = tensor("op_4120_cast_fp16")]; + tensor var_4122_interleave_0 = const()[name = tensor("op_4122_interleave_0"), val = tensor(false)]; + tensor var_4122_cast_fp16 = concat(axis = var_3497, interleave = var_4122_interleave_0, values = (var_4094_cast_fp16, var_4096_cast_fp16, var_4098_cast_fp16, var_4100_cast_fp16))[name = tensor("op_4122_cast_fp16")]; + tensor var_4124_interleave_0 = const()[name = tensor("op_4124_interleave_0"), val = tensor(false)]; + tensor var_4124_cast_fp16 = concat(axis = var_3497, interleave = var_4124_interleave_0, values = (var_4102_cast_fp16, var_4104_cast_fp16, var_4106_cast_fp16, var_4108_cast_fp16))[name = tensor("op_4124_cast_fp16")]; + tensor input_41_interleave_0 = const()[name = tensor("input_41_interleave_0"), val = tensor(false)]; + tensor input_41_cast_fp16 = concat(axis = var_3510, interleave = input_41_interleave_0, values = (var_4110_cast_fp16, var_4112_cast_fp16, var_4114_cast_fp16, var_4116_cast_fp16, var_4118_cast_fp16, var_4120_cast_fp16, var_4122_cast_fp16, var_4124_cast_fp16))[name = tensor("input_41_cast_fp16")]; + tensor var_4129 = const()[name = tensor("op_4129"), val = tensor([1, 1])]; + tensor var_4131 = const()[name = tensor("op_4131"), val = tensor([1, 1])]; + tensor obj_pad_type_0 = const()[name = tensor("obj_pad_type_0"), val = tensor("custom")]; + tensor obj_pad_0 = const()[name = tensor("obj_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36460160)))]; + tensor layers_5_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36984512)))]; + tensor obj_cast_fp16 = conv(bias = layers_5_self_attn_o_proj_bias_to_fp16, dilations = var_4131, groups = var_3510, pad = obj_pad_0, pad_type = obj_pad_type_0, strides = var_4129, weight = layers_5_self_attn_o_proj_weight_to_fp16, x = input_41_cast_fp16)[name = tensor("obj_cast_fp16")]; + tensor inputs_23_cast_fp16 = add(x = inputs_21_cast_fp16, y = obj_cast_fp16)[name = tensor("inputs_23_cast_fp16")]; + tensor var_4137 = const()[name = tensor("op_4137"), val = tensor([1])]; + tensor channels_mean_23_cast_fp16 = reduce_mean(axes = var_4137, keep_dims = var_3511, x = inputs_23_cast_fp16)[name = tensor("channels_mean_23_cast_fp16")]; + tensor zero_mean_23_cast_fp16 = sub(x = inputs_23_cast_fp16, y = channels_mean_23_cast_fp16)[name = tensor("zero_mean_23_cast_fp16")]; + tensor zero_mean_sq_23_cast_fp16 = mul(x = zero_mean_23_cast_fp16, y = zero_mean_23_cast_fp16)[name = tensor("zero_mean_sq_23_cast_fp16")]; + tensor var_4141 = const()[name = tensor("op_4141"), val = tensor([1])]; + tensor var_4142_cast_fp16 = reduce_mean(axes = var_4141, keep_dims = var_3511, x = zero_mean_sq_23_cast_fp16)[name = tensor("op_4142_cast_fp16")]; + tensor var_4143_to_fp16 = const()[name = tensor("op_4143_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_4144_cast_fp16 = add(x = var_4142_cast_fp16, y = var_4143_to_fp16)[name = tensor("op_4144_cast_fp16")]; + tensor denom_23_epsilon_0_to_fp16 = const()[name = tensor("denom_23_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_23_cast_fp16 = rsqrt(epsilon = denom_23_epsilon_0_to_fp16, x = var_4144_cast_fp16)[name = tensor("denom_23_cast_fp16")]; + tensor out_23_cast_fp16 = mul(x = zero_mean_23_cast_fp16, y = denom_23_cast_fp16)[name = tensor("out_23_cast_fp16")]; + tensor input_43_gamma_0_to_fp16 = const()[name = tensor("input_43_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36985600)))]; + tensor input_43_beta_0_to_fp16 = const()[name = tensor("input_43_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36986688)))]; + tensor input_43_epsilon_0_to_fp16 = const()[name = tensor("input_43_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_43_cast_fp16 = batch_norm(beta = input_43_beta_0_to_fp16, epsilon = input_43_epsilon_0_to_fp16, gamma = input_43_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_23_cast_fp16)[name = tensor("input_43_cast_fp16")]; + tensor var_4155 = const()[name = tensor("op_4155"), val = tensor([1, 1])]; + tensor var_4157 = const()[name = tensor("op_4157"), val = tensor([1, 1])]; + tensor input_45_pad_type_0 = const()[name = tensor("input_45_pad_type_0"), val = tensor("custom")]; + tensor input_45_pad_0 = const()[name = tensor("input_45_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_fc1_weight_to_fp16 = const()[name = tensor("layers_5_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36987776)))]; + tensor layers_5_fc1_bias_to_fp16 = const()[name = tensor("layers_5_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39084992)))]; + tensor input_45_cast_fp16 = conv(bias = layers_5_fc1_bias_to_fp16, dilations = var_4157, groups = var_3510, pad = input_45_pad_0, pad_type = input_45_pad_type_0, strides = var_4155, weight = layers_5_fc1_weight_to_fp16, x = input_43_cast_fp16)[name = tensor("input_45_cast_fp16")]; + tensor input_mode_0 = const()[name = tensor("input_mode_0"), val = tensor("EXACT")]; + tensor input_cast_fp16 = gelu(mode = input_mode_0, x = input_45_cast_fp16)[name = tensor("input_cast_fp16")]; + tensor var_4163 = const()[name = tensor("op_4163"), val = tensor([1, 1])]; + tensor var_4165 = const()[name = tensor("op_4165"), val = tensor([1, 1])]; + tensor hidden_states_pad_type_0 = const()[name = tensor("hidden_states_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_pad_0 = const()[name = tensor("hidden_states_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_fc2_weight_to_fp16 = const()[name = tensor("layers_5_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39089152)))]; + tensor layers_5_fc2_bias_to_fp16 = const()[name = tensor("layers_5_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41186368)))]; + tensor hidden_states_cast_fp16 = conv(bias = layers_5_fc2_bias_to_fp16, dilations = var_4165, groups = var_3510, pad = hidden_states_pad_0, pad_type = hidden_states_pad_type_0, strides = var_4163, weight = layers_5_fc2_weight_to_fp16, x = input_cast_fp16)[name = tensor("hidden_states_cast_fp16")]; + tensor inputs_cast_fp16 = add(x = inputs_23_cast_fp16, y = hidden_states_cast_fp16)[name = tensor("inputs_cast_fp16")]; + tensor var_4171 = const()[name = tensor("op_4171"), val = tensor(true)]; + tensor var_4175 = const()[name = tensor("op_4175"), val = tensor([1])]; + tensor channels_mean_cast_fp16 = reduce_mean(axes = var_4175, keep_dims = var_4171, x = inputs_cast_fp16)[name = tensor("channels_mean_cast_fp16")]; + tensor zero_mean_cast_fp16 = sub(x = inputs_cast_fp16, y = channels_mean_cast_fp16)[name = tensor("zero_mean_cast_fp16")]; + tensor zero_mean_sq_cast_fp16 = mul(x = zero_mean_cast_fp16, y = zero_mean_cast_fp16)[name = tensor("zero_mean_sq_cast_fp16")]; + tensor var_4179 = const()[name = tensor("op_4179"), val = tensor([1])]; + tensor var_4180_cast_fp16 = reduce_mean(axes = var_4179, keep_dims = var_4171, x = zero_mean_sq_cast_fp16)[name = tensor("op_4180_cast_fp16")]; + tensor var_4181_to_fp16 = const()[name = tensor("op_4181_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_4182_cast_fp16 = add(x = var_4180_cast_fp16, y = var_4181_to_fp16)[name = tensor("op_4182_cast_fp16")]; + tensor denom_epsilon_0_to_fp16 = const()[name = tensor("denom_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_cast_fp16 = rsqrt(epsilon = denom_epsilon_0_to_fp16, x = var_4182_cast_fp16)[name = tensor("denom_cast_fp16")]; + tensor out_cast_fp16 = mul(x = zero_mean_cast_fp16, y = denom_cast_fp16)[name = tensor("out_cast_fp16")]; + tensor encoder_output_embeds_type_fp32_gamma_0_to_fp16 = const()[name = tensor("encoder_output_embeds_type_fp32_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41187456)))]; + tensor encoder_output_embeds_type_fp32_beta_0_to_fp16 = const()[name = tensor("encoder_output_embeds_type_fp32_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41188544)))]; + tensor encoder_output_embeds_type_fp32_epsilon_0_to_fp16 = const()[name = tensor("encoder_output_embeds_type_fp32_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor encoder_output_embeds = batch_norm(beta = encoder_output_embeds_type_fp32_beta_0_to_fp16, epsilon = encoder_output_embeds_type_fp32_epsilon_0_to_fp16, gamma = encoder_output_embeds_type_fp32_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_cast_fp16)[name = tensor("encoder_output_embeds_type_fp32_cast_fp16")]; + } -> (encoder_output_embeds); +} \ No newline at end of file diff --git a/openai_whisper-base/AudioEncoder.mlmodelc/model.mlmodel b/openai_whisper-base/AudioEncoder.mlmodelc/model.mlmodel new file mode 100644 index 0000000000000000000000000000000000000000..50615c952c30a945ce18682e38a3a78eecddc358 --- /dev/null +++ b/openai_whisper-base/AudioEncoder.mlmodelc/model.mlmodel @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1d42038f84b508da5ce9b953302387ffedc097c346d36a56b765109002b6080e +size 79853 diff --git a/openai_whisper-base/AudioEncoder.mlmodelc/weights/weight.bin b/openai_whisper-base/AudioEncoder.mlmodelc/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..8fdbf685bba3a1efe3b57459cb3dbf088e92438d --- /dev/null +++ b/openai_whisper-base/AudioEncoder.mlmodelc/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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"predict" + } +] \ No newline at end of file diff --git a/openai_whisper-base/MelSpectrogram.mlmodelc/model.mil b/openai_whisper-base/MelSpectrogram.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..a63d7fa99d6d86db1b76a1f53640cb4aa25e0210 --- /dev/null +++ b/openai_whisper-base/MelSpectrogram.mlmodelc/model.mil @@ -0,0 +1,66 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.2.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})] +{ + func main(tensor audio) { + tensor var_10 = const()[name = tensor("op_10"), val = tensor([1, 1, 480000])]; + tensor input_1_cast_fp16 = reshape(shape = var_10, x = audio)[name = tensor("input_1_cast_fp16")]; + tensor input_3_pad_0 = const()[name = tensor("input_3_pad_0"), val = tensor([0, 0, 0, 0, 200, 200])]; + tensor input_3_mode_0 = const()[name = tensor("input_3_mode_0"), val = tensor("reflect")]; + tensor input_3_constant_val_0_to_fp16 = const()[name = tensor("input_3_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; + tensor input_3_cast_fp16 = pad(constant_val = input_3_constant_val_0_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = tensor("input_3_cast_fp16")]; + tensor var_22 = const()[name = tensor("op_22"), val = tensor([480400])]; + tensor input_cast_fp16 = reshape(shape = var_22, x = input_3_cast_fp16)[name = tensor("input_cast_fp16")]; + tensor expand_dims_0_axes_0 = const()[name = tensor("expand_dims_0_axes_0"), val = tensor([0])]; + tensor expand_dims_0_cast_fp16 = expand_dims(axes = expand_dims_0_axes_0, x = input_cast_fp16)[name = tensor("expand_dims_0_cast_fp16")]; + tensor expand_dims_3 = const()[name = tensor("expand_dims_3"), val = tensor([160])]; + tensor expand_dims_4_axes_0 = const()[name = tensor("expand_dims_4_axes_0"), val = tensor([1])]; + tensor expand_dims_4_cast_fp16 = expand_dims(axes = expand_dims_4_axes_0, x = expand_dims_0_cast_fp16)[name = tensor("expand_dims_4_cast_fp16")]; + tensor conv_0_pad_type_0 = const()[name = tensor("conv_0_pad_type_0"), val = tensor("valid")]; + tensor conv_0_pad_0 = const()[name = tensor("conv_0_pad_0"), val = tensor([0, 0])]; + tensor conv_0_dilations_0 = const()[name = tensor("conv_0_dilations_0"), val = tensor([1])]; + tensor conv_0_groups_0 = const()[name = tensor("conv_0_groups_0"), val = tensor(1)]; + tensor expand_dims_1_to_fp16 = const()[name = tensor("expand_dims_1_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor conv_0_cast_fp16 = conv(dilations = conv_0_dilations_0, groups = conv_0_groups_0, pad = conv_0_pad_0, pad_type = conv_0_pad_type_0, strides = expand_dims_3, weight = expand_dims_1_to_fp16, x = expand_dims_4_cast_fp16)[name = tensor("conv_0_cast_fp16")]; + tensor conv_1_pad_type_0 = const()[name = tensor("conv_1_pad_type_0"), val = tensor("valid")]; + tensor conv_1_pad_0 = const()[name = tensor("conv_1_pad_0"), val = tensor([0, 0])]; + tensor conv_1_dilations_0 = const()[name = tensor("conv_1_dilations_0"), val = tensor([1])]; + tensor conv_1_groups_0 = const()[name = tensor("conv_1_groups_0"), val = tensor(1)]; + tensor expand_dims_2_to_fp16 = const()[name = tensor("expand_dims_2_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160960)))]; + tensor conv_1_cast_fp16 = conv(dilations = conv_1_dilations_0, groups = conv_1_groups_0, pad = conv_1_pad_0, pad_type = conv_1_pad_type_0, strides = expand_dims_3, weight = expand_dims_2_to_fp16, x = expand_dims_4_cast_fp16)[name = tensor("conv_1_cast_fp16")]; + tensor squeeze_0_axes_0 = const()[name = tensor("squeeze_0_axes_0"), val = tensor([0])]; + tensor squeeze_0_cast_fp16 = squeeze(axes = squeeze_0_axes_0, x = conv_0_cast_fp16)[name = tensor("squeeze_0_cast_fp16")]; + tensor squeeze_1_axes_0 = const()[name = tensor("squeeze_1_axes_0"), val = tensor([0])]; + tensor squeeze_1_cast_fp16 = squeeze(axes = squeeze_1_axes_0, x = conv_1_cast_fp16)[name = tensor("squeeze_1_cast_fp16")]; + tensor square_0_cast_fp16 = square(x = squeeze_0_cast_fp16)[name = tensor("square_0_cast_fp16")]; + tensor square_1_cast_fp16 = square(x = squeeze_1_cast_fp16)[name = tensor("square_1_cast_fp16")]; + tensor add_1_cast_fp16 = add(x = square_0_cast_fp16, y = square_1_cast_fp16)[name = tensor("add_1_cast_fp16")]; + tensor magnitudes_1_cast_fp16 = identity(x = add_1_cast_fp16)[name = tensor("magnitudes_1_cast_fp16")]; + tensor magnitudes_begin_0 = const()[name = tensor("magnitudes_begin_0"), val = tensor([0, 0])]; + tensor magnitudes_end_0 = const()[name = tensor("magnitudes_end_0"), val = tensor([201, 3000])]; + tensor magnitudes_end_mask_0 = const()[name = tensor("magnitudes_end_mask_0"), val = tensor([true, false])]; + tensor magnitudes_cast_fp16 = slice_by_index(begin = magnitudes_begin_0, end = magnitudes_end_0, end_mask = magnitudes_end_mask_0, x = magnitudes_1_cast_fp16)[name = tensor("magnitudes_cast_fp16")]; + tensor mel_spec_1_transpose_x_0 = const()[name = tensor("mel_spec_1_transpose_x_0"), val = tensor(false)]; + tensor mel_spec_1_transpose_y_0 = const()[name = tensor("mel_spec_1_transpose_y_0"), val = tensor(false)]; + tensor mel_filters_to_fp16 = const()[name = tensor("mel_filters_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(321856)))]; + tensor mel_spec_1_cast_fp16 = matmul(transpose_x = mel_spec_1_transpose_x_0, transpose_y = mel_spec_1_transpose_y_0, x = mel_filters_to_fp16, y = magnitudes_cast_fp16)[name = tensor("mel_spec_1_cast_fp16")]; + tensor var_41_to_fp16 = const()[name = tensor("op_41_to_fp16"), val = tensor(0x1p-24)]; + tensor mel_spec_cast_fp16 = add(x = mel_spec_1_cast_fp16, y = var_41_to_fp16)[name = tensor("mel_spec_cast_fp16")]; + tensor log_0_epsilon_0_to_fp16 = const()[name = tensor("log_0_epsilon_0_to_fp16"), val = tensor(0x0p+0)]; + tensor log_0_cast_fp16 = log(epsilon = log_0_epsilon_0_to_fp16, x = mel_spec_cast_fp16)[name = tensor("log_0_cast_fp16")]; + tensor mul_0_y_0_to_fp16 = const()[name = tensor("mul_0_y_0_to_fp16"), val = tensor(0x1.bccp-2)]; + tensor mul_0_cast_fp16 = mul(x = log_0_cast_fp16, y = mul_0_y_0_to_fp16)[name = tensor("mul_0_cast_fp16")]; + tensor var_44_keep_dims_0 = const()[name = tensor("op_44_keep_dims_0"), val = tensor(false)]; + tensor var_44_cast_fp16 = reduce_max(keep_dims = var_44_keep_dims_0, x = mul_0_cast_fp16)[name = tensor("op_44_cast_fp16")]; + tensor var_46_to_fp16 = const()[name = tensor("op_46_to_fp16"), val = tensor(0x1p+3)]; + tensor var_47_cast_fp16 = sub(x = var_44_cast_fp16, y = var_46_to_fp16)[name = tensor("op_47_cast_fp16")]; + tensor log_spec_3_cast_fp16 = maximum(x = mul_0_cast_fp16, y = var_47_cast_fp16)[name = tensor("log_spec_3_cast_fp16")]; + tensor var_50_to_fp16 = const()[name = tensor("op_50_to_fp16"), val = tensor(0x1p+2)]; + tensor var_51_cast_fp16 = add(x = log_spec_3_cast_fp16, y = var_50_to_fp16)[name = tensor("op_51_cast_fp16")]; + tensor _inversed_log_spec_y_0_to_fp16 = const()[name = tensor("_inversed_log_spec_y_0_to_fp16"), val = tensor(0x1p-2)]; + tensor _inversed_log_spec_cast_fp16 = mul(x = var_51_cast_fp16, y = _inversed_log_spec_y_0_to_fp16)[name = tensor("_inversed_log_spec_cast_fp16")]; + tensor var_55_axes_0 = const()[name = tensor("op_55_axes_0"), val = tensor([0])]; + tensor var_55_cast_fp16 = expand_dims(axes = var_55_axes_0, x = _inversed_log_spec_cast_fp16)[name = tensor("op_55_cast_fp16")]; + tensor var_62_axes_0 = const()[name = tensor("op_62_axes_0"), val = tensor([2])]; + tensor melspectrogram_features = expand_dims(axes = var_62_axes_0, x = var_55_cast_fp16)[name = tensor("op_62_cast_fp16")]; + } -> (melspectrogram_features); +} \ No newline at end of file diff --git a/openai_whisper-base/MelSpectrogram.mlmodelc/weights/weight.bin 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"shortDescription" : "", + "shape" : "[1]", + "name" : "input_ids", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Int32", + "formattedType" : "MultiArray (Int32 1)", + "shortDescription" : "", + "shape" : "[1]", + "name" : "cache_length", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float16", + "formattedType" : "MultiArray (Float16 1 × 3072 × 1 × 224)", + "shortDescription" : "", + "shape" : "[1, 3072, 1, 224]", + "name" : "key_cache", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float16", + "formattedType" : "MultiArray (Float16 1 × 3072 × 1 × 224)", + "shortDescription" : "", + "shape" : "[1, 3072, 1, 224]", + "name" : "value_cache", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float16", + "formattedType" : "MultiArray (Float16 1 × 224)", + "shortDescription" : "", + "shape" : "[1, 224]", + "name" : "kv_cache_update_mask", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float16", + "formattedType" : "MultiArray (Float16 1 × 512 × 1 × 1500)", + "shortDescription" : "", + "shape" : "[1, 512, 1, 1500]", + "name" : "encoder_output_embeds", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float16", + "formattedType" : "MultiArray (Float16 1 × 224)", + "shortDescription" : "", + "shape" : "[1, 224]", + "name" : "decoder_key_padding_mask", + "type" : "MultiArray" + } + ], + "generatedClassName" : "TextDecoder", + "method" : "predict" + } +] \ No newline at end of file diff --git a/openai_whisper-base/TextDecoder.mlmodelc/model.mil b/openai_whisper-base/TextDecoder.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..bdf5741552d15c82459d7e398927f7972a4fe195 --- /dev/null +++ b/openai_whisper-base/TextDecoder.mlmodelc/model.mil @@ -0,0 +1,1115 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.2.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})] +{ + func main(tensor cache_length, tensor decoder_key_padding_mask, tensor encoder_output_embeds, tensor input_ids, tensor key_cache, tensor kv_cache_update_mask, tensor value_cache) { + tensor var_28_axis_0 = const()[name = tensor("op_28_axis_0"), val = tensor(0)]; + tensor var_28_batch_dims_0 = const()[name = tensor("op_28_batch_dims_0"), val = tensor(0)]; + tensor embed_tokens_weight_to_fp16 = const()[name = tensor("embed_tokens_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor var_28_cast_fp16 = gather(axis = var_28_axis_0, batch_dims = var_28_batch_dims_0, indices = input_ids, x = embed_tokens_weight_to_fp16)[name = tensor("op_28_cast_fp16")]; + tensor var_32_axis_0 = const()[name = tensor("op_32_axis_0"), val = tensor(0)]; + tensor var_32_batch_dims_0 = const()[name = tensor("op_32_batch_dims_0"), val = tensor(0)]; + tensor embed_positions_weight_to_fp16 = const()[name = tensor("embed_positions_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53109888)))]; + tensor var_32_cast_fp16 = gather(axis = var_32_axis_0, batch_dims = var_32_batch_dims_0, indices = cache_length, x = embed_positions_weight_to_fp16)[name = tensor("op_32_cast_fp16")]; + tensor hidden_states_1_cast_fp16 = add(x = var_28_cast_fp16, y = var_32_cast_fp16)[name = tensor("hidden_states_1_cast_fp16")]; + tensor var_46_axes_0 = const()[name = tensor("op_46_axes_0"), val = tensor([2])]; + tensor var_46_cast_fp16 = expand_dims(axes = var_46_axes_0, x = hidden_states_1_cast_fp16)[name = tensor("op_46_cast_fp16")]; + tensor inputs_1_axes_0 = const()[name = tensor("inputs_1_axes_0"), val = tensor([3])]; + tensor inputs_1_cast_fp16 = expand_dims(axes = inputs_1_axes_0, x = var_46_cast_fp16)[name = tensor("inputs_1_cast_fp16")]; + tensor tile_0 = const()[name = tensor("tile_0"), val = tensor([512, 512, 512, 512, 512, 512])]; + tensor var_51_axis_0 = const()[name = tensor("op_51_axis_0"), val = tensor(1)]; + tensor var_51_cast_fp16_0, tensor var_51_cast_fp16_1, tensor var_51_cast_fp16_2, tensor var_51_cast_fp16_3, tensor var_51_cast_fp16_4, tensor var_51_cast_fp16_5 = split(axis = var_51_axis_0, split_sizes = tile_0, x = key_cache)[name = tensor("op_51_cast_fp16")]; + tensor tile_1 = const()[name = tensor("tile_1"), val = tensor([512, 512, 512, 512, 512, 512])]; + tensor var_60_axis_0 = const()[name = tensor("op_60_axis_0"), val = tensor(1)]; + tensor var_60_cast_fp16_0, tensor var_60_cast_fp16_1, tensor var_60_cast_fp16_2, tensor var_60_cast_fp16_3, tensor var_60_cast_fp16_4, tensor var_60_cast_fp16_5 = split(axis = var_60_axis_0, split_sizes = tile_1, x = value_cache)[name = tensor("op_60_cast_fp16")]; + tensor var_72 = const()[name = tensor("op_72"), val = tensor(3)]; + tensor var_79 = const()[name = tensor("op_79"), val = tensor(1)]; + tensor var_80 = const()[name = tensor("op_80"), val = tensor(true)]; + tensor var_92 = const()[name = tensor("op_92"), val = tensor([1])]; + tensor channels_mean_1_cast_fp16 = reduce_mean(axes = var_92, keep_dims = var_80, x = inputs_1_cast_fp16)[name = tensor("channels_mean_1_cast_fp16")]; + tensor zero_mean_1_cast_fp16 = sub(x = inputs_1_cast_fp16, y = channels_mean_1_cast_fp16)[name = tensor("zero_mean_1_cast_fp16")]; + tensor zero_mean_sq_1_cast_fp16 = mul(x = zero_mean_1_cast_fp16, y = zero_mean_1_cast_fp16)[name = tensor("zero_mean_sq_1_cast_fp16")]; + tensor var_96 = const()[name = tensor("op_96"), val = tensor([1])]; + tensor var_97_cast_fp16 = reduce_mean(axes = var_96, keep_dims = var_80, x = zero_mean_sq_1_cast_fp16)[name = tensor("op_97_cast_fp16")]; + tensor var_98_to_fp16 = const()[name = tensor("op_98_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_99_cast_fp16 = add(x = var_97_cast_fp16, y = var_98_to_fp16)[name = tensor("op_99_cast_fp16")]; + tensor denom_1_epsilon_0_to_fp16 = const()[name = tensor("denom_1_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_1_cast_fp16 = rsqrt(epsilon = denom_1_epsilon_0_to_fp16, x = var_99_cast_fp16)[name = tensor("denom_1_cast_fp16")]; + tensor out_1_cast_fp16 = mul(x = zero_mean_1_cast_fp16, y = denom_1_cast_fp16)[name = tensor("out_1_cast_fp16")]; + tensor obj_1_mean_0_to_fp16 = const()[name = tensor("obj_1_mean_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53568704)))]; + tensor obj_1_variance_0_to_fp16 = const()[name = tensor("obj_1_variance_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53569792)))]; + tensor obj_1_gamma_0_to_fp16 = const()[name = tensor("obj_1_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53570880)))]; + tensor obj_1_beta_0_to_fp16 = const()[name = tensor("obj_1_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53571968)))]; + tensor obj_1_epsilon_0_to_fp16 = const()[name = tensor("obj_1_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_1_cast_fp16 = batch_norm(beta = obj_1_beta_0_to_fp16, epsilon = obj_1_epsilon_0_to_fp16, gamma = obj_1_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_1_cast_fp16)[name = tensor("obj_1_cast_fp16")]; + tensor var_114 = const()[name = tensor("op_114"), val = tensor([1, 1])]; + tensor var_116 = const()[name = tensor("op_116"), val = tensor([1, 1])]; + tensor query_1_pad_type_0 = const()[name = tensor("query_1_pad_type_0"), val = tensor("custom")]; + tensor query_1_pad_0 = const()[name = tensor("query_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53573056)))]; + tensor layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54097408)))]; + tensor query_1_cast_fp16 = conv(bias = layers_0_self_attn_q_proj_bias_to_fp16, dilations = var_116, groups = var_79, pad = query_1_pad_0, pad_type = query_1_pad_type_0, strides = var_114, weight = layers_0_self_attn_q_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("query_1_cast_fp16")]; + tensor var_120 = const()[name = tensor("op_120"), val = tensor([1, 1])]; + tensor var_122 = const()[name = tensor("op_122"), val = tensor([1, 1])]; + tensor current_key_1_pad_type_0 = const()[name = tensor("current_key_1_pad_type_0"), val = tensor("custom")]; + tensor current_key_1_pad_0 = const()[name = tensor("current_key_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54098496)))]; + tensor current_key_1_cast_fp16 = conv(dilations = var_122, groups = var_79, pad = current_key_1_pad_0, pad_type = current_key_1_pad_type_0, strides = var_120, weight = layers_0_self_attn_k_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("current_key_1_cast_fp16")]; + tensor var_127 = const()[name = tensor("op_127"), val = tensor([1, 1])]; + tensor var_129 = const()[name = tensor("op_129"), val = tensor([1, 1])]; + tensor current_value_1_pad_type_0 = const()[name = tensor("current_value_1_pad_type_0"), val = tensor("custom")]; + tensor current_value_1_pad_0 = const()[name = tensor("current_value_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54622848)))]; + tensor layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55147200)))]; + tensor current_value_1_cast_fp16 = conv(bias = layers_0_self_attn_v_proj_bias_to_fp16, dilations = var_129, groups = var_79, pad = current_value_1_pad_0, pad_type = current_value_1_pad_type_0, strides = var_127, weight = layers_0_self_attn_v_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("current_value_1_cast_fp16")]; + tensor var_133_axes_0 = const()[name = tensor("op_133_axes_0"), val = tensor([1])]; + tensor var_133_cast_fp16 = expand_dims(axes = var_133_axes_0, x = kv_cache_update_mask)[name = tensor("op_133_cast_fp16")]; + tensor var_134_axes_0 = const()[name = tensor("op_134_axes_0"), val = tensor([2])]; + tensor var_134_cast_fp16 = expand_dims(axes = var_134_axes_0, x = var_133_cast_fp16)[name = tensor("op_134_cast_fp16")]; + tensor var_136_cast_fp16 = mul(x = current_key_1_cast_fp16, y = var_134_cast_fp16)[name = tensor("op_136_cast_fp16")]; + tensor var_73_to_fp16 = const()[name = tensor("op_73_to_fp16"), val = tensor(0x1p+0)]; + tensor var_137_cast_fp16 = sub(x = var_73_to_fp16, y = var_134_cast_fp16)[name = tensor("op_137_cast_fp16")]; + tensor var_138_cast_fp16 = mul(x = var_51_cast_fp16_0, y = var_137_cast_fp16)[name = tensor("op_138_cast_fp16")]; + tensor key_1_cast_fp16 = add(x = var_136_cast_fp16, y = var_138_cast_fp16)[name = tensor("key_1_cast_fp16")]; + tensor var_140_cast_fp16 = mul(x = current_value_1_cast_fp16, y = var_134_cast_fp16)[name = tensor("op_140_cast_fp16")]; + tensor var_142_cast_fp16 = mul(x = var_60_cast_fp16_0, y = var_137_cast_fp16)[name = tensor("op_142_cast_fp16")]; + tensor value_1_cast_fp16 = add(x = var_140_cast_fp16, y = var_142_cast_fp16)[name = tensor("value_1_cast_fp16")]; + tensor var_145 = const()[name = tensor("op_145"), val = tensor([1, 8, 64, -1])]; + tensor var_146_cast_fp16 = reshape(shape = var_145, x = query_1_cast_fp16)[name = tensor("op_146_cast_fp16")]; + tensor var_147_to_fp16 = const()[name = tensor("op_147_to_fp16"), val = tensor(0x1p-3)]; + tensor var_148_cast_fp16 = mul(x = var_146_cast_fp16, y = var_147_to_fp16)[name = tensor("op_148_cast_fp16")]; + tensor var_149 = const()[name = tensor("op_149"), val = tensor([1, 8, 64, -1])]; + tensor var_150_cast_fp16 = reshape(shape = var_149, x = key_1_cast_fp16)[name = tensor("op_150_cast_fp16")]; + tensor mh_w_1_transpose_x_0 = const()[name = tensor("mh_w_1_transpose_x_0"), val = tensor(true)]; + tensor mh_w_1_transpose_y_0 = const()[name = tensor("mh_w_1_transpose_y_0"), val = tensor(false)]; + tensor mh_w_1_cast_fp16 = matmul(transpose_x = mh_w_1_transpose_x_0, transpose_y = mh_w_1_transpose_y_0, x = var_148_cast_fp16, y = var_150_cast_fp16)[name = tensor("mh_w_1_cast_fp16")]; + tensor var_154_axes_0 = const()[name = tensor("op_154_axes_0"), val = tensor([1])]; + tensor var_154_cast_fp16 = expand_dims(axes = var_154_axes_0, x = decoder_key_padding_mask)[name = tensor("op_154_cast_fp16")]; + tensor var_155_axes_0 = const()[name = tensor("op_155_axes_0"), val = tensor([2])]; + tensor var_155_cast_fp16 = expand_dims(axes = var_155_axes_0, x = var_154_cast_fp16)[name = tensor("op_155_cast_fp16")]; + tensor mh_w_3_cast_fp16 = add(x = mh_w_1_cast_fp16, y = var_155_cast_fp16)[name = tensor("mh_w_3_cast_fp16")]; + tensor var_158_cast_fp16 = softmax(axis = var_72, x = mh_w_3_cast_fp16)[name = tensor("op_158_cast_fp16")]; + tensor var_159 = const()[name = tensor("op_159"), val = tensor([1, 8, 64, -1])]; + tensor var_160_cast_fp16 = reshape(shape = var_159, x = value_1_cast_fp16)[name = tensor("op_160_cast_fp16")]; + tensor attn_1_transpose_x_0 = const()[name = tensor("attn_1_transpose_x_0"), val = tensor(false)]; + tensor attn_1_transpose_y_0 = const()[name = tensor("attn_1_transpose_y_0"), val = tensor(true)]; + tensor attn_1_cast_fp16 = matmul(transpose_x = attn_1_transpose_x_0, transpose_y = attn_1_transpose_y_0, x = var_160_cast_fp16, y = var_158_cast_fp16)[name = tensor("attn_1_cast_fp16")]; + tensor var_163 = const()[name = tensor("op_163"), val = tensor([1, 512, 1, -1])]; + tensor input_1_cast_fp16 = reshape(shape = var_163, x = attn_1_cast_fp16)[name = tensor("input_1_cast_fp16")]; + tensor var_167 = const()[name = tensor("op_167"), val = tensor([1, 1])]; + tensor var_169 = const()[name = tensor("op_169"), val = tensor([1, 1])]; + tensor obj_7_pad_type_0 = const()[name = tensor("obj_7_pad_type_0"), val = tensor("custom")]; + tensor obj_7_pad_0 = const()[name = tensor("obj_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55148288)))]; + tensor layers_0_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55672640)))]; + tensor obj_7_cast_fp16 = conv(bias = layers_0_self_attn_o_proj_bias_to_fp16, dilations = var_169, groups = var_79, pad = obj_7_pad_0, pad_type = obj_7_pad_type_0, strides = var_167, weight = layers_0_self_attn_o_proj_weight_to_fp16, x = input_1_cast_fp16)[name = tensor("obj_7_cast_fp16")]; + tensor inputs_3_cast_fp16 = add(x = inputs_1_cast_fp16, y = obj_7_cast_fp16)[name = tensor("inputs_3_cast_fp16")]; + tensor var_179 = const()[name = tensor("op_179"), val = tensor([1])]; + tensor channels_mean_3_cast_fp16 = reduce_mean(axes = var_179, keep_dims = var_80, x = inputs_3_cast_fp16)[name = tensor("channels_mean_3_cast_fp16")]; + tensor zero_mean_3_cast_fp16 = sub(x = inputs_3_cast_fp16, y = channels_mean_3_cast_fp16)[name = tensor("zero_mean_3_cast_fp16")]; + tensor zero_mean_sq_3_cast_fp16 = mul(x = zero_mean_3_cast_fp16, y = zero_mean_3_cast_fp16)[name = tensor("zero_mean_sq_3_cast_fp16")]; + tensor var_183 = const()[name = tensor("op_183"), val = tensor([1])]; + tensor var_184_cast_fp16 = reduce_mean(axes = var_183, keep_dims = var_80, x = zero_mean_sq_3_cast_fp16)[name = tensor("op_184_cast_fp16")]; + tensor var_185_to_fp16 = const()[name = tensor("op_185_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_186_cast_fp16 = add(x = var_184_cast_fp16, y = var_185_to_fp16)[name = tensor("op_186_cast_fp16")]; + tensor denom_3_epsilon_0_to_fp16 = const()[name = tensor("denom_3_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_3_cast_fp16 = rsqrt(epsilon = denom_3_epsilon_0_to_fp16, x = var_186_cast_fp16)[name = tensor("denom_3_cast_fp16")]; + tensor out_3_cast_fp16 = mul(x = zero_mean_3_cast_fp16, y = denom_3_cast_fp16)[name = tensor("out_3_cast_fp16")]; + tensor obj_9_gamma_0_to_fp16 = const()[name = tensor("obj_9_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55673728)))]; + tensor obj_9_beta_0_to_fp16 = const()[name = tensor("obj_9_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55674816)))]; + tensor obj_9_epsilon_0_to_fp16 = const()[name = tensor("obj_9_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_9_cast_fp16 = batch_norm(beta = obj_9_beta_0_to_fp16, epsilon = obj_9_epsilon_0_to_fp16, gamma = obj_9_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_3_cast_fp16)[name = tensor("obj_9_cast_fp16")]; + tensor var_201 = const()[name = tensor("op_201"), val = tensor([1, 1])]; + tensor var_203 = const()[name = tensor("op_203"), val = tensor([1, 1])]; + tensor query_3_pad_type_0 = const()[name = tensor("query_3_pad_type_0"), val = tensor("custom")]; + tensor query_3_pad_0 = const()[name = tensor("query_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55675904)))]; + tensor layers_0_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_0_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(56200256)))]; + tensor query_3_cast_fp16 = conv(bias = layers_0_encoder_attn_q_proj_bias_to_fp16, dilations = var_203, groups = var_79, pad = query_3_pad_0, pad_type = query_3_pad_type_0, strides = var_201, weight = layers_0_encoder_attn_q_proj_weight_to_fp16, x = obj_9_cast_fp16)[name = tensor("query_3_cast_fp16")]; + tensor var_207 = const()[name = tensor("op_207"), val = tensor([1, 1])]; + tensor var_209 = const()[name = tensor("op_209"), val = tensor([1, 1])]; + tensor key_3_pad_type_0 = const()[name = tensor("key_3_pad_type_0"), val = tensor("custom")]; + tensor key_3_pad_0 = const()[name = tensor("key_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(56201344)))]; + tensor key_3_cast_fp16 = conv(dilations = var_209, groups = var_79, pad = key_3_pad_0, pad_type = key_3_pad_type_0, strides = var_207, weight = layers_0_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_3_cast_fp16")]; + tensor var_214 = const()[name = tensor("op_214"), val = tensor([1, 1])]; + tensor var_216 = const()[name = tensor("op_216"), val = tensor([1, 1])]; + tensor value_3_pad_type_0 = const()[name = tensor("value_3_pad_type_0"), val = tensor("custom")]; + tensor value_3_pad_0 = const()[name = tensor("value_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(56725696)))]; + tensor layers_0_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_0_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57250048)))]; + tensor value_3_cast_fp16 = conv(bias = layers_0_encoder_attn_v_proj_bias_to_fp16, dilations = var_216, groups = var_79, pad = value_3_pad_0, pad_type = value_3_pad_type_0, strides = var_214, weight = layers_0_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_3_cast_fp16")]; + tensor var_220 = const()[name = tensor("op_220"), val = tensor([1, 8, 64, -1])]; + tensor var_221_cast_fp16 = reshape(shape = var_220, x = query_3_cast_fp16)[name = tensor("op_221_cast_fp16")]; + tensor var_222_to_fp16 = const()[name = tensor("op_222_to_fp16"), val = tensor(0x1p-3)]; + tensor var_223_cast_fp16 = mul(x = var_221_cast_fp16, y = var_222_to_fp16)[name = tensor("op_223_cast_fp16")]; + tensor var_224 = const()[name = tensor("op_224"), val = tensor([1, 8, 64, -1])]; + tensor var_225_cast_fp16 = reshape(shape = var_224, x = key_3_cast_fp16)[name = tensor("op_225_cast_fp16")]; + tensor mh_w_5_transpose_x_0 = const()[name = tensor("mh_w_5_transpose_x_0"), val = tensor(true)]; + tensor mh_w_5_transpose_y_0 = const()[name = tensor("mh_w_5_transpose_y_0"), val = tensor(false)]; + tensor mh_w_5_cast_fp16 = matmul(transpose_x = mh_w_5_transpose_x_0, transpose_y = mh_w_5_transpose_y_0, x = var_223_cast_fp16, y = var_225_cast_fp16)[name = tensor("mh_w_5_cast_fp16")]; + tensor obj_13_cast_fp16 = softmax(axis = var_72, x = mh_w_5_cast_fp16)[name = tensor("obj_13_cast_fp16")]; + tensor var_229 = const()[name = tensor("op_229"), val = tensor([1, 8, 64, -1])]; + tensor var_230_cast_fp16 = reshape(shape = var_229, x = value_3_cast_fp16)[name = tensor("op_230_cast_fp16")]; + tensor attn_3_transpose_x_0 = const()[name = tensor("attn_3_transpose_x_0"), val = tensor(false)]; + tensor attn_3_transpose_y_0 = const()[name = tensor("attn_3_transpose_y_0"), val = tensor(true)]; + tensor attn_3_cast_fp16 = matmul(transpose_x = attn_3_transpose_x_0, transpose_y = attn_3_transpose_y_0, x = var_230_cast_fp16, y = obj_13_cast_fp16)[name = tensor("attn_3_cast_fp16")]; + tensor var_233 = const()[name = tensor("op_233"), val = tensor([1, 512, 1, -1])]; + tensor input_3_cast_fp16 = reshape(shape = var_233, x = attn_3_cast_fp16)[name = tensor("input_3_cast_fp16")]; + tensor var_237 = const()[name = tensor("op_237"), val = tensor([1, 1])]; + tensor var_239 = const()[name = tensor("op_239"), val = tensor([1, 1])]; + tensor obj_11_pad_type_0 = const()[name = tensor("obj_11_pad_type_0"), val = tensor("custom")]; + tensor obj_11_pad_0 = const()[name = tensor("obj_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57251136)))]; + tensor layers_0_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_0_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57775488)))]; + tensor obj_11_cast_fp16 = conv(bias = layers_0_encoder_attn_o_proj_bias_to_fp16, dilations = var_239, groups = var_79, pad = obj_11_pad_0, pad_type = obj_11_pad_type_0, strides = var_237, weight = layers_0_encoder_attn_o_proj_weight_to_fp16, x = input_3_cast_fp16)[name = tensor("obj_11_cast_fp16")]; + tensor inputs_5_cast_fp16 = add(x = inputs_3_cast_fp16, y = obj_11_cast_fp16)[name = tensor("inputs_5_cast_fp16")]; + tensor var_245 = const()[name = tensor("op_245"), val = tensor([1])]; + tensor channels_mean_5_cast_fp16 = reduce_mean(axes = var_245, keep_dims = var_80, x = inputs_5_cast_fp16)[name = tensor("channels_mean_5_cast_fp16")]; + tensor zero_mean_5_cast_fp16 = sub(x = inputs_5_cast_fp16, y = channels_mean_5_cast_fp16)[name = tensor("zero_mean_5_cast_fp16")]; + tensor zero_mean_sq_5_cast_fp16 = mul(x = zero_mean_5_cast_fp16, y = zero_mean_5_cast_fp16)[name = tensor("zero_mean_sq_5_cast_fp16")]; + tensor var_249 = const()[name = tensor("op_249"), val = tensor([1])]; + tensor var_250_cast_fp16 = reduce_mean(axes = var_249, keep_dims = var_80, x = zero_mean_sq_5_cast_fp16)[name = tensor("op_250_cast_fp16")]; + tensor var_251_to_fp16 = const()[name = tensor("op_251_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_252_cast_fp16 = add(x = var_250_cast_fp16, y = var_251_to_fp16)[name = tensor("op_252_cast_fp16")]; + tensor denom_5_epsilon_0_to_fp16 = const()[name = tensor("denom_5_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_5_cast_fp16 = rsqrt(epsilon = denom_5_epsilon_0_to_fp16, x = var_252_cast_fp16)[name = tensor("denom_5_cast_fp16")]; + tensor out_5_cast_fp16 = mul(x = zero_mean_5_cast_fp16, y = denom_5_cast_fp16)[name = tensor("out_5_cast_fp16")]; + tensor input_5_gamma_0_to_fp16 = const()[name = tensor("input_5_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57776576)))]; + tensor input_5_beta_0_to_fp16 = const()[name = tensor("input_5_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57777664)))]; + tensor input_5_epsilon_0_to_fp16 = const()[name = tensor("input_5_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_5_cast_fp16 = batch_norm(beta = input_5_beta_0_to_fp16, epsilon = input_5_epsilon_0_to_fp16, gamma = input_5_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_5_cast_fp16)[name = tensor("input_5_cast_fp16")]; + tensor var_263 = const()[name = tensor("op_263"), val = tensor([1, 1])]; + tensor var_265 = const()[name = tensor("op_265"), val = tensor([1, 1])]; + tensor input_7_pad_type_0 = const()[name = tensor("input_7_pad_type_0"), val = tensor("custom")]; + tensor input_7_pad_0 = const()[name = tensor("input_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_fc1_weight_to_fp16 = const()[name = tensor("layers_0_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57778752)))]; + tensor layers_0_fc1_bias_to_fp16 = const()[name = tensor("layers_0_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59875968)))]; + tensor input_7_cast_fp16 = conv(bias = layers_0_fc1_bias_to_fp16, dilations = var_265, groups = var_79, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = var_263, weight = layers_0_fc1_weight_to_fp16, x = input_5_cast_fp16)[name = tensor("input_7_cast_fp16")]; + tensor input_9_mode_0 = const()[name = tensor("input_9_mode_0"), val = tensor("EXACT")]; + tensor input_9_cast_fp16 = gelu(mode = input_9_mode_0, x = input_7_cast_fp16)[name = tensor("input_9_cast_fp16")]; + tensor var_271 = const()[name = tensor("op_271"), val = tensor([1, 1])]; + tensor var_273 = const()[name = tensor("op_273"), val = tensor([1, 1])]; + tensor hidden_states_3_pad_type_0 = const()[name = tensor("hidden_states_3_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_3_pad_0 = const()[name = tensor("hidden_states_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_fc2_weight_to_fp16 = const()[name = tensor("layers_0_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59880128)))]; + tensor layers_0_fc2_bias_to_fp16 = const()[name = tensor("layers_0_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61977344)))]; + tensor hidden_states_3_cast_fp16 = conv(bias = layers_0_fc2_bias_to_fp16, dilations = var_273, groups = var_79, pad = hidden_states_3_pad_0, pad_type = hidden_states_3_pad_type_0, strides = var_271, weight = layers_0_fc2_weight_to_fp16, x = input_9_cast_fp16)[name = tensor("hidden_states_3_cast_fp16")]; + tensor inputs_7_cast_fp16 = add(x = inputs_5_cast_fp16, y = hidden_states_3_cast_fp16)[name = tensor("inputs_7_cast_fp16")]; + tensor var_286 = const()[name = tensor("op_286"), val = tensor(3)]; + tensor var_293 = const()[name = tensor("op_293"), val = tensor(1)]; + tensor var_294 = const()[name = tensor("op_294"), val = tensor(true)]; + tensor var_306 = const()[name = tensor("op_306"), val = tensor([1])]; + tensor channels_mean_7_cast_fp16 = reduce_mean(axes = var_306, keep_dims = var_294, x = inputs_7_cast_fp16)[name = tensor("channels_mean_7_cast_fp16")]; + tensor zero_mean_7_cast_fp16 = sub(x = inputs_7_cast_fp16, y = channels_mean_7_cast_fp16)[name = tensor("zero_mean_7_cast_fp16")]; + tensor zero_mean_sq_7_cast_fp16 = mul(x = zero_mean_7_cast_fp16, y = zero_mean_7_cast_fp16)[name = tensor("zero_mean_sq_7_cast_fp16")]; + tensor var_310 = const()[name = tensor("op_310"), val = tensor([1])]; + tensor var_311_cast_fp16 = reduce_mean(axes = var_310, keep_dims = var_294, x = zero_mean_sq_7_cast_fp16)[name = tensor("op_311_cast_fp16")]; + tensor var_312_to_fp16 = const()[name = tensor("op_312_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_313_cast_fp16 = add(x = var_311_cast_fp16, y = var_312_to_fp16)[name = tensor("op_313_cast_fp16")]; + tensor denom_7_epsilon_0_to_fp16 = const()[name = tensor("denom_7_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_7_cast_fp16 = rsqrt(epsilon = denom_7_epsilon_0_to_fp16, x = var_313_cast_fp16)[name = tensor("denom_7_cast_fp16")]; + tensor out_7_cast_fp16 = mul(x = zero_mean_7_cast_fp16, y = denom_7_cast_fp16)[name = tensor("out_7_cast_fp16")]; + tensor obj_15_gamma_0_to_fp16 = const()[name = tensor("obj_15_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61978432)))]; + tensor obj_15_beta_0_to_fp16 = const()[name = tensor("obj_15_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61979520)))]; + tensor obj_15_epsilon_0_to_fp16 = const()[name = tensor("obj_15_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_15_cast_fp16 = batch_norm(beta = obj_15_beta_0_to_fp16, epsilon = obj_15_epsilon_0_to_fp16, gamma = obj_15_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_7_cast_fp16)[name = tensor("obj_15_cast_fp16")]; + tensor var_328 = const()[name = tensor("op_328"), val = tensor([1, 1])]; + tensor var_330 = const()[name = tensor("op_330"), val = tensor([1, 1])]; + tensor query_5_pad_type_0 = const()[name = tensor("query_5_pad_type_0"), val = tensor("custom")]; + tensor query_5_pad_0 = const()[name = tensor("query_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61980608)))]; + tensor layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62504960)))]; + tensor query_5_cast_fp16 = conv(bias = layers_1_self_attn_q_proj_bias_to_fp16, dilations = var_330, groups = var_293, pad = query_5_pad_0, pad_type = query_5_pad_type_0, strides = var_328, weight = layers_1_self_attn_q_proj_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor("query_5_cast_fp16")]; + tensor var_334 = const()[name = tensor("op_334"), val = tensor([1, 1])]; + tensor var_336 = const()[name = tensor("op_336"), val = tensor([1, 1])]; + tensor current_key_3_pad_type_0 = const()[name = tensor("current_key_3_pad_type_0"), val = tensor("custom")]; + tensor current_key_3_pad_0 = const()[name = tensor("current_key_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62506048)))]; + tensor current_key_3_cast_fp16 = conv(dilations = var_336, groups = var_293, pad = current_key_3_pad_0, pad_type = current_key_3_pad_type_0, strides = var_334, weight = layers_1_self_attn_k_proj_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor("current_key_3_cast_fp16")]; + tensor var_341 = const()[name = tensor("op_341"), val = tensor([1, 1])]; + tensor var_343 = const()[name = tensor("op_343"), val = tensor([1, 1])]; + tensor current_value_3_pad_type_0 = const()[name = tensor("current_value_3_pad_type_0"), val = tensor("custom")]; + tensor current_value_3_pad_0 = const()[name = tensor("current_value_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63030400)))]; + tensor layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63554752)))]; + tensor current_value_3_cast_fp16 = conv(bias = layers_1_self_attn_v_proj_bias_to_fp16, dilations = var_343, groups = var_293, pad = current_value_3_pad_0, pad_type = current_value_3_pad_type_0, strides = var_341, weight = layers_1_self_attn_v_proj_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor("current_value_3_cast_fp16")]; + tensor var_350_cast_fp16 = mul(x = current_key_3_cast_fp16, y = var_134_cast_fp16)[name = tensor("op_350_cast_fp16")]; + tensor var_352_cast_fp16 = mul(x = var_51_cast_fp16_1, y = var_137_cast_fp16)[name = tensor("op_352_cast_fp16")]; + tensor key_5_cast_fp16 = add(x = var_350_cast_fp16, y = var_352_cast_fp16)[name = tensor("key_5_cast_fp16")]; + tensor var_354_cast_fp16 = mul(x = current_value_3_cast_fp16, y = var_134_cast_fp16)[name = tensor("op_354_cast_fp16")]; + tensor var_356_cast_fp16 = mul(x = var_60_cast_fp16_1, y = var_137_cast_fp16)[name = tensor("op_356_cast_fp16")]; + tensor value_5_cast_fp16 = add(x = var_354_cast_fp16, y = var_356_cast_fp16)[name = tensor("value_5_cast_fp16")]; + tensor var_359 = const()[name = tensor("op_359"), val = tensor([1, 8, 64, -1])]; + tensor var_360_cast_fp16 = reshape(shape = var_359, x = query_5_cast_fp16)[name = tensor("op_360_cast_fp16")]; + tensor var_361_to_fp16 = const()[name = tensor("op_361_to_fp16"), val = tensor(0x1p-3)]; + tensor var_362_cast_fp16 = mul(x = var_360_cast_fp16, y = var_361_to_fp16)[name = tensor("op_362_cast_fp16")]; + tensor var_363 = const()[name = tensor("op_363"), val = tensor([1, 8, 64, -1])]; + tensor var_364_cast_fp16 = reshape(shape = var_363, x = key_5_cast_fp16)[name = tensor("op_364_cast_fp16")]; + tensor mh_w_7_transpose_x_0 = const()[name = tensor("mh_w_7_transpose_x_0"), val = tensor(true)]; + tensor mh_w_7_transpose_y_0 = const()[name = tensor("mh_w_7_transpose_y_0"), val = tensor(false)]; + tensor mh_w_7_cast_fp16 = matmul(transpose_x = mh_w_7_transpose_x_0, transpose_y = mh_w_7_transpose_y_0, x = var_362_cast_fp16, y = var_364_cast_fp16)[name = tensor("mh_w_7_cast_fp16")]; + tensor mh_w_9_cast_fp16 = add(x = mh_w_7_cast_fp16, y = var_155_cast_fp16)[name = tensor("mh_w_9_cast_fp16")]; + tensor var_372_cast_fp16 = softmax(axis = var_286, x = mh_w_9_cast_fp16)[name = tensor("op_372_cast_fp16")]; + tensor var_373 = const()[name = tensor("op_373"), val = tensor([1, 8, 64, -1])]; + tensor var_374_cast_fp16 = reshape(shape = var_373, x = value_5_cast_fp16)[name = tensor("op_374_cast_fp16")]; + tensor attn_5_transpose_x_0 = const()[name = tensor("attn_5_transpose_x_0"), val = tensor(false)]; + tensor attn_5_transpose_y_0 = const()[name = tensor("attn_5_transpose_y_0"), val = tensor(true)]; + tensor attn_5_cast_fp16 = matmul(transpose_x = attn_5_transpose_x_0, transpose_y = attn_5_transpose_y_0, x = var_374_cast_fp16, y = var_372_cast_fp16)[name = tensor("attn_5_cast_fp16")]; + tensor var_377 = const()[name = tensor("op_377"), val = tensor([1, 512, 1, -1])]; + tensor input_11_cast_fp16 = reshape(shape = var_377, x = attn_5_cast_fp16)[name = tensor("input_11_cast_fp16")]; + tensor var_381 = const()[name = tensor("op_381"), val = tensor([1, 1])]; + tensor var_383 = const()[name = tensor("op_383"), val = tensor([1, 1])]; + tensor obj_21_pad_type_0 = const()[name = tensor("obj_21_pad_type_0"), val = tensor("custom")]; + tensor obj_21_pad_0 = const()[name = tensor("obj_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63555840)))]; + tensor layers_1_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64080192)))]; + tensor obj_21_cast_fp16 = conv(bias = layers_1_self_attn_o_proj_bias_to_fp16, dilations = var_383, groups = var_293, pad = obj_21_pad_0, pad_type = obj_21_pad_type_0, strides = var_381, weight = layers_1_self_attn_o_proj_weight_to_fp16, x = input_11_cast_fp16)[name = tensor("obj_21_cast_fp16")]; + tensor inputs_9_cast_fp16 = add(x = inputs_7_cast_fp16, y = obj_21_cast_fp16)[name = tensor("inputs_9_cast_fp16")]; + tensor var_393 = const()[name = tensor("op_393"), val = tensor([1])]; + tensor channels_mean_9_cast_fp16 = reduce_mean(axes = var_393, keep_dims = var_294, x = inputs_9_cast_fp16)[name = tensor("channels_mean_9_cast_fp16")]; + tensor zero_mean_9_cast_fp16 = sub(x = inputs_9_cast_fp16, y = channels_mean_9_cast_fp16)[name = tensor("zero_mean_9_cast_fp16")]; + tensor zero_mean_sq_9_cast_fp16 = mul(x = zero_mean_9_cast_fp16, y = zero_mean_9_cast_fp16)[name = tensor("zero_mean_sq_9_cast_fp16")]; + tensor var_397 = const()[name = tensor("op_397"), val = tensor([1])]; + tensor var_398_cast_fp16 = reduce_mean(axes = var_397, keep_dims = var_294, x = zero_mean_sq_9_cast_fp16)[name = tensor("op_398_cast_fp16")]; + tensor var_399_to_fp16 = const()[name = tensor("op_399_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_400_cast_fp16 = add(x = var_398_cast_fp16, y = var_399_to_fp16)[name = tensor("op_400_cast_fp16")]; + tensor denom_9_epsilon_0_to_fp16 = const()[name = tensor("denom_9_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_9_cast_fp16 = rsqrt(epsilon = denom_9_epsilon_0_to_fp16, x = var_400_cast_fp16)[name = tensor("denom_9_cast_fp16")]; + tensor out_9_cast_fp16 = mul(x = zero_mean_9_cast_fp16, y = denom_9_cast_fp16)[name = tensor("out_9_cast_fp16")]; + tensor obj_23_gamma_0_to_fp16 = const()[name = tensor("obj_23_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64081280)))]; + tensor obj_23_beta_0_to_fp16 = const()[name = tensor("obj_23_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64082368)))]; + tensor obj_23_epsilon_0_to_fp16 = const()[name = tensor("obj_23_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_23_cast_fp16 = batch_norm(beta = obj_23_beta_0_to_fp16, epsilon = obj_23_epsilon_0_to_fp16, gamma = obj_23_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_9_cast_fp16)[name = tensor("obj_23_cast_fp16")]; + tensor var_415 = const()[name = tensor("op_415"), val = tensor([1, 1])]; + tensor var_417 = const()[name = tensor("op_417"), val = tensor([1, 1])]; + tensor query_7_pad_type_0 = const()[name = tensor("query_7_pad_type_0"), val = tensor("custom")]; + tensor query_7_pad_0 = const()[name = tensor("query_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64083456)))]; + tensor layers_1_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_1_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64607808)))]; + tensor query_7_cast_fp16 = conv(bias = layers_1_encoder_attn_q_proj_bias_to_fp16, dilations = var_417, groups = var_293, pad = query_7_pad_0, pad_type = query_7_pad_type_0, strides = var_415, weight = layers_1_encoder_attn_q_proj_weight_to_fp16, x = obj_23_cast_fp16)[name = tensor("query_7_cast_fp16")]; + tensor var_421 = const()[name = tensor("op_421"), val = tensor([1, 1])]; + tensor var_423 = const()[name = tensor("op_423"), val = tensor([1, 1])]; + tensor key_7_pad_type_0 = const()[name = tensor("key_7_pad_type_0"), val = tensor("custom")]; + tensor key_7_pad_0 = const()[name = tensor("key_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64608896)))]; + tensor key_7_cast_fp16 = conv(dilations = var_423, groups = var_293, pad = key_7_pad_0, pad_type = key_7_pad_type_0, strides = var_421, weight = layers_1_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_7_cast_fp16")]; + tensor var_428 = const()[name = tensor("op_428"), val = tensor([1, 1])]; + tensor var_430 = const()[name = tensor("op_430"), val = tensor([1, 1])]; + tensor value_7_pad_type_0 = const()[name = tensor("value_7_pad_type_0"), val = tensor("custom")]; + tensor value_7_pad_0 = const()[name = tensor("value_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65133248)))]; + tensor layers_1_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_1_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65657600)))]; + tensor value_7_cast_fp16 = conv(bias = layers_1_encoder_attn_v_proj_bias_to_fp16, dilations = var_430, groups = var_293, pad = value_7_pad_0, pad_type = value_7_pad_type_0, strides = var_428, weight = layers_1_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_7_cast_fp16")]; + tensor var_434 = const()[name = tensor("op_434"), val = tensor([1, 8, 64, -1])]; + tensor var_435_cast_fp16 = reshape(shape = var_434, x = query_7_cast_fp16)[name = tensor("op_435_cast_fp16")]; + tensor var_436_to_fp16 = const()[name = tensor("op_436_to_fp16"), val = tensor(0x1p-3)]; + tensor var_437_cast_fp16 = mul(x = var_435_cast_fp16, y = var_436_to_fp16)[name = tensor("op_437_cast_fp16")]; + tensor var_438 = const()[name = tensor("op_438"), val = tensor([1, 8, 64, -1])]; + tensor var_439_cast_fp16 = reshape(shape = var_438, x = key_7_cast_fp16)[name = tensor("op_439_cast_fp16")]; + tensor mh_w_11_transpose_x_0 = const()[name = tensor("mh_w_11_transpose_x_0"), val = tensor(true)]; + tensor mh_w_11_transpose_y_0 = const()[name = tensor("mh_w_11_transpose_y_0"), val = tensor(false)]; + tensor mh_w_11_cast_fp16 = matmul(transpose_x = mh_w_11_transpose_x_0, transpose_y = mh_w_11_transpose_y_0, x = var_437_cast_fp16, y = var_439_cast_fp16)[name = tensor("mh_w_11_cast_fp16")]; + tensor obj_27_cast_fp16 = softmax(axis = var_286, x = mh_w_11_cast_fp16)[name = tensor("obj_27_cast_fp16")]; + tensor var_443 = const()[name = tensor("op_443"), val = tensor([1, 8, 64, -1])]; + tensor var_444_cast_fp16 = reshape(shape = var_443, x = value_7_cast_fp16)[name = tensor("op_444_cast_fp16")]; + tensor attn_7_transpose_x_0 = const()[name = tensor("attn_7_transpose_x_0"), val = tensor(false)]; + tensor attn_7_transpose_y_0 = const()[name = tensor("attn_7_transpose_y_0"), val = tensor(true)]; + tensor attn_7_cast_fp16 = matmul(transpose_x = attn_7_transpose_x_0, transpose_y = attn_7_transpose_y_0, x = var_444_cast_fp16, y = obj_27_cast_fp16)[name = tensor("attn_7_cast_fp16")]; + tensor var_447 = const()[name = tensor("op_447"), val = tensor([1, 512, 1, -1])]; + tensor input_13_cast_fp16 = reshape(shape = var_447, x = attn_7_cast_fp16)[name = tensor("input_13_cast_fp16")]; + tensor var_451 = const()[name = tensor("op_451"), val = tensor([1, 1])]; + tensor var_453 = const()[name = tensor("op_453"), val = tensor([1, 1])]; + tensor obj_25_pad_type_0 = const()[name = tensor("obj_25_pad_type_0"), val = tensor("custom")]; + tensor obj_25_pad_0 = const()[name = tensor("obj_25_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65658688)))]; + tensor layers_1_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_1_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66183040)))]; + tensor obj_25_cast_fp16 = conv(bias = layers_1_encoder_attn_o_proj_bias_to_fp16, dilations = var_453, groups = var_293, pad = obj_25_pad_0, pad_type = obj_25_pad_type_0, strides = var_451, weight = layers_1_encoder_attn_o_proj_weight_to_fp16, x = input_13_cast_fp16)[name = tensor("obj_25_cast_fp16")]; + tensor inputs_11_cast_fp16 = add(x = inputs_9_cast_fp16, y = obj_25_cast_fp16)[name = tensor("inputs_11_cast_fp16")]; + tensor var_459 = const()[name = tensor("op_459"), val = tensor([1])]; + tensor channels_mean_11_cast_fp16 = reduce_mean(axes = var_459, keep_dims = var_294, x = inputs_11_cast_fp16)[name = tensor("channels_mean_11_cast_fp16")]; + tensor zero_mean_11_cast_fp16 = sub(x = inputs_11_cast_fp16, y = channels_mean_11_cast_fp16)[name = tensor("zero_mean_11_cast_fp16")]; + tensor zero_mean_sq_11_cast_fp16 = mul(x = zero_mean_11_cast_fp16, y = zero_mean_11_cast_fp16)[name = tensor("zero_mean_sq_11_cast_fp16")]; + tensor var_463 = const()[name = tensor("op_463"), val = tensor([1])]; + tensor var_464_cast_fp16 = reduce_mean(axes = var_463, keep_dims = var_294, x = zero_mean_sq_11_cast_fp16)[name = tensor("op_464_cast_fp16")]; + tensor var_465_to_fp16 = const()[name = tensor("op_465_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_466_cast_fp16 = add(x = var_464_cast_fp16, y = var_465_to_fp16)[name = tensor("op_466_cast_fp16")]; + tensor denom_11_epsilon_0_to_fp16 = const()[name = tensor("denom_11_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_11_cast_fp16 = rsqrt(epsilon = denom_11_epsilon_0_to_fp16, x = var_466_cast_fp16)[name = tensor("denom_11_cast_fp16")]; + tensor out_11_cast_fp16 = mul(x = zero_mean_11_cast_fp16, y = denom_11_cast_fp16)[name = tensor("out_11_cast_fp16")]; + tensor input_15_gamma_0_to_fp16 = const()[name = tensor("input_15_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66184128)))]; + tensor input_15_beta_0_to_fp16 = const()[name = tensor("input_15_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66185216)))]; + tensor input_15_epsilon_0_to_fp16 = const()[name = tensor("input_15_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_15_cast_fp16 = batch_norm(beta = input_15_beta_0_to_fp16, epsilon = input_15_epsilon_0_to_fp16, gamma = input_15_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_11_cast_fp16)[name = tensor("input_15_cast_fp16")]; + tensor var_477 = const()[name = tensor("op_477"), val = tensor([1, 1])]; + tensor var_479 = const()[name = tensor("op_479"), val = tensor([1, 1])]; + tensor input_17_pad_type_0 = const()[name = tensor("input_17_pad_type_0"), val = tensor("custom")]; + tensor input_17_pad_0 = const()[name = tensor("input_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_fc1_weight_to_fp16 = const()[name = tensor("layers_1_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66186304)))]; + tensor layers_1_fc1_bias_to_fp16 = const()[name = tensor("layers_1_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(68283520)))]; + tensor input_17_cast_fp16 = conv(bias = layers_1_fc1_bias_to_fp16, dilations = var_479, groups = var_293, pad = input_17_pad_0, pad_type = input_17_pad_type_0, strides = var_477, weight = layers_1_fc1_weight_to_fp16, x = input_15_cast_fp16)[name = tensor("input_17_cast_fp16")]; + tensor input_19_mode_0 = const()[name = tensor("input_19_mode_0"), val = tensor("EXACT")]; + tensor input_19_cast_fp16 = gelu(mode = input_19_mode_0, x = input_17_cast_fp16)[name = tensor("input_19_cast_fp16")]; + tensor var_485 = const()[name = tensor("op_485"), val = tensor([1, 1])]; + tensor var_487 = const()[name = tensor("op_487"), val = tensor([1, 1])]; + tensor hidden_states_5_pad_type_0 = const()[name = tensor("hidden_states_5_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_5_pad_0 = const()[name = tensor("hidden_states_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_fc2_weight_to_fp16 = const()[name = tensor("layers_1_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(68287680)))]; + tensor layers_1_fc2_bias_to_fp16 = const()[name = tensor("layers_1_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70384896)))]; + tensor hidden_states_5_cast_fp16 = conv(bias = layers_1_fc2_bias_to_fp16, dilations = var_487, groups = var_293, pad = hidden_states_5_pad_0, pad_type = hidden_states_5_pad_type_0, strides = var_485, weight = layers_1_fc2_weight_to_fp16, x = input_19_cast_fp16)[name = tensor("hidden_states_5_cast_fp16")]; + tensor inputs_13_cast_fp16 = add(x = inputs_11_cast_fp16, y = hidden_states_5_cast_fp16)[name = tensor("inputs_13_cast_fp16")]; + tensor var_500 = const()[name = tensor("op_500"), val = tensor(3)]; + tensor var_507 = const()[name = tensor("op_507"), val = tensor(1)]; + tensor var_508 = const()[name = tensor("op_508"), val = tensor(true)]; + tensor var_520 = const()[name = tensor("op_520"), val = tensor([1])]; + tensor channels_mean_13_cast_fp16 = reduce_mean(axes = var_520, keep_dims = var_508, x = inputs_13_cast_fp16)[name = tensor("channels_mean_13_cast_fp16")]; + tensor zero_mean_13_cast_fp16 = sub(x = inputs_13_cast_fp16, y = channels_mean_13_cast_fp16)[name = tensor("zero_mean_13_cast_fp16")]; + tensor zero_mean_sq_13_cast_fp16 = mul(x = zero_mean_13_cast_fp16, y = zero_mean_13_cast_fp16)[name = tensor("zero_mean_sq_13_cast_fp16")]; + tensor var_524 = const()[name = tensor("op_524"), val = tensor([1])]; + tensor var_525_cast_fp16 = reduce_mean(axes = var_524, keep_dims = var_508, x = zero_mean_sq_13_cast_fp16)[name = tensor("op_525_cast_fp16")]; + tensor var_526_to_fp16 = const()[name = tensor("op_526_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_527_cast_fp16 = add(x = var_525_cast_fp16, y = var_526_to_fp16)[name = tensor("op_527_cast_fp16")]; + tensor denom_13_epsilon_0_to_fp16 = const()[name = tensor("denom_13_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_13_cast_fp16 = rsqrt(epsilon = denom_13_epsilon_0_to_fp16, x = var_527_cast_fp16)[name = tensor("denom_13_cast_fp16")]; + tensor out_13_cast_fp16 = mul(x = zero_mean_13_cast_fp16, y = denom_13_cast_fp16)[name = tensor("out_13_cast_fp16")]; + tensor obj_29_gamma_0_to_fp16 = const()[name = tensor("obj_29_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70385984)))]; + tensor obj_29_beta_0_to_fp16 = const()[name = tensor("obj_29_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70387072)))]; + tensor obj_29_epsilon_0_to_fp16 = const()[name = tensor("obj_29_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_29_cast_fp16 = batch_norm(beta = obj_29_beta_0_to_fp16, epsilon = obj_29_epsilon_0_to_fp16, gamma = obj_29_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_13_cast_fp16)[name = tensor("obj_29_cast_fp16")]; + tensor var_542 = const()[name = tensor("op_542"), val = tensor([1, 1])]; + tensor var_544 = const()[name = tensor("op_544"), val = tensor([1, 1])]; + tensor query_9_pad_type_0 = const()[name = tensor("query_9_pad_type_0"), val = tensor("custom")]; + tensor query_9_pad_0 = const()[name = tensor("query_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70388160)))]; + tensor layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70912512)))]; + tensor query_9_cast_fp16 = conv(bias = layers_2_self_attn_q_proj_bias_to_fp16, dilations = var_544, groups = var_507, pad = query_9_pad_0, pad_type = query_9_pad_type_0, strides = var_542, weight = layers_2_self_attn_q_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("query_9_cast_fp16")]; + tensor var_548 = const()[name = tensor("op_548"), val = tensor([1, 1])]; + tensor var_550 = const()[name = tensor("op_550"), val = tensor([1, 1])]; + tensor current_key_5_pad_type_0 = const()[name = tensor("current_key_5_pad_type_0"), val = tensor("custom")]; + tensor current_key_5_pad_0 = const()[name = tensor("current_key_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70913600)))]; + tensor current_key_5_cast_fp16 = conv(dilations = var_550, groups = var_507, pad = current_key_5_pad_0, pad_type = current_key_5_pad_type_0, strides = var_548, weight = layers_2_self_attn_k_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("current_key_5_cast_fp16")]; + tensor var_555 = const()[name = tensor("op_555"), val = tensor([1, 1])]; + tensor var_557 = const()[name = tensor("op_557"), val = tensor([1, 1])]; + tensor current_value_5_pad_type_0 = const()[name = tensor("current_value_5_pad_type_0"), val = tensor("custom")]; + tensor current_value_5_pad_0 = const()[name = tensor("current_value_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71437952)))]; + tensor layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71962304)))]; + tensor current_value_5_cast_fp16 = conv(bias = layers_2_self_attn_v_proj_bias_to_fp16, dilations = var_557, groups = var_507, pad = current_value_5_pad_0, pad_type = current_value_5_pad_type_0, strides = var_555, weight = layers_2_self_attn_v_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("current_value_5_cast_fp16")]; + tensor var_564_cast_fp16 = mul(x = current_key_5_cast_fp16, y = var_134_cast_fp16)[name = tensor("op_564_cast_fp16")]; + tensor var_566_cast_fp16 = mul(x = var_51_cast_fp16_2, y = var_137_cast_fp16)[name = tensor("op_566_cast_fp16")]; + tensor key_9_cast_fp16 = add(x = var_564_cast_fp16, y = var_566_cast_fp16)[name = tensor("key_9_cast_fp16")]; + tensor var_568_cast_fp16 = mul(x = current_value_5_cast_fp16, y = var_134_cast_fp16)[name = tensor("op_568_cast_fp16")]; + tensor var_570_cast_fp16 = mul(x = var_60_cast_fp16_2, y = var_137_cast_fp16)[name = tensor("op_570_cast_fp16")]; + tensor value_9_cast_fp16 = add(x = var_568_cast_fp16, y = var_570_cast_fp16)[name = tensor("value_9_cast_fp16")]; + tensor var_573 = const()[name = tensor("op_573"), val = tensor([1, 8, 64, -1])]; + tensor var_574_cast_fp16 = reshape(shape = var_573, x = query_9_cast_fp16)[name = tensor("op_574_cast_fp16")]; + tensor var_575_to_fp16 = const()[name = tensor("op_575_to_fp16"), val = tensor(0x1p-3)]; + tensor var_576_cast_fp16 = mul(x = var_574_cast_fp16, y = var_575_to_fp16)[name = tensor("op_576_cast_fp16")]; + tensor var_577 = const()[name = tensor("op_577"), val = tensor([1, 8, 64, -1])]; + tensor var_578_cast_fp16 = reshape(shape = var_577, x = key_9_cast_fp16)[name = tensor("op_578_cast_fp16")]; + tensor mh_w_13_transpose_x_0 = const()[name = tensor("mh_w_13_transpose_x_0"), val = tensor(true)]; + tensor mh_w_13_transpose_y_0 = const()[name = tensor("mh_w_13_transpose_y_0"), val = tensor(false)]; + tensor mh_w_13_cast_fp16 = matmul(transpose_x = mh_w_13_transpose_x_0, transpose_y = mh_w_13_transpose_y_0, x = var_576_cast_fp16, y = var_578_cast_fp16)[name = tensor("mh_w_13_cast_fp16")]; + tensor mh_w_15_cast_fp16 = add(x = mh_w_13_cast_fp16, y = var_155_cast_fp16)[name = tensor("mh_w_15_cast_fp16")]; + tensor var_586_cast_fp16 = softmax(axis = var_500, x = mh_w_15_cast_fp16)[name = tensor("op_586_cast_fp16")]; + tensor var_587 = const()[name = tensor("op_587"), val = tensor([1, 8, 64, -1])]; + tensor var_588_cast_fp16 = reshape(shape = var_587, x = value_9_cast_fp16)[name = tensor("op_588_cast_fp16")]; + tensor attn_9_transpose_x_0 = const()[name = tensor("attn_9_transpose_x_0"), val = tensor(false)]; + tensor attn_9_transpose_y_0 = const()[name = tensor("attn_9_transpose_y_0"), val = tensor(true)]; + tensor attn_9_cast_fp16 = matmul(transpose_x = attn_9_transpose_x_0, transpose_y = attn_9_transpose_y_0, x = var_588_cast_fp16, y = var_586_cast_fp16)[name = tensor("attn_9_cast_fp16")]; + tensor var_591 = const()[name = tensor("op_591"), val = tensor([1, 512, 1, -1])]; + tensor input_21_cast_fp16 = reshape(shape = var_591, x = attn_9_cast_fp16)[name = tensor("input_21_cast_fp16")]; + tensor var_595 = const()[name = tensor("op_595"), val = tensor([1, 1])]; + tensor var_597 = const()[name = tensor("op_597"), val = tensor([1, 1])]; + tensor obj_35_pad_type_0 = const()[name = tensor("obj_35_pad_type_0"), val = tensor("custom")]; + tensor obj_35_pad_0 = const()[name = tensor("obj_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71963392)))]; + tensor layers_2_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72487744)))]; + tensor obj_35_cast_fp16 = conv(bias = layers_2_self_attn_o_proj_bias_to_fp16, dilations = var_597, groups = var_507, pad = obj_35_pad_0, pad_type = obj_35_pad_type_0, strides = var_595, weight = layers_2_self_attn_o_proj_weight_to_fp16, x = input_21_cast_fp16)[name = tensor("obj_35_cast_fp16")]; + tensor inputs_15_cast_fp16 = add(x = inputs_13_cast_fp16, y = obj_35_cast_fp16)[name = tensor("inputs_15_cast_fp16")]; + tensor var_607 = const()[name = tensor("op_607"), val = tensor([1])]; + tensor channels_mean_15_cast_fp16 = reduce_mean(axes = var_607, keep_dims = var_508, x = inputs_15_cast_fp16)[name = tensor("channels_mean_15_cast_fp16")]; + tensor zero_mean_15_cast_fp16 = sub(x = inputs_15_cast_fp16, y = channels_mean_15_cast_fp16)[name = tensor("zero_mean_15_cast_fp16")]; + tensor zero_mean_sq_15_cast_fp16 = mul(x = zero_mean_15_cast_fp16, y = zero_mean_15_cast_fp16)[name = tensor("zero_mean_sq_15_cast_fp16")]; + tensor var_611 = const()[name = tensor("op_611"), val = tensor([1])]; + tensor var_612_cast_fp16 = reduce_mean(axes = var_611, keep_dims = var_508, x = zero_mean_sq_15_cast_fp16)[name = tensor("op_612_cast_fp16")]; + tensor var_613_to_fp16 = const()[name = tensor("op_613_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_614_cast_fp16 = add(x = var_612_cast_fp16, y = var_613_to_fp16)[name = tensor("op_614_cast_fp16")]; + tensor denom_15_epsilon_0_to_fp16 = const()[name = tensor("denom_15_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_15_cast_fp16 = rsqrt(epsilon = denom_15_epsilon_0_to_fp16, x = var_614_cast_fp16)[name = tensor("denom_15_cast_fp16")]; + tensor out_15_cast_fp16 = mul(x = zero_mean_15_cast_fp16, y = denom_15_cast_fp16)[name = tensor("out_15_cast_fp16")]; + tensor obj_37_gamma_0_to_fp16 = const()[name = tensor("obj_37_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72488832)))]; + tensor obj_37_beta_0_to_fp16 = const()[name = tensor("obj_37_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72489920)))]; + tensor obj_37_epsilon_0_to_fp16 = const()[name = tensor("obj_37_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_37_cast_fp16 = batch_norm(beta = obj_37_beta_0_to_fp16, epsilon = obj_37_epsilon_0_to_fp16, gamma = obj_37_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_15_cast_fp16)[name = tensor("obj_37_cast_fp16")]; + tensor var_629 = const()[name = tensor("op_629"), val = tensor([1, 1])]; + tensor var_631 = const()[name = tensor("op_631"), val = tensor([1, 1])]; + tensor query_11_pad_type_0 = const()[name = tensor("query_11_pad_type_0"), val = tensor("custom")]; + tensor query_11_pad_0 = const()[name = tensor("query_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72491008)))]; + tensor layers_2_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_2_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73015360)))]; + tensor query_11_cast_fp16 = conv(bias = layers_2_encoder_attn_q_proj_bias_to_fp16, dilations = var_631, groups = var_507, pad = query_11_pad_0, pad_type = query_11_pad_type_0, strides = var_629, weight = layers_2_encoder_attn_q_proj_weight_to_fp16, x = obj_37_cast_fp16)[name = tensor("query_11_cast_fp16")]; + tensor var_635 = const()[name = tensor("op_635"), val = tensor([1, 1])]; + tensor var_637 = const()[name = tensor("op_637"), val = tensor([1, 1])]; + tensor key_11_pad_type_0 = const()[name = tensor("key_11_pad_type_0"), val = tensor("custom")]; + tensor key_11_pad_0 = const()[name = tensor("key_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73016448)))]; + tensor key_11_cast_fp16 = conv(dilations = var_637, groups = var_507, pad = key_11_pad_0, pad_type = key_11_pad_type_0, strides = var_635, weight = layers_2_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_11_cast_fp16")]; + tensor var_642 = const()[name = tensor("op_642"), val = tensor([1, 1])]; + tensor var_644 = const()[name = tensor("op_644"), val = tensor([1, 1])]; + tensor value_11_pad_type_0 = const()[name = tensor("value_11_pad_type_0"), val = tensor("custom")]; + tensor value_11_pad_0 = const()[name = tensor("value_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73540800)))]; + tensor layers_2_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_2_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74065152)))]; + tensor value_11_cast_fp16 = conv(bias = layers_2_encoder_attn_v_proj_bias_to_fp16, dilations = var_644, groups = var_507, pad = value_11_pad_0, pad_type = value_11_pad_type_0, strides = var_642, weight = layers_2_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_11_cast_fp16")]; + tensor var_648 = const()[name = tensor("op_648"), val = tensor([1, 8, 64, -1])]; + tensor var_649_cast_fp16 = reshape(shape = var_648, x = query_11_cast_fp16)[name = tensor("op_649_cast_fp16")]; + tensor var_650_to_fp16 = const()[name = tensor("op_650_to_fp16"), val = tensor(0x1p-3)]; + tensor var_651_cast_fp16 = mul(x = var_649_cast_fp16, y = var_650_to_fp16)[name = tensor("op_651_cast_fp16")]; + tensor var_652 = const()[name = tensor("op_652"), val = tensor([1, 8, 64, -1])]; + tensor var_653_cast_fp16 = reshape(shape = var_652, x = key_11_cast_fp16)[name = tensor("op_653_cast_fp16")]; + tensor mh_w_17_transpose_x_0 = const()[name = tensor("mh_w_17_transpose_x_0"), val = tensor(true)]; + tensor mh_w_17_transpose_y_0 = const()[name = tensor("mh_w_17_transpose_y_0"), val = tensor(false)]; + tensor mh_w_17_cast_fp16 = matmul(transpose_x = mh_w_17_transpose_x_0, transpose_y = mh_w_17_transpose_y_0, x = var_651_cast_fp16, y = var_653_cast_fp16)[name = tensor("mh_w_17_cast_fp16")]; + tensor obj_41_cast_fp16 = softmax(axis = var_500, x = mh_w_17_cast_fp16)[name = tensor("obj_41_cast_fp16")]; + tensor var_657 = const()[name = tensor("op_657"), val = tensor([1, 8, 64, -1])]; + tensor var_658_cast_fp16 = reshape(shape = var_657, x = value_11_cast_fp16)[name = tensor("op_658_cast_fp16")]; + tensor attn_11_transpose_x_0 = const()[name = tensor("attn_11_transpose_x_0"), val = tensor(false)]; + tensor attn_11_transpose_y_0 = const()[name = tensor("attn_11_transpose_y_0"), val = tensor(true)]; + tensor attn_11_cast_fp16 = matmul(transpose_x = attn_11_transpose_x_0, transpose_y = attn_11_transpose_y_0, x = var_658_cast_fp16, y = obj_41_cast_fp16)[name = tensor("attn_11_cast_fp16")]; + tensor var_661 = const()[name = tensor("op_661"), val = tensor([1, 512, 1, -1])]; + tensor input_23_cast_fp16 = reshape(shape = var_661, x = attn_11_cast_fp16)[name = tensor("input_23_cast_fp16")]; + tensor var_665 = const()[name = tensor("op_665"), val = tensor([1, 1])]; + tensor var_667 = const()[name = tensor("op_667"), val = tensor([1, 1])]; + tensor obj_39_pad_type_0 = const()[name = tensor("obj_39_pad_type_0"), val = tensor("custom")]; + tensor obj_39_pad_0 = const()[name = tensor("obj_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74066240)))]; + tensor layers_2_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_2_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74590592)))]; + tensor obj_39_cast_fp16 = conv(bias = layers_2_encoder_attn_o_proj_bias_to_fp16, dilations = var_667, groups = var_507, pad = obj_39_pad_0, pad_type = obj_39_pad_type_0, strides = var_665, weight = layers_2_encoder_attn_o_proj_weight_to_fp16, x = input_23_cast_fp16)[name = tensor("obj_39_cast_fp16")]; + tensor inputs_17_cast_fp16 = add(x = inputs_15_cast_fp16, y = obj_39_cast_fp16)[name = tensor("inputs_17_cast_fp16")]; + tensor var_673 = const()[name = tensor("op_673"), val = tensor([1])]; + tensor channels_mean_17_cast_fp16 = reduce_mean(axes = var_673, keep_dims = var_508, x = inputs_17_cast_fp16)[name = tensor("channels_mean_17_cast_fp16")]; + tensor zero_mean_17_cast_fp16 = sub(x = inputs_17_cast_fp16, y = channels_mean_17_cast_fp16)[name = tensor("zero_mean_17_cast_fp16")]; + tensor zero_mean_sq_17_cast_fp16 = mul(x = zero_mean_17_cast_fp16, y = zero_mean_17_cast_fp16)[name = tensor("zero_mean_sq_17_cast_fp16")]; + tensor var_677 = const()[name = tensor("op_677"), val = tensor([1])]; + tensor var_678_cast_fp16 = reduce_mean(axes = var_677, keep_dims = var_508, x = zero_mean_sq_17_cast_fp16)[name = tensor("op_678_cast_fp16")]; + tensor var_679_to_fp16 = const()[name = tensor("op_679_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_680_cast_fp16 = add(x = var_678_cast_fp16, y = var_679_to_fp16)[name = tensor("op_680_cast_fp16")]; + tensor denom_17_epsilon_0_to_fp16 = const()[name = tensor("denom_17_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_17_cast_fp16 = rsqrt(epsilon = denom_17_epsilon_0_to_fp16, x = var_680_cast_fp16)[name = tensor("denom_17_cast_fp16")]; + tensor out_17_cast_fp16 = mul(x = zero_mean_17_cast_fp16, y = denom_17_cast_fp16)[name = tensor("out_17_cast_fp16")]; + tensor input_25_gamma_0_to_fp16 = const()[name = tensor("input_25_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74591680)))]; + tensor input_25_beta_0_to_fp16 = const()[name = tensor("input_25_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74592768)))]; + tensor input_25_epsilon_0_to_fp16 = const()[name = tensor("input_25_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_25_cast_fp16 = batch_norm(beta = input_25_beta_0_to_fp16, epsilon = input_25_epsilon_0_to_fp16, gamma = input_25_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_17_cast_fp16)[name = tensor("input_25_cast_fp16")]; + tensor var_691 = const()[name = tensor("op_691"), val = tensor([1, 1])]; + tensor var_693 = const()[name = tensor("op_693"), val = tensor([1, 1])]; + tensor input_27_pad_type_0 = const()[name = tensor("input_27_pad_type_0"), val = tensor("custom")]; + tensor input_27_pad_0 = const()[name = tensor("input_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_fc1_weight_to_fp16 = const()[name = tensor("layers_2_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74593856)))]; + tensor layers_2_fc1_bias_to_fp16 = const()[name = tensor("layers_2_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76691072)))]; + tensor input_27_cast_fp16 = conv(bias = layers_2_fc1_bias_to_fp16, dilations = var_693, groups = var_507, pad = input_27_pad_0, pad_type = input_27_pad_type_0, strides = var_691, weight = layers_2_fc1_weight_to_fp16, x = input_25_cast_fp16)[name = tensor("input_27_cast_fp16")]; + tensor input_29_mode_0 = const()[name = tensor("input_29_mode_0"), val = tensor("EXACT")]; + tensor input_29_cast_fp16 = gelu(mode = input_29_mode_0, x = input_27_cast_fp16)[name = tensor("input_29_cast_fp16")]; + tensor var_699 = const()[name = tensor("op_699"), val = tensor([1, 1])]; + tensor var_701 = const()[name = tensor("op_701"), val = tensor([1, 1])]; + tensor hidden_states_7_pad_type_0 = const()[name = tensor("hidden_states_7_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_7_pad_0 = const()[name = tensor("hidden_states_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_fc2_weight_to_fp16 = const()[name = tensor("layers_2_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76695232)))]; + tensor layers_2_fc2_bias_to_fp16 = const()[name = tensor("layers_2_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78792448)))]; + tensor hidden_states_7_cast_fp16 = conv(bias = layers_2_fc2_bias_to_fp16, dilations = var_701, groups = var_507, pad = hidden_states_7_pad_0, pad_type = hidden_states_7_pad_type_0, strides = var_699, weight = layers_2_fc2_weight_to_fp16, x = input_29_cast_fp16)[name = tensor("hidden_states_7_cast_fp16")]; + tensor inputs_19_cast_fp16 = add(x = inputs_17_cast_fp16, y = hidden_states_7_cast_fp16)[name = tensor("inputs_19_cast_fp16")]; + tensor var_714 = const()[name = tensor("op_714"), val = tensor(3)]; + tensor var_721 = const()[name = tensor("op_721"), val = tensor(1)]; + tensor var_722 = const()[name = tensor("op_722"), val = tensor(true)]; + tensor var_734 = const()[name = tensor("op_734"), val = tensor([1])]; + tensor channels_mean_19_cast_fp16 = reduce_mean(axes = var_734, keep_dims = var_722, x = inputs_19_cast_fp16)[name = tensor("channels_mean_19_cast_fp16")]; + tensor zero_mean_19_cast_fp16 = sub(x = inputs_19_cast_fp16, y = channels_mean_19_cast_fp16)[name = tensor("zero_mean_19_cast_fp16")]; + tensor zero_mean_sq_19_cast_fp16 = mul(x = zero_mean_19_cast_fp16, y = zero_mean_19_cast_fp16)[name = tensor("zero_mean_sq_19_cast_fp16")]; + tensor var_738 = const()[name = tensor("op_738"), val = tensor([1])]; + tensor var_739_cast_fp16 = reduce_mean(axes = var_738, keep_dims = var_722, x = zero_mean_sq_19_cast_fp16)[name = tensor("op_739_cast_fp16")]; + tensor var_740_to_fp16 = const()[name = tensor("op_740_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_741_cast_fp16 = add(x = var_739_cast_fp16, y = var_740_to_fp16)[name = tensor("op_741_cast_fp16")]; + tensor denom_19_epsilon_0_to_fp16 = const()[name = tensor("denom_19_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_19_cast_fp16 = rsqrt(epsilon = denom_19_epsilon_0_to_fp16, x = var_741_cast_fp16)[name = tensor("denom_19_cast_fp16")]; + tensor out_19_cast_fp16 = mul(x = zero_mean_19_cast_fp16, y = denom_19_cast_fp16)[name = tensor("out_19_cast_fp16")]; + tensor obj_43_gamma_0_to_fp16 = const()[name = tensor("obj_43_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78793536)))]; + tensor obj_43_beta_0_to_fp16 = const()[name = tensor("obj_43_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78794624)))]; + tensor obj_43_epsilon_0_to_fp16 = const()[name = tensor("obj_43_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_43_cast_fp16 = batch_norm(beta = obj_43_beta_0_to_fp16, epsilon = obj_43_epsilon_0_to_fp16, gamma = obj_43_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_19_cast_fp16)[name = tensor("obj_43_cast_fp16")]; + tensor var_756 = const()[name = tensor("op_756"), val = tensor([1, 1])]; + tensor var_758 = const()[name = tensor("op_758"), val = tensor([1, 1])]; + tensor query_13_pad_type_0 = const()[name = tensor("query_13_pad_type_0"), val = tensor("custom")]; + tensor query_13_pad_0 = const()[name = tensor("query_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78795712)))]; + tensor layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79320064)))]; + tensor query_13_cast_fp16 = conv(bias = layers_3_self_attn_q_proj_bias_to_fp16, dilations = var_758, groups = var_721, pad = query_13_pad_0, pad_type = query_13_pad_type_0, strides = var_756, weight = layers_3_self_attn_q_proj_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor("query_13_cast_fp16")]; + tensor var_762 = const()[name = tensor("op_762"), val = tensor([1, 1])]; + tensor var_764 = const()[name = tensor("op_764"), val = tensor([1, 1])]; + tensor current_key_7_pad_type_0 = const()[name = tensor("current_key_7_pad_type_0"), val = tensor("custom")]; + tensor current_key_7_pad_0 = const()[name = tensor("current_key_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79321152)))]; + tensor current_key_7_cast_fp16 = conv(dilations = var_764, groups = var_721, pad = current_key_7_pad_0, pad_type = current_key_7_pad_type_0, strides = var_762, weight = layers_3_self_attn_k_proj_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor("current_key_7_cast_fp16")]; + tensor var_769 = const()[name = tensor("op_769"), val = tensor([1, 1])]; + tensor var_771 = const()[name = tensor("op_771"), val = tensor([1, 1])]; + tensor current_value_7_pad_type_0 = const()[name = tensor("current_value_7_pad_type_0"), val = tensor("custom")]; + tensor current_value_7_pad_0 = const()[name = tensor("current_value_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79845504)))]; + tensor layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80369856)))]; + tensor current_value_7_cast_fp16 = conv(bias = layers_3_self_attn_v_proj_bias_to_fp16, dilations = var_771, groups = var_721, pad = current_value_7_pad_0, pad_type = current_value_7_pad_type_0, strides = var_769, weight = layers_3_self_attn_v_proj_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor("current_value_7_cast_fp16")]; + tensor var_778_cast_fp16 = mul(x = current_key_7_cast_fp16, y = var_134_cast_fp16)[name = tensor("op_778_cast_fp16")]; + tensor var_780_cast_fp16 = mul(x = var_51_cast_fp16_3, y = var_137_cast_fp16)[name = tensor("op_780_cast_fp16")]; + tensor key_13_cast_fp16 = add(x = var_778_cast_fp16, y = var_780_cast_fp16)[name = tensor("key_13_cast_fp16")]; + tensor var_782_cast_fp16 = mul(x = current_value_7_cast_fp16, y = var_134_cast_fp16)[name = tensor("op_782_cast_fp16")]; + tensor var_784_cast_fp16 = mul(x = var_60_cast_fp16_3, y = var_137_cast_fp16)[name = tensor("op_784_cast_fp16")]; + tensor value_13_cast_fp16 = add(x = var_782_cast_fp16, y = var_784_cast_fp16)[name = tensor("value_13_cast_fp16")]; + tensor var_787 = const()[name = tensor("op_787"), val = tensor([1, 8, 64, -1])]; + tensor var_788_cast_fp16 = reshape(shape = var_787, x = query_13_cast_fp16)[name = tensor("op_788_cast_fp16")]; + tensor var_789_to_fp16 = const()[name = tensor("op_789_to_fp16"), val = tensor(0x1p-3)]; + tensor var_790_cast_fp16 = mul(x = var_788_cast_fp16, y = var_789_to_fp16)[name = tensor("op_790_cast_fp16")]; + tensor var_791 = const()[name = tensor("op_791"), val = tensor([1, 8, 64, -1])]; + tensor var_792_cast_fp16 = reshape(shape = var_791, x = key_13_cast_fp16)[name = tensor("op_792_cast_fp16")]; + tensor mh_w_19_transpose_x_0 = const()[name = tensor("mh_w_19_transpose_x_0"), val = tensor(true)]; + tensor mh_w_19_transpose_y_0 = const()[name = tensor("mh_w_19_transpose_y_0"), val = tensor(false)]; + tensor mh_w_19_cast_fp16 = matmul(transpose_x = mh_w_19_transpose_x_0, transpose_y = mh_w_19_transpose_y_0, x = var_790_cast_fp16, y = var_792_cast_fp16)[name = tensor("mh_w_19_cast_fp16")]; + tensor mh_w_21_cast_fp16 = add(x = mh_w_19_cast_fp16, y = var_155_cast_fp16)[name = tensor("mh_w_21_cast_fp16")]; + tensor var_800_cast_fp16 = softmax(axis = var_714, x = mh_w_21_cast_fp16)[name = tensor("op_800_cast_fp16")]; + tensor var_801 = const()[name = tensor("op_801"), val = tensor([1, 8, 64, -1])]; + tensor var_802_cast_fp16 = reshape(shape = var_801, x = value_13_cast_fp16)[name = tensor("op_802_cast_fp16")]; + tensor attn_13_transpose_x_0 = const()[name = tensor("attn_13_transpose_x_0"), val = tensor(false)]; + tensor attn_13_transpose_y_0 = const()[name = tensor("attn_13_transpose_y_0"), val = tensor(true)]; + tensor attn_13_cast_fp16 = matmul(transpose_x = attn_13_transpose_x_0, transpose_y = attn_13_transpose_y_0, x = var_802_cast_fp16, y = var_800_cast_fp16)[name = tensor("attn_13_cast_fp16")]; + tensor var_805 = const()[name = tensor("op_805"), val = tensor([1, 512, 1, -1])]; + tensor input_31_cast_fp16 = reshape(shape = var_805, x = attn_13_cast_fp16)[name = tensor("input_31_cast_fp16")]; + tensor var_809 = const()[name = tensor("op_809"), val = tensor([1, 1])]; + tensor var_811 = const()[name = tensor("op_811"), val = tensor([1, 1])]; + tensor obj_49_pad_type_0 = const()[name = tensor("obj_49_pad_type_0"), val = tensor("custom")]; + tensor obj_49_pad_0 = const()[name = tensor("obj_49_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80370944)))]; + tensor layers_3_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80895296)))]; + tensor obj_49_cast_fp16 = conv(bias = layers_3_self_attn_o_proj_bias_to_fp16, dilations = var_811, groups = var_721, pad = obj_49_pad_0, pad_type = obj_49_pad_type_0, strides = var_809, weight = layers_3_self_attn_o_proj_weight_to_fp16, x = input_31_cast_fp16)[name = tensor("obj_49_cast_fp16")]; + tensor inputs_21_cast_fp16 = add(x = inputs_19_cast_fp16, y = obj_49_cast_fp16)[name = tensor("inputs_21_cast_fp16")]; + tensor var_821 = const()[name = tensor("op_821"), val = tensor([1])]; + tensor channels_mean_21_cast_fp16 = reduce_mean(axes = var_821, keep_dims = var_722, x = inputs_21_cast_fp16)[name = tensor("channels_mean_21_cast_fp16")]; + tensor zero_mean_21_cast_fp16 = sub(x = inputs_21_cast_fp16, y = channels_mean_21_cast_fp16)[name = tensor("zero_mean_21_cast_fp16")]; + tensor zero_mean_sq_21_cast_fp16 = mul(x = zero_mean_21_cast_fp16, y = zero_mean_21_cast_fp16)[name = tensor("zero_mean_sq_21_cast_fp16")]; + tensor var_825 = const()[name = tensor("op_825"), val = tensor([1])]; + tensor var_826_cast_fp16 = reduce_mean(axes = var_825, keep_dims = var_722, x = zero_mean_sq_21_cast_fp16)[name = tensor("op_826_cast_fp16")]; + tensor var_827_to_fp16 = const()[name = tensor("op_827_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_828_cast_fp16 = add(x = var_826_cast_fp16, y = var_827_to_fp16)[name = tensor("op_828_cast_fp16")]; + tensor denom_21_epsilon_0_to_fp16 = const()[name = tensor("denom_21_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_21_cast_fp16 = rsqrt(epsilon = denom_21_epsilon_0_to_fp16, x = var_828_cast_fp16)[name = tensor("denom_21_cast_fp16")]; + tensor out_21_cast_fp16 = mul(x = zero_mean_21_cast_fp16, y = denom_21_cast_fp16)[name = tensor("out_21_cast_fp16")]; + tensor obj_51_gamma_0_to_fp16 = const()[name = tensor("obj_51_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80896384)))]; + tensor obj_51_beta_0_to_fp16 = const()[name = tensor("obj_51_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80897472)))]; + tensor obj_51_epsilon_0_to_fp16 = const()[name = tensor("obj_51_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_51_cast_fp16 = batch_norm(beta = obj_51_beta_0_to_fp16, epsilon = obj_51_epsilon_0_to_fp16, gamma = obj_51_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_21_cast_fp16)[name = tensor("obj_51_cast_fp16")]; + tensor var_843 = const()[name = tensor("op_843"), val = tensor([1, 1])]; + tensor var_845 = const()[name = tensor("op_845"), val = tensor([1, 1])]; + tensor query_15_pad_type_0 = const()[name = tensor("query_15_pad_type_0"), val = tensor("custom")]; + tensor query_15_pad_0 = const()[name = tensor("query_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80898560)))]; + tensor layers_3_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_3_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81422912)))]; + tensor query_15_cast_fp16 = conv(bias = layers_3_encoder_attn_q_proj_bias_to_fp16, dilations = var_845, groups = var_721, pad = query_15_pad_0, pad_type = query_15_pad_type_0, strides = var_843, weight = layers_3_encoder_attn_q_proj_weight_to_fp16, x = obj_51_cast_fp16)[name = tensor("query_15_cast_fp16")]; + tensor var_849 = const()[name = tensor("op_849"), val = tensor([1, 1])]; + tensor var_851 = const()[name = tensor("op_851"), val = tensor([1, 1])]; + tensor key_15_pad_type_0 = const()[name = tensor("key_15_pad_type_0"), val = tensor("custom")]; + tensor key_15_pad_0 = const()[name = tensor("key_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81424000)))]; + tensor key_15_cast_fp16 = conv(dilations = var_851, groups = var_721, pad = key_15_pad_0, pad_type = key_15_pad_type_0, strides = var_849, weight = layers_3_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_15_cast_fp16")]; + tensor var_856 = const()[name = tensor("op_856"), val = tensor([1, 1])]; + tensor var_858 = const()[name = tensor("op_858"), val = tensor([1, 1])]; + tensor value_15_pad_type_0 = const()[name = tensor("value_15_pad_type_0"), val = tensor("custom")]; + tensor value_15_pad_0 = const()[name = tensor("value_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81948352)))]; + tensor layers_3_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_3_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82472704)))]; + tensor value_15_cast_fp16 = conv(bias = layers_3_encoder_attn_v_proj_bias_to_fp16, dilations = var_858, groups = var_721, pad = value_15_pad_0, pad_type = value_15_pad_type_0, strides = var_856, weight = layers_3_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_15_cast_fp16")]; + tensor var_862 = const()[name = tensor("op_862"), val = tensor([1, 8, 64, -1])]; + tensor var_863_cast_fp16 = reshape(shape = var_862, x = query_15_cast_fp16)[name = tensor("op_863_cast_fp16")]; + tensor var_864_to_fp16 = const()[name = tensor("op_864_to_fp16"), val = tensor(0x1p-3)]; + tensor var_865_cast_fp16 = mul(x = var_863_cast_fp16, y = var_864_to_fp16)[name = tensor("op_865_cast_fp16")]; + tensor var_866 = const()[name = tensor("op_866"), val = tensor([1, 8, 64, -1])]; + tensor var_867_cast_fp16 = reshape(shape = var_866, x = key_15_cast_fp16)[name = tensor("op_867_cast_fp16")]; + tensor mh_w_23_transpose_x_0 = const()[name = tensor("mh_w_23_transpose_x_0"), val = tensor(true)]; + tensor mh_w_23_transpose_y_0 = const()[name = tensor("mh_w_23_transpose_y_0"), val = tensor(false)]; + tensor mh_w_23_cast_fp16 = matmul(transpose_x = mh_w_23_transpose_x_0, transpose_y = mh_w_23_transpose_y_0, x = var_865_cast_fp16, y = var_867_cast_fp16)[name = tensor("mh_w_23_cast_fp16")]; + tensor obj_55_cast_fp16 = softmax(axis = var_714, x = mh_w_23_cast_fp16)[name = tensor("obj_55_cast_fp16")]; + tensor var_871 = const()[name = tensor("op_871"), val = tensor([1, 8, 64, -1])]; + tensor var_872_cast_fp16 = reshape(shape = var_871, x = value_15_cast_fp16)[name = tensor("op_872_cast_fp16")]; + tensor attn_15_transpose_x_0 = const()[name = tensor("attn_15_transpose_x_0"), val = tensor(false)]; + tensor attn_15_transpose_y_0 = const()[name = tensor("attn_15_transpose_y_0"), val = tensor(true)]; + tensor attn_15_cast_fp16 = matmul(transpose_x = attn_15_transpose_x_0, transpose_y = attn_15_transpose_y_0, x = var_872_cast_fp16, y = obj_55_cast_fp16)[name = tensor("attn_15_cast_fp16")]; + tensor var_875 = const()[name = tensor("op_875"), val = tensor([1, 512, 1, -1])]; + tensor input_33_cast_fp16 = reshape(shape = var_875, x = attn_15_cast_fp16)[name = tensor("input_33_cast_fp16")]; + tensor var_879 = const()[name = tensor("op_879"), val = tensor([1, 1])]; + tensor var_881 = const()[name = tensor("op_881"), val = tensor([1, 1])]; + tensor obj_53_pad_type_0 = const()[name = tensor("obj_53_pad_type_0"), val = tensor("custom")]; + tensor obj_53_pad_0 = const()[name = tensor("obj_53_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82473792)))]; + tensor layers_3_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_3_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82998144)))]; + tensor obj_53_cast_fp16 = conv(bias = layers_3_encoder_attn_o_proj_bias_to_fp16, dilations = var_881, groups = var_721, pad = obj_53_pad_0, pad_type = obj_53_pad_type_0, strides = var_879, weight = layers_3_encoder_attn_o_proj_weight_to_fp16, x = input_33_cast_fp16)[name = tensor("obj_53_cast_fp16")]; + tensor inputs_23_cast_fp16 = add(x = inputs_21_cast_fp16, y = obj_53_cast_fp16)[name = tensor("inputs_23_cast_fp16")]; + tensor var_890 = const()[name = tensor("op_890"), val = tensor([1])]; + tensor channels_mean_23_cast_fp16 = reduce_mean(axes = var_890, keep_dims = var_722, x = inputs_23_cast_fp16)[name = tensor("channels_mean_23_cast_fp16")]; + tensor zero_mean_23_cast_fp16 = sub(x = inputs_23_cast_fp16, y = channels_mean_23_cast_fp16)[name = tensor("zero_mean_23_cast_fp16")]; + tensor zero_mean_sq_23_cast_fp16 = mul(x = zero_mean_23_cast_fp16, y = zero_mean_23_cast_fp16)[name = tensor("zero_mean_sq_23_cast_fp16")]; + tensor var_894 = const()[name = tensor("op_894"), val = tensor([1])]; + tensor var_895_cast_fp16 = reduce_mean(axes = var_894, keep_dims = var_722, x = zero_mean_sq_23_cast_fp16)[name = tensor("op_895_cast_fp16")]; + tensor var_896_to_fp16 = const()[name = tensor("op_896_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_897_cast_fp16 = add(x = var_895_cast_fp16, y = var_896_to_fp16)[name = tensor("op_897_cast_fp16")]; + tensor denom_23_epsilon_0_to_fp16 = const()[name = tensor("denom_23_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_23_cast_fp16 = rsqrt(epsilon = denom_23_epsilon_0_to_fp16, x = var_897_cast_fp16)[name = tensor("denom_23_cast_fp16")]; + tensor out_23_cast_fp16 = mul(x = zero_mean_23_cast_fp16, y = denom_23_cast_fp16)[name = tensor("out_23_cast_fp16")]; + tensor input_35_gamma_0_to_fp16 = const()[name = tensor("input_35_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82999232)))]; + tensor input_35_beta_0_to_fp16 = const()[name = tensor("input_35_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83000320)))]; + tensor input_35_epsilon_0_to_fp16 = const()[name = tensor("input_35_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_35_cast_fp16 = batch_norm(beta = input_35_beta_0_to_fp16, epsilon = input_35_epsilon_0_to_fp16, gamma = input_35_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_23_cast_fp16)[name = tensor("input_35_cast_fp16")]; + tensor var_908 = const()[name = tensor("op_908"), val = tensor([1, 1])]; + tensor var_910 = const()[name = tensor("op_910"), val = tensor([1, 1])]; + tensor input_37_pad_type_0 = const()[name = tensor("input_37_pad_type_0"), val = tensor("custom")]; + tensor input_37_pad_0 = const()[name = tensor("input_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_fc1_weight_to_fp16 = const()[name = tensor("layers_3_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83001408)))]; + tensor layers_3_fc1_bias_to_fp16 = const()[name = tensor("layers_3_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85098624)))]; + tensor input_37_cast_fp16 = conv(bias = layers_3_fc1_bias_to_fp16, dilations = var_910, groups = var_721, pad = input_37_pad_0, pad_type = input_37_pad_type_0, strides = var_908, weight = layers_3_fc1_weight_to_fp16, x = input_35_cast_fp16)[name = tensor("input_37_cast_fp16")]; + tensor input_39_mode_0 = const()[name = tensor("input_39_mode_0"), val = tensor("EXACT")]; + tensor input_39_cast_fp16 = gelu(mode = input_39_mode_0, x = input_37_cast_fp16)[name = tensor("input_39_cast_fp16")]; + tensor var_916 = const()[name = tensor("op_916"), val = tensor([1, 1])]; + tensor var_918 = const()[name = tensor("op_918"), val = tensor([1, 1])]; + tensor hidden_states_9_pad_type_0 = const()[name = tensor("hidden_states_9_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_9_pad_0 = const()[name = tensor("hidden_states_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_fc2_weight_to_fp16 = const()[name = tensor("layers_3_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85102784)))]; + tensor layers_3_fc2_bias_to_fp16 = const()[name = tensor("layers_3_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87200000)))]; + tensor hidden_states_9_cast_fp16 = conv(bias = layers_3_fc2_bias_to_fp16, dilations = var_918, groups = var_721, pad = hidden_states_9_pad_0, pad_type = hidden_states_9_pad_type_0, strides = var_916, weight = layers_3_fc2_weight_to_fp16, x = input_39_cast_fp16)[name = tensor("hidden_states_9_cast_fp16")]; + tensor inputs_25_cast_fp16 = add(x = inputs_23_cast_fp16, y = hidden_states_9_cast_fp16)[name = tensor("inputs_25_cast_fp16")]; + tensor var_932 = const()[name = tensor("op_932"), val = tensor(3)]; + tensor var_939 = const()[name = tensor("op_939"), val = tensor(1)]; + tensor var_940 = const()[name = tensor("op_940"), val = tensor(true)]; + tensor var_952 = const()[name = tensor("op_952"), val = tensor([1])]; + tensor channels_mean_25_cast_fp16 = reduce_mean(axes = var_952, keep_dims = var_940, x = inputs_25_cast_fp16)[name = tensor("channels_mean_25_cast_fp16")]; + tensor zero_mean_25_cast_fp16 = sub(x = inputs_25_cast_fp16, y = channels_mean_25_cast_fp16)[name = tensor("zero_mean_25_cast_fp16")]; + tensor zero_mean_sq_25_cast_fp16 = mul(x = zero_mean_25_cast_fp16, y = zero_mean_25_cast_fp16)[name = tensor("zero_mean_sq_25_cast_fp16")]; + tensor var_956 = const()[name = tensor("op_956"), val = tensor([1])]; + tensor var_957_cast_fp16 = reduce_mean(axes = var_956, keep_dims = var_940, x = zero_mean_sq_25_cast_fp16)[name = tensor("op_957_cast_fp16")]; + tensor var_958_to_fp16 = const()[name = tensor("op_958_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_959_cast_fp16 = add(x = var_957_cast_fp16, y = var_958_to_fp16)[name = tensor("op_959_cast_fp16")]; + tensor denom_25_epsilon_0_to_fp16 = const()[name = tensor("denom_25_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_25_cast_fp16 = rsqrt(epsilon = denom_25_epsilon_0_to_fp16, x = var_959_cast_fp16)[name = tensor("denom_25_cast_fp16")]; + tensor out_25_cast_fp16 = mul(x = zero_mean_25_cast_fp16, y = denom_25_cast_fp16)[name = tensor("out_25_cast_fp16")]; + tensor obj_57_gamma_0_to_fp16 = const()[name = tensor("obj_57_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87201088)))]; + tensor obj_57_beta_0_to_fp16 = const()[name = tensor("obj_57_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87202176)))]; + tensor obj_57_epsilon_0_to_fp16 = const()[name = tensor("obj_57_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_57_cast_fp16 = batch_norm(beta = obj_57_beta_0_to_fp16, epsilon = obj_57_epsilon_0_to_fp16, gamma = obj_57_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_25_cast_fp16)[name = tensor("obj_57_cast_fp16")]; + tensor var_974 = const()[name = tensor("op_974"), val = tensor([1, 1])]; + tensor var_976 = const()[name = tensor("op_976"), val = tensor([1, 1])]; + tensor query_17_pad_type_0 = const()[name = tensor("query_17_pad_type_0"), val = tensor("custom")]; + tensor query_17_pad_0 = const()[name = tensor("query_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87203264)))]; + tensor layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87727616)))]; + tensor query_17_cast_fp16 = conv(bias = layers_4_self_attn_q_proj_bias_to_fp16, dilations = var_976, groups = var_939, pad = query_17_pad_0, pad_type = query_17_pad_type_0, strides = var_974, weight = layers_4_self_attn_q_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("query_17_cast_fp16")]; + tensor var_980 = const()[name = tensor("op_980"), val = tensor([1, 1])]; + tensor var_982 = const()[name = tensor("op_982"), val = tensor([1, 1])]; + tensor current_key_9_pad_type_0 = const()[name = tensor("current_key_9_pad_type_0"), val = tensor("custom")]; + tensor current_key_9_pad_0 = const()[name = tensor("current_key_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87728704)))]; + tensor current_key_9_cast_fp16 = conv(dilations = var_982, groups = var_939, pad = current_key_9_pad_0, pad_type = current_key_9_pad_type_0, strides = var_980, weight = layers_4_self_attn_k_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("current_key_9_cast_fp16")]; + tensor var_987 = const()[name = tensor("op_987"), val = tensor([1, 1])]; + tensor var_989 = const()[name = tensor("op_989"), val = tensor([1, 1])]; + tensor current_value_9_pad_type_0 = const()[name = tensor("current_value_9_pad_type_0"), val = tensor("custom")]; + tensor current_value_9_pad_0 = const()[name = tensor("current_value_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88253056)))]; + tensor layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88777408)))]; + tensor current_value_9_cast_fp16 = conv(bias = layers_4_self_attn_v_proj_bias_to_fp16, dilations = var_989, groups = var_939, pad = current_value_9_pad_0, pad_type = current_value_9_pad_type_0, strides = var_987, weight = layers_4_self_attn_v_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("current_value_9_cast_fp16")]; + tensor var_996_cast_fp16 = mul(x = current_key_9_cast_fp16, y = var_134_cast_fp16)[name = tensor("op_996_cast_fp16")]; + tensor var_998_cast_fp16 = mul(x = var_51_cast_fp16_4, y = var_137_cast_fp16)[name = tensor("op_998_cast_fp16")]; + tensor key_17_cast_fp16 = add(x = var_996_cast_fp16, y = var_998_cast_fp16)[name = tensor("key_17_cast_fp16")]; + tensor var_1000_cast_fp16 = mul(x = current_value_9_cast_fp16, y = var_134_cast_fp16)[name = tensor("op_1000_cast_fp16")]; + tensor var_1002_cast_fp16 = mul(x = var_60_cast_fp16_4, y = var_137_cast_fp16)[name = tensor("op_1002_cast_fp16")]; + tensor value_17_cast_fp16 = add(x = var_1000_cast_fp16, y = var_1002_cast_fp16)[name = tensor("value_17_cast_fp16")]; + tensor var_1005 = const()[name = tensor("op_1005"), val = tensor([1, 8, 64, -1])]; + tensor var_1006_cast_fp16 = reshape(shape = var_1005, x = query_17_cast_fp16)[name = tensor("op_1006_cast_fp16")]; + tensor var_1007_to_fp16 = const()[name = tensor("op_1007_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1008_cast_fp16 = mul(x = var_1006_cast_fp16, y = var_1007_to_fp16)[name = tensor("op_1008_cast_fp16")]; + tensor var_1009 = const()[name = tensor("op_1009"), val = tensor([1, 8, 64, -1])]; + tensor var_1010_cast_fp16 = reshape(shape = var_1009, x = key_17_cast_fp16)[name = tensor("op_1010_cast_fp16")]; + tensor mh_w_25_transpose_x_0 = const()[name = tensor("mh_w_25_transpose_x_0"), val = tensor(true)]; + tensor mh_w_25_transpose_y_0 = const()[name = tensor("mh_w_25_transpose_y_0"), val = tensor(false)]; + tensor mh_w_25_cast_fp16 = matmul(transpose_x = mh_w_25_transpose_x_0, transpose_y = mh_w_25_transpose_y_0, x = var_1008_cast_fp16, y = var_1010_cast_fp16)[name = tensor("mh_w_25_cast_fp16")]; + tensor mh_w_27_cast_fp16 = add(x = mh_w_25_cast_fp16, y = var_155_cast_fp16)[name = tensor("mh_w_27_cast_fp16")]; + tensor var_1018_cast_fp16 = softmax(axis = var_932, x = mh_w_27_cast_fp16)[name = tensor("op_1018_cast_fp16")]; + tensor var_1019 = const()[name = tensor("op_1019"), val = tensor([1, 8, 64, -1])]; + tensor var_1020_cast_fp16 = reshape(shape = var_1019, x = value_17_cast_fp16)[name = tensor("op_1020_cast_fp16")]; + tensor attn_17_transpose_x_0 = const()[name = tensor("attn_17_transpose_x_0"), val = tensor(false)]; + tensor attn_17_transpose_y_0 = const()[name = tensor("attn_17_transpose_y_0"), val = tensor(true)]; + tensor attn_17_cast_fp16 = matmul(transpose_x = attn_17_transpose_x_0, transpose_y = attn_17_transpose_y_0, x = var_1020_cast_fp16, y = var_1018_cast_fp16)[name = tensor("attn_17_cast_fp16")]; + tensor var_1023 = const()[name = tensor("op_1023"), val = tensor([1, 512, 1, -1])]; + tensor input_41_cast_fp16 = reshape(shape = var_1023, x = attn_17_cast_fp16)[name = tensor("input_41_cast_fp16")]; + tensor var_1027 = const()[name = tensor("op_1027"), val = tensor([1, 1])]; + tensor var_1029 = const()[name = tensor("op_1029"), val = tensor([1, 1])]; + tensor obj_63_pad_type_0 = const()[name = tensor("obj_63_pad_type_0"), val = tensor("custom")]; + tensor obj_63_pad_0 = const()[name = tensor("obj_63_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88778496)))]; + tensor layers_4_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89302848)))]; + tensor obj_63_cast_fp16 = conv(bias = layers_4_self_attn_o_proj_bias_to_fp16, dilations = var_1029, groups = var_939, pad = obj_63_pad_0, pad_type = obj_63_pad_type_0, strides = var_1027, weight = layers_4_self_attn_o_proj_weight_to_fp16, x = input_41_cast_fp16)[name = tensor("obj_63_cast_fp16")]; + tensor inputs_27_cast_fp16 = add(x = inputs_25_cast_fp16, y = obj_63_cast_fp16)[name = tensor("inputs_27_cast_fp16")]; + tensor var_1039 = const()[name = tensor("op_1039"), val = tensor([1])]; + tensor channels_mean_27_cast_fp16 = reduce_mean(axes = var_1039, keep_dims = var_940, x = inputs_27_cast_fp16)[name = tensor("channels_mean_27_cast_fp16")]; + tensor zero_mean_27_cast_fp16 = sub(x = inputs_27_cast_fp16, y = channels_mean_27_cast_fp16)[name = tensor("zero_mean_27_cast_fp16")]; + tensor zero_mean_sq_27_cast_fp16 = mul(x = zero_mean_27_cast_fp16, y = zero_mean_27_cast_fp16)[name = tensor("zero_mean_sq_27_cast_fp16")]; + tensor var_1043 = const()[name = tensor("op_1043"), val = tensor([1])]; + tensor var_1044_cast_fp16 = reduce_mean(axes = var_1043, keep_dims = var_940, x = zero_mean_sq_27_cast_fp16)[name = tensor("op_1044_cast_fp16")]; + tensor var_1045_to_fp16 = const()[name = tensor("op_1045_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1046_cast_fp16 = add(x = var_1044_cast_fp16, y = var_1045_to_fp16)[name = tensor("op_1046_cast_fp16")]; + tensor denom_27_epsilon_0_to_fp16 = const()[name = tensor("denom_27_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_27_cast_fp16 = rsqrt(epsilon = denom_27_epsilon_0_to_fp16, x = var_1046_cast_fp16)[name = tensor("denom_27_cast_fp16")]; + tensor out_27_cast_fp16 = mul(x = zero_mean_27_cast_fp16, y = denom_27_cast_fp16)[name = tensor("out_27_cast_fp16")]; + tensor obj_65_gamma_0_to_fp16 = const()[name = tensor("obj_65_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89303936)))]; + tensor obj_65_beta_0_to_fp16 = const()[name = tensor("obj_65_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89305024)))]; + tensor obj_65_epsilon_0_to_fp16 = const()[name = tensor("obj_65_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_65_cast_fp16 = batch_norm(beta = obj_65_beta_0_to_fp16, epsilon = obj_65_epsilon_0_to_fp16, gamma = obj_65_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_27_cast_fp16)[name = tensor("obj_65_cast_fp16")]; + tensor var_1061 = const()[name = tensor("op_1061"), val = tensor([1, 1])]; + tensor var_1063 = const()[name = tensor("op_1063"), val = tensor([1, 1])]; + tensor query_19_pad_type_0 = const()[name = tensor("query_19_pad_type_0"), val = tensor("custom")]; + tensor query_19_pad_0 = const()[name = tensor("query_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89306112)))]; + tensor layers_4_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_4_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89830464)))]; + tensor query_19_cast_fp16 = conv(bias = layers_4_encoder_attn_q_proj_bias_to_fp16, dilations = var_1063, groups = var_939, pad = query_19_pad_0, pad_type = query_19_pad_type_0, strides = var_1061, weight = layers_4_encoder_attn_q_proj_weight_to_fp16, x = obj_65_cast_fp16)[name = tensor("query_19_cast_fp16")]; + tensor var_1067 = const()[name = tensor("op_1067"), val = tensor([1, 1])]; + tensor var_1069 = const()[name = tensor("op_1069"), val = tensor([1, 1])]; + tensor key_19_pad_type_0 = const()[name = tensor("key_19_pad_type_0"), val = tensor("custom")]; + tensor key_19_pad_0 = const()[name = tensor("key_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89831552)))]; + tensor key_19_cast_fp16 = conv(dilations = var_1069, groups = var_939, pad = key_19_pad_0, pad_type = key_19_pad_type_0, strides = var_1067, weight = layers_4_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_19_cast_fp16")]; + tensor var_1074 = const()[name = tensor("op_1074"), val = tensor([1, 1])]; + tensor var_1076 = const()[name = tensor("op_1076"), val = tensor([1, 1])]; + tensor value_19_pad_type_0 = const()[name = tensor("value_19_pad_type_0"), val = tensor("custom")]; + tensor value_19_pad_0 = const()[name = tensor("value_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90355904)))]; + tensor layers_4_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_4_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90880256)))]; + tensor value_19_cast_fp16 = conv(bias = layers_4_encoder_attn_v_proj_bias_to_fp16, dilations = var_1076, groups = var_939, pad = value_19_pad_0, pad_type = value_19_pad_type_0, strides = var_1074, weight = layers_4_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_19_cast_fp16")]; + tensor var_1080 = const()[name = tensor("op_1080"), val = tensor([1, 8, 64, -1])]; + tensor var_1081_cast_fp16 = reshape(shape = var_1080, x = query_19_cast_fp16)[name = tensor("op_1081_cast_fp16")]; + tensor var_1082_to_fp16 = const()[name = tensor("op_1082_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1083_cast_fp16 = mul(x = var_1081_cast_fp16, y = var_1082_to_fp16)[name = tensor("op_1083_cast_fp16")]; + tensor var_1084 = const()[name = tensor("op_1084"), val = tensor([1, 8, 64, -1])]; + tensor var_1085_cast_fp16 = reshape(shape = var_1084, x = key_19_cast_fp16)[name = tensor("op_1085_cast_fp16")]; + tensor mh_w_29_transpose_x_0 = const()[name = tensor("mh_w_29_transpose_x_0"), val = tensor(true)]; + tensor mh_w_29_transpose_y_0 = const()[name = tensor("mh_w_29_transpose_y_0"), val = tensor(false)]; + tensor mh_w_29_cast_fp16 = matmul(transpose_x = mh_w_29_transpose_x_0, transpose_y = mh_w_29_transpose_y_0, x = var_1083_cast_fp16, y = var_1085_cast_fp16)[name = tensor("mh_w_29_cast_fp16")]; + tensor obj_69_cast_fp16 = softmax(axis = var_932, x = mh_w_29_cast_fp16)[name = tensor("obj_69_cast_fp16")]; + tensor var_1089 = const()[name = tensor("op_1089"), val = tensor([1, 8, 64, -1])]; + tensor var_1090_cast_fp16 = reshape(shape = var_1089, x = value_19_cast_fp16)[name = tensor("op_1090_cast_fp16")]; + tensor attn_19_transpose_x_0 = const()[name = tensor("attn_19_transpose_x_0"), val = tensor(false)]; + tensor attn_19_transpose_y_0 = const()[name = tensor("attn_19_transpose_y_0"), val = tensor(true)]; + tensor attn_19_cast_fp16 = matmul(transpose_x = attn_19_transpose_x_0, transpose_y = attn_19_transpose_y_0, x = var_1090_cast_fp16, y = obj_69_cast_fp16)[name = tensor("attn_19_cast_fp16")]; + tensor var_1093 = const()[name = tensor("op_1093"), val = tensor([1, 512, 1, -1])]; + tensor input_43_cast_fp16 = reshape(shape = var_1093, x = attn_19_cast_fp16)[name = tensor("input_43_cast_fp16")]; + tensor var_1097 = const()[name = tensor("op_1097"), val = tensor([1, 1])]; + tensor var_1099 = const()[name = tensor("op_1099"), val = tensor([1, 1])]; + tensor obj_67_pad_type_0 = const()[name = tensor("obj_67_pad_type_0"), val = tensor("custom")]; + tensor obj_67_pad_0 = const()[name = tensor("obj_67_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90881344)))]; + tensor layers_4_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_4_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91405696)))]; + tensor obj_67_cast_fp16 = conv(bias = layers_4_encoder_attn_o_proj_bias_to_fp16, dilations = var_1099, groups = var_939, pad = obj_67_pad_0, pad_type = obj_67_pad_type_0, strides = var_1097, weight = layers_4_encoder_attn_o_proj_weight_to_fp16, x = input_43_cast_fp16)[name = tensor("obj_67_cast_fp16")]; + tensor inputs_29_cast_fp16 = add(x = inputs_27_cast_fp16, y = obj_67_cast_fp16)[name = tensor("inputs_29_cast_fp16")]; + tensor var_1108 = const()[name = tensor("op_1108"), val = tensor([1])]; + tensor channels_mean_29_cast_fp16 = reduce_mean(axes = var_1108, keep_dims = var_940, x = inputs_29_cast_fp16)[name = tensor("channels_mean_29_cast_fp16")]; + tensor zero_mean_29_cast_fp16 = sub(x = inputs_29_cast_fp16, y = channels_mean_29_cast_fp16)[name = tensor("zero_mean_29_cast_fp16")]; + tensor zero_mean_sq_29_cast_fp16 = mul(x = zero_mean_29_cast_fp16, y = zero_mean_29_cast_fp16)[name = tensor("zero_mean_sq_29_cast_fp16")]; + tensor var_1112 = const()[name = tensor("op_1112"), val = tensor([1])]; + tensor var_1113_cast_fp16 = reduce_mean(axes = var_1112, keep_dims = var_940, x = zero_mean_sq_29_cast_fp16)[name = tensor("op_1113_cast_fp16")]; + tensor var_1114_to_fp16 = const()[name = tensor("op_1114_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1115_cast_fp16 = add(x = var_1113_cast_fp16, y = var_1114_to_fp16)[name = tensor("op_1115_cast_fp16")]; + tensor denom_29_epsilon_0_to_fp16 = const()[name = tensor("denom_29_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_29_cast_fp16 = rsqrt(epsilon = denom_29_epsilon_0_to_fp16, x = var_1115_cast_fp16)[name = tensor("denom_29_cast_fp16")]; + tensor out_29_cast_fp16 = mul(x = zero_mean_29_cast_fp16, y = denom_29_cast_fp16)[name = tensor("out_29_cast_fp16")]; + tensor input_45_gamma_0_to_fp16 = const()[name = tensor("input_45_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91406784)))]; + tensor input_45_beta_0_to_fp16 = const()[name = tensor("input_45_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91407872)))]; + tensor input_45_epsilon_0_to_fp16 = const()[name = tensor("input_45_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_45_cast_fp16 = batch_norm(beta = input_45_beta_0_to_fp16, epsilon = input_45_epsilon_0_to_fp16, gamma = input_45_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_29_cast_fp16)[name = tensor("input_45_cast_fp16")]; + tensor var_1126 = const()[name = tensor("op_1126"), val = tensor([1, 1])]; + tensor var_1128 = const()[name = tensor("op_1128"), val = tensor([1, 1])]; + tensor input_47_pad_type_0 = const()[name = tensor("input_47_pad_type_0"), val = tensor("custom")]; + tensor input_47_pad_0 = const()[name = tensor("input_47_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_fc1_weight_to_fp16 = const()[name = tensor("layers_4_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91408960)))]; + tensor layers_4_fc1_bias_to_fp16 = const()[name = tensor("layers_4_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93506176)))]; + tensor input_47_cast_fp16 = conv(bias = layers_4_fc1_bias_to_fp16, dilations = var_1128, groups = var_939, pad = input_47_pad_0, pad_type = input_47_pad_type_0, strides = var_1126, weight = layers_4_fc1_weight_to_fp16, x = input_45_cast_fp16)[name = tensor("input_47_cast_fp16")]; + tensor input_49_mode_0 = const()[name = tensor("input_49_mode_0"), val = tensor("EXACT")]; + tensor input_49_cast_fp16 = gelu(mode = input_49_mode_0, x = input_47_cast_fp16)[name = tensor("input_49_cast_fp16")]; + tensor var_1134 = const()[name = tensor("op_1134"), val = tensor([1, 1])]; + tensor var_1136 = const()[name = tensor("op_1136"), val = tensor([1, 1])]; + tensor hidden_states_11_pad_type_0 = const()[name = tensor("hidden_states_11_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_11_pad_0 = const()[name = tensor("hidden_states_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_fc2_weight_to_fp16 = const()[name = tensor("layers_4_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93510336)))]; + tensor layers_4_fc2_bias_to_fp16 = const()[name = tensor("layers_4_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95607552)))]; + tensor hidden_states_11_cast_fp16 = conv(bias = layers_4_fc2_bias_to_fp16, dilations = var_1136, groups = var_939, pad = hidden_states_11_pad_0, pad_type = hidden_states_11_pad_type_0, strides = var_1134, weight = layers_4_fc2_weight_to_fp16, x = input_49_cast_fp16)[name = tensor("hidden_states_11_cast_fp16")]; + tensor inputs_31_cast_fp16 = add(x = inputs_29_cast_fp16, y = hidden_states_11_cast_fp16)[name = tensor("inputs_31_cast_fp16")]; + tensor var_1150 = const()[name = tensor("op_1150"), val = tensor(3)]; + tensor var_1157 = const()[name = tensor("op_1157"), val = tensor(1)]; + tensor var_1158 = const()[name = tensor("op_1158"), val = tensor(true)]; + tensor var_1170 = const()[name = tensor("op_1170"), val = tensor([1])]; + tensor channels_mean_31_cast_fp16 = reduce_mean(axes = var_1170, keep_dims = var_1158, x = inputs_31_cast_fp16)[name = tensor("channels_mean_31_cast_fp16")]; + tensor zero_mean_31_cast_fp16 = sub(x = inputs_31_cast_fp16, y = channels_mean_31_cast_fp16)[name = tensor("zero_mean_31_cast_fp16")]; + tensor zero_mean_sq_31_cast_fp16 = mul(x = zero_mean_31_cast_fp16, y = zero_mean_31_cast_fp16)[name = tensor("zero_mean_sq_31_cast_fp16")]; + tensor var_1174 = const()[name = tensor("op_1174"), val = tensor([1])]; + tensor var_1175_cast_fp16 = reduce_mean(axes = var_1174, keep_dims = var_1158, x = zero_mean_sq_31_cast_fp16)[name = tensor("op_1175_cast_fp16")]; + tensor var_1176_to_fp16 = const()[name = tensor("op_1176_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1177_cast_fp16 = add(x = var_1175_cast_fp16, y = var_1176_to_fp16)[name = tensor("op_1177_cast_fp16")]; + tensor denom_31_epsilon_0_to_fp16 = const()[name = tensor("denom_31_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_31_cast_fp16 = rsqrt(epsilon = denom_31_epsilon_0_to_fp16, x = var_1177_cast_fp16)[name = tensor("denom_31_cast_fp16")]; + tensor out_31_cast_fp16 = mul(x = zero_mean_31_cast_fp16, y = denom_31_cast_fp16)[name = tensor("out_31_cast_fp16")]; + tensor obj_71_gamma_0_to_fp16 = const()[name = tensor("obj_71_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95608640)))]; + tensor obj_71_beta_0_to_fp16 = const()[name = tensor("obj_71_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95609728)))]; + tensor obj_71_epsilon_0_to_fp16 = const()[name = tensor("obj_71_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_71_cast_fp16 = batch_norm(beta = obj_71_beta_0_to_fp16, epsilon = obj_71_epsilon_0_to_fp16, gamma = obj_71_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_31_cast_fp16)[name = tensor("obj_71_cast_fp16")]; + tensor var_1192 = const()[name = tensor("op_1192"), val = tensor([1, 1])]; + tensor var_1194 = const()[name = tensor("op_1194"), val = tensor([1, 1])]; + tensor query_21_pad_type_0 = const()[name = tensor("query_21_pad_type_0"), val = tensor("custom")]; + tensor query_21_pad_0 = const()[name = tensor("query_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95610816)))]; + tensor layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(96135168)))]; + tensor query_21_cast_fp16 = conv(bias = layers_5_self_attn_q_proj_bias_to_fp16, dilations = var_1194, groups = var_1157, pad = query_21_pad_0, pad_type = query_21_pad_type_0, strides = var_1192, weight = layers_5_self_attn_q_proj_weight_to_fp16, x = obj_71_cast_fp16)[name = tensor("query_21_cast_fp16")]; + tensor var_1198 = const()[name = tensor("op_1198"), val = tensor([1, 1])]; + tensor var_1200 = const()[name = tensor("op_1200"), val = tensor([1, 1])]; + tensor current_key_pad_type_0 = const()[name = tensor("current_key_pad_type_0"), val = tensor("custom")]; + tensor current_key_pad_0 = const()[name = tensor("current_key_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(96136256)))]; + tensor current_key_cast_fp16 = conv(dilations = var_1200, groups = var_1157, pad = current_key_pad_0, pad_type = current_key_pad_type_0, strides = var_1198, weight = layers_5_self_attn_k_proj_weight_to_fp16, x = obj_71_cast_fp16)[name = tensor("current_key_cast_fp16")]; + tensor var_1205 = const()[name = tensor("op_1205"), val = tensor([1, 1])]; + tensor var_1207 = const()[name = tensor("op_1207"), val = tensor([1, 1])]; + tensor current_value_pad_type_0 = const()[name = tensor("current_value_pad_type_0"), val = tensor("custom")]; + tensor current_value_pad_0 = const()[name = tensor("current_value_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(96660608)))]; + tensor layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97184960)))]; + tensor current_value_cast_fp16 = conv(bias = layers_5_self_attn_v_proj_bias_to_fp16, dilations = var_1207, groups = var_1157, pad = current_value_pad_0, pad_type = current_value_pad_type_0, strides = var_1205, weight = layers_5_self_attn_v_proj_weight_to_fp16, x = obj_71_cast_fp16)[name = tensor("current_value_cast_fp16")]; + tensor var_1214_cast_fp16 = mul(x = current_key_cast_fp16, y = var_134_cast_fp16)[name = tensor("op_1214_cast_fp16")]; + tensor var_1216_cast_fp16 = mul(x = var_51_cast_fp16_5, y = var_137_cast_fp16)[name = tensor("op_1216_cast_fp16")]; + tensor key_21_cast_fp16 = add(x = var_1214_cast_fp16, y = var_1216_cast_fp16)[name = tensor("key_21_cast_fp16")]; + tensor var_1218_cast_fp16 = mul(x = current_value_cast_fp16, y = var_134_cast_fp16)[name = tensor("op_1218_cast_fp16")]; + tensor var_1220_cast_fp16 = mul(x = var_60_cast_fp16_5, y = var_137_cast_fp16)[name = tensor("op_1220_cast_fp16")]; + tensor value_21_cast_fp16 = add(x = var_1218_cast_fp16, y = var_1220_cast_fp16)[name = tensor("value_21_cast_fp16")]; + tensor var_1223 = const()[name = tensor("op_1223"), val = tensor([1, 8, 64, -1])]; + tensor var_1224_cast_fp16 = reshape(shape = var_1223, x = query_21_cast_fp16)[name = tensor("op_1224_cast_fp16")]; + tensor var_1225_to_fp16 = const()[name = tensor("op_1225_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1226_cast_fp16 = mul(x = var_1224_cast_fp16, y = var_1225_to_fp16)[name = tensor("op_1226_cast_fp16")]; + tensor var_1227 = const()[name = tensor("op_1227"), val = tensor([1, 8, 64, -1])]; + tensor var_1228_cast_fp16 = reshape(shape = var_1227, x = key_21_cast_fp16)[name = tensor("op_1228_cast_fp16")]; + tensor mh_w_31_transpose_x_0 = const()[name = tensor("mh_w_31_transpose_x_0"), val = tensor(true)]; + tensor mh_w_31_transpose_y_0 = const()[name = tensor("mh_w_31_transpose_y_0"), val = tensor(false)]; + tensor mh_w_31_cast_fp16 = matmul(transpose_x = mh_w_31_transpose_x_0, transpose_y = mh_w_31_transpose_y_0, x = var_1226_cast_fp16, y = var_1228_cast_fp16)[name = tensor("mh_w_31_cast_fp16")]; + tensor mh_w_33_cast_fp16 = add(x = mh_w_31_cast_fp16, y = var_155_cast_fp16)[name = tensor("mh_w_33_cast_fp16")]; + tensor var_1236_cast_fp16 = softmax(axis = var_1150, x = mh_w_33_cast_fp16)[name = tensor("op_1236_cast_fp16")]; + tensor var_1237 = const()[name = tensor("op_1237"), val = tensor([1, 8, 64, -1])]; + tensor var_1238_cast_fp16 = reshape(shape = var_1237, x = value_21_cast_fp16)[name = tensor("op_1238_cast_fp16")]; + tensor attn_21_transpose_x_0 = const()[name = tensor("attn_21_transpose_x_0"), val = tensor(false)]; + tensor attn_21_transpose_y_0 = const()[name = tensor("attn_21_transpose_y_0"), val = tensor(true)]; + tensor attn_21_cast_fp16 = matmul(transpose_x = attn_21_transpose_x_0, transpose_y = attn_21_transpose_y_0, x = var_1238_cast_fp16, y = var_1236_cast_fp16)[name = tensor("attn_21_cast_fp16")]; + tensor var_1241 = const()[name = tensor("op_1241"), val = tensor([1, 512, 1, -1])]; + tensor input_51_cast_fp16 = reshape(shape = var_1241, x = attn_21_cast_fp16)[name = tensor("input_51_cast_fp16")]; + tensor var_1245 = const()[name = tensor("op_1245"), val = tensor([1, 1])]; + tensor var_1247 = const()[name = tensor("op_1247"), val = tensor([1, 1])]; + tensor obj_77_pad_type_0 = const()[name = tensor("obj_77_pad_type_0"), val = tensor("custom")]; + tensor obj_77_pad_0 = const()[name = tensor("obj_77_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97186048)))]; + tensor layers_5_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97710400)))]; + tensor obj_77_cast_fp16 = conv(bias = layers_5_self_attn_o_proj_bias_to_fp16, dilations = var_1247, groups = var_1157, pad = obj_77_pad_0, pad_type = obj_77_pad_type_0, strides = var_1245, weight = layers_5_self_attn_o_proj_weight_to_fp16, x = input_51_cast_fp16)[name = tensor("obj_77_cast_fp16")]; + tensor inputs_33_cast_fp16 = add(x = inputs_31_cast_fp16, y = obj_77_cast_fp16)[name = tensor("inputs_33_cast_fp16")]; + tensor var_1257 = const()[name = tensor("op_1257"), val = tensor([1])]; + tensor channels_mean_33_cast_fp16 = reduce_mean(axes = var_1257, keep_dims = var_1158, x = inputs_33_cast_fp16)[name = tensor("channels_mean_33_cast_fp16")]; + tensor zero_mean_33_cast_fp16 = sub(x = inputs_33_cast_fp16, y = channels_mean_33_cast_fp16)[name = tensor("zero_mean_33_cast_fp16")]; + tensor zero_mean_sq_33_cast_fp16 = mul(x = zero_mean_33_cast_fp16, y = zero_mean_33_cast_fp16)[name = tensor("zero_mean_sq_33_cast_fp16")]; + tensor var_1261 = const()[name = tensor("op_1261"), val = tensor([1])]; + tensor var_1262_cast_fp16 = reduce_mean(axes = var_1261, keep_dims = var_1158, x = zero_mean_sq_33_cast_fp16)[name = tensor("op_1262_cast_fp16")]; + tensor var_1263_to_fp16 = const()[name = tensor("op_1263_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1264_cast_fp16 = add(x = var_1262_cast_fp16, y = var_1263_to_fp16)[name = tensor("op_1264_cast_fp16")]; + tensor denom_33_epsilon_0_to_fp16 = const()[name = tensor("denom_33_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_33_cast_fp16 = rsqrt(epsilon = denom_33_epsilon_0_to_fp16, x = var_1264_cast_fp16)[name = tensor("denom_33_cast_fp16")]; + tensor out_33_cast_fp16 = mul(x = zero_mean_33_cast_fp16, y = denom_33_cast_fp16)[name = tensor("out_33_cast_fp16")]; + tensor obj_79_gamma_0_to_fp16 = const()[name = tensor("obj_79_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97711488)))]; + tensor obj_79_beta_0_to_fp16 = const()[name = tensor("obj_79_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97712576)))]; + tensor obj_79_epsilon_0_to_fp16 = const()[name = tensor("obj_79_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_79_cast_fp16 = batch_norm(beta = obj_79_beta_0_to_fp16, epsilon = obj_79_epsilon_0_to_fp16, gamma = obj_79_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_33_cast_fp16)[name = tensor("obj_79_cast_fp16")]; + tensor var_1279 = const()[name = tensor("op_1279"), val = tensor([1, 1])]; + tensor var_1281 = const()[name = tensor("op_1281"), val = tensor([1, 1])]; + tensor query_pad_type_0 = const()[name = tensor("query_pad_type_0"), val = tensor("custom")]; + tensor query_pad_0 = const()[name = tensor("query_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97713664)))]; + tensor layers_5_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_5_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98238016)))]; + tensor query_cast_fp16 = conv(bias = layers_5_encoder_attn_q_proj_bias_to_fp16, dilations = var_1281, groups = var_1157, pad = query_pad_0, pad_type = query_pad_type_0, strides = var_1279, weight = layers_5_encoder_attn_q_proj_weight_to_fp16, x = obj_79_cast_fp16)[name = tensor("query_cast_fp16")]; + tensor var_1285 = const()[name = tensor("op_1285"), val = tensor([1, 1])]; + tensor var_1287 = const()[name = tensor("op_1287"), val = tensor([1, 1])]; + tensor key_pad_type_0 = const()[name = tensor("key_pad_type_0"), val = tensor("custom")]; + tensor key_pad_0 = const()[name = tensor("key_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98239104)))]; + tensor key_cast_fp16 = conv(dilations = var_1287, groups = var_1157, pad = key_pad_0, pad_type = key_pad_type_0, strides = var_1285, weight = layers_5_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_cast_fp16")]; + tensor var_1292 = const()[name = tensor("op_1292"), val = tensor([1, 1])]; + tensor var_1294 = const()[name = tensor("op_1294"), val = tensor([1, 1])]; + tensor value_pad_type_0 = const()[name = tensor("value_pad_type_0"), val = tensor("custom")]; + tensor value_pad_0 = const()[name = tensor("value_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98763456)))]; + tensor layers_5_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_5_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99287808)))]; + tensor value_cast_fp16 = conv(bias = layers_5_encoder_attn_v_proj_bias_to_fp16, dilations = var_1294, groups = var_1157, pad = value_pad_0, pad_type = value_pad_type_0, strides = var_1292, weight = layers_5_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_cast_fp16")]; + tensor var_1298 = const()[name = tensor("op_1298"), val = tensor([1, 8, 64, -1])]; + tensor var_1299_cast_fp16 = reshape(shape = var_1298, x = query_cast_fp16)[name = tensor("op_1299_cast_fp16")]; + tensor var_1300_to_fp16 = const()[name = tensor("op_1300_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1301_cast_fp16 = mul(x = var_1299_cast_fp16, y = var_1300_to_fp16)[name = tensor("op_1301_cast_fp16")]; + tensor var_1302 = const()[name = tensor("op_1302"), val = tensor([1, 8, 64, -1])]; + tensor var_1303_cast_fp16 = reshape(shape = var_1302, x = key_cast_fp16)[name = tensor("op_1303_cast_fp16")]; + tensor mh_w_transpose_x_0 = const()[name = tensor("mh_w_transpose_x_0"), val = tensor(true)]; + tensor mh_w_transpose_y_0 = const()[name = tensor("mh_w_transpose_y_0"), val = tensor(false)]; + tensor mh_w_cast_fp16 = matmul(transpose_x = mh_w_transpose_x_0, transpose_y = mh_w_transpose_y_0, x = var_1301_cast_fp16, y = var_1303_cast_fp16)[name = tensor("mh_w_cast_fp16")]; + tensor obj_83_cast_fp16 = softmax(axis = var_1150, x = mh_w_cast_fp16)[name = tensor("obj_83_cast_fp16")]; + tensor var_1307 = const()[name = tensor("op_1307"), val = tensor([1, 8, 64, -1])]; + tensor var_1308_cast_fp16 = reshape(shape = var_1307, x = value_cast_fp16)[name = tensor("op_1308_cast_fp16")]; + tensor attn_transpose_x_0 = const()[name = tensor("attn_transpose_x_0"), val = tensor(false)]; + tensor attn_transpose_y_0 = const()[name = tensor("attn_transpose_y_0"), val = tensor(true)]; + tensor attn_cast_fp16 = matmul(transpose_x = attn_transpose_x_0, transpose_y = attn_transpose_y_0, x = var_1308_cast_fp16, y = obj_83_cast_fp16)[name = tensor("attn_cast_fp16")]; + tensor var_1311 = const()[name = tensor("op_1311"), val = tensor([1, 512, 1, -1])]; + tensor input_53_cast_fp16 = reshape(shape = var_1311, x = attn_cast_fp16)[name = tensor("input_53_cast_fp16")]; + tensor var_1315 = const()[name = tensor("op_1315"), val = tensor([1, 1])]; + tensor var_1317 = const()[name = tensor("op_1317"), val = tensor([1, 1])]; + tensor obj_81_pad_type_0 = const()[name = tensor("obj_81_pad_type_0"), val = tensor("custom")]; + tensor obj_81_pad_0 = const()[name = tensor("obj_81_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99288896)))]; + tensor layers_5_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_5_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99813248)))]; + tensor obj_81_cast_fp16 = conv(bias = layers_5_encoder_attn_o_proj_bias_to_fp16, dilations = var_1317, groups = var_1157, pad = obj_81_pad_0, pad_type = obj_81_pad_type_0, strides = var_1315, weight = layers_5_encoder_attn_o_proj_weight_to_fp16, x = input_53_cast_fp16)[name = tensor("obj_81_cast_fp16")]; + tensor inputs_35_cast_fp16 = add(x = inputs_33_cast_fp16, y = obj_81_cast_fp16)[name = tensor("inputs_35_cast_fp16")]; + tensor var_1326 = const()[name = tensor("op_1326"), val = tensor([1])]; + tensor channels_mean_35_cast_fp16 = reduce_mean(axes = var_1326, keep_dims = var_1158, x = inputs_35_cast_fp16)[name = tensor("channels_mean_35_cast_fp16")]; + tensor zero_mean_35_cast_fp16 = sub(x = inputs_35_cast_fp16, y = channels_mean_35_cast_fp16)[name = tensor("zero_mean_35_cast_fp16")]; + tensor zero_mean_sq_35_cast_fp16 = mul(x = zero_mean_35_cast_fp16, y = zero_mean_35_cast_fp16)[name = tensor("zero_mean_sq_35_cast_fp16")]; + tensor var_1330 = const()[name = tensor("op_1330"), val = tensor([1])]; + tensor var_1331_cast_fp16 = reduce_mean(axes = var_1330, keep_dims = var_1158, x = zero_mean_sq_35_cast_fp16)[name = tensor("op_1331_cast_fp16")]; + tensor var_1332_to_fp16 = const()[name = tensor("op_1332_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1333_cast_fp16 = add(x = var_1331_cast_fp16, y = var_1332_to_fp16)[name = tensor("op_1333_cast_fp16")]; + tensor denom_35_epsilon_0_to_fp16 = const()[name = tensor("denom_35_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_35_cast_fp16 = rsqrt(epsilon = denom_35_epsilon_0_to_fp16, x = var_1333_cast_fp16)[name = tensor("denom_35_cast_fp16")]; + tensor out_35_cast_fp16 = mul(x = zero_mean_35_cast_fp16, y = denom_35_cast_fp16)[name = tensor("out_35_cast_fp16")]; + tensor input_55_gamma_0_to_fp16 = const()[name = tensor("input_55_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99814336)))]; + tensor input_55_beta_0_to_fp16 = const()[name = tensor("input_55_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99815424)))]; + tensor input_55_epsilon_0_to_fp16 = const()[name = tensor("input_55_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_55_cast_fp16 = batch_norm(beta = input_55_beta_0_to_fp16, epsilon = input_55_epsilon_0_to_fp16, gamma = input_55_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_35_cast_fp16)[name = tensor("input_55_cast_fp16")]; + tensor var_1344 = const()[name = tensor("op_1344"), val = tensor([1, 1])]; + tensor var_1346 = const()[name = tensor("op_1346"), val = tensor([1, 1])]; + tensor input_57_pad_type_0 = const()[name = tensor("input_57_pad_type_0"), val = tensor("custom")]; + tensor input_57_pad_0 = const()[name = tensor("input_57_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_fc1_weight_to_fp16 = const()[name = tensor("layers_5_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99816512)))]; + tensor layers_5_fc1_bias_to_fp16 = const()[name = tensor("layers_5_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101913728)))]; + tensor input_57_cast_fp16 = conv(bias = layers_5_fc1_bias_to_fp16, dilations = var_1346, groups = var_1157, pad = input_57_pad_0, pad_type = input_57_pad_type_0, strides = var_1344, weight = layers_5_fc1_weight_to_fp16, x = input_55_cast_fp16)[name = tensor("input_57_cast_fp16")]; + tensor input_mode_0 = const()[name = tensor("input_mode_0"), val = tensor("EXACT")]; + tensor input_cast_fp16 = gelu(mode = input_mode_0, x = input_57_cast_fp16)[name = tensor("input_cast_fp16")]; + tensor var_1352 = const()[name = tensor("op_1352"), val = tensor([1, 1])]; + tensor var_1354 = const()[name = tensor("op_1354"), val = tensor([1, 1])]; + tensor hidden_states_13_pad_type_0 = const()[name = tensor("hidden_states_13_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_13_pad_0 = const()[name = tensor("hidden_states_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_fc2_weight_to_fp16 = const()[name = tensor("layers_5_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101917888)))]; + tensor layers_5_fc2_bias_to_fp16 = const()[name = tensor("layers_5_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104015104)))]; + tensor hidden_states_13_cast_fp16 = conv(bias = layers_5_fc2_bias_to_fp16, dilations = var_1354, groups = var_1157, pad = hidden_states_13_pad_0, pad_type = hidden_states_13_pad_type_0, strides = var_1352, weight = layers_5_fc2_weight_to_fp16, x = input_cast_fp16)[name = tensor("hidden_states_13_cast_fp16")]; + tensor inputs_cast_fp16 = add(x = inputs_35_cast_fp16, y = hidden_states_13_cast_fp16)[name = tensor("inputs_cast_fp16")]; + tensor var_1365 = const()[name = tensor("op_1365"), val = tensor(true)]; + tensor var_1369 = const()[name = tensor("op_1369"), val = tensor([1])]; + tensor channels_mean_cast_fp16 = reduce_mean(axes = var_1369, keep_dims = var_1365, x = inputs_cast_fp16)[name = tensor("channels_mean_cast_fp16")]; + tensor zero_mean_cast_fp16 = sub(x = inputs_cast_fp16, y = channels_mean_cast_fp16)[name = tensor("zero_mean_cast_fp16")]; + tensor zero_mean_sq_cast_fp16 = mul(x = zero_mean_cast_fp16, y = zero_mean_cast_fp16)[name = tensor("zero_mean_sq_cast_fp16")]; + tensor var_1373 = const()[name = tensor("op_1373"), val = tensor([1])]; + tensor var_1374_cast_fp16 = reduce_mean(axes = var_1373, keep_dims = var_1365, x = zero_mean_sq_cast_fp16)[name = tensor("op_1374_cast_fp16")]; + tensor var_1375_to_fp16 = const()[name = tensor("op_1375_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1376_cast_fp16 = add(x = var_1374_cast_fp16, y = var_1375_to_fp16)[name = tensor("op_1376_cast_fp16")]; + tensor denom_epsilon_0_to_fp16 = const()[name = tensor("denom_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_cast_fp16 = rsqrt(epsilon = denom_epsilon_0_to_fp16, x = var_1376_cast_fp16)[name = tensor("denom_cast_fp16")]; + tensor out_cast_fp16 = mul(x = zero_mean_cast_fp16, y = denom_cast_fp16)[name = tensor("out_cast_fp16")]; + tensor hidden_states_gamma_0_to_fp16 = const()[name = tensor("hidden_states_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104016192)))]; + tensor hidden_states_beta_0_to_fp16 = const()[name = tensor("hidden_states_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104017280)))]; + tensor hidden_states_epsilon_0_to_fp16 = const()[name = tensor("hidden_states_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor hidden_states_cast_fp16 = batch_norm(beta = hidden_states_beta_0_to_fp16, epsilon = hidden_states_epsilon_0_to_fp16, gamma = hidden_states_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_cast_fp16)[name = tensor("hidden_states_cast_fp16")]; + tensor var_1386_axes_0 = const()[name = tensor("op_1386_axes_0"), val = tensor([2])]; + tensor var_1386_cast_fp16 = squeeze(axes = var_1386_axes_0, x = hidden_states_cast_fp16)[name = tensor("op_1386_cast_fp16")]; + tensor var_1389_perm_0 = const()[name = tensor("op_1389_perm_0"), val = tensor([0, 2, 1])]; + tensor linear_0_bias_0_to_fp16 = const()[name = tensor("linear_0_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104018368)))]; + tensor transpose_0 = transpose(perm = var_1389_perm_0, x = var_1386_cast_fp16)[name = tensor("transpose_0")]; + tensor logits = linear(bias = linear_0_bias_0_to_fp16, weight = embed_tokens_weight_to_fp16, x = transpose_0)[name = tensor("linear_0_cast_fp16")]; + tensor var_1393 = const()[name = tensor("op_1393"), val = tensor(1)]; + tensor obj_87_interleave_0 = const()[name = tensor("obj_87_interleave_0"), val = tensor(false)]; + tensor key_cache_updates = concat(axis = var_1393, interleave = obj_87_interleave_0, values = (current_key_1_cast_fp16, current_key_3_cast_fp16, current_key_5_cast_fp16, current_key_7_cast_fp16, current_key_9_cast_fp16, current_key_cast_fp16))[name = tensor("obj_87_cast_fp16")]; + tensor var_1396 = const()[name = tensor("op_1396"), val = tensor(1)]; + tensor obj_89_interleave_0 = const()[name = tensor("obj_89_interleave_0"), val = tensor(false)]; + tensor value_cache_updates = concat(axis = var_1396, interleave = obj_89_interleave_0, values = (current_value_1_cast_fp16, current_value_3_cast_fp16, current_value_5_cast_fp16, current_value_7_cast_fp16, current_value_9_cast_fp16, current_value_cast_fp16))[name = tensor("obj_89_cast_fp16")]; + tensor var_1407_begin_0 = const()[name = tensor("op_1407_begin_0"), val = tensor([0, 1, 0, 0])]; + tensor var_1407_end_0 = const()[name = tensor("op_1407_end_0"), val = tensor([1, 2, 1, 1500])]; + tensor var_1407_end_mask_0 = const()[name = tensor("op_1407_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1407_cast_fp16 = slice_by_index(begin = var_1407_begin_0, end = var_1407_end_0, end_mask = var_1407_end_mask_0, x = obj_55_cast_fp16)[name = tensor("op_1407_cast_fp16")]; + tensor var_1410_begin_0 = const()[name = tensor("op_1410_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1410_end_0 = const()[name = tensor("op_1410_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_1410_end_mask_0 = const()[name = tensor("op_1410_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_1410_squeeze_mask_0 = const()[name = tensor("op_1410_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_1410_cast_fp16 = slice_by_index(begin = var_1410_begin_0, end = var_1410_end_0, end_mask = var_1410_end_mask_0, squeeze_mask = var_1410_squeeze_mask_0, x = var_1407_cast_fp16)[name = tensor("op_1410_cast_fp16")]; + tensor var_1425_begin_0 = const()[name = tensor("op_1425_begin_0"), val = tensor([0, 2, 0, 0])]; + tensor var_1425_end_0 = const()[name = tensor("op_1425_end_0"), val = tensor([1, 3, 1, 1500])]; + tensor var_1425_end_mask_0 = const()[name = tensor("op_1425_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1425_cast_fp16 = slice_by_index(begin = var_1425_begin_0, end = var_1425_end_0, end_mask = var_1425_end_mask_0, x = obj_69_cast_fp16)[name = tensor("op_1425_cast_fp16")]; + tensor var_1428_begin_0 = const()[name = tensor("op_1428_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1428_end_0 = const()[name = tensor("op_1428_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_1428_end_mask_0 = const()[name = tensor("op_1428_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_1428_squeeze_mask_0 = const()[name = tensor("op_1428_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_1428_cast_fp16 = slice_by_index(begin = var_1428_begin_0, end = var_1428_end_0, end_mask = var_1428_end_mask_0, squeeze_mask = var_1428_squeeze_mask_0, x = var_1425_cast_fp16)[name = tensor("op_1428_cast_fp16")]; + tensor var_1443_begin_0 = const()[name = tensor("op_1443_begin_0"), val = tensor([0, 3, 0, 0])]; + tensor var_1443_end_0 = const()[name = tensor("op_1443_end_0"), val = tensor([1, 4, 1, 1500])]; + tensor var_1443_end_mask_0 = const()[name = tensor("op_1443_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1443_cast_fp16 = slice_by_index(begin = var_1443_begin_0, end = var_1443_end_0, end_mask = var_1443_end_mask_0, x = obj_69_cast_fp16)[name = tensor("op_1443_cast_fp16")]; + tensor var_1446_begin_0 = const()[name = tensor("op_1446_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1446_end_0 = const()[name = tensor("op_1446_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_1446_end_mask_0 = const()[name = tensor("op_1446_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_1446_squeeze_mask_0 = const()[name = tensor("op_1446_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_1446_cast_fp16 = slice_by_index(begin = var_1446_begin_0, end = var_1446_end_0, end_mask = var_1446_end_mask_0, squeeze_mask = var_1446_squeeze_mask_0, x = var_1443_cast_fp16)[name = tensor("op_1446_cast_fp16")]; + tensor var_1461_begin_0 = const()[name = tensor("op_1461_begin_0"), val = tensor([0, 7, 0, 0])]; + tensor var_1461_end_0 = const()[name = tensor("op_1461_end_0"), val = tensor([1, 8, 1, 1500])]; + tensor var_1461_end_mask_0 = const()[name = tensor("op_1461_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1461_cast_fp16 = slice_by_index(begin = var_1461_begin_0, end = var_1461_end_0, end_mask = var_1461_end_mask_0, x = obj_69_cast_fp16)[name = tensor("op_1461_cast_fp16")]; + tensor var_1464_begin_0 = const()[name = tensor("op_1464_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1464_end_0 = const()[name = tensor("op_1464_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_1464_end_mask_0 = const()[name = tensor("op_1464_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_1464_squeeze_mask_0 = const()[name = tensor("op_1464_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_1464_cast_fp16 = slice_by_index(begin = var_1464_begin_0, end = var_1464_end_0, end_mask = var_1464_end_mask_0, squeeze_mask = var_1464_squeeze_mask_0, x = var_1461_cast_fp16)[name = tensor("op_1464_cast_fp16")]; + tensor var_1479_begin_0 = const()[name = tensor("op_1479_begin_0"), val = tensor([0, 1, 0, 0])]; + tensor var_1479_end_0 = const()[name = tensor("op_1479_end_0"), val = tensor([1, 2, 1, 1500])]; + tensor var_1479_end_mask_0 = const()[name = tensor("op_1479_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1479_cast_fp16 = slice_by_index(begin = var_1479_begin_0, end = var_1479_end_0, end_mask = var_1479_end_mask_0, x = obj_83_cast_fp16)[name = tensor("op_1479_cast_fp16")]; + tensor var_1482_begin_0 = const()[name = tensor("op_1482_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1482_end_0 = const()[name = tensor("op_1482_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_1482_end_mask_0 = const()[name = tensor("op_1482_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_1482_squeeze_mask_0 = const()[name = tensor("op_1482_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_1482_cast_fp16 = slice_by_index(begin = var_1482_begin_0, end = var_1482_end_0, end_mask = var_1482_end_mask_0, squeeze_mask = var_1482_squeeze_mask_0, x = var_1479_cast_fp16)[name = tensor("op_1482_cast_fp16")]; + tensor var_1497_begin_0 = const()[name = tensor("op_1497_begin_0"), val = tensor([0, 2, 0, 0])]; + tensor var_1497_end_0 = const()[name = tensor("op_1497_end_0"), val = tensor([1, 3, 1, 1500])]; + tensor var_1497_end_mask_0 = const()[name = tensor("op_1497_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1497_cast_fp16 = slice_by_index(begin = var_1497_begin_0, end = var_1497_end_0, end_mask = var_1497_end_mask_0, x = obj_83_cast_fp16)[name = tensor("op_1497_cast_fp16")]; + tensor var_1500_begin_0 = const()[name = tensor("op_1500_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1500_end_0 = const()[name = tensor("op_1500_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_1500_end_mask_0 = const()[name = tensor("op_1500_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_1500_squeeze_mask_0 = const()[name = tensor("op_1500_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_1500_cast_fp16 = slice_by_index(begin = var_1500_begin_0, end = var_1500_end_0, end_mask = var_1500_end_mask_0, squeeze_mask = var_1500_squeeze_mask_0, x = var_1497_cast_fp16)[name = tensor("op_1500_cast_fp16")]; + tensor var_1515_begin_0 = const()[name = tensor("op_1515_begin_0"), val = tensor([0, 4, 0, 0])]; + tensor var_1515_end_0 = const()[name = tensor("op_1515_end_0"), val = tensor([1, 5, 1, 1500])]; + tensor var_1515_end_mask_0 = const()[name = tensor("op_1515_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1515_cast_fp16 = slice_by_index(begin = var_1515_begin_0, end = var_1515_end_0, end_mask = var_1515_end_mask_0, x = obj_83_cast_fp16)[name = tensor("op_1515_cast_fp16")]; + tensor var_1518_begin_0 = const()[name = tensor("op_1518_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1518_end_0 = const()[name = tensor("op_1518_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_1518_end_mask_0 = const()[name = tensor("op_1518_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_1518_squeeze_mask_0 = const()[name = tensor("op_1518_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_1518_cast_fp16 = slice_by_index(begin = var_1518_begin_0, end = var_1518_end_0, end_mask = var_1518_end_mask_0, squeeze_mask = var_1518_squeeze_mask_0, x = var_1515_cast_fp16)[name = tensor("op_1518_cast_fp16")]; + tensor var_1533_begin_0 = const()[name = tensor("op_1533_begin_0"), val = tensor([0, 6, 0, 0])]; + tensor var_1533_end_0 = const()[name = tensor("op_1533_end_0"), val = tensor([1, 7, 1, 1500])]; + tensor var_1533_end_mask_0 = const()[name = tensor("op_1533_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1533_cast_fp16 = slice_by_index(begin = var_1533_begin_0, end = var_1533_end_0, end_mask = var_1533_end_mask_0, x = obj_83_cast_fp16)[name = tensor("op_1533_cast_fp16")]; + tensor var_1536_begin_0 = const()[name = tensor("op_1536_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1536_end_0 = const()[name = tensor("op_1536_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_1536_end_mask_0 = const()[name = tensor("op_1536_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_1536_squeeze_mask_0 = const()[name = tensor("op_1536_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_1536_cast_fp16 = slice_by_index(begin = var_1536_begin_0, end = var_1536_end_0, end_mask = var_1536_end_mask_0, squeeze_mask = var_1536_squeeze_mask_0, x = var_1533_cast_fp16)[name = tensor("op_1536_cast_fp16")]; + tensor var_1543 = const()[name = tensor("op_1543"), val = tensor(1)]; + tensor var_1544_interleave_0 = const()[name = tensor("op_1544_interleave_0"), val = tensor(false)]; + tensor var_1544_cast_fp16 = concat(axis = var_1543, interleave = var_1544_interleave_0, values = (var_1410_cast_fp16, var_1428_cast_fp16, var_1446_cast_fp16, var_1464_cast_fp16, var_1482_cast_fp16, var_1500_cast_fp16, var_1518_cast_fp16, var_1536_cast_fp16))[name = tensor("op_1544_cast_fp16")]; + tensor var_1546 = const()[name = tensor("op_1546"), val = tensor([1])]; + tensor var_1547 = const()[name = tensor("op_1547"), val = tensor(false)]; + tensor alignment_heads_weights = reduce_mean(axes = var_1546, keep_dims = var_1547, x = var_1544_cast_fp16)[name = tensor("obj_cast_fp16")]; + } -> (logits, key_cache_updates, value_cache_updates, alignment_heads_weights); +} \ No newline at end of file diff --git a/openai_whisper-base/TextDecoder.mlmodelc/model.mlmodel b/openai_whisper-base/TextDecoder.mlmodelc/model.mlmodel new file mode 100644 index 0000000000000000000000000000000000000000..dd03f976fadf935ea2810a9b15d602faf1e8624c --- /dev/null +++ b/openai_whisper-base/TextDecoder.mlmodelc/model.mlmodel @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ae260ff7b95d0c957c3c1f4df4dbeaa0ae6c76bacc55eb86caca8f6820d346f0 +size 164481 diff --git a/openai_whisper-base/TextDecoder.mlmodelc/weights/weight.bin b/openai_whisper-base/TextDecoder.mlmodelc/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..d7a5837254783b1a1342f54b28bcdfcfd6706da0 --- /dev/null +++ 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: "0", + "dataType" : "Float16", + "formattedType" : "MultiArray (Float16 1 × 80 × 1 × 3000)", + "shortDescription" : "", + "shape" : "[1, 80, 1, 3000]", + "name" : "melspectrogram_features", + "type" : "MultiArray" + } + ], + "generatedClassName" : "AudioEncoder", + "method" : "predict" + } +] \ No newline at end of file diff --git a/openai_whisper-medium/AudioEncoder.mlmodelc/model.mil b/openai_whisper-medium/AudioEncoder.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..f055f94d2a260093c68f9c29edda631455de97ca --- /dev/null +++ b/openai_whisper-medium/AudioEncoder.mlmodelc/model.mil @@ -0,0 +1,2029 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3401.3.1"}, {"coremlc-version", "3401.4.1"}, {"coremltools-component-torch", "2.5.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.2"}})] +{ + func main(tensor melspectrogram_features) { + tensor var_90_pad_type_0 = const()[name = tensor("op_90_pad_type_0"), val = tensor("custom")]; + tensor var_90_pad_0 = const()[name = tensor("op_90_pad_0"), val = tensor([0, 0, 1, 1])]; + tensor var_90_strides_0 = const()[name = tensor("op_90_strides_0"), val = tensor([1, 1])]; + tensor var_90_dilations_0 = const()[name = tensor("op_90_dilations_0"), val = tensor([1, 1])]; + tensor var_90_groups_0 = const()[name = tensor("op_90_groups_0"), val = tensor(1)]; + tensor var_65_to_fp16 = const()[name = tensor("op_65_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor var_71_to_fp16 = const()[name = tensor("op_71_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(491648)))]; + tensor var_90_cast_fp16 = conv(bias = var_71_to_fp16, dilations = var_90_dilations_0, groups = var_90_groups_0, pad = var_90_pad_0, pad_type = var_90_pad_type_0, strides = var_90_strides_0, weight = var_65_to_fp16, x = melspectrogram_features)[name = tensor("op_90_cast_fp16")]; + tensor hidden_states_1_mode_0 = const()[name = tensor("hidden_states_1_mode_0"), val = tensor("EXACT")]; + tensor hidden_states_1_cast_fp16 = gelu(mode = hidden_states_1_mode_0, x = var_90_cast_fp16)[name = tensor("hidden_states_1_cast_fp16")]; + tensor var_130_pad_type_0 = const()[name = tensor("op_130_pad_type_0"), val = tensor("custom")]; + tensor var_130_pad_0 = const()[name = tensor("op_130_pad_0"), val = tensor([0, 0, 1, 1])]; + tensor var_130_strides_0 = const()[name = tensor("op_130_strides_0"), val = tensor([2, 2])]; + tensor var_130_dilations_0 = const()[name = tensor("op_130_dilations_0"), val = tensor([1, 1])]; + tensor var_130_groups_0 = const()[name = tensor("op_130_groups_0"), val = tensor(1)]; + tensor var_105_to_fp16 = const()[name = tensor("op_105_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(493760)))]; + tensor var_111_to_fp16 = const()[name = tensor("op_111_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6785280)))]; + tensor var_130_cast_fp16 = conv(bias = var_111_to_fp16, dilations = var_130_dilations_0, groups = var_130_groups_0, pad = var_130_pad_0, pad_type = var_130_pad_type_0, strides = var_130_strides_0, weight = var_105_to_fp16, x = hidden_states_1_cast_fp16)[name = tensor("op_130_cast_fp16")]; + tensor hidden_states_3_mode_0 = const()[name = tensor("hidden_states_3_mode_0"), val = tensor("EXACT")]; + tensor hidden_states_3_cast_fp16 = gelu(mode = hidden_states_3_mode_0, x = var_130_cast_fp16)[name = tensor("hidden_states_3_cast_fp16")]; + tensor var_148_to_fp16 = const()[name = tensor("op_148_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6787392)))]; + tensor inputs_1_cast_fp16 = add(x = hidden_states_3_cast_fp16, y = var_148_to_fp16)[name = tensor("inputs_1_cast_fp16")]; + tensor var_158 = const()[name = tensor("op_158"), val = tensor(3)]; + tensor out_1_axes_0 = const()[name = tensor("out_1_axes_0"), val = tensor([1])]; + tensor var_180_to_fp16 = const()[name = tensor("op_180_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_1_cast_fp16 = layer_norm(axes = out_1_axes_0, epsilon = var_180_to_fp16, x = inputs_1_cast_fp16)[name = tensor("out_1_cast_fp16")]; + tensor obj_1_mean_0_to_fp16 = const()[name = tensor("obj_1_mean_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9859456)))]; + tensor obj_1_variance_0_to_fp16 = const()[name = tensor("obj_1_variance_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9861568)))]; + tensor obj_1_gamma_0_to_fp16 = const()[name = tensor("obj_1_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9863680)))]; + tensor obj_1_beta_0_to_fp16 = const()[name = tensor("obj_1_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9865792)))]; + tensor obj_1_epsilon_0_to_fp16 = const()[name = tensor("obj_1_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_1_cast_fp16 = batch_norm(beta = obj_1_beta_0_to_fp16, epsilon = obj_1_epsilon_0_to_fp16, gamma = obj_1_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_1_cast_fp16)[name = tensor("obj_1_cast_fp16")]; + tensor query_1_pad_type_0 = const()[name = tensor("query_1_pad_type_0"), val = tensor("valid")]; + tensor query_1_strides_0 = const()[name = tensor("query_1_strides_0"), val = tensor([1, 1])]; + tensor query_1_pad_0 = const()[name = tensor("query_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_1_dilations_0 = const()[name = tensor("query_1_dilations_0"), val = tensor([1, 1])]; + tensor query_1_groups_0 = const()[name = tensor("query_1_groups_0"), val = tensor(1)]; + tensor layers_0_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9867904)))]; + tensor layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11965120)))]; + tensor query_1_cast_fp16 = conv(bias = layers_0_self_attn_q_proj_bias_to_fp16, dilations = query_1_dilations_0, groups = query_1_groups_0, pad = query_1_pad_0, pad_type = query_1_pad_type_0, strides = query_1_strides_0, weight = layers_0_self_attn_q_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("query_1_cast_fp16")]; + tensor key_1_pad_type_0 = const()[name = tensor("key_1_pad_type_0"), val = tensor("valid")]; + tensor key_1_strides_0 = const()[name = tensor("key_1_strides_0"), val = tensor([1, 1])]; + tensor key_1_pad_0 = const()[name = tensor("key_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_1_dilations_0 = const()[name = tensor("key_1_dilations_0"), val = tensor([1, 1])]; + tensor key_1_groups_0 = const()[name = tensor("key_1_groups_0"), val = tensor(1)]; + tensor layers_0_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11967232)))]; + tensor key_1_cast_fp16 = conv(dilations = key_1_dilations_0, groups = key_1_groups_0, pad = key_1_pad_0, pad_type = key_1_pad_type_0, strides = key_1_strides_0, weight = layers_0_self_attn_k_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("key_1_cast_fp16")]; + tensor value_1_pad_type_0 = const()[name = tensor("value_1_pad_type_0"), val = tensor("valid")]; + tensor value_1_strides_0 = const()[name = tensor("value_1_strides_0"), val = tensor([1, 1])]; + tensor value_1_pad_0 = const()[name = tensor("value_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_1_dilations_0 = const()[name = tensor("value_1_dilations_0"), val = tensor([1, 1])]; + tensor value_1_groups_0 = const()[name = tensor("value_1_groups_0"), val = tensor(1)]; + tensor layers_0_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14064448)))]; + tensor layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16161664)))]; + tensor value_1_cast_fp16 = conv(bias = layers_0_self_attn_v_proj_bias_to_fp16, dilations = value_1_dilations_0, groups = value_1_groups_0, pad = value_1_pad_0, pad_type = value_1_pad_type_0, strides = value_1_strides_0, weight = layers_0_self_attn_v_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("value_1_cast_fp16")]; + tensor var_216 = const()[name = tensor("op_216"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_1_cast_fp16 = reshape(shape = var_216, x = query_1_cast_fp16)[name = tensor("mh_q_1_cast_fp16")]; + tensor var_218_to_fp16 = const()[name = tensor("op_218_to_fp16"), val = tensor(0x1p-3)]; + tensor var_219_cast_fp16 = mul(x = mh_q_1_cast_fp16, y = var_218_to_fp16)[name = tensor("op_219_cast_fp16")]; + tensor var_222 = const()[name = tensor("op_222"), val = tensor([1, 16, 64, 1500])]; + tensor var_223_cast_fp16 = reshape(shape = var_222, x = key_1_cast_fp16)[name = tensor("op_223_cast_fp16")]; + tensor mh_w_1_transpose_x_0 = const()[name = tensor("mh_w_1_transpose_x_0"), val = tensor(true)]; + tensor mh_w_1_transpose_y_0 = const()[name = tensor("mh_w_1_transpose_y_0"), val = tensor(false)]; + tensor mh_w_1_cast_fp16 = matmul(transpose_x = mh_w_1_transpose_x_0, transpose_y = mh_w_1_transpose_y_0, x = var_219_cast_fp16, y = var_223_cast_fp16)[name = tensor("mh_w_1_cast_fp16")]; + tensor var_226_cast_fp16 = softmax(axis = var_158, x = mh_w_1_cast_fp16)[name = tensor("op_226_cast_fp16")]; + tensor var_227 = const()[name = tensor("op_227"), val = tensor([1, 16, 64, 1500])]; + tensor var_228_cast_fp16 = reshape(shape = var_227, x = value_1_cast_fp16)[name = tensor("op_228_cast_fp16")]; + tensor attn_1_transpose_x_0 = const()[name = tensor("attn_1_transpose_x_0"), val = tensor(false)]; + tensor attn_1_transpose_y_0 = const()[name = tensor("attn_1_transpose_y_0"), val = tensor(true)]; + tensor attn_1_cast_fp16 = matmul(transpose_x = attn_1_transpose_x_0, transpose_y = attn_1_transpose_y_0, x = var_228_cast_fp16, y = var_226_cast_fp16)[name = tensor("attn_1_cast_fp16")]; + tensor var_231 = const()[name = tensor("op_231"), val = tensor([1, 1024, 1, 1500])]; + tensor input_1_cast_fp16 = reshape(shape = var_231, x = attn_1_cast_fp16)[name = tensor("input_1_cast_fp16")]; + tensor obj_3_pad_type_0 = const()[name = tensor("obj_3_pad_type_0"), val = tensor("valid")]; + tensor obj_3_strides_0 = const()[name = tensor("obj_3_strides_0"), val = tensor([1, 1])]; + tensor obj_3_pad_0 = const()[name = tensor("obj_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_3_dilations_0 = const()[name = tensor("obj_3_dilations_0"), val = tensor([1, 1])]; + tensor obj_3_groups_0 = const()[name = tensor("obj_3_groups_0"), val = tensor(1)]; + tensor layers_0_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16163776)))]; + tensor layers_0_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18260992)))]; + tensor obj_3_cast_fp16 = conv(bias = layers_0_self_attn_o_proj_bias_to_fp16, dilations = obj_3_dilations_0, groups = obj_3_groups_0, pad = obj_3_pad_0, pad_type = obj_3_pad_type_0, strides = obj_3_strides_0, weight = layers_0_self_attn_o_proj_weight_to_fp16, x = input_1_cast_fp16)[name = tensor("obj_3_cast_fp16")]; + tensor inputs_3_cast_fp16 = add(x = inputs_1_cast_fp16, y = obj_3_cast_fp16)[name = tensor("inputs_3_cast_fp16")]; + tensor out_3_axes_0 = const()[name = tensor("out_3_axes_0"), val = tensor([1])]; + tensor var_249_to_fp16 = const()[name = tensor("op_249_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_3_cast_fp16 = layer_norm(axes = out_3_axes_0, epsilon = var_249_to_fp16, x = inputs_3_cast_fp16)[name = tensor("out_3_cast_fp16")]; + tensor input_3_gamma_0_to_fp16 = const()[name = tensor("input_3_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18263104)))]; + tensor input_3_beta_0_to_fp16 = const()[name = tensor("input_3_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18265216)))]; + tensor input_3_epsilon_0_to_fp16 = const()[name = tensor("input_3_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_3_cast_fp16 = batch_norm(beta = input_3_beta_0_to_fp16, epsilon = input_3_epsilon_0_to_fp16, gamma = input_3_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_3_cast_fp16)[name = tensor("input_3_cast_fp16")]; + tensor input_5_pad_type_0 = const()[name = tensor("input_5_pad_type_0"), val = tensor("valid")]; + tensor input_5_strides_0 = const()[name = tensor("input_5_strides_0"), val = tensor([1, 1])]; + tensor input_5_pad_0 = const()[name = tensor("input_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_5_dilations_0 = const()[name = tensor("input_5_dilations_0"), val = tensor([1, 1])]; + tensor input_5_groups_0 = const()[name = tensor("input_5_groups_0"), val = tensor(1)]; + tensor layers_0_fc1_weight_to_fp16 = const()[name = tensor("layers_0_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18267328)))]; + tensor layers_0_fc1_bias_to_fp16 = const()[name = tensor("layers_0_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26656000)))]; + tensor input_5_cast_fp16 = conv(bias = layers_0_fc1_bias_to_fp16, dilations = input_5_dilations_0, groups = input_5_groups_0, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = input_5_strides_0, weight = layers_0_fc1_weight_to_fp16, x = input_3_cast_fp16)[name = tensor("input_5_cast_fp16")]; + tensor input_7_mode_0 = const()[name = tensor("input_7_mode_0"), val = tensor("EXACT")]; + tensor input_7_cast_fp16 = gelu(mode = input_7_mode_0, x = input_5_cast_fp16)[name = tensor("input_7_cast_fp16")]; + tensor hidden_states_5_pad_type_0 = const()[name = tensor("hidden_states_5_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_5_strides_0 = const()[name = tensor("hidden_states_5_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_5_pad_0 = const()[name = tensor("hidden_states_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_5_dilations_0 = const()[name = tensor("hidden_states_5_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_5_groups_0 = const()[name = tensor("hidden_states_5_groups_0"), val = tensor(1)]; + tensor layers_0_fc2_weight_to_fp16 = const()[name = tensor("layers_0_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26664256)))]; + tensor layers_0_fc2_bias_to_fp16 = const()[name = tensor("layers_0_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35052928)))]; + tensor hidden_states_5_cast_fp16 = conv(bias = layers_0_fc2_bias_to_fp16, dilations = hidden_states_5_dilations_0, groups = hidden_states_5_groups_0, pad = hidden_states_5_pad_0, pad_type = hidden_states_5_pad_type_0, strides = hidden_states_5_strides_0, weight = layers_0_fc2_weight_to_fp16, x = input_7_cast_fp16)[name = tensor("hidden_states_5_cast_fp16")]; + tensor inputs_5_cast_fp16 = add(x = inputs_3_cast_fp16, y = hidden_states_5_cast_fp16)[name = tensor("inputs_5_cast_fp16")]; + tensor var_278 = const()[name = tensor("op_278"), val = tensor(3)]; + tensor out_5_axes_0 = const()[name = tensor("out_5_axes_0"), val = tensor([1])]; + tensor var_300_to_fp16 = const()[name = tensor("op_300_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_5_cast_fp16 = layer_norm(axes = out_5_axes_0, epsilon = var_300_to_fp16, x = inputs_5_cast_fp16)[name = tensor("out_5_cast_fp16")]; + tensor obj_5_gamma_0_to_fp16 = const()[name = tensor("obj_5_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35055040)))]; + tensor obj_5_beta_0_to_fp16 = const()[name = tensor("obj_5_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35057152)))]; + tensor obj_5_epsilon_0_to_fp16 = const()[name = tensor("obj_5_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_5_cast_fp16 = batch_norm(beta = obj_5_beta_0_to_fp16, epsilon = obj_5_epsilon_0_to_fp16, gamma = obj_5_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_5_cast_fp16)[name = tensor("obj_5_cast_fp16")]; + tensor query_3_pad_type_0 = const()[name = tensor("query_3_pad_type_0"), val = tensor("valid")]; + tensor query_3_strides_0 = const()[name = tensor("query_3_strides_0"), val = tensor([1, 1])]; + tensor query_3_pad_0 = const()[name = tensor("query_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_3_dilations_0 = const()[name = tensor("query_3_dilations_0"), val = tensor([1, 1])]; + tensor query_3_groups_0 = const()[name = tensor("query_3_groups_0"), val = tensor(1)]; + tensor layers_1_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35059264)))]; + tensor layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37156480)))]; + tensor query_3_cast_fp16 = conv(bias = layers_1_self_attn_q_proj_bias_to_fp16, dilations = query_3_dilations_0, groups = query_3_groups_0, pad = query_3_pad_0, pad_type = query_3_pad_type_0, strides = query_3_strides_0, weight = layers_1_self_attn_q_proj_weight_to_fp16, x = obj_5_cast_fp16)[name = tensor("query_3_cast_fp16")]; + tensor key_3_pad_type_0 = const()[name = tensor("key_3_pad_type_0"), val = tensor("valid")]; + tensor key_3_strides_0 = const()[name = tensor("key_3_strides_0"), val = tensor([1, 1])]; + tensor key_3_pad_0 = const()[name = tensor("key_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_3_dilations_0 = const()[name = tensor("key_3_dilations_0"), val = tensor([1, 1])]; + tensor key_3_groups_0 = const()[name = tensor("key_3_groups_0"), val = tensor(1)]; + tensor layers_1_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37158592)))]; + tensor key_3_cast_fp16 = conv(dilations = key_3_dilations_0, groups = key_3_groups_0, pad = key_3_pad_0, pad_type = key_3_pad_type_0, strides = key_3_strides_0, weight = layers_1_self_attn_k_proj_weight_to_fp16, x = obj_5_cast_fp16)[name = tensor("key_3_cast_fp16")]; + tensor value_3_pad_type_0 = const()[name = tensor("value_3_pad_type_0"), val = tensor("valid")]; + tensor value_3_strides_0 = const()[name = tensor("value_3_strides_0"), val = tensor([1, 1])]; + tensor value_3_pad_0 = const()[name = tensor("value_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_3_dilations_0 = const()[name = tensor("value_3_dilations_0"), val = tensor([1, 1])]; + tensor value_3_groups_0 = const()[name = tensor("value_3_groups_0"), val = tensor(1)]; + tensor layers_1_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39255808)))]; + tensor layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41353024)))]; + tensor value_3_cast_fp16 = conv(bias = layers_1_self_attn_v_proj_bias_to_fp16, dilations = value_3_dilations_0, groups = value_3_groups_0, pad = value_3_pad_0, pad_type = value_3_pad_type_0, strides = value_3_strides_0, weight = layers_1_self_attn_v_proj_weight_to_fp16, x = obj_5_cast_fp16)[name = tensor("value_3_cast_fp16")]; + tensor var_336 = const()[name = tensor("op_336"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_3_cast_fp16 = reshape(shape = var_336, x = query_3_cast_fp16)[name = tensor("mh_q_3_cast_fp16")]; + tensor var_338_to_fp16 = const()[name = tensor("op_338_to_fp16"), val = tensor(0x1p-3)]; + tensor var_339_cast_fp16 = mul(x = mh_q_3_cast_fp16, y = var_338_to_fp16)[name = tensor("op_339_cast_fp16")]; + tensor var_342 = const()[name = tensor("op_342"), val = tensor([1, 16, 64, 1500])]; + tensor var_343_cast_fp16 = reshape(shape = var_342, x = key_3_cast_fp16)[name = tensor("op_343_cast_fp16")]; + tensor mh_w_3_transpose_x_0 = const()[name = tensor("mh_w_3_transpose_x_0"), val = tensor(true)]; + tensor mh_w_3_transpose_y_0 = const()[name = tensor("mh_w_3_transpose_y_0"), val = tensor(false)]; + tensor mh_w_3_cast_fp16 = matmul(transpose_x = mh_w_3_transpose_x_0, transpose_y = mh_w_3_transpose_y_0, x = var_339_cast_fp16, y = var_343_cast_fp16)[name = tensor("mh_w_3_cast_fp16")]; + tensor var_346_cast_fp16 = softmax(axis = var_278, x = mh_w_3_cast_fp16)[name = tensor("op_346_cast_fp16")]; + tensor var_347 = const()[name = tensor("op_347"), val = tensor([1, 16, 64, 1500])]; + tensor var_348_cast_fp16 = reshape(shape = var_347, x = value_3_cast_fp16)[name = tensor("op_348_cast_fp16")]; + tensor attn_3_transpose_x_0 = const()[name = tensor("attn_3_transpose_x_0"), val = tensor(false)]; + tensor attn_3_transpose_y_0 = const()[name = tensor("attn_3_transpose_y_0"), val = tensor(true)]; + tensor attn_3_cast_fp16 = matmul(transpose_x = attn_3_transpose_x_0, transpose_y = attn_3_transpose_y_0, x = var_348_cast_fp16, y = var_346_cast_fp16)[name = tensor("attn_3_cast_fp16")]; + tensor var_351 = const()[name = tensor("op_351"), val = tensor([1, 1024, 1, 1500])]; + tensor input_9_cast_fp16 = reshape(shape = var_351, x = attn_3_cast_fp16)[name = tensor("input_9_cast_fp16")]; + tensor obj_7_pad_type_0 = const()[name = tensor("obj_7_pad_type_0"), val = tensor("valid")]; + tensor obj_7_strides_0 = const()[name = tensor("obj_7_strides_0"), val = tensor([1, 1])]; + tensor obj_7_pad_0 = const()[name = tensor("obj_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_7_dilations_0 = const()[name = tensor("obj_7_dilations_0"), val = tensor([1, 1])]; + tensor obj_7_groups_0 = const()[name = tensor("obj_7_groups_0"), val = tensor(1)]; + tensor layers_1_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41355136)))]; + tensor layers_1_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(43452352)))]; + tensor obj_7_cast_fp16 = conv(bias = layers_1_self_attn_o_proj_bias_to_fp16, dilations = obj_7_dilations_0, groups = obj_7_groups_0, pad = obj_7_pad_0, pad_type = obj_7_pad_type_0, strides = obj_7_strides_0, weight = layers_1_self_attn_o_proj_weight_to_fp16, x = input_9_cast_fp16)[name = tensor("obj_7_cast_fp16")]; + tensor inputs_7_cast_fp16 = add(x = inputs_5_cast_fp16, y = obj_7_cast_fp16)[name = tensor("inputs_7_cast_fp16")]; + tensor out_7_axes_0 = const()[name = tensor("out_7_axes_0"), val = tensor([1])]; + tensor var_369_to_fp16 = const()[name = tensor("op_369_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_7_cast_fp16 = layer_norm(axes = out_7_axes_0, epsilon = var_369_to_fp16, x = inputs_7_cast_fp16)[name = tensor("out_7_cast_fp16")]; + tensor input_11_gamma_0_to_fp16 = const()[name = tensor("input_11_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(43454464)))]; + tensor input_11_beta_0_to_fp16 = const()[name = tensor("input_11_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(43456576)))]; + tensor input_11_epsilon_0_to_fp16 = const()[name = tensor("input_11_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_11_cast_fp16 = batch_norm(beta = input_11_beta_0_to_fp16, epsilon = input_11_epsilon_0_to_fp16, gamma = input_11_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_7_cast_fp16)[name = tensor("input_11_cast_fp16")]; + tensor input_13_pad_type_0 = const()[name = tensor("input_13_pad_type_0"), val = tensor("valid")]; + tensor input_13_strides_0 = const()[name = tensor("input_13_strides_0"), val = tensor([1, 1])]; + tensor input_13_pad_0 = const()[name = tensor("input_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_13_dilations_0 = const()[name = tensor("input_13_dilations_0"), val = tensor([1, 1])]; + tensor input_13_groups_0 = const()[name = tensor("input_13_groups_0"), val = tensor(1)]; + tensor layers_1_fc1_weight_to_fp16 = const()[name = tensor("layers_1_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(43458688)))]; + tensor layers_1_fc1_bias_to_fp16 = const()[name = tensor("layers_1_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51847360)))]; + tensor input_13_cast_fp16 = conv(bias = layers_1_fc1_bias_to_fp16, dilations = input_13_dilations_0, groups = input_13_groups_0, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = input_13_strides_0, weight = layers_1_fc1_weight_to_fp16, x = input_11_cast_fp16)[name = tensor("input_13_cast_fp16")]; + tensor input_15_mode_0 = const()[name = tensor("input_15_mode_0"), val = tensor("EXACT")]; + tensor input_15_cast_fp16 = gelu(mode = input_15_mode_0, x = input_13_cast_fp16)[name = tensor("input_15_cast_fp16")]; + tensor hidden_states_7_pad_type_0 = const()[name = tensor("hidden_states_7_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_7_strides_0 = const()[name = tensor("hidden_states_7_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_7_pad_0 = const()[name = tensor("hidden_states_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_7_dilations_0 = const()[name = tensor("hidden_states_7_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_7_groups_0 = const()[name = tensor("hidden_states_7_groups_0"), val = tensor(1)]; + tensor layers_1_fc2_weight_to_fp16 = const()[name = tensor("layers_1_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51855616)))]; + tensor layers_1_fc2_bias_to_fp16 = const()[name = tensor("layers_1_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60244288)))]; + tensor hidden_states_7_cast_fp16 = conv(bias = layers_1_fc2_bias_to_fp16, dilations = hidden_states_7_dilations_0, groups = hidden_states_7_groups_0, pad = hidden_states_7_pad_0, pad_type = hidden_states_7_pad_type_0, strides = hidden_states_7_strides_0, weight = layers_1_fc2_weight_to_fp16, x = input_15_cast_fp16)[name = tensor("hidden_states_7_cast_fp16")]; + tensor inputs_9_cast_fp16 = add(x = inputs_7_cast_fp16, y = hidden_states_7_cast_fp16)[name = tensor("inputs_9_cast_fp16")]; + tensor var_398 = const()[name = tensor("op_398"), val = tensor(3)]; + tensor out_9_axes_0 = const()[name = tensor("out_9_axes_0"), val = tensor([1])]; + tensor var_420_to_fp16 = const()[name = tensor("op_420_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_9_cast_fp16 = layer_norm(axes = out_9_axes_0, epsilon = var_420_to_fp16, x = inputs_9_cast_fp16)[name = tensor("out_9_cast_fp16")]; + tensor obj_9_gamma_0_to_fp16 = const()[name = tensor("obj_9_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60246400)))]; + tensor obj_9_beta_0_to_fp16 = const()[name = tensor("obj_9_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60248512)))]; + tensor obj_9_epsilon_0_to_fp16 = const()[name = tensor("obj_9_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_9_cast_fp16 = batch_norm(beta = obj_9_beta_0_to_fp16, epsilon = obj_9_epsilon_0_to_fp16, gamma = obj_9_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_9_cast_fp16)[name = tensor("obj_9_cast_fp16")]; + tensor query_5_pad_type_0 = const()[name = tensor("query_5_pad_type_0"), val = tensor("valid")]; + tensor query_5_strides_0 = const()[name = tensor("query_5_strides_0"), val = tensor([1, 1])]; + tensor query_5_pad_0 = const()[name = tensor("query_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_5_dilations_0 = const()[name = tensor("query_5_dilations_0"), val = tensor([1, 1])]; + tensor query_5_groups_0 = const()[name = tensor("query_5_groups_0"), val = tensor(1)]; + tensor layers_2_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60250624)))]; + tensor layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62347840)))]; + tensor query_5_cast_fp16 = conv(bias = layers_2_self_attn_q_proj_bias_to_fp16, dilations = query_5_dilations_0, groups = query_5_groups_0, pad = query_5_pad_0, pad_type = query_5_pad_type_0, strides = query_5_strides_0, weight = layers_2_self_attn_q_proj_weight_to_fp16, x = obj_9_cast_fp16)[name = tensor("query_5_cast_fp16")]; + tensor key_5_pad_type_0 = const()[name = tensor("key_5_pad_type_0"), val = tensor("valid")]; + tensor key_5_strides_0 = const()[name = tensor("key_5_strides_0"), val = tensor([1, 1])]; + tensor key_5_pad_0 = const()[name = tensor("key_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_5_dilations_0 = const()[name = tensor("key_5_dilations_0"), val = tensor([1, 1])]; + tensor key_5_groups_0 = const()[name = tensor("key_5_groups_0"), val = tensor(1)]; + tensor layers_2_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62349952)))]; + tensor key_5_cast_fp16 = conv(dilations = key_5_dilations_0, groups = key_5_groups_0, pad = key_5_pad_0, pad_type = key_5_pad_type_0, strides = key_5_strides_0, weight = layers_2_self_attn_k_proj_weight_to_fp16, x = obj_9_cast_fp16)[name = tensor("key_5_cast_fp16")]; + tensor value_5_pad_type_0 = const()[name = tensor("value_5_pad_type_0"), val = tensor("valid")]; + tensor value_5_strides_0 = const()[name = tensor("value_5_strides_0"), val = tensor([1, 1])]; + tensor value_5_pad_0 = const()[name = tensor("value_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_5_dilations_0 = const()[name = tensor("value_5_dilations_0"), val = tensor([1, 1])]; + tensor value_5_groups_0 = const()[name = tensor("value_5_groups_0"), val = tensor(1)]; + tensor layers_2_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64447168)))]; + tensor layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66544384)))]; + tensor value_5_cast_fp16 = conv(bias = layers_2_self_attn_v_proj_bias_to_fp16, dilations = value_5_dilations_0, groups = value_5_groups_0, pad = value_5_pad_0, pad_type = value_5_pad_type_0, strides = value_5_strides_0, weight = layers_2_self_attn_v_proj_weight_to_fp16, x = obj_9_cast_fp16)[name = tensor("value_5_cast_fp16")]; + tensor var_456 = const()[name = tensor("op_456"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_5_cast_fp16 = reshape(shape = var_456, x = query_5_cast_fp16)[name = tensor("mh_q_5_cast_fp16")]; + tensor var_458_to_fp16 = const()[name = tensor("op_458_to_fp16"), val = tensor(0x1p-3)]; + tensor var_459_cast_fp16 = mul(x = mh_q_5_cast_fp16, y = var_458_to_fp16)[name = tensor("op_459_cast_fp16")]; + tensor var_462 = const()[name = tensor("op_462"), val = tensor([1, 16, 64, 1500])]; + tensor var_463_cast_fp16 = reshape(shape = var_462, x = key_5_cast_fp16)[name = tensor("op_463_cast_fp16")]; + tensor mh_w_5_transpose_x_0 = const()[name = tensor("mh_w_5_transpose_x_0"), val = tensor(true)]; + tensor mh_w_5_transpose_y_0 = const()[name = tensor("mh_w_5_transpose_y_0"), val = tensor(false)]; + tensor mh_w_5_cast_fp16 = matmul(transpose_x = mh_w_5_transpose_x_0, transpose_y = mh_w_5_transpose_y_0, x = var_459_cast_fp16, y = var_463_cast_fp16)[name = tensor("mh_w_5_cast_fp16")]; + tensor var_466_cast_fp16 = softmax(axis = var_398, x = mh_w_5_cast_fp16)[name = tensor("op_466_cast_fp16")]; + tensor var_467 = const()[name = tensor("op_467"), val = tensor([1, 16, 64, 1500])]; + tensor var_468_cast_fp16 = reshape(shape = var_467, x = value_5_cast_fp16)[name = tensor("op_468_cast_fp16")]; + tensor attn_5_transpose_x_0 = const()[name = tensor("attn_5_transpose_x_0"), val = tensor(false)]; + tensor attn_5_transpose_y_0 = const()[name = tensor("attn_5_transpose_y_0"), val = tensor(true)]; + tensor attn_5_cast_fp16 = matmul(transpose_x = attn_5_transpose_x_0, transpose_y = attn_5_transpose_y_0, x = var_468_cast_fp16, y = var_466_cast_fp16)[name = tensor("attn_5_cast_fp16")]; + tensor var_471 = const()[name = tensor("op_471"), val = tensor([1, 1024, 1, 1500])]; + tensor input_17_cast_fp16 = reshape(shape = var_471, x = attn_5_cast_fp16)[name = tensor("input_17_cast_fp16")]; + tensor obj_11_pad_type_0 = const()[name = tensor("obj_11_pad_type_0"), val = tensor("valid")]; + tensor obj_11_strides_0 = const()[name = tensor("obj_11_strides_0"), val = tensor([1, 1])]; + tensor obj_11_pad_0 = const()[name = tensor("obj_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_11_dilations_0 = const()[name = tensor("obj_11_dilations_0"), val = tensor([1, 1])]; + tensor obj_11_groups_0 = const()[name = tensor("obj_11_groups_0"), val = tensor(1)]; + tensor layers_2_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66546496)))]; + tensor layers_2_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(68643712)))]; + tensor obj_11_cast_fp16 = conv(bias = layers_2_self_attn_o_proj_bias_to_fp16, dilations = obj_11_dilations_0, groups = obj_11_groups_0, pad = obj_11_pad_0, pad_type = obj_11_pad_type_0, strides = obj_11_strides_0, weight = layers_2_self_attn_o_proj_weight_to_fp16, x = input_17_cast_fp16)[name = tensor("obj_11_cast_fp16")]; + tensor inputs_11_cast_fp16 = add(x = inputs_9_cast_fp16, y = obj_11_cast_fp16)[name = tensor("inputs_11_cast_fp16")]; + tensor out_11_axes_0 = const()[name = tensor("out_11_axes_0"), val = tensor([1])]; + tensor var_489_to_fp16 = const()[name = tensor("op_489_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_11_cast_fp16 = layer_norm(axes = out_11_axes_0, epsilon = var_489_to_fp16, x = inputs_11_cast_fp16)[name = tensor("out_11_cast_fp16")]; + tensor input_19_gamma_0_to_fp16 = const()[name = tensor("input_19_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(68645824)))]; + tensor input_19_beta_0_to_fp16 = const()[name = tensor("input_19_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(68647936)))]; + tensor input_19_epsilon_0_to_fp16 = const()[name = tensor("input_19_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_19_cast_fp16 = batch_norm(beta = input_19_beta_0_to_fp16, epsilon = input_19_epsilon_0_to_fp16, gamma = input_19_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_11_cast_fp16)[name = tensor("input_19_cast_fp16")]; + tensor input_21_pad_type_0 = const()[name = tensor("input_21_pad_type_0"), val = tensor("valid")]; + tensor input_21_strides_0 = const()[name = tensor("input_21_strides_0"), val = tensor([1, 1])]; + tensor input_21_pad_0 = const()[name = tensor("input_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_21_dilations_0 = const()[name = tensor("input_21_dilations_0"), val = tensor([1, 1])]; + tensor input_21_groups_0 = const()[name = tensor("input_21_groups_0"), val = tensor(1)]; + tensor layers_2_fc1_weight_to_fp16 = const()[name = tensor("layers_2_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(68650048)))]; + tensor layers_2_fc1_bias_to_fp16 = const()[name = tensor("layers_2_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77038720)))]; + tensor input_21_cast_fp16 = conv(bias = layers_2_fc1_bias_to_fp16, dilations = input_21_dilations_0, groups = input_21_groups_0, pad = input_21_pad_0, pad_type = input_21_pad_type_0, strides = input_21_strides_0, weight = layers_2_fc1_weight_to_fp16, x = input_19_cast_fp16)[name = tensor("input_21_cast_fp16")]; + tensor input_23_mode_0 = const()[name = tensor("input_23_mode_0"), val = tensor("EXACT")]; + tensor input_23_cast_fp16 = gelu(mode = input_23_mode_0, x = input_21_cast_fp16)[name = tensor("input_23_cast_fp16")]; + tensor hidden_states_9_pad_type_0 = const()[name = tensor("hidden_states_9_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_9_strides_0 = const()[name = tensor("hidden_states_9_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_9_pad_0 = const()[name = tensor("hidden_states_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_9_dilations_0 = const()[name = tensor("hidden_states_9_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_9_groups_0 = const()[name = tensor("hidden_states_9_groups_0"), val = tensor(1)]; + tensor layers_2_fc2_weight_to_fp16 = const()[name = tensor("layers_2_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77046976)))]; + tensor layers_2_fc2_bias_to_fp16 = const()[name = tensor("layers_2_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85435648)))]; + tensor hidden_states_9_cast_fp16 = conv(bias = layers_2_fc2_bias_to_fp16, dilations = hidden_states_9_dilations_0, groups = hidden_states_9_groups_0, pad = hidden_states_9_pad_0, pad_type = hidden_states_9_pad_type_0, strides = hidden_states_9_strides_0, weight = layers_2_fc2_weight_to_fp16, x = input_23_cast_fp16)[name = tensor("hidden_states_9_cast_fp16")]; + tensor inputs_13_cast_fp16 = add(x = inputs_11_cast_fp16, y = hidden_states_9_cast_fp16)[name = tensor("inputs_13_cast_fp16")]; + tensor var_518 = const()[name = tensor("op_518"), val = tensor(3)]; + tensor out_13_axes_0 = const()[name = tensor("out_13_axes_0"), val = tensor([1])]; + tensor var_540_to_fp16 = const()[name = tensor("op_540_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_13_cast_fp16 = layer_norm(axes = out_13_axes_0, epsilon = var_540_to_fp16, x = inputs_13_cast_fp16)[name = tensor("out_13_cast_fp16")]; + tensor obj_13_gamma_0_to_fp16 = const()[name = tensor("obj_13_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85437760)))]; + tensor obj_13_beta_0_to_fp16 = const()[name = tensor("obj_13_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85439872)))]; + tensor obj_13_epsilon_0_to_fp16 = const()[name = tensor("obj_13_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_13_cast_fp16 = batch_norm(beta = obj_13_beta_0_to_fp16, epsilon = obj_13_epsilon_0_to_fp16, gamma = obj_13_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_13_cast_fp16)[name = tensor("obj_13_cast_fp16")]; + tensor query_7_pad_type_0 = const()[name = tensor("query_7_pad_type_0"), val = tensor("valid")]; + tensor query_7_strides_0 = const()[name = tensor("query_7_strides_0"), val = tensor([1, 1])]; + tensor query_7_pad_0 = const()[name = tensor("query_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_7_dilations_0 = const()[name = tensor("query_7_dilations_0"), val = tensor([1, 1])]; + tensor query_7_groups_0 = const()[name = tensor("query_7_groups_0"), val = tensor(1)]; + tensor layers_3_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85441984)))]; + tensor layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87539200)))]; + tensor query_7_cast_fp16 = conv(bias = layers_3_self_attn_q_proj_bias_to_fp16, dilations = query_7_dilations_0, groups = query_7_groups_0, pad = query_7_pad_0, pad_type = query_7_pad_type_0, strides = query_7_strides_0, weight = layers_3_self_attn_q_proj_weight_to_fp16, x = obj_13_cast_fp16)[name = tensor("query_7_cast_fp16")]; + tensor key_7_pad_type_0 = const()[name = tensor("key_7_pad_type_0"), val = tensor("valid")]; + tensor key_7_strides_0 = const()[name = tensor("key_7_strides_0"), val = tensor([1, 1])]; + tensor key_7_pad_0 = const()[name = tensor("key_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_7_dilations_0 = const()[name = tensor("key_7_dilations_0"), val = tensor([1, 1])]; + tensor key_7_groups_0 = const()[name = tensor("key_7_groups_0"), val = tensor(1)]; + tensor layers_3_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87541312)))]; + tensor key_7_cast_fp16 = conv(dilations = key_7_dilations_0, groups = key_7_groups_0, pad = key_7_pad_0, pad_type = key_7_pad_type_0, strides = key_7_strides_0, weight = layers_3_self_attn_k_proj_weight_to_fp16, x = obj_13_cast_fp16)[name = tensor("key_7_cast_fp16")]; + tensor value_7_pad_type_0 = const()[name = tensor("value_7_pad_type_0"), val = tensor("valid")]; + tensor value_7_strides_0 = const()[name = tensor("value_7_strides_0"), val = tensor([1, 1])]; + tensor value_7_pad_0 = const()[name = tensor("value_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_7_dilations_0 = const()[name = tensor("value_7_dilations_0"), val = tensor([1, 1])]; + tensor value_7_groups_0 = const()[name = tensor("value_7_groups_0"), val = tensor(1)]; + tensor layers_3_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89638528)))]; + tensor layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91735744)))]; + tensor value_7_cast_fp16 = conv(bias = layers_3_self_attn_v_proj_bias_to_fp16, dilations = value_7_dilations_0, groups = value_7_groups_0, pad = value_7_pad_0, pad_type = value_7_pad_type_0, strides = value_7_strides_0, weight = layers_3_self_attn_v_proj_weight_to_fp16, x = obj_13_cast_fp16)[name = tensor("value_7_cast_fp16")]; + tensor var_576 = const()[name = tensor("op_576"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_7_cast_fp16 = reshape(shape = var_576, x = query_7_cast_fp16)[name = tensor("mh_q_7_cast_fp16")]; + tensor var_578_to_fp16 = const()[name = tensor("op_578_to_fp16"), val = tensor(0x1p-3)]; + tensor var_579_cast_fp16 = mul(x = mh_q_7_cast_fp16, y = var_578_to_fp16)[name = tensor("op_579_cast_fp16")]; + tensor var_582 = const()[name = tensor("op_582"), val = tensor([1, 16, 64, 1500])]; + tensor var_583_cast_fp16 = reshape(shape = var_582, x = key_7_cast_fp16)[name = tensor("op_583_cast_fp16")]; + tensor mh_w_7_transpose_x_0 = const()[name = tensor("mh_w_7_transpose_x_0"), val = tensor(true)]; + tensor mh_w_7_transpose_y_0 = const()[name = tensor("mh_w_7_transpose_y_0"), val = tensor(false)]; + tensor mh_w_7_cast_fp16 = matmul(transpose_x = mh_w_7_transpose_x_0, transpose_y = mh_w_7_transpose_y_0, x = var_579_cast_fp16, y = var_583_cast_fp16)[name = tensor("mh_w_7_cast_fp16")]; + tensor var_586_cast_fp16 = softmax(axis = var_518, x = mh_w_7_cast_fp16)[name = tensor("op_586_cast_fp16")]; + tensor var_587 = const()[name = tensor("op_587"), val = tensor([1, 16, 64, 1500])]; + tensor var_588_cast_fp16 = reshape(shape = var_587, x = value_7_cast_fp16)[name = tensor("op_588_cast_fp16")]; + tensor attn_7_transpose_x_0 = const()[name = tensor("attn_7_transpose_x_0"), val = tensor(false)]; + tensor attn_7_transpose_y_0 = const()[name = tensor("attn_7_transpose_y_0"), val = tensor(true)]; + tensor attn_7_cast_fp16 = matmul(transpose_x = attn_7_transpose_x_0, transpose_y = attn_7_transpose_y_0, x = var_588_cast_fp16, y = var_586_cast_fp16)[name = tensor("attn_7_cast_fp16")]; + tensor var_591 = const()[name = tensor("op_591"), val = tensor([1, 1024, 1, 1500])]; + tensor input_25_cast_fp16 = reshape(shape = var_591, x = attn_7_cast_fp16)[name = tensor("input_25_cast_fp16")]; + tensor obj_15_pad_type_0 = const()[name = tensor("obj_15_pad_type_0"), val = tensor("valid")]; + tensor obj_15_strides_0 = const()[name = tensor("obj_15_strides_0"), val = tensor([1, 1])]; + tensor obj_15_pad_0 = const()[name = tensor("obj_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_15_dilations_0 = const()[name = tensor("obj_15_dilations_0"), val = tensor([1, 1])]; + tensor obj_15_groups_0 = const()[name = tensor("obj_15_groups_0"), val = tensor(1)]; + tensor layers_3_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91737856)))]; + tensor layers_3_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93835072)))]; + tensor obj_15_cast_fp16 = conv(bias = layers_3_self_attn_o_proj_bias_to_fp16, dilations = obj_15_dilations_0, groups = obj_15_groups_0, pad = obj_15_pad_0, pad_type = obj_15_pad_type_0, strides = obj_15_strides_0, weight = layers_3_self_attn_o_proj_weight_to_fp16, x = input_25_cast_fp16)[name = tensor("obj_15_cast_fp16")]; + tensor inputs_15_cast_fp16 = add(x = inputs_13_cast_fp16, y = obj_15_cast_fp16)[name = tensor("inputs_15_cast_fp16")]; + tensor out_15_axes_0 = const()[name = tensor("out_15_axes_0"), val = tensor([1])]; + tensor var_609_to_fp16 = const()[name = tensor("op_609_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_15_cast_fp16 = layer_norm(axes = out_15_axes_0, epsilon = var_609_to_fp16, x = inputs_15_cast_fp16)[name = tensor("out_15_cast_fp16")]; + tensor input_27_gamma_0_to_fp16 = const()[name = tensor("input_27_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93837184)))]; + tensor input_27_beta_0_to_fp16 = const()[name = tensor("input_27_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93839296)))]; + tensor input_27_epsilon_0_to_fp16 = const()[name = tensor("input_27_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_27_cast_fp16 = batch_norm(beta = input_27_beta_0_to_fp16, epsilon = input_27_epsilon_0_to_fp16, gamma = input_27_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_15_cast_fp16)[name = tensor("input_27_cast_fp16")]; + tensor input_29_pad_type_0 = const()[name = tensor("input_29_pad_type_0"), val = tensor("valid")]; + tensor input_29_strides_0 = const()[name = tensor("input_29_strides_0"), val = tensor([1, 1])]; + tensor input_29_pad_0 = const()[name = tensor("input_29_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_29_dilations_0 = const()[name = tensor("input_29_dilations_0"), val = tensor([1, 1])]; + tensor input_29_groups_0 = const()[name = tensor("input_29_groups_0"), val = tensor(1)]; + tensor layers_3_fc1_weight_to_fp16 = const()[name = tensor("layers_3_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93841408)))]; + tensor layers_3_fc1_bias_to_fp16 = const()[name = tensor("layers_3_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102230080)))]; + tensor input_29_cast_fp16 = conv(bias = layers_3_fc1_bias_to_fp16, dilations = input_29_dilations_0, groups = input_29_groups_0, pad = input_29_pad_0, pad_type = input_29_pad_type_0, strides = input_29_strides_0, weight = layers_3_fc1_weight_to_fp16, x = input_27_cast_fp16)[name = tensor("input_29_cast_fp16")]; + tensor input_31_mode_0 = const()[name = tensor("input_31_mode_0"), val = tensor("EXACT")]; + tensor input_31_cast_fp16 = gelu(mode = input_31_mode_0, x = input_29_cast_fp16)[name = tensor("input_31_cast_fp16")]; + tensor hidden_states_11_pad_type_0 = const()[name = tensor("hidden_states_11_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_11_strides_0 = const()[name = tensor("hidden_states_11_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_11_pad_0 = const()[name = tensor("hidden_states_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_11_dilations_0 = const()[name = tensor("hidden_states_11_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_11_groups_0 = const()[name = tensor("hidden_states_11_groups_0"), val = tensor(1)]; + tensor layers_3_fc2_weight_to_fp16 = const()[name = tensor("layers_3_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102238336)))]; + tensor layers_3_fc2_bias_to_fp16 = const()[name = tensor("layers_3_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110627008)))]; + tensor hidden_states_11_cast_fp16 = conv(bias = layers_3_fc2_bias_to_fp16, dilations = hidden_states_11_dilations_0, groups = hidden_states_11_groups_0, pad = hidden_states_11_pad_0, pad_type = hidden_states_11_pad_type_0, strides = hidden_states_11_strides_0, weight = layers_3_fc2_weight_to_fp16, x = input_31_cast_fp16)[name = tensor("hidden_states_11_cast_fp16")]; + tensor inputs_17_cast_fp16 = add(x = inputs_15_cast_fp16, y = hidden_states_11_cast_fp16)[name = tensor("inputs_17_cast_fp16")]; + tensor var_638 = const()[name = tensor("op_638"), val = tensor(3)]; + tensor out_17_axes_0 = const()[name = tensor("out_17_axes_0"), val = tensor([1])]; + tensor var_660_to_fp16 = const()[name = tensor("op_660_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_17_cast_fp16 = layer_norm(axes = out_17_axes_0, epsilon = var_660_to_fp16, x = inputs_17_cast_fp16)[name = tensor("out_17_cast_fp16")]; + tensor obj_17_gamma_0_to_fp16 = const()[name = tensor("obj_17_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110629120)))]; + tensor obj_17_beta_0_to_fp16 = const()[name = tensor("obj_17_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110631232)))]; + tensor obj_17_epsilon_0_to_fp16 = const()[name = tensor("obj_17_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_17_cast_fp16 = batch_norm(beta = obj_17_beta_0_to_fp16, epsilon = obj_17_epsilon_0_to_fp16, gamma = obj_17_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_17_cast_fp16)[name = tensor("obj_17_cast_fp16")]; + tensor query_9_pad_type_0 = const()[name = tensor("query_9_pad_type_0"), val = tensor("valid")]; + tensor query_9_strides_0 = const()[name = tensor("query_9_strides_0"), val = tensor([1, 1])]; + tensor query_9_pad_0 = const()[name = tensor("query_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_9_dilations_0 = const()[name = tensor("query_9_dilations_0"), val = tensor([1, 1])]; + tensor query_9_groups_0 = const()[name = tensor("query_9_groups_0"), val = tensor(1)]; + tensor layers_4_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110633344)))]; + tensor layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(112730560)))]; + tensor query_9_cast_fp16 = conv(bias = layers_4_self_attn_q_proj_bias_to_fp16, dilations = query_9_dilations_0, groups = query_9_groups_0, pad = query_9_pad_0, pad_type = query_9_pad_type_0, strides = query_9_strides_0, weight = layers_4_self_attn_q_proj_weight_to_fp16, x = obj_17_cast_fp16)[name = tensor("query_9_cast_fp16")]; + tensor key_9_pad_type_0 = const()[name = tensor("key_9_pad_type_0"), val = tensor("valid")]; + tensor key_9_strides_0 = const()[name = tensor("key_9_strides_0"), val = tensor([1, 1])]; + tensor key_9_pad_0 = const()[name = tensor("key_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_9_dilations_0 = const()[name = tensor("key_9_dilations_0"), val = tensor([1, 1])]; + tensor key_9_groups_0 = const()[name = tensor("key_9_groups_0"), val = tensor(1)]; + tensor layers_4_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(112732672)))]; + tensor key_9_cast_fp16 = conv(dilations = key_9_dilations_0, groups = key_9_groups_0, pad = key_9_pad_0, pad_type = key_9_pad_type_0, strides = key_9_strides_0, weight = layers_4_self_attn_k_proj_weight_to_fp16, x = obj_17_cast_fp16)[name = tensor("key_9_cast_fp16")]; + tensor value_9_pad_type_0 = const()[name = tensor("value_9_pad_type_0"), val = tensor("valid")]; + tensor value_9_strides_0 = const()[name = tensor("value_9_strides_0"), val = tensor([1, 1])]; + tensor value_9_pad_0 = const()[name = tensor("value_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_9_dilations_0 = const()[name = tensor("value_9_dilations_0"), val = tensor([1, 1])]; + tensor value_9_groups_0 = const()[name = tensor("value_9_groups_0"), val = tensor(1)]; + tensor layers_4_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114829888)))]; + tensor layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116927104)))]; + tensor value_9_cast_fp16 = conv(bias = layers_4_self_attn_v_proj_bias_to_fp16, dilations = value_9_dilations_0, groups = value_9_groups_0, pad = value_9_pad_0, pad_type = value_9_pad_type_0, strides = value_9_strides_0, weight = layers_4_self_attn_v_proj_weight_to_fp16, x = obj_17_cast_fp16)[name = tensor("value_9_cast_fp16")]; + tensor var_696 = const()[name = tensor("op_696"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_9_cast_fp16 = reshape(shape = var_696, x = query_9_cast_fp16)[name = tensor("mh_q_9_cast_fp16")]; + tensor var_698_to_fp16 = const()[name = tensor("op_698_to_fp16"), val = tensor(0x1p-3)]; + tensor var_699_cast_fp16 = mul(x = mh_q_9_cast_fp16, y = var_698_to_fp16)[name = tensor("op_699_cast_fp16")]; + tensor var_702 = const()[name = tensor("op_702"), val = tensor([1, 16, 64, 1500])]; + tensor var_703_cast_fp16 = reshape(shape = var_702, x = key_9_cast_fp16)[name = tensor("op_703_cast_fp16")]; + tensor mh_w_9_transpose_x_0 = const()[name = tensor("mh_w_9_transpose_x_0"), val = tensor(true)]; + tensor mh_w_9_transpose_y_0 = const()[name = tensor("mh_w_9_transpose_y_0"), val = tensor(false)]; + tensor mh_w_9_cast_fp16 = matmul(transpose_x = mh_w_9_transpose_x_0, transpose_y = mh_w_9_transpose_y_0, x = var_699_cast_fp16, y = var_703_cast_fp16)[name = tensor("mh_w_9_cast_fp16")]; + tensor var_706_cast_fp16 = softmax(axis = var_638, x = mh_w_9_cast_fp16)[name = tensor("op_706_cast_fp16")]; + tensor var_707 = const()[name = tensor("op_707"), val = tensor([1, 16, 64, 1500])]; + tensor var_708_cast_fp16 = reshape(shape = var_707, x = value_9_cast_fp16)[name = tensor("op_708_cast_fp16")]; + tensor attn_9_transpose_x_0 = const()[name = tensor("attn_9_transpose_x_0"), val = tensor(false)]; + tensor attn_9_transpose_y_0 = const()[name = tensor("attn_9_transpose_y_0"), val = tensor(true)]; + tensor attn_9_cast_fp16 = matmul(transpose_x = attn_9_transpose_x_0, transpose_y = attn_9_transpose_y_0, x = var_708_cast_fp16, y = var_706_cast_fp16)[name = tensor("attn_9_cast_fp16")]; + tensor var_711 = const()[name = tensor("op_711"), val = tensor([1, 1024, 1, 1500])]; + tensor input_33_cast_fp16 = reshape(shape = var_711, x = attn_9_cast_fp16)[name = tensor("input_33_cast_fp16")]; + tensor obj_19_pad_type_0 = const()[name = tensor("obj_19_pad_type_0"), val = tensor("valid")]; + tensor obj_19_strides_0 = const()[name = tensor("obj_19_strides_0"), val = tensor([1, 1])]; + tensor obj_19_pad_0 = const()[name = tensor("obj_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_19_dilations_0 = const()[name = tensor("obj_19_dilations_0"), val = tensor([1, 1])]; + tensor obj_19_groups_0 = const()[name = tensor("obj_19_groups_0"), val = tensor(1)]; + tensor layers_4_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116929216)))]; + tensor layers_4_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119026432)))]; + tensor obj_19_cast_fp16 = conv(bias = layers_4_self_attn_o_proj_bias_to_fp16, dilations = obj_19_dilations_0, groups = obj_19_groups_0, pad = obj_19_pad_0, pad_type = obj_19_pad_type_0, strides = obj_19_strides_0, weight = layers_4_self_attn_o_proj_weight_to_fp16, x = input_33_cast_fp16)[name = tensor("obj_19_cast_fp16")]; + tensor inputs_19_cast_fp16 = add(x = inputs_17_cast_fp16, y = obj_19_cast_fp16)[name = tensor("inputs_19_cast_fp16")]; + tensor out_19_axes_0 = const()[name = tensor("out_19_axes_0"), val = tensor([1])]; + tensor var_729_to_fp16 = const()[name = tensor("op_729_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_19_cast_fp16 = layer_norm(axes = out_19_axes_0, epsilon = var_729_to_fp16, x = inputs_19_cast_fp16)[name = tensor("out_19_cast_fp16")]; + tensor input_35_gamma_0_to_fp16 = const()[name = tensor("input_35_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119028544)))]; + tensor input_35_beta_0_to_fp16 = const()[name = tensor("input_35_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119030656)))]; + tensor input_35_epsilon_0_to_fp16 = const()[name = tensor("input_35_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_35_cast_fp16 = batch_norm(beta = input_35_beta_0_to_fp16, epsilon = input_35_epsilon_0_to_fp16, gamma = input_35_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_19_cast_fp16)[name = tensor("input_35_cast_fp16")]; + tensor input_37_pad_type_0 = const()[name = tensor("input_37_pad_type_0"), val = tensor("valid")]; + tensor input_37_strides_0 = const()[name = tensor("input_37_strides_0"), val = tensor([1, 1])]; + tensor input_37_pad_0 = const()[name = tensor("input_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_37_dilations_0 = const()[name = tensor("input_37_dilations_0"), val = tensor([1, 1])]; + tensor input_37_groups_0 = const()[name = tensor("input_37_groups_0"), val = tensor(1)]; + tensor layers_4_fc1_weight_to_fp16 = const()[name = tensor("layers_4_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119032768)))]; + tensor layers_4_fc1_bias_to_fp16 = const()[name = tensor("layers_4_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127421440)))]; + tensor input_37_cast_fp16 = conv(bias = layers_4_fc1_bias_to_fp16, dilations = input_37_dilations_0, groups = input_37_groups_0, pad = input_37_pad_0, pad_type = input_37_pad_type_0, strides = input_37_strides_0, weight = layers_4_fc1_weight_to_fp16, x = input_35_cast_fp16)[name = tensor("input_37_cast_fp16")]; + tensor input_39_mode_0 = const()[name = tensor("input_39_mode_0"), val = tensor("EXACT")]; + tensor input_39_cast_fp16 = gelu(mode = input_39_mode_0, x = input_37_cast_fp16)[name = tensor("input_39_cast_fp16")]; + tensor hidden_states_13_pad_type_0 = const()[name = tensor("hidden_states_13_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_13_strides_0 = const()[name = tensor("hidden_states_13_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_13_pad_0 = const()[name = tensor("hidden_states_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_13_dilations_0 = const()[name = tensor("hidden_states_13_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_13_groups_0 = const()[name = tensor("hidden_states_13_groups_0"), val = tensor(1)]; + tensor layers_4_fc2_weight_to_fp16 = const()[name = tensor("layers_4_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127429696)))]; + tensor layers_4_fc2_bias_to_fp16 = const()[name = tensor("layers_4_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135818368)))]; + tensor hidden_states_13_cast_fp16 = conv(bias = layers_4_fc2_bias_to_fp16, dilations = hidden_states_13_dilations_0, groups = hidden_states_13_groups_0, pad = hidden_states_13_pad_0, pad_type = hidden_states_13_pad_type_0, strides = hidden_states_13_strides_0, weight = layers_4_fc2_weight_to_fp16, x = input_39_cast_fp16)[name = tensor("hidden_states_13_cast_fp16")]; + tensor inputs_21_cast_fp16 = add(x = inputs_19_cast_fp16, y = hidden_states_13_cast_fp16)[name = tensor("inputs_21_cast_fp16")]; + tensor var_758 = const()[name = tensor("op_758"), val = tensor(3)]; + tensor out_21_axes_0 = const()[name = tensor("out_21_axes_0"), val = tensor([1])]; + tensor var_780_to_fp16 = const()[name = tensor("op_780_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_21_cast_fp16 = layer_norm(axes = out_21_axes_0, epsilon = var_780_to_fp16, x = inputs_21_cast_fp16)[name = tensor("out_21_cast_fp16")]; + tensor obj_21_gamma_0_to_fp16 = const()[name = tensor("obj_21_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135820480)))]; + tensor obj_21_beta_0_to_fp16 = const()[name = tensor("obj_21_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135822592)))]; + tensor obj_21_epsilon_0_to_fp16 = const()[name = tensor("obj_21_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_21_cast_fp16 = batch_norm(beta = obj_21_beta_0_to_fp16, epsilon = obj_21_epsilon_0_to_fp16, gamma = obj_21_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_21_cast_fp16)[name = tensor("obj_21_cast_fp16")]; + tensor query_11_pad_type_0 = const()[name = tensor("query_11_pad_type_0"), val = tensor("valid")]; + tensor query_11_strides_0 = const()[name = tensor("query_11_strides_0"), val = tensor([1, 1])]; + tensor query_11_pad_0 = const()[name = tensor("query_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_11_dilations_0 = const()[name = tensor("query_11_dilations_0"), val = tensor([1, 1])]; + tensor query_11_groups_0 = const()[name = tensor("query_11_groups_0"), val = tensor(1)]; + tensor layers_5_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135824704)))]; + tensor layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137921920)))]; + tensor query_11_cast_fp16 = conv(bias = layers_5_self_attn_q_proj_bias_to_fp16, dilations = query_11_dilations_0, groups = query_11_groups_0, pad = query_11_pad_0, pad_type = query_11_pad_type_0, strides = query_11_strides_0, weight = layers_5_self_attn_q_proj_weight_to_fp16, x = obj_21_cast_fp16)[name = tensor("query_11_cast_fp16")]; + tensor key_11_pad_type_0 = const()[name = tensor("key_11_pad_type_0"), val = tensor("valid")]; + tensor key_11_strides_0 = const()[name = tensor("key_11_strides_0"), val = tensor([1, 1])]; + tensor key_11_pad_0 = const()[name = tensor("key_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_11_dilations_0 = const()[name = tensor("key_11_dilations_0"), val = tensor([1, 1])]; + tensor key_11_groups_0 = const()[name = tensor("key_11_groups_0"), val = tensor(1)]; + tensor layers_5_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137924032)))]; + tensor key_11_cast_fp16 = conv(dilations = key_11_dilations_0, groups = key_11_groups_0, pad = key_11_pad_0, pad_type = key_11_pad_type_0, strides = key_11_strides_0, weight = layers_5_self_attn_k_proj_weight_to_fp16, x = obj_21_cast_fp16)[name = tensor("key_11_cast_fp16")]; + tensor value_11_pad_type_0 = const()[name = tensor("value_11_pad_type_0"), val = tensor("valid")]; + tensor value_11_strides_0 = const()[name = tensor("value_11_strides_0"), val = tensor([1, 1])]; + tensor value_11_pad_0 = const()[name = tensor("value_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_11_dilations_0 = const()[name = tensor("value_11_dilations_0"), val = tensor([1, 1])]; + tensor value_11_groups_0 = const()[name = tensor("value_11_groups_0"), val = tensor(1)]; + tensor layers_5_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140021248)))]; + tensor layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142118464)))]; + tensor value_11_cast_fp16 = conv(bias = layers_5_self_attn_v_proj_bias_to_fp16, dilations = value_11_dilations_0, groups = value_11_groups_0, pad = value_11_pad_0, pad_type = value_11_pad_type_0, strides = value_11_strides_0, weight = layers_5_self_attn_v_proj_weight_to_fp16, x = obj_21_cast_fp16)[name = tensor("value_11_cast_fp16")]; + tensor var_816 = const()[name = tensor("op_816"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_11_cast_fp16 = reshape(shape = var_816, x = query_11_cast_fp16)[name = tensor("mh_q_11_cast_fp16")]; + tensor var_818_to_fp16 = const()[name = tensor("op_818_to_fp16"), val = tensor(0x1p-3)]; + tensor var_819_cast_fp16 = mul(x = mh_q_11_cast_fp16, y = var_818_to_fp16)[name = tensor("op_819_cast_fp16")]; + tensor var_822 = const()[name = tensor("op_822"), val = tensor([1, 16, 64, 1500])]; + tensor var_823_cast_fp16 = reshape(shape = var_822, x = key_11_cast_fp16)[name = tensor("op_823_cast_fp16")]; + tensor mh_w_11_transpose_x_0 = const()[name = tensor("mh_w_11_transpose_x_0"), val = tensor(true)]; + tensor mh_w_11_transpose_y_0 = const()[name = tensor("mh_w_11_transpose_y_0"), val = tensor(false)]; + tensor mh_w_11_cast_fp16 = matmul(transpose_x = mh_w_11_transpose_x_0, transpose_y = mh_w_11_transpose_y_0, x = var_819_cast_fp16, y = var_823_cast_fp16)[name = tensor("mh_w_11_cast_fp16")]; + tensor var_826_cast_fp16 = softmax(axis = var_758, x = mh_w_11_cast_fp16)[name = tensor("op_826_cast_fp16")]; + tensor var_827 = const()[name = tensor("op_827"), val = tensor([1, 16, 64, 1500])]; + tensor var_828_cast_fp16 = reshape(shape = var_827, x = value_11_cast_fp16)[name = tensor("op_828_cast_fp16")]; + tensor attn_11_transpose_x_0 = const()[name = tensor("attn_11_transpose_x_0"), val = tensor(false)]; + tensor attn_11_transpose_y_0 = const()[name = tensor("attn_11_transpose_y_0"), val = tensor(true)]; + tensor attn_11_cast_fp16 = matmul(transpose_x = attn_11_transpose_x_0, transpose_y = attn_11_transpose_y_0, x = var_828_cast_fp16, y = var_826_cast_fp16)[name = tensor("attn_11_cast_fp16")]; + tensor var_831 = const()[name = tensor("op_831"), val = tensor([1, 1024, 1, 1500])]; + tensor input_41_cast_fp16 = reshape(shape = var_831, x = attn_11_cast_fp16)[name = tensor("input_41_cast_fp16")]; + tensor obj_23_pad_type_0 = const()[name = tensor("obj_23_pad_type_0"), val = tensor("valid")]; + tensor obj_23_strides_0 = const()[name = tensor("obj_23_strides_0"), val = tensor([1, 1])]; + tensor obj_23_pad_0 = const()[name = tensor("obj_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_23_dilations_0 = const()[name = tensor("obj_23_dilations_0"), val = tensor([1, 1])]; + tensor obj_23_groups_0 = const()[name = tensor("obj_23_groups_0"), val = tensor(1)]; + tensor layers_5_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142120576)))]; + tensor layers_5_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(144217792)))]; + tensor obj_23_cast_fp16 = conv(bias = layers_5_self_attn_o_proj_bias_to_fp16, dilations = obj_23_dilations_0, groups = obj_23_groups_0, pad = obj_23_pad_0, pad_type = obj_23_pad_type_0, strides = obj_23_strides_0, weight = layers_5_self_attn_o_proj_weight_to_fp16, x = input_41_cast_fp16)[name = tensor("obj_23_cast_fp16")]; + tensor inputs_23_cast_fp16 = add(x = inputs_21_cast_fp16, y = obj_23_cast_fp16)[name = tensor("inputs_23_cast_fp16")]; + tensor out_23_axes_0 = const()[name = tensor("out_23_axes_0"), val = tensor([1])]; + tensor var_849_to_fp16 = const()[name = tensor("op_849_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_23_cast_fp16 = layer_norm(axes = out_23_axes_0, epsilon = var_849_to_fp16, x = inputs_23_cast_fp16)[name = tensor("out_23_cast_fp16")]; + tensor input_43_gamma_0_to_fp16 = const()[name = tensor("input_43_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(144219904)))]; + tensor input_43_beta_0_to_fp16 = const()[name = tensor("input_43_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(144222016)))]; + tensor input_43_epsilon_0_to_fp16 = const()[name = tensor("input_43_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_43_cast_fp16 = batch_norm(beta = input_43_beta_0_to_fp16, epsilon = input_43_epsilon_0_to_fp16, gamma = input_43_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_23_cast_fp16)[name = tensor("input_43_cast_fp16")]; + tensor input_45_pad_type_0 = const()[name = tensor("input_45_pad_type_0"), val = tensor("valid")]; + tensor input_45_strides_0 = const()[name = tensor("input_45_strides_0"), val = tensor([1, 1])]; + tensor input_45_pad_0 = const()[name = tensor("input_45_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_45_dilations_0 = const()[name = tensor("input_45_dilations_0"), val = tensor([1, 1])]; + tensor input_45_groups_0 = const()[name = tensor("input_45_groups_0"), val = tensor(1)]; + tensor layers_5_fc1_weight_to_fp16 = const()[name = tensor("layers_5_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(144224128)))]; + tensor layers_5_fc1_bias_to_fp16 = const()[name = tensor("layers_5_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(152612800)))]; + tensor input_45_cast_fp16 = conv(bias = layers_5_fc1_bias_to_fp16, dilations = input_45_dilations_0, groups = input_45_groups_0, pad = input_45_pad_0, pad_type = input_45_pad_type_0, strides = input_45_strides_0, weight = layers_5_fc1_weight_to_fp16, x = input_43_cast_fp16)[name = tensor("input_45_cast_fp16")]; + tensor input_47_mode_0 = const()[name = tensor("input_47_mode_0"), val = tensor("EXACT")]; + tensor input_47_cast_fp16 = gelu(mode = input_47_mode_0, x = input_45_cast_fp16)[name = tensor("input_47_cast_fp16")]; + tensor hidden_states_15_pad_type_0 = const()[name = tensor("hidden_states_15_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_15_strides_0 = const()[name = tensor("hidden_states_15_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_15_pad_0 = const()[name = tensor("hidden_states_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_15_dilations_0 = const()[name = tensor("hidden_states_15_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_15_groups_0 = const()[name = tensor("hidden_states_15_groups_0"), val = tensor(1)]; + tensor layers_5_fc2_weight_to_fp16 = const()[name = tensor("layers_5_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(152621056)))]; + tensor layers_5_fc2_bias_to_fp16 = const()[name = tensor("layers_5_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161009728)))]; + tensor hidden_states_15_cast_fp16 = conv(bias = layers_5_fc2_bias_to_fp16, dilations = hidden_states_15_dilations_0, groups = hidden_states_15_groups_0, pad = hidden_states_15_pad_0, pad_type = hidden_states_15_pad_type_0, strides = hidden_states_15_strides_0, weight = layers_5_fc2_weight_to_fp16, x = input_47_cast_fp16)[name = tensor("hidden_states_15_cast_fp16")]; + tensor inputs_25_cast_fp16 = add(x = inputs_23_cast_fp16, y = hidden_states_15_cast_fp16)[name = tensor("inputs_25_cast_fp16")]; + tensor var_878 = const()[name = tensor("op_878"), val = tensor(3)]; + tensor out_25_axes_0 = const()[name = tensor("out_25_axes_0"), val = tensor([1])]; + tensor var_900_to_fp16 = const()[name = tensor("op_900_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_25_cast_fp16 = layer_norm(axes = out_25_axes_0, epsilon = var_900_to_fp16, x = inputs_25_cast_fp16)[name = tensor("out_25_cast_fp16")]; + tensor obj_25_gamma_0_to_fp16 = const()[name = tensor("obj_25_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161011840)))]; + tensor obj_25_beta_0_to_fp16 = const()[name = tensor("obj_25_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161013952)))]; + tensor obj_25_epsilon_0_to_fp16 = const()[name = tensor("obj_25_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_25_cast_fp16 = batch_norm(beta = obj_25_beta_0_to_fp16, epsilon = obj_25_epsilon_0_to_fp16, gamma = obj_25_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_25_cast_fp16)[name = tensor("obj_25_cast_fp16")]; + tensor query_13_pad_type_0 = const()[name = tensor("query_13_pad_type_0"), val = tensor("valid")]; + tensor query_13_strides_0 = const()[name = tensor("query_13_strides_0"), val = tensor([1, 1])]; + tensor query_13_pad_0 = const()[name = tensor("query_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_13_dilations_0 = const()[name = tensor("query_13_dilations_0"), val = tensor([1, 1])]; + tensor query_13_groups_0 = const()[name = tensor("query_13_groups_0"), val = tensor(1)]; + tensor layers_6_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161016064)))]; + tensor layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(163113280)))]; + tensor query_13_cast_fp16 = conv(bias = layers_6_self_attn_q_proj_bias_to_fp16, dilations = query_13_dilations_0, groups = query_13_groups_0, pad = query_13_pad_0, pad_type = query_13_pad_type_0, strides = query_13_strides_0, weight = layers_6_self_attn_q_proj_weight_to_fp16, x = obj_25_cast_fp16)[name = tensor("query_13_cast_fp16")]; + tensor key_13_pad_type_0 = const()[name = tensor("key_13_pad_type_0"), val = tensor("valid")]; + tensor key_13_strides_0 = const()[name = tensor("key_13_strides_0"), val = tensor([1, 1])]; + tensor key_13_pad_0 = const()[name = tensor("key_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_13_dilations_0 = const()[name = tensor("key_13_dilations_0"), val = tensor([1, 1])]; + tensor key_13_groups_0 = const()[name = tensor("key_13_groups_0"), val = tensor(1)]; + tensor layers_6_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(163115392)))]; + tensor key_13_cast_fp16 = conv(dilations = key_13_dilations_0, groups = key_13_groups_0, pad = key_13_pad_0, pad_type = key_13_pad_type_0, strides = key_13_strides_0, weight = layers_6_self_attn_k_proj_weight_to_fp16, x = obj_25_cast_fp16)[name = tensor("key_13_cast_fp16")]; + tensor value_13_pad_type_0 = const()[name = tensor("value_13_pad_type_0"), val = tensor("valid")]; + tensor value_13_strides_0 = const()[name = tensor("value_13_strides_0"), val = tensor([1, 1])]; + tensor value_13_pad_0 = const()[name = tensor("value_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_13_dilations_0 = const()[name = tensor("value_13_dilations_0"), val = tensor([1, 1])]; + tensor value_13_groups_0 = const()[name = tensor("value_13_groups_0"), val = tensor(1)]; + tensor layers_6_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165212608)))]; + tensor layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(167309824)))]; + tensor value_13_cast_fp16 = conv(bias = layers_6_self_attn_v_proj_bias_to_fp16, dilations = value_13_dilations_0, groups = value_13_groups_0, pad = value_13_pad_0, pad_type = value_13_pad_type_0, strides = value_13_strides_0, weight = layers_6_self_attn_v_proj_weight_to_fp16, x = obj_25_cast_fp16)[name = tensor("value_13_cast_fp16")]; + tensor var_936 = const()[name = tensor("op_936"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_13_cast_fp16 = reshape(shape = var_936, x = query_13_cast_fp16)[name = tensor("mh_q_13_cast_fp16")]; + tensor var_938_to_fp16 = const()[name = tensor("op_938_to_fp16"), val = tensor(0x1p-3)]; + tensor var_939_cast_fp16 = mul(x = mh_q_13_cast_fp16, y = var_938_to_fp16)[name = tensor("op_939_cast_fp16")]; + tensor var_942 = const()[name = tensor("op_942"), val = tensor([1, 16, 64, 1500])]; + tensor var_943_cast_fp16 = reshape(shape = var_942, x = key_13_cast_fp16)[name = tensor("op_943_cast_fp16")]; + tensor mh_w_13_transpose_x_0 = const()[name = tensor("mh_w_13_transpose_x_0"), val = tensor(true)]; + tensor mh_w_13_transpose_y_0 = const()[name = tensor("mh_w_13_transpose_y_0"), val = tensor(false)]; + tensor mh_w_13_cast_fp16 = matmul(transpose_x = mh_w_13_transpose_x_0, transpose_y = mh_w_13_transpose_y_0, x = var_939_cast_fp16, y = var_943_cast_fp16)[name = tensor("mh_w_13_cast_fp16")]; + tensor var_946_cast_fp16 = softmax(axis = var_878, x = mh_w_13_cast_fp16)[name = tensor("op_946_cast_fp16")]; + tensor var_947 = const()[name = tensor("op_947"), val = tensor([1, 16, 64, 1500])]; + tensor var_948_cast_fp16 = reshape(shape = var_947, x = value_13_cast_fp16)[name = tensor("op_948_cast_fp16")]; + tensor attn_13_transpose_x_0 = const()[name = tensor("attn_13_transpose_x_0"), val = tensor(false)]; + tensor attn_13_transpose_y_0 = const()[name = tensor("attn_13_transpose_y_0"), val = tensor(true)]; + tensor attn_13_cast_fp16 = matmul(transpose_x = attn_13_transpose_x_0, transpose_y = attn_13_transpose_y_0, x = var_948_cast_fp16, y = var_946_cast_fp16)[name = tensor("attn_13_cast_fp16")]; + tensor var_951 = const()[name = tensor("op_951"), val = tensor([1, 1024, 1, 1500])]; + tensor input_49_cast_fp16 = reshape(shape = var_951, x = attn_13_cast_fp16)[name = tensor("input_49_cast_fp16")]; + tensor obj_27_pad_type_0 = const()[name = tensor("obj_27_pad_type_0"), val = tensor("valid")]; + tensor obj_27_strides_0 = const()[name = tensor("obj_27_strides_0"), val = tensor([1, 1])]; + tensor obj_27_pad_0 = const()[name = tensor("obj_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_27_dilations_0 = const()[name = tensor("obj_27_dilations_0"), val = tensor([1, 1])]; + tensor obj_27_groups_0 = const()[name = tensor("obj_27_groups_0"), val = tensor(1)]; + tensor layers_6_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(167311936)))]; + tensor layers_6_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(169409152)))]; + tensor obj_27_cast_fp16 = conv(bias = layers_6_self_attn_o_proj_bias_to_fp16, dilations = obj_27_dilations_0, groups = obj_27_groups_0, pad = obj_27_pad_0, pad_type = obj_27_pad_type_0, strides = obj_27_strides_0, weight = layers_6_self_attn_o_proj_weight_to_fp16, x = input_49_cast_fp16)[name = tensor("obj_27_cast_fp16")]; + tensor inputs_27_cast_fp16 = add(x = inputs_25_cast_fp16, y = obj_27_cast_fp16)[name = tensor("inputs_27_cast_fp16")]; + tensor out_27_axes_0 = const()[name = tensor("out_27_axes_0"), val = tensor([1])]; + tensor var_969_to_fp16 = const()[name = tensor("op_969_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_27_cast_fp16 = layer_norm(axes = out_27_axes_0, epsilon = var_969_to_fp16, x = inputs_27_cast_fp16)[name = tensor("out_27_cast_fp16")]; + tensor input_51_gamma_0_to_fp16 = const()[name = tensor("input_51_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(169411264)))]; + tensor input_51_beta_0_to_fp16 = const()[name = tensor("input_51_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(169413376)))]; + tensor input_51_epsilon_0_to_fp16 = const()[name = tensor("input_51_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_51_cast_fp16 = batch_norm(beta = input_51_beta_0_to_fp16, epsilon = input_51_epsilon_0_to_fp16, gamma = input_51_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_27_cast_fp16)[name = tensor("input_51_cast_fp16")]; + tensor input_53_pad_type_0 = const()[name = tensor("input_53_pad_type_0"), val = tensor("valid")]; + tensor input_53_strides_0 = const()[name = tensor("input_53_strides_0"), val = tensor([1, 1])]; + tensor input_53_pad_0 = const()[name = tensor("input_53_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_53_dilations_0 = const()[name = tensor("input_53_dilations_0"), val = tensor([1, 1])]; + tensor input_53_groups_0 = const()[name = tensor("input_53_groups_0"), val = tensor(1)]; + tensor layers_6_fc1_weight_to_fp16 = const()[name = tensor("layers_6_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(169415488)))]; + tensor layers_6_fc1_bias_to_fp16 = const()[name = tensor("layers_6_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177804160)))]; + tensor input_53_cast_fp16 = conv(bias = layers_6_fc1_bias_to_fp16, dilations = input_53_dilations_0, groups = input_53_groups_0, pad = input_53_pad_0, pad_type = input_53_pad_type_0, strides = input_53_strides_0, weight = layers_6_fc1_weight_to_fp16, x = input_51_cast_fp16)[name = tensor("input_53_cast_fp16")]; + tensor input_55_mode_0 = const()[name = tensor("input_55_mode_0"), val = tensor("EXACT")]; + tensor input_55_cast_fp16 = gelu(mode = input_55_mode_0, x = input_53_cast_fp16)[name = tensor("input_55_cast_fp16")]; + tensor hidden_states_17_pad_type_0 = const()[name = tensor("hidden_states_17_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_17_strides_0 = const()[name = tensor("hidden_states_17_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_17_pad_0 = const()[name = tensor("hidden_states_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_17_dilations_0 = const()[name = tensor("hidden_states_17_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_17_groups_0 = const()[name = tensor("hidden_states_17_groups_0"), val = tensor(1)]; + tensor layers_6_fc2_weight_to_fp16 = const()[name = tensor("layers_6_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177812416)))]; + tensor layers_6_fc2_bias_to_fp16 = const()[name = tensor("layers_6_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186201088)))]; + tensor hidden_states_17_cast_fp16 = conv(bias = layers_6_fc2_bias_to_fp16, dilations = hidden_states_17_dilations_0, groups = hidden_states_17_groups_0, pad = hidden_states_17_pad_0, pad_type = hidden_states_17_pad_type_0, strides = hidden_states_17_strides_0, weight = layers_6_fc2_weight_to_fp16, x = input_55_cast_fp16)[name = tensor("hidden_states_17_cast_fp16")]; + tensor inputs_29_cast_fp16 = add(x = inputs_27_cast_fp16, y = hidden_states_17_cast_fp16)[name = tensor("inputs_29_cast_fp16")]; + tensor var_998 = const()[name = tensor("op_998"), val = tensor(3)]; + tensor out_29_axes_0 = const()[name = tensor("out_29_axes_0"), val = tensor([1])]; + tensor var_1020_to_fp16 = const()[name = tensor("op_1020_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_29_cast_fp16 = layer_norm(axes = out_29_axes_0, epsilon = var_1020_to_fp16, x = inputs_29_cast_fp16)[name = tensor("out_29_cast_fp16")]; + tensor obj_29_gamma_0_to_fp16 = const()[name = tensor("obj_29_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186203200)))]; + tensor obj_29_beta_0_to_fp16 = const()[name = tensor("obj_29_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186205312)))]; + tensor obj_29_epsilon_0_to_fp16 = const()[name = tensor("obj_29_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_29_cast_fp16 = batch_norm(beta = obj_29_beta_0_to_fp16, epsilon = obj_29_epsilon_0_to_fp16, gamma = obj_29_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_29_cast_fp16)[name = tensor("obj_29_cast_fp16")]; + tensor query_15_pad_type_0 = const()[name = tensor("query_15_pad_type_0"), val = tensor("valid")]; + tensor query_15_strides_0 = const()[name = tensor("query_15_strides_0"), val = tensor([1, 1])]; + tensor query_15_pad_0 = const()[name = tensor("query_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_15_dilations_0 = const()[name = tensor("query_15_dilations_0"), val = tensor([1, 1])]; + tensor query_15_groups_0 = const()[name = tensor("query_15_groups_0"), val = tensor(1)]; + tensor layers_7_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186207424)))]; + tensor layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(188304640)))]; + tensor query_15_cast_fp16 = conv(bias = layers_7_self_attn_q_proj_bias_to_fp16, dilations = query_15_dilations_0, groups = query_15_groups_0, pad = query_15_pad_0, pad_type = query_15_pad_type_0, strides = query_15_strides_0, weight = layers_7_self_attn_q_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("query_15_cast_fp16")]; + tensor key_15_pad_type_0 = const()[name = tensor("key_15_pad_type_0"), val = tensor("valid")]; + tensor key_15_strides_0 = const()[name = tensor("key_15_strides_0"), val = tensor([1, 1])]; + tensor key_15_pad_0 = const()[name = tensor("key_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_15_dilations_0 = const()[name = tensor("key_15_dilations_0"), val = tensor([1, 1])]; + tensor key_15_groups_0 = const()[name = tensor("key_15_groups_0"), val = tensor(1)]; + tensor layers_7_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(188306752)))]; + tensor key_15_cast_fp16 = conv(dilations = key_15_dilations_0, groups = key_15_groups_0, pad = key_15_pad_0, pad_type = key_15_pad_type_0, strides = key_15_strides_0, weight = layers_7_self_attn_k_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("key_15_cast_fp16")]; + tensor value_15_pad_type_0 = const()[name = tensor("value_15_pad_type_0"), val = tensor("valid")]; + tensor value_15_strides_0 = const()[name = tensor("value_15_strides_0"), val = tensor([1, 1])]; + tensor value_15_pad_0 = const()[name = tensor("value_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_15_dilations_0 = const()[name = tensor("value_15_dilations_0"), val = tensor([1, 1])]; + tensor value_15_groups_0 = const()[name = tensor("value_15_groups_0"), val = tensor(1)]; + tensor layers_7_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(190403968)))]; + tensor layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(192501184)))]; + tensor value_15_cast_fp16 = conv(bias = layers_7_self_attn_v_proj_bias_to_fp16, dilations = value_15_dilations_0, groups = value_15_groups_0, pad = value_15_pad_0, pad_type = value_15_pad_type_0, strides = value_15_strides_0, weight = layers_7_self_attn_v_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("value_15_cast_fp16")]; + tensor var_1056 = const()[name = tensor("op_1056"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_15_cast_fp16 = reshape(shape = var_1056, x = query_15_cast_fp16)[name = tensor("mh_q_15_cast_fp16")]; + tensor var_1058_to_fp16 = const()[name = tensor("op_1058_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1059_cast_fp16 = mul(x = mh_q_15_cast_fp16, y = var_1058_to_fp16)[name = tensor("op_1059_cast_fp16")]; + tensor var_1062 = const()[name = tensor("op_1062"), val = tensor([1, 16, 64, 1500])]; + tensor var_1063_cast_fp16 = reshape(shape = var_1062, x = key_15_cast_fp16)[name = tensor("op_1063_cast_fp16")]; + tensor mh_w_15_transpose_x_0 = const()[name = tensor("mh_w_15_transpose_x_0"), val = tensor(true)]; + tensor mh_w_15_transpose_y_0 = const()[name = tensor("mh_w_15_transpose_y_0"), val = tensor(false)]; + tensor mh_w_15_cast_fp16 = matmul(transpose_x = mh_w_15_transpose_x_0, transpose_y = mh_w_15_transpose_y_0, x = var_1059_cast_fp16, y = var_1063_cast_fp16)[name = tensor("mh_w_15_cast_fp16")]; + tensor var_1066_cast_fp16 = softmax(axis = var_998, x = mh_w_15_cast_fp16)[name = tensor("op_1066_cast_fp16")]; + tensor var_1067 = const()[name = tensor("op_1067"), val = tensor([1, 16, 64, 1500])]; + tensor var_1068_cast_fp16 = reshape(shape = var_1067, x = value_15_cast_fp16)[name = tensor("op_1068_cast_fp16")]; + tensor attn_15_transpose_x_0 = const()[name = tensor("attn_15_transpose_x_0"), val = tensor(false)]; + tensor attn_15_transpose_y_0 = const()[name = tensor("attn_15_transpose_y_0"), val = tensor(true)]; + tensor attn_15_cast_fp16 = matmul(transpose_x = attn_15_transpose_x_0, transpose_y = attn_15_transpose_y_0, x = var_1068_cast_fp16, y = var_1066_cast_fp16)[name = tensor("attn_15_cast_fp16")]; + tensor var_1071 = const()[name = tensor("op_1071"), val = tensor([1, 1024, 1, 1500])]; + tensor input_57_cast_fp16 = reshape(shape = var_1071, x = attn_15_cast_fp16)[name = tensor("input_57_cast_fp16")]; + tensor obj_31_pad_type_0 = const()[name = tensor("obj_31_pad_type_0"), val = tensor("valid")]; + tensor obj_31_strides_0 = const()[name = tensor("obj_31_strides_0"), val = tensor([1, 1])]; + tensor obj_31_pad_0 = const()[name = tensor("obj_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_31_dilations_0 = const()[name = tensor("obj_31_dilations_0"), val = tensor([1, 1])]; + tensor obj_31_groups_0 = const()[name = tensor("obj_31_groups_0"), val = tensor(1)]; + tensor layers_7_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(192503296)))]; + tensor layers_7_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(194600512)))]; + tensor obj_31_cast_fp16 = conv(bias = layers_7_self_attn_o_proj_bias_to_fp16, dilations = obj_31_dilations_0, groups = obj_31_groups_0, pad = obj_31_pad_0, pad_type = obj_31_pad_type_0, strides = obj_31_strides_0, weight = layers_7_self_attn_o_proj_weight_to_fp16, x = input_57_cast_fp16)[name = tensor("obj_31_cast_fp16")]; + tensor inputs_31_cast_fp16 = add(x = inputs_29_cast_fp16, y = obj_31_cast_fp16)[name = tensor("inputs_31_cast_fp16")]; + tensor out_31_axes_0 = const()[name = tensor("out_31_axes_0"), val = tensor([1])]; + tensor var_1089_to_fp16 = const()[name = tensor("op_1089_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_31_cast_fp16 = layer_norm(axes = out_31_axes_0, epsilon = var_1089_to_fp16, x = inputs_31_cast_fp16)[name = tensor("out_31_cast_fp16")]; + tensor input_59_gamma_0_to_fp16 = const()[name = tensor("input_59_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(194602624)))]; + tensor input_59_beta_0_to_fp16 = const()[name = tensor("input_59_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(194604736)))]; + tensor input_59_epsilon_0_to_fp16 = const()[name = tensor("input_59_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_59_cast_fp16 = batch_norm(beta = input_59_beta_0_to_fp16, epsilon = input_59_epsilon_0_to_fp16, gamma = input_59_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_31_cast_fp16)[name = tensor("input_59_cast_fp16")]; + tensor input_61_pad_type_0 = const()[name = tensor("input_61_pad_type_0"), val = tensor("valid")]; + tensor input_61_strides_0 = const()[name = tensor("input_61_strides_0"), val = tensor([1, 1])]; + tensor input_61_pad_0 = const()[name = tensor("input_61_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_61_dilations_0 = const()[name = tensor("input_61_dilations_0"), val = tensor([1, 1])]; + tensor input_61_groups_0 = const()[name = tensor("input_61_groups_0"), val = tensor(1)]; + tensor layers_7_fc1_weight_to_fp16 = const()[name = tensor("layers_7_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(194606848)))]; + tensor layers_7_fc1_bias_to_fp16 = const()[name = tensor("layers_7_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202995520)))]; + tensor input_61_cast_fp16 = conv(bias = layers_7_fc1_bias_to_fp16, dilations = input_61_dilations_0, groups = input_61_groups_0, pad = input_61_pad_0, pad_type = input_61_pad_type_0, strides = input_61_strides_0, weight = layers_7_fc1_weight_to_fp16, x = input_59_cast_fp16)[name = tensor("input_61_cast_fp16")]; + tensor input_63_mode_0 = const()[name = tensor("input_63_mode_0"), val = tensor("EXACT")]; + tensor input_63_cast_fp16 = gelu(mode = input_63_mode_0, x = input_61_cast_fp16)[name = tensor("input_63_cast_fp16")]; + tensor hidden_states_19_pad_type_0 = const()[name = tensor("hidden_states_19_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_19_strides_0 = const()[name = tensor("hidden_states_19_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_19_pad_0 = const()[name = tensor("hidden_states_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_19_dilations_0 = const()[name = tensor("hidden_states_19_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_19_groups_0 = const()[name = tensor("hidden_states_19_groups_0"), val = tensor(1)]; + tensor layers_7_fc2_weight_to_fp16 = const()[name = tensor("layers_7_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203003776)))]; + tensor layers_7_fc2_bias_to_fp16 = const()[name = tensor("layers_7_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(211392448)))]; + tensor hidden_states_19_cast_fp16 = conv(bias = layers_7_fc2_bias_to_fp16, dilations = hidden_states_19_dilations_0, groups = hidden_states_19_groups_0, pad = hidden_states_19_pad_0, pad_type = hidden_states_19_pad_type_0, strides = hidden_states_19_strides_0, weight = layers_7_fc2_weight_to_fp16, x = input_63_cast_fp16)[name = tensor("hidden_states_19_cast_fp16")]; + tensor inputs_33_cast_fp16 = add(x = inputs_31_cast_fp16, y = hidden_states_19_cast_fp16)[name = tensor("inputs_33_cast_fp16")]; + tensor var_1118 = const()[name = tensor("op_1118"), val = tensor(3)]; + tensor out_33_axes_0 = const()[name = tensor("out_33_axes_0"), val = tensor([1])]; + tensor var_1140_to_fp16 = const()[name = tensor("op_1140_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_33_cast_fp16 = layer_norm(axes = out_33_axes_0, epsilon = var_1140_to_fp16, x = inputs_33_cast_fp16)[name = tensor("out_33_cast_fp16")]; + tensor obj_33_gamma_0_to_fp16 = const()[name = tensor("obj_33_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(211394560)))]; + tensor obj_33_beta_0_to_fp16 = const()[name = tensor("obj_33_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(211396672)))]; + tensor obj_33_epsilon_0_to_fp16 = const()[name = tensor("obj_33_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_33_cast_fp16 = batch_norm(beta = obj_33_beta_0_to_fp16, epsilon = obj_33_epsilon_0_to_fp16, gamma = obj_33_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_33_cast_fp16)[name = tensor("obj_33_cast_fp16")]; + tensor query_17_pad_type_0 = const()[name = tensor("query_17_pad_type_0"), val = tensor("valid")]; + tensor query_17_strides_0 = const()[name = tensor("query_17_strides_0"), val = tensor([1, 1])]; + tensor query_17_pad_0 = const()[name = tensor("query_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_17_dilations_0 = const()[name = tensor("query_17_dilations_0"), val = tensor([1, 1])]; + tensor query_17_groups_0 = const()[name = tensor("query_17_groups_0"), val = tensor(1)]; + tensor layers_8_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(211398784)))]; + tensor layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(213496000)))]; + tensor query_17_cast_fp16 = conv(bias = layers_8_self_attn_q_proj_bias_to_fp16, dilations = query_17_dilations_0, groups = query_17_groups_0, pad = query_17_pad_0, pad_type = query_17_pad_type_0, strides = query_17_strides_0, weight = layers_8_self_attn_q_proj_weight_to_fp16, x = obj_33_cast_fp16)[name = tensor("query_17_cast_fp16")]; + tensor key_17_pad_type_0 = const()[name = tensor("key_17_pad_type_0"), val = tensor("valid")]; + tensor key_17_strides_0 = const()[name = tensor("key_17_strides_0"), val = tensor([1, 1])]; + tensor key_17_pad_0 = const()[name = tensor("key_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_17_dilations_0 = const()[name = tensor("key_17_dilations_0"), val = tensor([1, 1])]; + tensor key_17_groups_0 = const()[name = tensor("key_17_groups_0"), val = tensor(1)]; + tensor layers_8_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(213498112)))]; + tensor key_17_cast_fp16 = conv(dilations = key_17_dilations_0, groups = key_17_groups_0, pad = key_17_pad_0, pad_type = key_17_pad_type_0, strides = key_17_strides_0, weight = layers_8_self_attn_k_proj_weight_to_fp16, x = obj_33_cast_fp16)[name = tensor("key_17_cast_fp16")]; + tensor value_17_pad_type_0 = const()[name = tensor("value_17_pad_type_0"), val = tensor("valid")]; + tensor value_17_strides_0 = const()[name = tensor("value_17_strides_0"), val = tensor([1, 1])]; + tensor value_17_pad_0 = const()[name = tensor("value_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_17_dilations_0 = const()[name = tensor("value_17_dilations_0"), val = tensor([1, 1])]; + tensor value_17_groups_0 = const()[name = tensor("value_17_groups_0"), val = tensor(1)]; + tensor layers_8_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215595328)))]; + tensor layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217692544)))]; + tensor value_17_cast_fp16 = conv(bias = layers_8_self_attn_v_proj_bias_to_fp16, dilations = value_17_dilations_0, groups = value_17_groups_0, pad = value_17_pad_0, pad_type = value_17_pad_type_0, strides = value_17_strides_0, weight = layers_8_self_attn_v_proj_weight_to_fp16, x = obj_33_cast_fp16)[name = tensor("value_17_cast_fp16")]; + tensor var_1176 = const()[name = tensor("op_1176"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_17_cast_fp16 = reshape(shape = var_1176, x = query_17_cast_fp16)[name = tensor("mh_q_17_cast_fp16")]; + tensor var_1178_to_fp16 = const()[name = tensor("op_1178_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1179_cast_fp16 = mul(x = mh_q_17_cast_fp16, y = var_1178_to_fp16)[name = tensor("op_1179_cast_fp16")]; + tensor var_1182 = const()[name = tensor("op_1182"), val = tensor([1, 16, 64, 1500])]; + tensor var_1183_cast_fp16 = reshape(shape = var_1182, x = key_17_cast_fp16)[name = tensor("op_1183_cast_fp16")]; + tensor mh_w_17_transpose_x_0 = const()[name = tensor("mh_w_17_transpose_x_0"), val = tensor(true)]; + tensor mh_w_17_transpose_y_0 = const()[name = tensor("mh_w_17_transpose_y_0"), val = tensor(false)]; + tensor mh_w_17_cast_fp16 = matmul(transpose_x = mh_w_17_transpose_x_0, transpose_y = mh_w_17_transpose_y_0, x = var_1179_cast_fp16, y = var_1183_cast_fp16)[name = tensor("mh_w_17_cast_fp16")]; + tensor var_1186_cast_fp16 = softmax(axis = var_1118, x = mh_w_17_cast_fp16)[name = tensor("op_1186_cast_fp16")]; + tensor var_1187 = const()[name = tensor("op_1187"), val = tensor([1, 16, 64, 1500])]; + tensor var_1188_cast_fp16 = reshape(shape = var_1187, x = value_17_cast_fp16)[name = tensor("op_1188_cast_fp16")]; + tensor attn_17_transpose_x_0 = const()[name = tensor("attn_17_transpose_x_0"), val = tensor(false)]; + tensor attn_17_transpose_y_0 = const()[name = tensor("attn_17_transpose_y_0"), val = tensor(true)]; + tensor attn_17_cast_fp16 = matmul(transpose_x = attn_17_transpose_x_0, transpose_y = attn_17_transpose_y_0, x = var_1188_cast_fp16, y = var_1186_cast_fp16)[name = tensor("attn_17_cast_fp16")]; + tensor var_1191 = const()[name = tensor("op_1191"), val = tensor([1, 1024, 1, 1500])]; + tensor input_65_cast_fp16 = reshape(shape = var_1191, x = attn_17_cast_fp16)[name = tensor("input_65_cast_fp16")]; + tensor obj_35_pad_type_0 = const()[name = tensor("obj_35_pad_type_0"), val = tensor("valid")]; + tensor obj_35_strides_0 = const()[name = tensor("obj_35_strides_0"), val = tensor([1, 1])]; + tensor obj_35_pad_0 = const()[name = tensor("obj_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_35_dilations_0 = const()[name = tensor("obj_35_dilations_0"), val = tensor([1, 1])]; + tensor obj_35_groups_0 = const()[name = tensor("obj_35_groups_0"), val = tensor(1)]; + tensor layers_8_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217694656)))]; + tensor layers_8_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(219791872)))]; + tensor obj_35_cast_fp16 = conv(bias = layers_8_self_attn_o_proj_bias_to_fp16, dilations = obj_35_dilations_0, groups = obj_35_groups_0, pad = obj_35_pad_0, pad_type = obj_35_pad_type_0, strides = obj_35_strides_0, weight = layers_8_self_attn_o_proj_weight_to_fp16, x = input_65_cast_fp16)[name = tensor("obj_35_cast_fp16")]; + tensor inputs_35_cast_fp16 = add(x = inputs_33_cast_fp16, y = obj_35_cast_fp16)[name = tensor("inputs_35_cast_fp16")]; + tensor out_35_axes_0 = const()[name = tensor("out_35_axes_0"), val = tensor([1])]; + tensor var_1209_to_fp16 = const()[name = tensor("op_1209_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_35_cast_fp16 = layer_norm(axes = out_35_axes_0, epsilon = var_1209_to_fp16, x = inputs_35_cast_fp16)[name = tensor("out_35_cast_fp16")]; + tensor input_67_gamma_0_to_fp16 = const()[name = tensor("input_67_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(219793984)))]; + tensor input_67_beta_0_to_fp16 = const()[name = tensor("input_67_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(219796096)))]; + tensor input_67_epsilon_0_to_fp16 = const()[name = tensor("input_67_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_67_cast_fp16 = batch_norm(beta = input_67_beta_0_to_fp16, epsilon = input_67_epsilon_0_to_fp16, gamma = input_67_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_35_cast_fp16)[name = tensor("input_67_cast_fp16")]; + tensor input_69_pad_type_0 = const()[name = tensor("input_69_pad_type_0"), val = tensor("valid")]; + tensor input_69_strides_0 = const()[name = tensor("input_69_strides_0"), val = tensor([1, 1])]; + tensor input_69_pad_0 = const()[name = tensor("input_69_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_69_dilations_0 = const()[name = tensor("input_69_dilations_0"), val = tensor([1, 1])]; + tensor input_69_groups_0 = const()[name = tensor("input_69_groups_0"), val = tensor(1)]; + tensor layers_8_fc1_weight_to_fp16 = const()[name = tensor("layers_8_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(219798208)))]; + tensor layers_8_fc1_bias_to_fp16 = const()[name = tensor("layers_8_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(228186880)))]; + tensor input_69_cast_fp16 = conv(bias = layers_8_fc1_bias_to_fp16, dilations = input_69_dilations_0, groups = input_69_groups_0, pad = input_69_pad_0, pad_type = input_69_pad_type_0, strides = input_69_strides_0, weight = layers_8_fc1_weight_to_fp16, x = input_67_cast_fp16)[name = tensor("input_69_cast_fp16")]; + tensor input_71_mode_0 = const()[name = tensor("input_71_mode_0"), val = tensor("EXACT")]; + tensor input_71_cast_fp16 = gelu(mode = input_71_mode_0, x = input_69_cast_fp16)[name = tensor("input_71_cast_fp16")]; + tensor hidden_states_21_pad_type_0 = const()[name = tensor("hidden_states_21_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_21_strides_0 = const()[name = tensor("hidden_states_21_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_21_pad_0 = const()[name = tensor("hidden_states_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_21_dilations_0 = const()[name = tensor("hidden_states_21_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_21_groups_0 = const()[name = tensor("hidden_states_21_groups_0"), val = tensor(1)]; + tensor layers_8_fc2_weight_to_fp16 = const()[name = tensor("layers_8_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(228195136)))]; + tensor layers_8_fc2_bias_to_fp16 = const()[name = tensor("layers_8_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236583808)))]; + tensor hidden_states_21_cast_fp16 = conv(bias = layers_8_fc2_bias_to_fp16, dilations = hidden_states_21_dilations_0, groups = hidden_states_21_groups_0, pad = hidden_states_21_pad_0, pad_type = hidden_states_21_pad_type_0, strides = hidden_states_21_strides_0, weight = layers_8_fc2_weight_to_fp16, x = input_71_cast_fp16)[name = tensor("hidden_states_21_cast_fp16")]; + tensor inputs_37_cast_fp16 = add(x = inputs_35_cast_fp16, y = hidden_states_21_cast_fp16)[name = tensor("inputs_37_cast_fp16")]; + tensor var_1238 = const()[name = tensor("op_1238"), val = tensor(3)]; + tensor out_37_axes_0 = const()[name = tensor("out_37_axes_0"), val = tensor([1])]; + tensor var_1260_to_fp16 = const()[name = tensor("op_1260_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_37_cast_fp16 = layer_norm(axes = out_37_axes_0, epsilon = var_1260_to_fp16, x = inputs_37_cast_fp16)[name = tensor("out_37_cast_fp16")]; + tensor obj_37_gamma_0_to_fp16 = const()[name = tensor("obj_37_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236585920)))]; + tensor obj_37_beta_0_to_fp16 = const()[name = tensor("obj_37_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236588032)))]; + tensor obj_37_epsilon_0_to_fp16 = const()[name = tensor("obj_37_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_37_cast_fp16 = batch_norm(beta = obj_37_beta_0_to_fp16, epsilon = obj_37_epsilon_0_to_fp16, gamma = obj_37_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_37_cast_fp16)[name = tensor("obj_37_cast_fp16")]; + tensor query_19_pad_type_0 = const()[name = tensor("query_19_pad_type_0"), val = tensor("valid")]; + tensor query_19_strides_0 = const()[name = tensor("query_19_strides_0"), val = tensor([1, 1])]; + tensor query_19_pad_0 = const()[name = tensor("query_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_19_dilations_0 = const()[name = tensor("query_19_dilations_0"), val = tensor([1, 1])]; + tensor query_19_groups_0 = const()[name = tensor("query_19_groups_0"), val = tensor(1)]; + tensor layers_9_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236590144)))]; + tensor layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(238687360)))]; + tensor query_19_cast_fp16 = conv(bias = layers_9_self_attn_q_proj_bias_to_fp16, dilations = query_19_dilations_0, groups = query_19_groups_0, pad = query_19_pad_0, pad_type = query_19_pad_type_0, strides = query_19_strides_0, weight = layers_9_self_attn_q_proj_weight_to_fp16, x = obj_37_cast_fp16)[name = tensor("query_19_cast_fp16")]; + tensor key_19_pad_type_0 = const()[name = tensor("key_19_pad_type_0"), val = tensor("valid")]; + tensor key_19_strides_0 = const()[name = tensor("key_19_strides_0"), val = tensor([1, 1])]; + tensor key_19_pad_0 = const()[name = tensor("key_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_19_dilations_0 = const()[name = tensor("key_19_dilations_0"), val = tensor([1, 1])]; + tensor key_19_groups_0 = const()[name = tensor("key_19_groups_0"), val = tensor(1)]; + tensor layers_9_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(238689472)))]; + tensor key_19_cast_fp16 = conv(dilations = key_19_dilations_0, groups = key_19_groups_0, pad = key_19_pad_0, pad_type = key_19_pad_type_0, strides = key_19_strides_0, weight = layers_9_self_attn_k_proj_weight_to_fp16, x = obj_37_cast_fp16)[name = tensor("key_19_cast_fp16")]; + tensor value_19_pad_type_0 = const()[name = tensor("value_19_pad_type_0"), val = tensor("valid")]; + tensor value_19_strides_0 = const()[name = tensor("value_19_strides_0"), val = tensor([1, 1])]; + tensor value_19_pad_0 = const()[name = tensor("value_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_19_dilations_0 = const()[name = tensor("value_19_dilations_0"), val = tensor([1, 1])]; + tensor value_19_groups_0 = const()[name = tensor("value_19_groups_0"), val = tensor(1)]; + tensor layers_9_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240786688)))]; + tensor layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242883904)))]; + tensor value_19_cast_fp16 = conv(bias = layers_9_self_attn_v_proj_bias_to_fp16, dilations = value_19_dilations_0, groups = value_19_groups_0, pad = value_19_pad_0, pad_type = value_19_pad_type_0, strides = value_19_strides_0, weight = layers_9_self_attn_v_proj_weight_to_fp16, x = obj_37_cast_fp16)[name = tensor("value_19_cast_fp16")]; + tensor var_1296 = const()[name = tensor("op_1296"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_19_cast_fp16 = reshape(shape = var_1296, x = query_19_cast_fp16)[name = tensor("mh_q_19_cast_fp16")]; + tensor var_1298_to_fp16 = const()[name = tensor("op_1298_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1299_cast_fp16 = mul(x = mh_q_19_cast_fp16, y = var_1298_to_fp16)[name = tensor("op_1299_cast_fp16")]; + tensor var_1302 = const()[name = tensor("op_1302"), val = tensor([1, 16, 64, 1500])]; + tensor var_1303_cast_fp16 = reshape(shape = var_1302, x = key_19_cast_fp16)[name = tensor("op_1303_cast_fp16")]; + tensor mh_w_19_transpose_x_0 = const()[name = tensor("mh_w_19_transpose_x_0"), val = tensor(true)]; + tensor mh_w_19_transpose_y_0 = const()[name = tensor("mh_w_19_transpose_y_0"), val = tensor(false)]; + tensor mh_w_19_cast_fp16 = matmul(transpose_x = mh_w_19_transpose_x_0, transpose_y = mh_w_19_transpose_y_0, x = var_1299_cast_fp16, y = var_1303_cast_fp16)[name = tensor("mh_w_19_cast_fp16")]; + tensor var_1306_cast_fp16 = softmax(axis = var_1238, x = mh_w_19_cast_fp16)[name = tensor("op_1306_cast_fp16")]; + tensor var_1307 = const()[name = tensor("op_1307"), val = tensor([1, 16, 64, 1500])]; + tensor var_1308_cast_fp16 = reshape(shape = var_1307, x = value_19_cast_fp16)[name = tensor("op_1308_cast_fp16")]; + tensor attn_19_transpose_x_0 = const()[name = tensor("attn_19_transpose_x_0"), val = tensor(false)]; + tensor attn_19_transpose_y_0 = const()[name = tensor("attn_19_transpose_y_0"), val = tensor(true)]; + tensor attn_19_cast_fp16 = matmul(transpose_x = attn_19_transpose_x_0, transpose_y = attn_19_transpose_y_0, x = var_1308_cast_fp16, y = var_1306_cast_fp16)[name = tensor("attn_19_cast_fp16")]; + tensor var_1311 = const()[name = tensor("op_1311"), val = tensor([1, 1024, 1, 1500])]; + tensor input_73_cast_fp16 = reshape(shape = var_1311, x = attn_19_cast_fp16)[name = tensor("input_73_cast_fp16")]; + tensor obj_39_pad_type_0 = const()[name = tensor("obj_39_pad_type_0"), val = tensor("valid")]; + tensor obj_39_strides_0 = const()[name = tensor("obj_39_strides_0"), val = tensor([1, 1])]; + tensor obj_39_pad_0 = const()[name = tensor("obj_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_39_dilations_0 = const()[name = tensor("obj_39_dilations_0"), val = tensor([1, 1])]; + tensor obj_39_groups_0 = const()[name = tensor("obj_39_groups_0"), val = tensor(1)]; + tensor layers_9_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242886016)))]; + tensor layers_9_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244983232)))]; + tensor obj_39_cast_fp16 = conv(bias = layers_9_self_attn_o_proj_bias_to_fp16, dilations = obj_39_dilations_0, groups = obj_39_groups_0, pad = obj_39_pad_0, pad_type = obj_39_pad_type_0, strides = obj_39_strides_0, weight = layers_9_self_attn_o_proj_weight_to_fp16, x = input_73_cast_fp16)[name = tensor("obj_39_cast_fp16")]; + tensor inputs_39_cast_fp16 = add(x = inputs_37_cast_fp16, y = obj_39_cast_fp16)[name = tensor("inputs_39_cast_fp16")]; + tensor out_39_axes_0 = const()[name = tensor("out_39_axes_0"), val = tensor([1])]; + tensor var_1329_to_fp16 = const()[name = tensor("op_1329_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_39_cast_fp16 = layer_norm(axes = out_39_axes_0, epsilon = var_1329_to_fp16, x = inputs_39_cast_fp16)[name = tensor("out_39_cast_fp16")]; + tensor input_75_gamma_0_to_fp16 = const()[name = tensor("input_75_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244985344)))]; + tensor input_75_beta_0_to_fp16 = const()[name = tensor("input_75_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244987456)))]; + tensor input_75_epsilon_0_to_fp16 = const()[name = tensor("input_75_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_75_cast_fp16 = batch_norm(beta = input_75_beta_0_to_fp16, epsilon = input_75_epsilon_0_to_fp16, gamma = input_75_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_39_cast_fp16)[name = tensor("input_75_cast_fp16")]; + tensor input_77_pad_type_0 = const()[name = tensor("input_77_pad_type_0"), val = tensor("valid")]; + tensor input_77_strides_0 = const()[name = tensor("input_77_strides_0"), val = tensor([1, 1])]; + tensor input_77_pad_0 = const()[name = tensor("input_77_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_77_dilations_0 = const()[name = tensor("input_77_dilations_0"), val = tensor([1, 1])]; + tensor input_77_groups_0 = const()[name = tensor("input_77_groups_0"), val = tensor(1)]; + tensor layers_9_fc1_weight_to_fp16 = const()[name = tensor("layers_9_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244989568)))]; + tensor layers_9_fc1_bias_to_fp16 = const()[name = tensor("layers_9_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(253378240)))]; + tensor input_77_cast_fp16 = conv(bias = layers_9_fc1_bias_to_fp16, dilations = input_77_dilations_0, groups = input_77_groups_0, pad = input_77_pad_0, pad_type = input_77_pad_type_0, strides = input_77_strides_0, weight = layers_9_fc1_weight_to_fp16, x = input_75_cast_fp16)[name = tensor("input_77_cast_fp16")]; + tensor input_79_mode_0 = const()[name = tensor("input_79_mode_0"), val = tensor("EXACT")]; + tensor input_79_cast_fp16 = gelu(mode = input_79_mode_0, x = input_77_cast_fp16)[name = tensor("input_79_cast_fp16")]; + tensor hidden_states_23_pad_type_0 = const()[name = tensor("hidden_states_23_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_23_strides_0 = const()[name = tensor("hidden_states_23_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_23_pad_0 = const()[name = tensor("hidden_states_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_23_dilations_0 = const()[name = tensor("hidden_states_23_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_23_groups_0 = const()[name = tensor("hidden_states_23_groups_0"), val = tensor(1)]; + tensor layers_9_fc2_weight_to_fp16 = const()[name = tensor("layers_9_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(253386496)))]; + tensor layers_9_fc2_bias_to_fp16 = const()[name = tensor("layers_9_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261775168)))]; + tensor hidden_states_23_cast_fp16 = conv(bias = layers_9_fc2_bias_to_fp16, dilations = hidden_states_23_dilations_0, groups = hidden_states_23_groups_0, pad = hidden_states_23_pad_0, pad_type = hidden_states_23_pad_type_0, strides = hidden_states_23_strides_0, weight = layers_9_fc2_weight_to_fp16, x = input_79_cast_fp16)[name = tensor("hidden_states_23_cast_fp16")]; + tensor inputs_41_cast_fp16 = add(x = inputs_39_cast_fp16, y = hidden_states_23_cast_fp16)[name = tensor("inputs_41_cast_fp16")]; + tensor var_1358 = const()[name = tensor("op_1358"), val = tensor(3)]; + tensor out_41_axes_0 = const()[name = tensor("out_41_axes_0"), val = tensor([1])]; + tensor var_1380_to_fp16 = const()[name = tensor("op_1380_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_41_cast_fp16 = layer_norm(axes = out_41_axes_0, epsilon = var_1380_to_fp16, x = inputs_41_cast_fp16)[name = tensor("out_41_cast_fp16")]; + tensor obj_41_gamma_0_to_fp16 = const()[name = tensor("obj_41_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261777280)))]; + tensor obj_41_beta_0_to_fp16 = const()[name = tensor("obj_41_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261779392)))]; + tensor obj_41_epsilon_0_to_fp16 = const()[name = tensor("obj_41_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_41_cast_fp16 = batch_norm(beta = obj_41_beta_0_to_fp16, epsilon = obj_41_epsilon_0_to_fp16, gamma = obj_41_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_41_cast_fp16)[name = tensor("obj_41_cast_fp16")]; + tensor query_21_pad_type_0 = const()[name = tensor("query_21_pad_type_0"), val = tensor("valid")]; + tensor query_21_strides_0 = const()[name = tensor("query_21_strides_0"), val = tensor([1, 1])]; + tensor query_21_pad_0 = const()[name = tensor("query_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_21_dilations_0 = const()[name = tensor("query_21_dilations_0"), val = tensor([1, 1])]; + tensor query_21_groups_0 = const()[name = tensor("query_21_groups_0"), val = tensor(1)]; + tensor layers_10_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261781504)))]; + tensor layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263878720)))]; + tensor query_21_cast_fp16 = conv(bias = layers_10_self_attn_q_proj_bias_to_fp16, dilations = query_21_dilations_0, groups = query_21_groups_0, pad = query_21_pad_0, pad_type = query_21_pad_type_0, strides = query_21_strides_0, weight = layers_10_self_attn_q_proj_weight_to_fp16, x = obj_41_cast_fp16)[name = tensor("query_21_cast_fp16")]; + tensor key_21_pad_type_0 = const()[name = tensor("key_21_pad_type_0"), val = tensor("valid")]; + tensor key_21_strides_0 = const()[name = tensor("key_21_strides_0"), val = tensor([1, 1])]; + tensor key_21_pad_0 = const()[name = tensor("key_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_21_dilations_0 = const()[name = tensor("key_21_dilations_0"), val = tensor([1, 1])]; + tensor key_21_groups_0 = const()[name = tensor("key_21_groups_0"), val = tensor(1)]; + tensor layers_10_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263880832)))]; + tensor key_21_cast_fp16 = conv(dilations = key_21_dilations_0, groups = key_21_groups_0, pad = key_21_pad_0, pad_type = key_21_pad_type_0, strides = key_21_strides_0, weight = layers_10_self_attn_k_proj_weight_to_fp16, x = obj_41_cast_fp16)[name = tensor("key_21_cast_fp16")]; + tensor value_21_pad_type_0 = const()[name = tensor("value_21_pad_type_0"), val = tensor("valid")]; + tensor value_21_strides_0 = const()[name = tensor("value_21_strides_0"), val = tensor([1, 1])]; + tensor value_21_pad_0 = const()[name = tensor("value_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_21_dilations_0 = const()[name = tensor("value_21_dilations_0"), val = tensor([1, 1])]; + tensor value_21_groups_0 = const()[name = tensor("value_21_groups_0"), val = tensor(1)]; + tensor layers_10_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265978048)))]; + tensor layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(268075264)))]; + tensor value_21_cast_fp16 = conv(bias = layers_10_self_attn_v_proj_bias_to_fp16, dilations = value_21_dilations_0, groups = value_21_groups_0, pad = value_21_pad_0, pad_type = value_21_pad_type_0, strides = value_21_strides_0, weight = layers_10_self_attn_v_proj_weight_to_fp16, x = obj_41_cast_fp16)[name = tensor("value_21_cast_fp16")]; + tensor var_1416 = const()[name = tensor("op_1416"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_21_cast_fp16 = reshape(shape = var_1416, x = query_21_cast_fp16)[name = tensor("mh_q_21_cast_fp16")]; + tensor var_1418_to_fp16 = const()[name = tensor("op_1418_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1419_cast_fp16 = mul(x = mh_q_21_cast_fp16, y = var_1418_to_fp16)[name = tensor("op_1419_cast_fp16")]; + tensor var_1422 = const()[name = tensor("op_1422"), val = tensor([1, 16, 64, 1500])]; + tensor var_1423_cast_fp16 = reshape(shape = var_1422, x = key_21_cast_fp16)[name = tensor("op_1423_cast_fp16")]; + tensor mh_w_21_transpose_x_0 = const()[name = tensor("mh_w_21_transpose_x_0"), val = tensor(true)]; + tensor mh_w_21_transpose_y_0 = const()[name = tensor("mh_w_21_transpose_y_0"), val = tensor(false)]; + tensor mh_w_21_cast_fp16 = matmul(transpose_x = mh_w_21_transpose_x_0, transpose_y = mh_w_21_transpose_y_0, x = var_1419_cast_fp16, y = var_1423_cast_fp16)[name = tensor("mh_w_21_cast_fp16")]; + tensor var_1426_cast_fp16 = softmax(axis = var_1358, x = mh_w_21_cast_fp16)[name = tensor("op_1426_cast_fp16")]; + tensor var_1427 = const()[name = tensor("op_1427"), val = tensor([1, 16, 64, 1500])]; + tensor var_1428_cast_fp16 = reshape(shape = var_1427, x = value_21_cast_fp16)[name = tensor("op_1428_cast_fp16")]; + tensor attn_21_transpose_x_0 = const()[name = tensor("attn_21_transpose_x_0"), val = tensor(false)]; + tensor attn_21_transpose_y_0 = const()[name = tensor("attn_21_transpose_y_0"), val = tensor(true)]; + tensor attn_21_cast_fp16 = matmul(transpose_x = attn_21_transpose_x_0, transpose_y = attn_21_transpose_y_0, x = var_1428_cast_fp16, y = var_1426_cast_fp16)[name = tensor("attn_21_cast_fp16")]; + tensor var_1431 = const()[name = tensor("op_1431"), val = tensor([1, 1024, 1, 1500])]; + tensor input_81_cast_fp16 = reshape(shape = var_1431, x = attn_21_cast_fp16)[name = tensor("input_81_cast_fp16")]; + tensor obj_43_pad_type_0 = const()[name = tensor("obj_43_pad_type_0"), val = tensor("valid")]; + tensor obj_43_strides_0 = const()[name = tensor("obj_43_strides_0"), val = tensor([1, 1])]; + tensor obj_43_pad_0 = const()[name = tensor("obj_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_43_dilations_0 = const()[name = tensor("obj_43_dilations_0"), val = tensor([1, 1])]; + tensor obj_43_groups_0 = const()[name = tensor("obj_43_groups_0"), val = tensor(1)]; + tensor layers_10_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(268077376)))]; + tensor layers_10_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(270174592)))]; + tensor obj_43_cast_fp16 = conv(bias = layers_10_self_attn_o_proj_bias_to_fp16, dilations = obj_43_dilations_0, groups = obj_43_groups_0, pad = obj_43_pad_0, pad_type = obj_43_pad_type_0, strides = obj_43_strides_0, weight = layers_10_self_attn_o_proj_weight_to_fp16, x = input_81_cast_fp16)[name = tensor("obj_43_cast_fp16")]; + tensor inputs_43_cast_fp16 = add(x = inputs_41_cast_fp16, y = obj_43_cast_fp16)[name = tensor("inputs_43_cast_fp16")]; + tensor out_43_axes_0 = const()[name = tensor("out_43_axes_0"), val = tensor([1])]; + tensor var_1449_to_fp16 = const()[name = tensor("op_1449_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_43_cast_fp16 = layer_norm(axes = out_43_axes_0, epsilon = var_1449_to_fp16, x = inputs_43_cast_fp16)[name = tensor("out_43_cast_fp16")]; + tensor input_83_gamma_0_to_fp16 = const()[name = tensor("input_83_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(270176704)))]; + tensor input_83_beta_0_to_fp16 = const()[name = tensor("input_83_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(270178816)))]; + tensor input_83_epsilon_0_to_fp16 = const()[name = tensor("input_83_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_83_cast_fp16 = batch_norm(beta = input_83_beta_0_to_fp16, epsilon = input_83_epsilon_0_to_fp16, gamma = input_83_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_43_cast_fp16)[name = tensor("input_83_cast_fp16")]; + tensor input_85_pad_type_0 = const()[name = tensor("input_85_pad_type_0"), val = tensor("valid")]; + tensor input_85_strides_0 = const()[name = tensor("input_85_strides_0"), val = tensor([1, 1])]; + tensor input_85_pad_0 = const()[name = tensor("input_85_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_85_dilations_0 = const()[name = tensor("input_85_dilations_0"), val = tensor([1, 1])]; + tensor input_85_groups_0 = const()[name = tensor("input_85_groups_0"), val = tensor(1)]; + tensor layers_10_fc1_weight_to_fp16 = const()[name = tensor("layers_10_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(270180928)))]; + tensor layers_10_fc1_bias_to_fp16 = const()[name = tensor("layers_10_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278569600)))]; + tensor input_85_cast_fp16 = conv(bias = layers_10_fc1_bias_to_fp16, dilations = input_85_dilations_0, groups = input_85_groups_0, pad = input_85_pad_0, pad_type = input_85_pad_type_0, strides = input_85_strides_0, weight = layers_10_fc1_weight_to_fp16, x = input_83_cast_fp16)[name = tensor("input_85_cast_fp16")]; + tensor input_87_mode_0 = const()[name = tensor("input_87_mode_0"), val = tensor("EXACT")]; + tensor input_87_cast_fp16 = gelu(mode = input_87_mode_0, x = input_85_cast_fp16)[name = tensor("input_87_cast_fp16")]; + tensor hidden_states_25_pad_type_0 = const()[name = tensor("hidden_states_25_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_25_strides_0 = const()[name = tensor("hidden_states_25_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_25_pad_0 = const()[name = tensor("hidden_states_25_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_25_dilations_0 = const()[name = tensor("hidden_states_25_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_25_groups_0 = const()[name = tensor("hidden_states_25_groups_0"), val = tensor(1)]; + tensor layers_10_fc2_weight_to_fp16 = const()[name = tensor("layers_10_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278577856)))]; + tensor layers_10_fc2_bias_to_fp16 = const()[name = tensor("layers_10_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286966528)))]; + tensor hidden_states_25_cast_fp16 = conv(bias = layers_10_fc2_bias_to_fp16, dilations = hidden_states_25_dilations_0, groups = hidden_states_25_groups_0, pad = hidden_states_25_pad_0, pad_type = hidden_states_25_pad_type_0, strides = hidden_states_25_strides_0, weight = layers_10_fc2_weight_to_fp16, x = input_87_cast_fp16)[name = tensor("hidden_states_25_cast_fp16")]; + tensor inputs_45_cast_fp16 = add(x = inputs_43_cast_fp16, y = hidden_states_25_cast_fp16)[name = tensor("inputs_45_cast_fp16")]; + tensor var_1478 = const()[name = tensor("op_1478"), val = tensor(3)]; + tensor out_45_axes_0 = const()[name = tensor("out_45_axes_0"), val = tensor([1])]; + tensor var_1500_to_fp16 = const()[name = tensor("op_1500_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_45_cast_fp16 = layer_norm(axes = out_45_axes_0, epsilon = var_1500_to_fp16, x = inputs_45_cast_fp16)[name = tensor("out_45_cast_fp16")]; + tensor obj_45_gamma_0_to_fp16 = const()[name = tensor("obj_45_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286968640)))]; + tensor obj_45_beta_0_to_fp16 = const()[name = tensor("obj_45_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286970752)))]; + tensor obj_45_epsilon_0_to_fp16 = const()[name = tensor("obj_45_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_45_cast_fp16 = batch_norm(beta = obj_45_beta_0_to_fp16, epsilon = obj_45_epsilon_0_to_fp16, gamma = obj_45_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_45_cast_fp16)[name = tensor("obj_45_cast_fp16")]; + tensor query_23_pad_type_0 = const()[name = tensor("query_23_pad_type_0"), val = tensor("valid")]; + tensor query_23_strides_0 = const()[name = tensor("query_23_strides_0"), val = tensor([1, 1])]; + tensor query_23_pad_0 = const()[name = tensor("query_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_23_dilations_0 = const()[name = tensor("query_23_dilations_0"), val = tensor([1, 1])]; + tensor query_23_groups_0 = const()[name = tensor("query_23_groups_0"), val = tensor(1)]; + tensor layers_11_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286972864)))]; + tensor layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289070080)))]; + tensor query_23_cast_fp16 = conv(bias = layers_11_self_attn_q_proj_bias_to_fp16, dilations = query_23_dilations_0, groups = query_23_groups_0, pad = query_23_pad_0, pad_type = query_23_pad_type_0, strides = query_23_strides_0, weight = layers_11_self_attn_q_proj_weight_to_fp16, x = obj_45_cast_fp16)[name = tensor("query_23_cast_fp16")]; + tensor key_23_pad_type_0 = const()[name = tensor("key_23_pad_type_0"), val = tensor("valid")]; + tensor key_23_strides_0 = const()[name = tensor("key_23_strides_0"), val = tensor([1, 1])]; + tensor key_23_pad_0 = const()[name = tensor("key_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_23_dilations_0 = const()[name = tensor("key_23_dilations_0"), val = tensor([1, 1])]; + tensor key_23_groups_0 = const()[name = tensor("key_23_groups_0"), val = tensor(1)]; + tensor layers_11_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289072192)))]; + tensor key_23_cast_fp16 = conv(dilations = key_23_dilations_0, groups = key_23_groups_0, pad = key_23_pad_0, pad_type = key_23_pad_type_0, strides = key_23_strides_0, weight = layers_11_self_attn_k_proj_weight_to_fp16, x = obj_45_cast_fp16)[name = tensor("key_23_cast_fp16")]; + tensor value_23_pad_type_0 = const()[name = tensor("value_23_pad_type_0"), val = tensor("valid")]; + tensor value_23_strides_0 = const()[name = tensor("value_23_strides_0"), val = tensor([1, 1])]; + tensor value_23_pad_0 = const()[name = tensor("value_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_23_dilations_0 = const()[name = tensor("value_23_dilations_0"), val = tensor([1, 1])]; + tensor value_23_groups_0 = const()[name = tensor("value_23_groups_0"), val = tensor(1)]; + tensor layers_11_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291169408)))]; + tensor layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293266624)))]; + tensor value_23_cast_fp16 = conv(bias = layers_11_self_attn_v_proj_bias_to_fp16, dilations = value_23_dilations_0, groups = value_23_groups_0, pad = value_23_pad_0, pad_type = value_23_pad_type_0, strides = value_23_strides_0, weight = layers_11_self_attn_v_proj_weight_to_fp16, x = obj_45_cast_fp16)[name = tensor("value_23_cast_fp16")]; + tensor var_1536 = const()[name = tensor("op_1536"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_23_cast_fp16 = reshape(shape = var_1536, x = query_23_cast_fp16)[name = tensor("mh_q_23_cast_fp16")]; + tensor var_1538_to_fp16 = const()[name = tensor("op_1538_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1539_cast_fp16 = mul(x = mh_q_23_cast_fp16, y = var_1538_to_fp16)[name = tensor("op_1539_cast_fp16")]; + tensor var_1542 = const()[name = tensor("op_1542"), val = tensor([1, 16, 64, 1500])]; + tensor var_1543_cast_fp16 = reshape(shape = var_1542, x = key_23_cast_fp16)[name = tensor("op_1543_cast_fp16")]; + tensor mh_w_23_transpose_x_0 = const()[name = tensor("mh_w_23_transpose_x_0"), val = tensor(true)]; + tensor mh_w_23_transpose_y_0 = const()[name = tensor("mh_w_23_transpose_y_0"), val = tensor(false)]; + tensor mh_w_23_cast_fp16 = matmul(transpose_x = mh_w_23_transpose_x_0, transpose_y = mh_w_23_transpose_y_0, x = var_1539_cast_fp16, y = var_1543_cast_fp16)[name = tensor("mh_w_23_cast_fp16")]; + tensor var_1546_cast_fp16 = softmax(axis = var_1478, x = mh_w_23_cast_fp16)[name = tensor("op_1546_cast_fp16")]; + tensor var_1547 = const()[name = tensor("op_1547"), val = tensor([1, 16, 64, 1500])]; + tensor var_1548_cast_fp16 = reshape(shape = var_1547, x = value_23_cast_fp16)[name = tensor("op_1548_cast_fp16")]; + tensor attn_23_transpose_x_0 = const()[name = tensor("attn_23_transpose_x_0"), val = tensor(false)]; + tensor attn_23_transpose_y_0 = const()[name = tensor("attn_23_transpose_y_0"), val = tensor(true)]; + tensor attn_23_cast_fp16 = matmul(transpose_x = attn_23_transpose_x_0, transpose_y = attn_23_transpose_y_0, x = var_1548_cast_fp16, y = var_1546_cast_fp16)[name = tensor("attn_23_cast_fp16")]; + tensor var_1551 = const()[name = tensor("op_1551"), val = tensor([1, 1024, 1, 1500])]; + tensor input_89_cast_fp16 = reshape(shape = var_1551, x = attn_23_cast_fp16)[name = tensor("input_89_cast_fp16")]; + tensor obj_47_pad_type_0 = const()[name = tensor("obj_47_pad_type_0"), val = tensor("valid")]; + tensor obj_47_strides_0 = const()[name = tensor("obj_47_strides_0"), val = tensor([1, 1])]; + tensor obj_47_pad_0 = const()[name = tensor("obj_47_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_47_dilations_0 = const()[name = tensor("obj_47_dilations_0"), val = tensor([1, 1])]; + tensor obj_47_groups_0 = const()[name = tensor("obj_47_groups_0"), val = tensor(1)]; + tensor layers_11_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293268736)))]; + tensor layers_11_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(295365952)))]; + tensor obj_47_cast_fp16 = conv(bias = layers_11_self_attn_o_proj_bias_to_fp16, dilations = obj_47_dilations_0, groups = obj_47_groups_0, pad = obj_47_pad_0, pad_type = obj_47_pad_type_0, strides = obj_47_strides_0, weight = layers_11_self_attn_o_proj_weight_to_fp16, x = input_89_cast_fp16)[name = tensor("obj_47_cast_fp16")]; + tensor inputs_47_cast_fp16 = add(x = inputs_45_cast_fp16, y = obj_47_cast_fp16)[name = tensor("inputs_47_cast_fp16")]; + tensor out_47_axes_0 = const()[name = tensor("out_47_axes_0"), val = tensor([1])]; + tensor var_1569_to_fp16 = const()[name = tensor("op_1569_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_47_cast_fp16 = layer_norm(axes = out_47_axes_0, epsilon = var_1569_to_fp16, x = inputs_47_cast_fp16)[name = tensor("out_47_cast_fp16")]; + tensor input_91_gamma_0_to_fp16 = const()[name = tensor("input_91_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(295368064)))]; + tensor input_91_beta_0_to_fp16 = const()[name = tensor("input_91_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(295370176)))]; + tensor input_91_epsilon_0_to_fp16 = const()[name = tensor("input_91_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_91_cast_fp16 = batch_norm(beta = input_91_beta_0_to_fp16, epsilon = input_91_epsilon_0_to_fp16, gamma = input_91_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_47_cast_fp16)[name = tensor("input_91_cast_fp16")]; + tensor input_93_pad_type_0 = const()[name = tensor("input_93_pad_type_0"), val = tensor("valid")]; + tensor input_93_strides_0 = const()[name = tensor("input_93_strides_0"), val = tensor([1, 1])]; + tensor input_93_pad_0 = const()[name = tensor("input_93_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_93_dilations_0 = const()[name = tensor("input_93_dilations_0"), val = tensor([1, 1])]; + tensor input_93_groups_0 = const()[name = tensor("input_93_groups_0"), val = tensor(1)]; + tensor layers_11_fc1_weight_to_fp16 = const()[name = tensor("layers_11_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(295372288)))]; + tensor layers_11_fc1_bias_to_fp16 = const()[name = tensor("layers_11_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303760960)))]; + tensor input_93_cast_fp16 = conv(bias = layers_11_fc1_bias_to_fp16, dilations = input_93_dilations_0, groups = input_93_groups_0, pad = input_93_pad_0, pad_type = input_93_pad_type_0, strides = input_93_strides_0, weight = layers_11_fc1_weight_to_fp16, x = input_91_cast_fp16)[name = tensor("input_93_cast_fp16")]; + tensor input_95_mode_0 = const()[name = tensor("input_95_mode_0"), val = tensor("EXACT")]; + tensor input_95_cast_fp16 = gelu(mode = input_95_mode_0, x = input_93_cast_fp16)[name = tensor("input_95_cast_fp16")]; + tensor hidden_states_27_pad_type_0 = const()[name = tensor("hidden_states_27_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_27_strides_0 = const()[name = tensor("hidden_states_27_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_27_pad_0 = const()[name = tensor("hidden_states_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_27_dilations_0 = const()[name = tensor("hidden_states_27_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_27_groups_0 = const()[name = tensor("hidden_states_27_groups_0"), val = tensor(1)]; + tensor layers_11_fc2_weight_to_fp16 = const()[name = tensor("layers_11_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303769216)))]; + tensor layers_11_fc2_bias_to_fp16 = const()[name = tensor("layers_11_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(312157888)))]; + tensor hidden_states_27_cast_fp16 = conv(bias = layers_11_fc2_bias_to_fp16, dilations = hidden_states_27_dilations_0, groups = hidden_states_27_groups_0, pad = hidden_states_27_pad_0, pad_type = hidden_states_27_pad_type_0, strides = hidden_states_27_strides_0, weight = layers_11_fc2_weight_to_fp16, x = input_95_cast_fp16)[name = tensor("hidden_states_27_cast_fp16")]; + tensor inputs_49_cast_fp16 = add(x = inputs_47_cast_fp16, y = hidden_states_27_cast_fp16)[name = tensor("inputs_49_cast_fp16")]; + tensor var_1598 = const()[name = tensor("op_1598"), val = tensor(3)]; + tensor out_49_axes_0 = const()[name = tensor("out_49_axes_0"), val = tensor([1])]; + tensor var_1620_to_fp16 = const()[name = tensor("op_1620_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_49_cast_fp16 = layer_norm(axes = out_49_axes_0, epsilon = var_1620_to_fp16, x = inputs_49_cast_fp16)[name = tensor("out_49_cast_fp16")]; + tensor obj_49_gamma_0_to_fp16 = const()[name = tensor("obj_49_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(312160000)))]; + tensor obj_49_beta_0_to_fp16 = const()[name = tensor("obj_49_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(312162112)))]; + tensor obj_49_epsilon_0_to_fp16 = const()[name = tensor("obj_49_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_49_cast_fp16 = batch_norm(beta = obj_49_beta_0_to_fp16, epsilon = obj_49_epsilon_0_to_fp16, gamma = obj_49_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_49_cast_fp16)[name = tensor("obj_49_cast_fp16")]; + tensor query_25_pad_type_0 = const()[name = tensor("query_25_pad_type_0"), val = tensor("valid")]; + tensor query_25_strides_0 = const()[name = tensor("query_25_strides_0"), val = tensor([1, 1])]; + tensor query_25_pad_0 = const()[name = tensor("query_25_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_25_dilations_0 = const()[name = tensor("query_25_dilations_0"), val = tensor([1, 1])]; + tensor query_25_groups_0 = const()[name = tensor("query_25_groups_0"), val = tensor(1)]; + tensor layers_12_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_12_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(312164224)))]; + tensor layers_12_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_12_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(314261440)))]; + tensor query_25_cast_fp16 = conv(bias = layers_12_self_attn_q_proj_bias_to_fp16, dilations = query_25_dilations_0, groups = query_25_groups_0, pad = query_25_pad_0, pad_type = query_25_pad_type_0, strides = query_25_strides_0, weight = layers_12_self_attn_q_proj_weight_to_fp16, x = obj_49_cast_fp16)[name = tensor("query_25_cast_fp16")]; + tensor key_25_pad_type_0 = const()[name = tensor("key_25_pad_type_0"), val = tensor("valid")]; + tensor key_25_strides_0 = const()[name = tensor("key_25_strides_0"), val = tensor([1, 1])]; + tensor key_25_pad_0 = const()[name = tensor("key_25_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_25_dilations_0 = const()[name = tensor("key_25_dilations_0"), val = tensor([1, 1])]; + tensor key_25_groups_0 = const()[name = tensor("key_25_groups_0"), val = tensor(1)]; + tensor layers_12_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_12_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(314263552)))]; + tensor key_25_cast_fp16 = conv(dilations = key_25_dilations_0, groups = key_25_groups_0, pad = key_25_pad_0, pad_type = key_25_pad_type_0, strides = key_25_strides_0, weight = layers_12_self_attn_k_proj_weight_to_fp16, x = obj_49_cast_fp16)[name = tensor("key_25_cast_fp16")]; + tensor value_25_pad_type_0 = const()[name = tensor("value_25_pad_type_0"), val = tensor("valid")]; + tensor value_25_strides_0 = const()[name = tensor("value_25_strides_0"), val = tensor([1, 1])]; + tensor value_25_pad_0 = const()[name = tensor("value_25_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_25_dilations_0 = const()[name = tensor("value_25_dilations_0"), val = tensor([1, 1])]; + tensor value_25_groups_0 = const()[name = tensor("value_25_groups_0"), val = tensor(1)]; + tensor layers_12_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_12_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(316360768)))]; + tensor layers_12_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_12_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318457984)))]; + tensor value_25_cast_fp16 = conv(bias = layers_12_self_attn_v_proj_bias_to_fp16, dilations = value_25_dilations_0, groups = value_25_groups_0, pad = value_25_pad_0, pad_type = value_25_pad_type_0, strides = value_25_strides_0, weight = layers_12_self_attn_v_proj_weight_to_fp16, x = obj_49_cast_fp16)[name = tensor("value_25_cast_fp16")]; + tensor var_1656 = const()[name = tensor("op_1656"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_25_cast_fp16 = reshape(shape = var_1656, x = query_25_cast_fp16)[name = tensor("mh_q_25_cast_fp16")]; + tensor var_1658_to_fp16 = const()[name = tensor("op_1658_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1659_cast_fp16 = mul(x = mh_q_25_cast_fp16, y = var_1658_to_fp16)[name = tensor("op_1659_cast_fp16")]; + tensor var_1662 = const()[name = tensor("op_1662"), val = tensor([1, 16, 64, 1500])]; + tensor var_1663_cast_fp16 = reshape(shape = var_1662, x = key_25_cast_fp16)[name = tensor("op_1663_cast_fp16")]; + tensor mh_w_25_transpose_x_0 = const()[name = tensor("mh_w_25_transpose_x_0"), val = tensor(true)]; + tensor mh_w_25_transpose_y_0 = const()[name = tensor("mh_w_25_transpose_y_0"), val = tensor(false)]; + tensor mh_w_25_cast_fp16 = matmul(transpose_x = mh_w_25_transpose_x_0, transpose_y = mh_w_25_transpose_y_0, x = var_1659_cast_fp16, y = var_1663_cast_fp16)[name = tensor("mh_w_25_cast_fp16")]; + tensor var_1666_cast_fp16 = softmax(axis = var_1598, x = mh_w_25_cast_fp16)[name = tensor("op_1666_cast_fp16")]; + tensor var_1667 = const()[name = tensor("op_1667"), val = tensor([1, 16, 64, 1500])]; + tensor var_1668_cast_fp16 = reshape(shape = var_1667, x = value_25_cast_fp16)[name = tensor("op_1668_cast_fp16")]; + tensor attn_25_transpose_x_0 = const()[name = tensor("attn_25_transpose_x_0"), val = tensor(false)]; + tensor attn_25_transpose_y_0 = const()[name = tensor("attn_25_transpose_y_0"), val = tensor(true)]; + tensor attn_25_cast_fp16 = matmul(transpose_x = attn_25_transpose_x_0, transpose_y = attn_25_transpose_y_0, x = var_1668_cast_fp16, y = var_1666_cast_fp16)[name = tensor("attn_25_cast_fp16")]; + tensor var_1671 = const()[name = tensor("op_1671"), val = tensor([1, 1024, 1, 1500])]; + tensor input_97_cast_fp16 = reshape(shape = var_1671, x = attn_25_cast_fp16)[name = tensor("input_97_cast_fp16")]; + tensor obj_51_pad_type_0 = const()[name = tensor("obj_51_pad_type_0"), val = tensor("valid")]; + tensor obj_51_strides_0 = const()[name = tensor("obj_51_strides_0"), val = tensor([1, 1])]; + tensor obj_51_pad_0 = const()[name = tensor("obj_51_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_51_dilations_0 = const()[name = tensor("obj_51_dilations_0"), val = tensor([1, 1])]; + tensor obj_51_groups_0 = const()[name = tensor("obj_51_groups_0"), val = tensor(1)]; + tensor layers_12_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_12_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318460096)))]; + tensor layers_12_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_12_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(320557312)))]; + tensor obj_51_cast_fp16 = conv(bias = layers_12_self_attn_o_proj_bias_to_fp16, dilations = obj_51_dilations_0, groups = obj_51_groups_0, pad = obj_51_pad_0, pad_type = obj_51_pad_type_0, strides = obj_51_strides_0, weight = layers_12_self_attn_o_proj_weight_to_fp16, x = input_97_cast_fp16)[name = tensor("obj_51_cast_fp16")]; + tensor inputs_51_cast_fp16 = add(x = inputs_49_cast_fp16, y = obj_51_cast_fp16)[name = tensor("inputs_51_cast_fp16")]; + tensor out_51_axes_0 = const()[name = tensor("out_51_axes_0"), val = tensor([1])]; + tensor var_1689_to_fp16 = const()[name = tensor("op_1689_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_51_cast_fp16 = layer_norm(axes = out_51_axes_0, epsilon = var_1689_to_fp16, x = inputs_51_cast_fp16)[name = tensor("out_51_cast_fp16")]; + tensor input_99_gamma_0_to_fp16 = const()[name = tensor("input_99_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(320559424)))]; + tensor input_99_beta_0_to_fp16 = const()[name = tensor("input_99_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(320561536)))]; + tensor input_99_epsilon_0_to_fp16 = const()[name = tensor("input_99_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_99_cast_fp16 = batch_norm(beta = input_99_beta_0_to_fp16, epsilon = input_99_epsilon_0_to_fp16, gamma = input_99_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_51_cast_fp16)[name = tensor("input_99_cast_fp16")]; + tensor input_101_pad_type_0 = const()[name = tensor("input_101_pad_type_0"), val = tensor("valid")]; + tensor input_101_strides_0 = const()[name = tensor("input_101_strides_0"), val = tensor([1, 1])]; + tensor input_101_pad_0 = const()[name = tensor("input_101_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_101_dilations_0 = const()[name = tensor("input_101_dilations_0"), val = tensor([1, 1])]; + tensor input_101_groups_0 = const()[name = tensor("input_101_groups_0"), val = tensor(1)]; + tensor layers_12_fc1_weight_to_fp16 = const()[name = tensor("layers_12_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(320563648)))]; + tensor layers_12_fc1_bias_to_fp16 = const()[name = tensor("layers_12_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(328952320)))]; + tensor input_101_cast_fp16 = conv(bias = layers_12_fc1_bias_to_fp16, dilations = input_101_dilations_0, groups = input_101_groups_0, pad = input_101_pad_0, pad_type = input_101_pad_type_0, strides = input_101_strides_0, weight = layers_12_fc1_weight_to_fp16, x = input_99_cast_fp16)[name = tensor("input_101_cast_fp16")]; + tensor input_103_mode_0 = const()[name = tensor("input_103_mode_0"), val = tensor("EXACT")]; + tensor input_103_cast_fp16 = gelu(mode = input_103_mode_0, x = input_101_cast_fp16)[name = tensor("input_103_cast_fp16")]; + tensor hidden_states_29_pad_type_0 = const()[name = tensor("hidden_states_29_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_29_strides_0 = const()[name = tensor("hidden_states_29_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_29_pad_0 = const()[name = tensor("hidden_states_29_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_29_dilations_0 = const()[name = tensor("hidden_states_29_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_29_groups_0 = const()[name = tensor("hidden_states_29_groups_0"), val = tensor(1)]; + tensor layers_12_fc2_weight_to_fp16 = const()[name = tensor("layers_12_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(328960576)))]; + tensor layers_12_fc2_bias_to_fp16 = const()[name = tensor("layers_12_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(337349248)))]; + tensor hidden_states_29_cast_fp16 = conv(bias = layers_12_fc2_bias_to_fp16, dilations = hidden_states_29_dilations_0, groups = hidden_states_29_groups_0, pad = hidden_states_29_pad_0, pad_type = hidden_states_29_pad_type_0, strides = hidden_states_29_strides_0, weight = layers_12_fc2_weight_to_fp16, x = input_103_cast_fp16)[name = tensor("hidden_states_29_cast_fp16")]; + tensor inputs_53_cast_fp16 = add(x = inputs_51_cast_fp16, y = hidden_states_29_cast_fp16)[name = tensor("inputs_53_cast_fp16")]; + tensor var_1718 = const()[name = tensor("op_1718"), val = tensor(3)]; + tensor out_53_axes_0 = const()[name = tensor("out_53_axes_0"), val = tensor([1])]; + tensor var_1740_to_fp16 = const()[name = tensor("op_1740_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_53_cast_fp16 = layer_norm(axes = out_53_axes_0, epsilon = var_1740_to_fp16, x = inputs_53_cast_fp16)[name = tensor("out_53_cast_fp16")]; + tensor obj_53_gamma_0_to_fp16 = const()[name = tensor("obj_53_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(337351360)))]; + tensor obj_53_beta_0_to_fp16 = const()[name = tensor("obj_53_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(337353472)))]; + tensor obj_53_epsilon_0_to_fp16 = const()[name = tensor("obj_53_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_53_cast_fp16 = batch_norm(beta = obj_53_beta_0_to_fp16, epsilon = obj_53_epsilon_0_to_fp16, gamma = obj_53_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_53_cast_fp16)[name = tensor("obj_53_cast_fp16")]; + tensor query_27_pad_type_0 = const()[name = tensor("query_27_pad_type_0"), val = tensor("valid")]; + tensor query_27_strides_0 = const()[name = tensor("query_27_strides_0"), val = tensor([1, 1])]; + tensor query_27_pad_0 = const()[name = tensor("query_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_27_dilations_0 = const()[name = tensor("query_27_dilations_0"), val = tensor([1, 1])]; + tensor query_27_groups_0 = const()[name = tensor("query_27_groups_0"), val = tensor(1)]; + tensor layers_13_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_13_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(337355584)))]; + tensor layers_13_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_13_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(339452800)))]; + tensor query_27_cast_fp16 = conv(bias = layers_13_self_attn_q_proj_bias_to_fp16, dilations = query_27_dilations_0, groups = query_27_groups_0, pad = query_27_pad_0, pad_type = query_27_pad_type_0, strides = query_27_strides_0, weight = layers_13_self_attn_q_proj_weight_to_fp16, x = obj_53_cast_fp16)[name = tensor("query_27_cast_fp16")]; + tensor key_27_pad_type_0 = const()[name = tensor("key_27_pad_type_0"), val = tensor("valid")]; + tensor key_27_strides_0 = const()[name = tensor("key_27_strides_0"), val = tensor([1, 1])]; + tensor key_27_pad_0 = const()[name = tensor("key_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_27_dilations_0 = const()[name = tensor("key_27_dilations_0"), val = tensor([1, 1])]; + tensor key_27_groups_0 = const()[name = tensor("key_27_groups_0"), val = tensor(1)]; + tensor layers_13_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_13_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(339454912)))]; + tensor key_27_cast_fp16 = conv(dilations = key_27_dilations_0, groups = key_27_groups_0, pad = key_27_pad_0, pad_type = key_27_pad_type_0, strides = key_27_strides_0, weight = layers_13_self_attn_k_proj_weight_to_fp16, x = obj_53_cast_fp16)[name = tensor("key_27_cast_fp16")]; + tensor value_27_pad_type_0 = const()[name = tensor("value_27_pad_type_0"), val = tensor("valid")]; + tensor value_27_strides_0 = const()[name = tensor("value_27_strides_0"), val = tensor([1, 1])]; + tensor value_27_pad_0 = const()[name = tensor("value_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_27_dilations_0 = const()[name = tensor("value_27_dilations_0"), val = tensor([1, 1])]; + tensor value_27_groups_0 = const()[name = tensor("value_27_groups_0"), val = tensor(1)]; + tensor layers_13_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_13_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(341552128)))]; + tensor layers_13_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_13_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(343649344)))]; + tensor value_27_cast_fp16 = conv(bias = layers_13_self_attn_v_proj_bias_to_fp16, dilations = value_27_dilations_0, groups = value_27_groups_0, pad = value_27_pad_0, pad_type = value_27_pad_type_0, strides = value_27_strides_0, weight = layers_13_self_attn_v_proj_weight_to_fp16, x = obj_53_cast_fp16)[name = tensor("value_27_cast_fp16")]; + tensor var_1776 = const()[name = tensor("op_1776"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_27_cast_fp16 = reshape(shape = var_1776, x = query_27_cast_fp16)[name = tensor("mh_q_27_cast_fp16")]; + tensor var_1778_to_fp16 = const()[name = tensor("op_1778_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1779_cast_fp16 = mul(x = mh_q_27_cast_fp16, y = var_1778_to_fp16)[name = tensor("op_1779_cast_fp16")]; + tensor var_1782 = const()[name = tensor("op_1782"), val = tensor([1, 16, 64, 1500])]; + tensor var_1783_cast_fp16 = reshape(shape = var_1782, x = key_27_cast_fp16)[name = tensor("op_1783_cast_fp16")]; + tensor mh_w_27_transpose_x_0 = const()[name = tensor("mh_w_27_transpose_x_0"), val = tensor(true)]; + tensor mh_w_27_transpose_y_0 = const()[name = tensor("mh_w_27_transpose_y_0"), val = tensor(false)]; + tensor mh_w_27_cast_fp16 = matmul(transpose_x = mh_w_27_transpose_x_0, transpose_y = mh_w_27_transpose_y_0, x = var_1779_cast_fp16, y = var_1783_cast_fp16)[name = tensor("mh_w_27_cast_fp16")]; + tensor var_1786_cast_fp16 = softmax(axis = var_1718, x = mh_w_27_cast_fp16)[name = tensor("op_1786_cast_fp16")]; + tensor var_1787 = const()[name = tensor("op_1787"), val = tensor([1, 16, 64, 1500])]; + tensor var_1788_cast_fp16 = reshape(shape = var_1787, x = value_27_cast_fp16)[name = tensor("op_1788_cast_fp16")]; + tensor attn_27_transpose_x_0 = const()[name = tensor("attn_27_transpose_x_0"), val = tensor(false)]; + tensor attn_27_transpose_y_0 = const()[name = tensor("attn_27_transpose_y_0"), val = tensor(true)]; + tensor attn_27_cast_fp16 = matmul(transpose_x = attn_27_transpose_x_0, transpose_y = attn_27_transpose_y_0, x = var_1788_cast_fp16, y = var_1786_cast_fp16)[name = tensor("attn_27_cast_fp16")]; + tensor var_1791 = const()[name = tensor("op_1791"), val = tensor([1, 1024, 1, 1500])]; + tensor input_105_cast_fp16 = reshape(shape = var_1791, x = attn_27_cast_fp16)[name = tensor("input_105_cast_fp16")]; + tensor obj_55_pad_type_0 = const()[name = tensor("obj_55_pad_type_0"), val = tensor("valid")]; + tensor obj_55_strides_0 = const()[name = tensor("obj_55_strides_0"), val = tensor([1, 1])]; + tensor obj_55_pad_0 = const()[name = tensor("obj_55_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_55_dilations_0 = const()[name = tensor("obj_55_dilations_0"), val = tensor([1, 1])]; + tensor obj_55_groups_0 = const()[name = tensor("obj_55_groups_0"), val = tensor(1)]; + tensor layers_13_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_13_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(343651456)))]; + tensor layers_13_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_13_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(345748672)))]; + tensor obj_55_cast_fp16 = conv(bias = layers_13_self_attn_o_proj_bias_to_fp16, dilations = obj_55_dilations_0, groups = obj_55_groups_0, pad = obj_55_pad_0, pad_type = obj_55_pad_type_0, strides = obj_55_strides_0, weight = layers_13_self_attn_o_proj_weight_to_fp16, x = input_105_cast_fp16)[name = tensor("obj_55_cast_fp16")]; + tensor inputs_55_cast_fp16 = add(x = inputs_53_cast_fp16, y = obj_55_cast_fp16)[name = tensor("inputs_55_cast_fp16")]; + tensor out_55_axes_0 = const()[name = tensor("out_55_axes_0"), val = tensor([1])]; + tensor var_1809_to_fp16 = const()[name = tensor("op_1809_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_55_cast_fp16 = layer_norm(axes = out_55_axes_0, epsilon = var_1809_to_fp16, x = inputs_55_cast_fp16)[name = tensor("out_55_cast_fp16")]; + tensor input_107_gamma_0_to_fp16 = const()[name = tensor("input_107_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(345750784)))]; + tensor input_107_beta_0_to_fp16 = const()[name = tensor("input_107_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(345752896)))]; + tensor input_107_epsilon_0_to_fp16 = const()[name = tensor("input_107_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_107_cast_fp16 = batch_norm(beta = input_107_beta_0_to_fp16, epsilon = input_107_epsilon_0_to_fp16, gamma = input_107_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_55_cast_fp16)[name = tensor("input_107_cast_fp16")]; + tensor input_109_pad_type_0 = const()[name = tensor("input_109_pad_type_0"), val = tensor("valid")]; + tensor input_109_strides_0 = const()[name = tensor("input_109_strides_0"), val = tensor([1, 1])]; + tensor input_109_pad_0 = const()[name = tensor("input_109_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_109_dilations_0 = const()[name = tensor("input_109_dilations_0"), val = tensor([1, 1])]; + tensor input_109_groups_0 = const()[name = tensor("input_109_groups_0"), val = tensor(1)]; + tensor layers_13_fc1_weight_to_fp16 = const()[name = tensor("layers_13_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(345755008)))]; + tensor layers_13_fc1_bias_to_fp16 = const()[name = tensor("layers_13_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(354143680)))]; + tensor input_109_cast_fp16 = conv(bias = layers_13_fc1_bias_to_fp16, dilations = input_109_dilations_0, groups = input_109_groups_0, pad = input_109_pad_0, pad_type = input_109_pad_type_0, strides = input_109_strides_0, weight = layers_13_fc1_weight_to_fp16, x = input_107_cast_fp16)[name = tensor("input_109_cast_fp16")]; + tensor input_111_mode_0 = const()[name = tensor("input_111_mode_0"), val = tensor("EXACT")]; + tensor input_111_cast_fp16 = gelu(mode = input_111_mode_0, x = input_109_cast_fp16)[name = tensor("input_111_cast_fp16")]; + tensor hidden_states_31_pad_type_0 = const()[name = tensor("hidden_states_31_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_31_strides_0 = const()[name = tensor("hidden_states_31_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_31_pad_0 = const()[name = tensor("hidden_states_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_31_dilations_0 = const()[name = tensor("hidden_states_31_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_31_groups_0 = const()[name = tensor("hidden_states_31_groups_0"), val = tensor(1)]; + tensor layers_13_fc2_weight_to_fp16 = const()[name = tensor("layers_13_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(354151936)))]; + tensor layers_13_fc2_bias_to_fp16 = const()[name = tensor("layers_13_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(362540608)))]; + tensor hidden_states_31_cast_fp16 = conv(bias = layers_13_fc2_bias_to_fp16, dilations = hidden_states_31_dilations_0, groups = hidden_states_31_groups_0, pad = hidden_states_31_pad_0, pad_type = hidden_states_31_pad_type_0, strides = hidden_states_31_strides_0, weight = layers_13_fc2_weight_to_fp16, x = input_111_cast_fp16)[name = tensor("hidden_states_31_cast_fp16")]; + tensor inputs_57_cast_fp16 = add(x = inputs_55_cast_fp16, y = hidden_states_31_cast_fp16)[name = tensor("inputs_57_cast_fp16")]; + tensor var_1838 = const()[name = tensor("op_1838"), val = tensor(3)]; + tensor out_57_axes_0 = const()[name = tensor("out_57_axes_0"), val = tensor([1])]; + tensor var_1860_to_fp16 = const()[name = tensor("op_1860_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_57_cast_fp16 = layer_norm(axes = out_57_axes_0, epsilon = var_1860_to_fp16, x = inputs_57_cast_fp16)[name = tensor("out_57_cast_fp16")]; + tensor obj_57_gamma_0_to_fp16 = const()[name = tensor("obj_57_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(362542720)))]; + tensor obj_57_beta_0_to_fp16 = const()[name = tensor("obj_57_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(362544832)))]; + tensor obj_57_epsilon_0_to_fp16 = const()[name = tensor("obj_57_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_57_cast_fp16 = batch_norm(beta = obj_57_beta_0_to_fp16, epsilon = obj_57_epsilon_0_to_fp16, gamma = obj_57_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_57_cast_fp16)[name = tensor("obj_57_cast_fp16")]; + tensor query_29_pad_type_0 = const()[name = tensor("query_29_pad_type_0"), val = tensor("valid")]; + tensor query_29_strides_0 = const()[name = tensor("query_29_strides_0"), val = tensor([1, 1])]; + tensor query_29_pad_0 = const()[name = tensor("query_29_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_29_dilations_0 = const()[name = tensor("query_29_dilations_0"), val = tensor([1, 1])]; + tensor query_29_groups_0 = const()[name = tensor("query_29_groups_0"), val = tensor(1)]; + tensor layers_14_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_14_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(362546944)))]; + tensor layers_14_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_14_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(364644160)))]; + tensor query_29_cast_fp16 = conv(bias = layers_14_self_attn_q_proj_bias_to_fp16, dilations = query_29_dilations_0, groups = query_29_groups_0, pad = query_29_pad_0, pad_type = query_29_pad_type_0, strides = query_29_strides_0, weight = layers_14_self_attn_q_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("query_29_cast_fp16")]; + tensor key_29_pad_type_0 = const()[name = tensor("key_29_pad_type_0"), val = tensor("valid")]; + tensor key_29_strides_0 = const()[name = tensor("key_29_strides_0"), val = tensor([1, 1])]; + tensor key_29_pad_0 = const()[name = tensor("key_29_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_29_dilations_0 = const()[name = tensor("key_29_dilations_0"), val = tensor([1, 1])]; + tensor key_29_groups_0 = const()[name = tensor("key_29_groups_0"), val = tensor(1)]; + tensor layers_14_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_14_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(364646272)))]; + tensor key_29_cast_fp16 = conv(dilations = key_29_dilations_0, groups = key_29_groups_0, pad = key_29_pad_0, pad_type = key_29_pad_type_0, strides = key_29_strides_0, weight = layers_14_self_attn_k_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("key_29_cast_fp16")]; + tensor value_29_pad_type_0 = const()[name = tensor("value_29_pad_type_0"), val = tensor("valid")]; + tensor value_29_strides_0 = const()[name = tensor("value_29_strides_0"), val = tensor([1, 1])]; + tensor value_29_pad_0 = const()[name = tensor("value_29_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_29_dilations_0 = const()[name = tensor("value_29_dilations_0"), val = tensor([1, 1])]; + tensor value_29_groups_0 = const()[name = tensor("value_29_groups_0"), val = tensor(1)]; + tensor layers_14_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_14_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(366743488)))]; + tensor layers_14_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_14_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(368840704)))]; + tensor value_29_cast_fp16 = conv(bias = layers_14_self_attn_v_proj_bias_to_fp16, dilations = value_29_dilations_0, groups = value_29_groups_0, pad = value_29_pad_0, pad_type = value_29_pad_type_0, strides = value_29_strides_0, weight = layers_14_self_attn_v_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("value_29_cast_fp16")]; + tensor var_1896 = const()[name = tensor("op_1896"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_29_cast_fp16 = reshape(shape = var_1896, x = query_29_cast_fp16)[name = tensor("mh_q_29_cast_fp16")]; + tensor var_1898_to_fp16 = const()[name = tensor("op_1898_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1899_cast_fp16 = mul(x = mh_q_29_cast_fp16, y = var_1898_to_fp16)[name = tensor("op_1899_cast_fp16")]; + tensor var_1902 = const()[name = tensor("op_1902"), val = tensor([1, 16, 64, 1500])]; + tensor var_1903_cast_fp16 = reshape(shape = var_1902, x = key_29_cast_fp16)[name = tensor("op_1903_cast_fp16")]; + tensor mh_w_29_transpose_x_0 = const()[name = tensor("mh_w_29_transpose_x_0"), val = tensor(true)]; + tensor mh_w_29_transpose_y_0 = const()[name = tensor("mh_w_29_transpose_y_0"), val = tensor(false)]; + tensor mh_w_29_cast_fp16 = matmul(transpose_x = mh_w_29_transpose_x_0, transpose_y = mh_w_29_transpose_y_0, x = var_1899_cast_fp16, y = var_1903_cast_fp16)[name = tensor("mh_w_29_cast_fp16")]; + tensor var_1906_cast_fp16 = softmax(axis = var_1838, x = mh_w_29_cast_fp16)[name = tensor("op_1906_cast_fp16")]; + tensor var_1907 = const()[name = tensor("op_1907"), val = tensor([1, 16, 64, 1500])]; + tensor var_1908_cast_fp16 = reshape(shape = var_1907, x = value_29_cast_fp16)[name = tensor("op_1908_cast_fp16")]; + tensor attn_29_transpose_x_0 = const()[name = tensor("attn_29_transpose_x_0"), val = tensor(false)]; + tensor attn_29_transpose_y_0 = const()[name = tensor("attn_29_transpose_y_0"), val = tensor(true)]; + tensor attn_29_cast_fp16 = matmul(transpose_x = attn_29_transpose_x_0, transpose_y = attn_29_transpose_y_0, x = var_1908_cast_fp16, y = var_1906_cast_fp16)[name = tensor("attn_29_cast_fp16")]; + tensor var_1911 = const()[name = tensor("op_1911"), val = tensor([1, 1024, 1, 1500])]; + tensor input_113_cast_fp16 = reshape(shape = var_1911, x = attn_29_cast_fp16)[name = tensor("input_113_cast_fp16")]; + tensor obj_59_pad_type_0 = const()[name = tensor("obj_59_pad_type_0"), val = tensor("valid")]; + tensor obj_59_strides_0 = const()[name = tensor("obj_59_strides_0"), val = tensor([1, 1])]; + tensor obj_59_pad_0 = const()[name = tensor("obj_59_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_59_dilations_0 = const()[name = tensor("obj_59_dilations_0"), val = tensor([1, 1])]; + tensor obj_59_groups_0 = const()[name = tensor("obj_59_groups_0"), val = tensor(1)]; + tensor layers_14_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_14_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(368842816)))]; + tensor layers_14_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_14_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(370940032)))]; + tensor obj_59_cast_fp16 = conv(bias = layers_14_self_attn_o_proj_bias_to_fp16, dilations = obj_59_dilations_0, groups = obj_59_groups_0, pad = obj_59_pad_0, pad_type = obj_59_pad_type_0, strides = obj_59_strides_0, weight = layers_14_self_attn_o_proj_weight_to_fp16, x = input_113_cast_fp16)[name = tensor("obj_59_cast_fp16")]; + tensor inputs_59_cast_fp16 = add(x = inputs_57_cast_fp16, y = obj_59_cast_fp16)[name = tensor("inputs_59_cast_fp16")]; + tensor out_59_axes_0 = const()[name = tensor("out_59_axes_0"), val = tensor([1])]; + tensor var_1929_to_fp16 = const()[name = tensor("op_1929_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_59_cast_fp16 = layer_norm(axes = out_59_axes_0, epsilon = var_1929_to_fp16, x = inputs_59_cast_fp16)[name = tensor("out_59_cast_fp16")]; + tensor input_115_gamma_0_to_fp16 = const()[name = tensor("input_115_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(370942144)))]; + tensor input_115_beta_0_to_fp16 = const()[name = tensor("input_115_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(370944256)))]; + tensor input_115_epsilon_0_to_fp16 = const()[name = tensor("input_115_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_115_cast_fp16 = batch_norm(beta = input_115_beta_0_to_fp16, epsilon = input_115_epsilon_0_to_fp16, gamma = input_115_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_59_cast_fp16)[name = tensor("input_115_cast_fp16")]; + tensor input_117_pad_type_0 = const()[name = tensor("input_117_pad_type_0"), val = tensor("valid")]; + tensor input_117_strides_0 = const()[name = tensor("input_117_strides_0"), val = tensor([1, 1])]; + tensor input_117_pad_0 = const()[name = tensor("input_117_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_117_dilations_0 = const()[name = tensor("input_117_dilations_0"), val = tensor([1, 1])]; + tensor input_117_groups_0 = const()[name = tensor("input_117_groups_0"), val = tensor(1)]; + tensor layers_14_fc1_weight_to_fp16 = const()[name = tensor("layers_14_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(370946368)))]; + tensor layers_14_fc1_bias_to_fp16 = const()[name = tensor("layers_14_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(379335040)))]; + tensor input_117_cast_fp16 = conv(bias = layers_14_fc1_bias_to_fp16, dilations = input_117_dilations_0, groups = input_117_groups_0, pad = input_117_pad_0, pad_type = input_117_pad_type_0, strides = input_117_strides_0, weight = layers_14_fc1_weight_to_fp16, x = input_115_cast_fp16)[name = tensor("input_117_cast_fp16")]; + tensor input_119_mode_0 = const()[name = tensor("input_119_mode_0"), val = tensor("EXACT")]; + tensor input_119_cast_fp16 = gelu(mode = input_119_mode_0, x = input_117_cast_fp16)[name = tensor("input_119_cast_fp16")]; + tensor hidden_states_33_pad_type_0 = const()[name = tensor("hidden_states_33_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_33_strides_0 = const()[name = tensor("hidden_states_33_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_33_pad_0 = const()[name = tensor("hidden_states_33_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_33_dilations_0 = const()[name = tensor("hidden_states_33_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_33_groups_0 = const()[name = tensor("hidden_states_33_groups_0"), val = tensor(1)]; + tensor layers_14_fc2_weight_to_fp16 = const()[name = tensor("layers_14_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(379343296)))]; + tensor layers_14_fc2_bias_to_fp16 = const()[name = tensor("layers_14_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387731968)))]; + tensor hidden_states_33_cast_fp16 = conv(bias = layers_14_fc2_bias_to_fp16, dilations = hidden_states_33_dilations_0, groups = hidden_states_33_groups_0, pad = hidden_states_33_pad_0, pad_type = hidden_states_33_pad_type_0, strides = hidden_states_33_strides_0, weight = layers_14_fc2_weight_to_fp16, x = input_119_cast_fp16)[name = tensor("hidden_states_33_cast_fp16")]; + tensor inputs_61_cast_fp16 = add(x = inputs_59_cast_fp16, y = hidden_states_33_cast_fp16)[name = tensor("inputs_61_cast_fp16")]; + tensor var_1958 = const()[name = tensor("op_1958"), val = tensor(3)]; + tensor out_61_axes_0 = const()[name = tensor("out_61_axes_0"), val = tensor([1])]; + tensor var_1980_to_fp16 = const()[name = tensor("op_1980_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_61_cast_fp16 = layer_norm(axes = out_61_axes_0, epsilon = var_1980_to_fp16, x = inputs_61_cast_fp16)[name = tensor("out_61_cast_fp16")]; + tensor obj_61_gamma_0_to_fp16 = const()[name = tensor("obj_61_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387734080)))]; + tensor obj_61_beta_0_to_fp16 = const()[name = tensor("obj_61_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387736192)))]; + tensor obj_61_epsilon_0_to_fp16 = const()[name = tensor("obj_61_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_61_cast_fp16 = batch_norm(beta = obj_61_beta_0_to_fp16, epsilon = obj_61_epsilon_0_to_fp16, gamma = obj_61_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_61_cast_fp16)[name = tensor("obj_61_cast_fp16")]; + tensor query_31_pad_type_0 = const()[name = tensor("query_31_pad_type_0"), val = tensor("valid")]; + tensor query_31_strides_0 = const()[name = tensor("query_31_strides_0"), val = tensor([1, 1])]; + tensor query_31_pad_0 = const()[name = tensor("query_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_31_dilations_0 = const()[name = tensor("query_31_dilations_0"), val = tensor([1, 1])]; + tensor query_31_groups_0 = const()[name = tensor("query_31_groups_0"), val = tensor(1)]; + tensor layers_15_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_15_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387738304)))]; + tensor layers_15_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_15_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(389835520)))]; + tensor query_31_cast_fp16 = conv(bias = layers_15_self_attn_q_proj_bias_to_fp16, dilations = query_31_dilations_0, groups = query_31_groups_0, pad = query_31_pad_0, pad_type = query_31_pad_type_0, strides = query_31_strides_0, weight = layers_15_self_attn_q_proj_weight_to_fp16, x = obj_61_cast_fp16)[name = tensor("query_31_cast_fp16")]; + tensor key_31_pad_type_0 = const()[name = tensor("key_31_pad_type_0"), val = tensor("valid")]; + tensor key_31_strides_0 = const()[name = tensor("key_31_strides_0"), val = tensor([1, 1])]; + tensor key_31_pad_0 = const()[name = tensor("key_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_31_dilations_0 = const()[name = tensor("key_31_dilations_0"), val = tensor([1, 1])]; + tensor key_31_groups_0 = const()[name = tensor("key_31_groups_0"), val = tensor(1)]; + tensor layers_15_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_15_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(389837632)))]; + tensor key_31_cast_fp16 = conv(dilations = key_31_dilations_0, groups = key_31_groups_0, pad = key_31_pad_0, pad_type = key_31_pad_type_0, strides = key_31_strides_0, weight = layers_15_self_attn_k_proj_weight_to_fp16, x = obj_61_cast_fp16)[name = tensor("key_31_cast_fp16")]; + tensor value_31_pad_type_0 = const()[name = tensor("value_31_pad_type_0"), val = tensor("valid")]; + tensor value_31_strides_0 = const()[name = tensor("value_31_strides_0"), val = tensor([1, 1])]; + tensor value_31_pad_0 = const()[name = tensor("value_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_31_dilations_0 = const()[name = tensor("value_31_dilations_0"), val = tensor([1, 1])]; + tensor value_31_groups_0 = const()[name = tensor("value_31_groups_0"), val = tensor(1)]; + tensor layers_15_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_15_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(391934848)))]; + tensor layers_15_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_15_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(394032064)))]; + tensor value_31_cast_fp16 = conv(bias = layers_15_self_attn_v_proj_bias_to_fp16, dilations = value_31_dilations_0, groups = value_31_groups_0, pad = value_31_pad_0, pad_type = value_31_pad_type_0, strides = value_31_strides_0, weight = layers_15_self_attn_v_proj_weight_to_fp16, x = obj_61_cast_fp16)[name = tensor("value_31_cast_fp16")]; + tensor var_2016 = const()[name = tensor("op_2016"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_31_cast_fp16 = reshape(shape = var_2016, x = query_31_cast_fp16)[name = tensor("mh_q_31_cast_fp16")]; + tensor var_2018_to_fp16 = const()[name = tensor("op_2018_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2019_cast_fp16 = mul(x = mh_q_31_cast_fp16, y = var_2018_to_fp16)[name = tensor("op_2019_cast_fp16")]; + tensor var_2022 = const()[name = tensor("op_2022"), val = tensor([1, 16, 64, 1500])]; + tensor var_2023_cast_fp16 = reshape(shape = var_2022, x = key_31_cast_fp16)[name = tensor("op_2023_cast_fp16")]; + tensor mh_w_31_transpose_x_0 = const()[name = tensor("mh_w_31_transpose_x_0"), val = tensor(true)]; + tensor mh_w_31_transpose_y_0 = const()[name = tensor("mh_w_31_transpose_y_0"), val = tensor(false)]; + tensor mh_w_31_cast_fp16 = matmul(transpose_x = mh_w_31_transpose_x_0, transpose_y = mh_w_31_transpose_y_0, x = var_2019_cast_fp16, y = var_2023_cast_fp16)[name = tensor("mh_w_31_cast_fp16")]; + tensor var_2026_cast_fp16 = softmax(axis = var_1958, x = mh_w_31_cast_fp16)[name = tensor("op_2026_cast_fp16")]; + tensor var_2027 = const()[name = tensor("op_2027"), val = tensor([1, 16, 64, 1500])]; + tensor var_2028_cast_fp16 = reshape(shape = var_2027, x = value_31_cast_fp16)[name = tensor("op_2028_cast_fp16")]; + tensor attn_31_transpose_x_0 = const()[name = tensor("attn_31_transpose_x_0"), val = tensor(false)]; + tensor attn_31_transpose_y_0 = const()[name = tensor("attn_31_transpose_y_0"), val = tensor(true)]; + tensor attn_31_cast_fp16 = matmul(transpose_x = attn_31_transpose_x_0, transpose_y = attn_31_transpose_y_0, x = var_2028_cast_fp16, y = var_2026_cast_fp16)[name = tensor("attn_31_cast_fp16")]; + tensor var_2031 = const()[name = tensor("op_2031"), val = tensor([1, 1024, 1, 1500])]; + tensor input_121_cast_fp16 = reshape(shape = var_2031, x = attn_31_cast_fp16)[name = tensor("input_121_cast_fp16")]; + tensor obj_63_pad_type_0 = const()[name = tensor("obj_63_pad_type_0"), val = tensor("valid")]; + tensor obj_63_strides_0 = const()[name = tensor("obj_63_strides_0"), val = tensor([1, 1])]; + tensor obj_63_pad_0 = const()[name = tensor("obj_63_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_63_dilations_0 = const()[name = tensor("obj_63_dilations_0"), val = tensor([1, 1])]; + tensor obj_63_groups_0 = const()[name = tensor("obj_63_groups_0"), val = tensor(1)]; + tensor layers_15_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_15_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(394034176)))]; + tensor layers_15_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_15_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(396131392)))]; + tensor obj_63_cast_fp16 = conv(bias = layers_15_self_attn_o_proj_bias_to_fp16, dilations = obj_63_dilations_0, groups = obj_63_groups_0, pad = obj_63_pad_0, pad_type = obj_63_pad_type_0, strides = obj_63_strides_0, weight = layers_15_self_attn_o_proj_weight_to_fp16, x = input_121_cast_fp16)[name = tensor("obj_63_cast_fp16")]; + tensor inputs_63_cast_fp16 = add(x = inputs_61_cast_fp16, y = obj_63_cast_fp16)[name = tensor("inputs_63_cast_fp16")]; + tensor out_63_axes_0 = const()[name = tensor("out_63_axes_0"), val = tensor([1])]; + tensor var_2049_to_fp16 = const()[name = tensor("op_2049_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_63_cast_fp16 = layer_norm(axes = out_63_axes_0, epsilon = var_2049_to_fp16, x = inputs_63_cast_fp16)[name = tensor("out_63_cast_fp16")]; + tensor input_123_gamma_0_to_fp16 = const()[name = tensor("input_123_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(396133504)))]; + tensor input_123_beta_0_to_fp16 = const()[name = tensor("input_123_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(396135616)))]; + tensor input_123_epsilon_0_to_fp16 = const()[name = tensor("input_123_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_123_cast_fp16 = batch_norm(beta = input_123_beta_0_to_fp16, epsilon = input_123_epsilon_0_to_fp16, gamma = input_123_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_63_cast_fp16)[name = tensor("input_123_cast_fp16")]; + tensor input_125_pad_type_0 = const()[name = tensor("input_125_pad_type_0"), val = tensor("valid")]; + tensor input_125_strides_0 = const()[name = tensor("input_125_strides_0"), val = tensor([1, 1])]; + tensor input_125_pad_0 = const()[name = tensor("input_125_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_125_dilations_0 = const()[name = tensor("input_125_dilations_0"), val = tensor([1, 1])]; + tensor input_125_groups_0 = const()[name = tensor("input_125_groups_0"), val = tensor(1)]; + tensor layers_15_fc1_weight_to_fp16 = const()[name = tensor("layers_15_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(396137728)))]; + tensor layers_15_fc1_bias_to_fp16 = const()[name = tensor("layers_15_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(404526400)))]; + tensor input_125_cast_fp16 = conv(bias = layers_15_fc1_bias_to_fp16, dilations = input_125_dilations_0, groups = input_125_groups_0, pad = input_125_pad_0, pad_type = input_125_pad_type_0, strides = input_125_strides_0, weight = layers_15_fc1_weight_to_fp16, x = input_123_cast_fp16)[name = tensor("input_125_cast_fp16")]; + tensor input_127_mode_0 = const()[name = tensor("input_127_mode_0"), val = tensor("EXACT")]; + tensor input_127_cast_fp16 = gelu(mode = input_127_mode_0, x = input_125_cast_fp16)[name = tensor("input_127_cast_fp16")]; + tensor hidden_states_35_pad_type_0 = const()[name = tensor("hidden_states_35_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_35_strides_0 = const()[name = tensor("hidden_states_35_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_35_pad_0 = const()[name = tensor("hidden_states_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_35_dilations_0 = const()[name = tensor("hidden_states_35_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_35_groups_0 = const()[name = tensor("hidden_states_35_groups_0"), val = tensor(1)]; + tensor layers_15_fc2_weight_to_fp16 = const()[name = tensor("layers_15_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(404534656)))]; + tensor layers_15_fc2_bias_to_fp16 = const()[name = tensor("layers_15_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412923328)))]; + tensor hidden_states_35_cast_fp16 = conv(bias = layers_15_fc2_bias_to_fp16, dilations = hidden_states_35_dilations_0, groups = hidden_states_35_groups_0, pad = hidden_states_35_pad_0, pad_type = hidden_states_35_pad_type_0, strides = hidden_states_35_strides_0, weight = layers_15_fc2_weight_to_fp16, x = input_127_cast_fp16)[name = tensor("hidden_states_35_cast_fp16")]; + tensor inputs_65_cast_fp16 = add(x = inputs_63_cast_fp16, y = hidden_states_35_cast_fp16)[name = tensor("inputs_65_cast_fp16")]; + tensor var_2078 = const()[name = tensor("op_2078"), val = tensor(3)]; + tensor out_65_axes_0 = const()[name = tensor("out_65_axes_0"), val = tensor([1])]; + tensor var_2100_to_fp16 = const()[name = tensor("op_2100_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_65_cast_fp16 = layer_norm(axes = out_65_axes_0, epsilon = var_2100_to_fp16, x = inputs_65_cast_fp16)[name = tensor("out_65_cast_fp16")]; + tensor obj_65_gamma_0_to_fp16 = const()[name = tensor("obj_65_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412925440)))]; + tensor obj_65_beta_0_to_fp16 = const()[name = tensor("obj_65_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412927552)))]; + tensor obj_65_epsilon_0_to_fp16 = const()[name = tensor("obj_65_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_65_cast_fp16 = batch_norm(beta = obj_65_beta_0_to_fp16, epsilon = obj_65_epsilon_0_to_fp16, gamma = obj_65_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_65_cast_fp16)[name = tensor("obj_65_cast_fp16")]; + tensor query_33_pad_type_0 = const()[name = tensor("query_33_pad_type_0"), val = tensor("valid")]; + tensor query_33_strides_0 = const()[name = tensor("query_33_strides_0"), val = tensor([1, 1])]; + tensor query_33_pad_0 = const()[name = tensor("query_33_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_33_dilations_0 = const()[name = tensor("query_33_dilations_0"), val = tensor([1, 1])]; + tensor query_33_groups_0 = const()[name = tensor("query_33_groups_0"), val = tensor(1)]; + tensor layers_16_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_16_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412929664)))]; + tensor layers_16_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_16_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(415026880)))]; + tensor query_33_cast_fp16 = conv(bias = layers_16_self_attn_q_proj_bias_to_fp16, dilations = query_33_dilations_0, groups = query_33_groups_0, pad = query_33_pad_0, pad_type = query_33_pad_type_0, strides = query_33_strides_0, weight = layers_16_self_attn_q_proj_weight_to_fp16, x = obj_65_cast_fp16)[name = tensor("query_33_cast_fp16")]; + tensor key_33_pad_type_0 = const()[name = tensor("key_33_pad_type_0"), val = tensor("valid")]; + tensor key_33_strides_0 = const()[name = tensor("key_33_strides_0"), val = tensor([1, 1])]; + tensor key_33_pad_0 = const()[name = tensor("key_33_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_33_dilations_0 = const()[name = tensor("key_33_dilations_0"), val = tensor([1, 1])]; + tensor key_33_groups_0 = const()[name = tensor("key_33_groups_0"), val = tensor(1)]; + tensor layers_16_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_16_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(415028992)))]; + tensor key_33_cast_fp16 = conv(dilations = key_33_dilations_0, groups = key_33_groups_0, pad = key_33_pad_0, pad_type = key_33_pad_type_0, strides = key_33_strides_0, weight = layers_16_self_attn_k_proj_weight_to_fp16, x = obj_65_cast_fp16)[name = tensor("key_33_cast_fp16")]; + tensor value_33_pad_type_0 = const()[name = tensor("value_33_pad_type_0"), val = tensor("valid")]; + tensor value_33_strides_0 = const()[name = tensor("value_33_strides_0"), val = tensor([1, 1])]; + tensor value_33_pad_0 = const()[name = tensor("value_33_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_33_dilations_0 = const()[name = tensor("value_33_dilations_0"), val = tensor([1, 1])]; + tensor value_33_groups_0 = const()[name = tensor("value_33_groups_0"), val = tensor(1)]; + tensor layers_16_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_16_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417126208)))]; + tensor layers_16_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_16_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(419223424)))]; + tensor value_33_cast_fp16 = conv(bias = layers_16_self_attn_v_proj_bias_to_fp16, dilations = value_33_dilations_0, groups = value_33_groups_0, pad = value_33_pad_0, pad_type = value_33_pad_type_0, strides = value_33_strides_0, weight = layers_16_self_attn_v_proj_weight_to_fp16, x = obj_65_cast_fp16)[name = tensor("value_33_cast_fp16")]; + tensor var_2136 = const()[name = tensor("op_2136"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_33_cast_fp16 = reshape(shape = var_2136, x = query_33_cast_fp16)[name = tensor("mh_q_33_cast_fp16")]; + tensor var_2138_to_fp16 = const()[name = tensor("op_2138_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2139_cast_fp16 = mul(x = mh_q_33_cast_fp16, y = var_2138_to_fp16)[name = tensor("op_2139_cast_fp16")]; + tensor var_2142 = const()[name = tensor("op_2142"), val = tensor([1, 16, 64, 1500])]; + tensor var_2143_cast_fp16 = reshape(shape = var_2142, x = key_33_cast_fp16)[name = tensor("op_2143_cast_fp16")]; + tensor mh_w_33_transpose_x_0 = const()[name = tensor("mh_w_33_transpose_x_0"), val = tensor(true)]; + tensor mh_w_33_transpose_y_0 = const()[name = tensor("mh_w_33_transpose_y_0"), val = tensor(false)]; + tensor mh_w_33_cast_fp16 = matmul(transpose_x = mh_w_33_transpose_x_0, transpose_y = mh_w_33_transpose_y_0, x = var_2139_cast_fp16, y = var_2143_cast_fp16)[name = tensor("mh_w_33_cast_fp16")]; + tensor var_2146_cast_fp16 = softmax(axis = var_2078, x = mh_w_33_cast_fp16)[name = tensor("op_2146_cast_fp16")]; + tensor var_2147 = const()[name = tensor("op_2147"), val = tensor([1, 16, 64, 1500])]; + tensor var_2148_cast_fp16 = reshape(shape = var_2147, x = value_33_cast_fp16)[name = tensor("op_2148_cast_fp16")]; + tensor attn_33_transpose_x_0 = const()[name = tensor("attn_33_transpose_x_0"), val = tensor(false)]; + tensor attn_33_transpose_y_0 = const()[name = tensor("attn_33_transpose_y_0"), val = tensor(true)]; + tensor attn_33_cast_fp16 = matmul(transpose_x = attn_33_transpose_x_0, transpose_y = attn_33_transpose_y_0, x = var_2148_cast_fp16, y = var_2146_cast_fp16)[name = tensor("attn_33_cast_fp16")]; + tensor var_2151 = const()[name = tensor("op_2151"), val = tensor([1, 1024, 1, 1500])]; + tensor input_129_cast_fp16 = reshape(shape = var_2151, x = attn_33_cast_fp16)[name = tensor("input_129_cast_fp16")]; + tensor obj_67_pad_type_0 = const()[name = tensor("obj_67_pad_type_0"), val = tensor("valid")]; + tensor obj_67_strides_0 = const()[name = tensor("obj_67_strides_0"), val = tensor([1, 1])]; + tensor obj_67_pad_0 = const()[name = tensor("obj_67_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_67_dilations_0 = const()[name = tensor("obj_67_dilations_0"), val = tensor([1, 1])]; + tensor obj_67_groups_0 = const()[name = tensor("obj_67_groups_0"), val = tensor(1)]; + tensor layers_16_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_16_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(419225536)))]; + tensor layers_16_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_16_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(421322752)))]; + tensor obj_67_cast_fp16 = conv(bias = layers_16_self_attn_o_proj_bias_to_fp16, dilations = obj_67_dilations_0, groups = obj_67_groups_0, pad = obj_67_pad_0, pad_type = obj_67_pad_type_0, strides = obj_67_strides_0, weight = layers_16_self_attn_o_proj_weight_to_fp16, x = input_129_cast_fp16)[name = tensor("obj_67_cast_fp16")]; + tensor inputs_67_cast_fp16 = add(x = inputs_65_cast_fp16, y = obj_67_cast_fp16)[name = tensor("inputs_67_cast_fp16")]; + tensor out_67_axes_0 = const()[name = tensor("out_67_axes_0"), val = tensor([1])]; + tensor var_2169_to_fp16 = const()[name = tensor("op_2169_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_67_cast_fp16 = layer_norm(axes = out_67_axes_0, epsilon = var_2169_to_fp16, x = inputs_67_cast_fp16)[name = tensor("out_67_cast_fp16")]; + tensor input_131_gamma_0_to_fp16 = const()[name = tensor("input_131_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(421324864)))]; + tensor input_131_beta_0_to_fp16 = const()[name = tensor("input_131_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(421326976)))]; + tensor input_131_epsilon_0_to_fp16 = const()[name = tensor("input_131_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_131_cast_fp16 = batch_norm(beta = input_131_beta_0_to_fp16, epsilon = input_131_epsilon_0_to_fp16, gamma = input_131_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_67_cast_fp16)[name = tensor("input_131_cast_fp16")]; + tensor input_133_pad_type_0 = const()[name = tensor("input_133_pad_type_0"), val = tensor("valid")]; + tensor input_133_strides_0 = const()[name = tensor("input_133_strides_0"), val = tensor([1, 1])]; + tensor input_133_pad_0 = const()[name = tensor("input_133_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_133_dilations_0 = const()[name = tensor("input_133_dilations_0"), val = tensor([1, 1])]; + tensor input_133_groups_0 = const()[name = tensor("input_133_groups_0"), val = tensor(1)]; + tensor layers_16_fc1_weight_to_fp16 = const()[name = tensor("layers_16_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(421329088)))]; + tensor layers_16_fc1_bias_to_fp16 = const()[name = tensor("layers_16_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(429717760)))]; + tensor input_133_cast_fp16 = conv(bias = layers_16_fc1_bias_to_fp16, dilations = input_133_dilations_0, groups = input_133_groups_0, pad = input_133_pad_0, pad_type = input_133_pad_type_0, strides = input_133_strides_0, weight = layers_16_fc1_weight_to_fp16, x = input_131_cast_fp16)[name = tensor("input_133_cast_fp16")]; + tensor input_135_mode_0 = const()[name = tensor("input_135_mode_0"), val = tensor("EXACT")]; + tensor input_135_cast_fp16 = gelu(mode = input_135_mode_0, x = input_133_cast_fp16)[name = tensor("input_135_cast_fp16")]; + tensor hidden_states_37_pad_type_0 = const()[name = tensor("hidden_states_37_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_37_strides_0 = const()[name = tensor("hidden_states_37_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_37_pad_0 = const()[name = tensor("hidden_states_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_37_dilations_0 = const()[name = tensor("hidden_states_37_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_37_groups_0 = const()[name = tensor("hidden_states_37_groups_0"), val = tensor(1)]; + tensor layers_16_fc2_weight_to_fp16 = const()[name = tensor("layers_16_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(429726016)))]; + tensor layers_16_fc2_bias_to_fp16 = const()[name = tensor("layers_16_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(438114688)))]; + tensor hidden_states_37_cast_fp16 = conv(bias = layers_16_fc2_bias_to_fp16, dilations = hidden_states_37_dilations_0, groups = hidden_states_37_groups_0, pad = hidden_states_37_pad_0, pad_type = hidden_states_37_pad_type_0, strides = hidden_states_37_strides_0, weight = layers_16_fc2_weight_to_fp16, x = input_135_cast_fp16)[name = tensor("hidden_states_37_cast_fp16")]; + tensor inputs_69_cast_fp16 = add(x = inputs_67_cast_fp16, y = hidden_states_37_cast_fp16)[name = tensor("inputs_69_cast_fp16")]; + tensor var_2198 = const()[name = tensor("op_2198"), val = tensor(3)]; + tensor out_69_axes_0 = const()[name = tensor("out_69_axes_0"), val = tensor([1])]; + tensor var_2220_to_fp16 = const()[name = tensor("op_2220_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_69_cast_fp16 = layer_norm(axes = out_69_axes_0, epsilon = var_2220_to_fp16, x = inputs_69_cast_fp16)[name = tensor("out_69_cast_fp16")]; + tensor obj_69_gamma_0_to_fp16 = const()[name = tensor("obj_69_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(438116800)))]; + tensor obj_69_beta_0_to_fp16 = const()[name = tensor("obj_69_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(438118912)))]; + tensor obj_69_epsilon_0_to_fp16 = const()[name = tensor("obj_69_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_69_cast_fp16 = batch_norm(beta = obj_69_beta_0_to_fp16, epsilon = obj_69_epsilon_0_to_fp16, gamma = obj_69_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_69_cast_fp16)[name = tensor("obj_69_cast_fp16")]; + tensor query_35_pad_type_0 = const()[name = tensor("query_35_pad_type_0"), val = tensor("valid")]; + tensor query_35_strides_0 = const()[name = tensor("query_35_strides_0"), val = tensor([1, 1])]; + tensor query_35_pad_0 = const()[name = tensor("query_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_35_dilations_0 = const()[name = tensor("query_35_dilations_0"), val = tensor([1, 1])]; + tensor query_35_groups_0 = const()[name = tensor("query_35_groups_0"), val = tensor(1)]; + tensor layers_17_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_17_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(438121024)))]; + tensor layers_17_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_17_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(440218240)))]; + tensor query_35_cast_fp16 = conv(bias = layers_17_self_attn_q_proj_bias_to_fp16, dilations = query_35_dilations_0, groups = query_35_groups_0, pad = query_35_pad_0, pad_type = query_35_pad_type_0, strides = query_35_strides_0, weight = layers_17_self_attn_q_proj_weight_to_fp16, x = obj_69_cast_fp16)[name = tensor("query_35_cast_fp16")]; + tensor key_35_pad_type_0 = const()[name = tensor("key_35_pad_type_0"), val = tensor("valid")]; + tensor key_35_strides_0 = const()[name = tensor("key_35_strides_0"), val = tensor([1, 1])]; + tensor key_35_pad_0 = const()[name = tensor("key_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_35_dilations_0 = const()[name = tensor("key_35_dilations_0"), val = tensor([1, 1])]; + tensor key_35_groups_0 = const()[name = tensor("key_35_groups_0"), val = tensor(1)]; + tensor layers_17_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_17_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(440220352)))]; + tensor key_35_cast_fp16 = conv(dilations = key_35_dilations_0, groups = key_35_groups_0, pad = key_35_pad_0, pad_type = key_35_pad_type_0, strides = key_35_strides_0, weight = layers_17_self_attn_k_proj_weight_to_fp16, x = obj_69_cast_fp16)[name = tensor("key_35_cast_fp16")]; + tensor value_35_pad_type_0 = const()[name = tensor("value_35_pad_type_0"), val = tensor("valid")]; + tensor value_35_strides_0 = const()[name = tensor("value_35_strides_0"), val = tensor([1, 1])]; + tensor value_35_pad_0 = const()[name = tensor("value_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_35_dilations_0 = const()[name = tensor("value_35_dilations_0"), val = tensor([1, 1])]; + tensor value_35_groups_0 = const()[name = tensor("value_35_groups_0"), val = tensor(1)]; + tensor layers_17_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_17_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(442317568)))]; + tensor layers_17_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_17_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(444414784)))]; + tensor value_35_cast_fp16 = conv(bias = layers_17_self_attn_v_proj_bias_to_fp16, dilations = value_35_dilations_0, groups = value_35_groups_0, pad = value_35_pad_0, pad_type = value_35_pad_type_0, strides = value_35_strides_0, weight = layers_17_self_attn_v_proj_weight_to_fp16, x = obj_69_cast_fp16)[name = tensor("value_35_cast_fp16")]; + tensor var_2256 = const()[name = tensor("op_2256"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_35_cast_fp16 = reshape(shape = var_2256, x = query_35_cast_fp16)[name = tensor("mh_q_35_cast_fp16")]; + tensor var_2258_to_fp16 = const()[name = tensor("op_2258_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2259_cast_fp16 = mul(x = mh_q_35_cast_fp16, y = var_2258_to_fp16)[name = tensor("op_2259_cast_fp16")]; + tensor var_2262 = const()[name = tensor("op_2262"), val = tensor([1, 16, 64, 1500])]; + tensor var_2263_cast_fp16 = reshape(shape = var_2262, x = key_35_cast_fp16)[name = tensor("op_2263_cast_fp16")]; + tensor mh_w_35_transpose_x_0 = const()[name = tensor("mh_w_35_transpose_x_0"), val = tensor(true)]; + tensor mh_w_35_transpose_y_0 = const()[name = tensor("mh_w_35_transpose_y_0"), val = tensor(false)]; + tensor mh_w_35_cast_fp16 = matmul(transpose_x = mh_w_35_transpose_x_0, transpose_y = mh_w_35_transpose_y_0, x = var_2259_cast_fp16, y = var_2263_cast_fp16)[name = tensor("mh_w_35_cast_fp16")]; + tensor var_2266_cast_fp16 = softmax(axis = var_2198, x = mh_w_35_cast_fp16)[name = tensor("op_2266_cast_fp16")]; + tensor var_2267 = const()[name = tensor("op_2267"), val = tensor([1, 16, 64, 1500])]; + tensor var_2268_cast_fp16 = reshape(shape = var_2267, x = value_35_cast_fp16)[name = tensor("op_2268_cast_fp16")]; + tensor attn_35_transpose_x_0 = const()[name = tensor("attn_35_transpose_x_0"), val = tensor(false)]; + tensor attn_35_transpose_y_0 = const()[name = tensor("attn_35_transpose_y_0"), val = tensor(true)]; + tensor attn_35_cast_fp16 = matmul(transpose_x = attn_35_transpose_x_0, transpose_y = attn_35_transpose_y_0, x = var_2268_cast_fp16, y = var_2266_cast_fp16)[name = tensor("attn_35_cast_fp16")]; + tensor var_2271 = const()[name = tensor("op_2271"), val = tensor([1, 1024, 1, 1500])]; + tensor input_137_cast_fp16 = reshape(shape = var_2271, x = attn_35_cast_fp16)[name = tensor("input_137_cast_fp16")]; + tensor obj_71_pad_type_0 = const()[name = tensor("obj_71_pad_type_0"), val = tensor("valid")]; + tensor obj_71_strides_0 = const()[name = tensor("obj_71_strides_0"), val = tensor([1, 1])]; + tensor obj_71_pad_0 = const()[name = tensor("obj_71_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_71_dilations_0 = const()[name = tensor("obj_71_dilations_0"), val = tensor([1, 1])]; + tensor obj_71_groups_0 = const()[name = tensor("obj_71_groups_0"), val = tensor(1)]; + tensor layers_17_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_17_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(444416896)))]; + tensor layers_17_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_17_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(446514112)))]; + tensor obj_71_cast_fp16 = conv(bias = layers_17_self_attn_o_proj_bias_to_fp16, dilations = obj_71_dilations_0, groups = obj_71_groups_0, pad = obj_71_pad_0, pad_type = obj_71_pad_type_0, strides = obj_71_strides_0, weight = layers_17_self_attn_o_proj_weight_to_fp16, x = input_137_cast_fp16)[name = tensor("obj_71_cast_fp16")]; + tensor inputs_71_cast_fp16 = add(x = inputs_69_cast_fp16, y = obj_71_cast_fp16)[name = tensor("inputs_71_cast_fp16")]; + tensor out_71_axes_0 = const()[name = tensor("out_71_axes_0"), val = tensor([1])]; + tensor var_2289_to_fp16 = const()[name = tensor("op_2289_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_71_cast_fp16 = layer_norm(axes = out_71_axes_0, epsilon = var_2289_to_fp16, x = inputs_71_cast_fp16)[name = tensor("out_71_cast_fp16")]; + tensor input_139_gamma_0_to_fp16 = const()[name = tensor("input_139_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(446516224)))]; + tensor input_139_beta_0_to_fp16 = const()[name = tensor("input_139_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(446518336)))]; + tensor input_139_epsilon_0_to_fp16 = const()[name = tensor("input_139_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_139_cast_fp16 = batch_norm(beta = input_139_beta_0_to_fp16, epsilon = input_139_epsilon_0_to_fp16, gamma = input_139_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_71_cast_fp16)[name = tensor("input_139_cast_fp16")]; + tensor input_141_pad_type_0 = const()[name = tensor("input_141_pad_type_0"), val = tensor("valid")]; + tensor input_141_strides_0 = const()[name = tensor("input_141_strides_0"), val = tensor([1, 1])]; + tensor input_141_pad_0 = const()[name = tensor("input_141_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_141_dilations_0 = const()[name = tensor("input_141_dilations_0"), val = tensor([1, 1])]; + tensor input_141_groups_0 = const()[name = tensor("input_141_groups_0"), val = tensor(1)]; + tensor layers_17_fc1_weight_to_fp16 = const()[name = tensor("layers_17_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(446520448)))]; + tensor layers_17_fc1_bias_to_fp16 = const()[name = tensor("layers_17_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(454909120)))]; + tensor input_141_cast_fp16 = conv(bias = layers_17_fc1_bias_to_fp16, dilations = input_141_dilations_0, groups = input_141_groups_0, pad = input_141_pad_0, pad_type = input_141_pad_type_0, strides = input_141_strides_0, weight = layers_17_fc1_weight_to_fp16, x = input_139_cast_fp16)[name = tensor("input_141_cast_fp16")]; + tensor input_143_mode_0 = const()[name = tensor("input_143_mode_0"), val = tensor("EXACT")]; + tensor input_143_cast_fp16 = gelu(mode = input_143_mode_0, x = input_141_cast_fp16)[name = tensor("input_143_cast_fp16")]; + tensor hidden_states_39_pad_type_0 = const()[name = tensor("hidden_states_39_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_39_strides_0 = const()[name = tensor("hidden_states_39_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_39_pad_0 = const()[name = tensor("hidden_states_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_39_dilations_0 = const()[name = tensor("hidden_states_39_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_39_groups_0 = const()[name = tensor("hidden_states_39_groups_0"), val = tensor(1)]; + tensor layers_17_fc2_weight_to_fp16 = const()[name = tensor("layers_17_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(454917376)))]; + tensor layers_17_fc2_bias_to_fp16 = const()[name = tensor("layers_17_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(463306048)))]; + tensor hidden_states_39_cast_fp16 = conv(bias = layers_17_fc2_bias_to_fp16, dilations = hidden_states_39_dilations_0, groups = hidden_states_39_groups_0, pad = hidden_states_39_pad_0, pad_type = hidden_states_39_pad_type_0, strides = hidden_states_39_strides_0, weight = layers_17_fc2_weight_to_fp16, x = input_143_cast_fp16)[name = tensor("hidden_states_39_cast_fp16")]; + tensor inputs_73_cast_fp16 = add(x = inputs_71_cast_fp16, y = hidden_states_39_cast_fp16)[name = tensor("inputs_73_cast_fp16")]; + tensor var_2318 = const()[name = tensor("op_2318"), val = tensor(3)]; + tensor out_73_axes_0 = const()[name = tensor("out_73_axes_0"), val = tensor([1])]; + tensor var_2340_to_fp16 = const()[name = tensor("op_2340_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_73_cast_fp16 = layer_norm(axes = out_73_axes_0, epsilon = var_2340_to_fp16, x = inputs_73_cast_fp16)[name = tensor("out_73_cast_fp16")]; + tensor obj_73_gamma_0_to_fp16 = const()[name = tensor("obj_73_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(463308160)))]; + tensor obj_73_beta_0_to_fp16 = const()[name = tensor("obj_73_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(463310272)))]; + tensor obj_73_epsilon_0_to_fp16 = const()[name = tensor("obj_73_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_73_cast_fp16 = batch_norm(beta = obj_73_beta_0_to_fp16, epsilon = obj_73_epsilon_0_to_fp16, gamma = obj_73_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_73_cast_fp16)[name = tensor("obj_73_cast_fp16")]; + tensor query_37_pad_type_0 = const()[name = tensor("query_37_pad_type_0"), val = tensor("valid")]; + tensor query_37_strides_0 = const()[name = tensor("query_37_strides_0"), val = tensor([1, 1])]; + tensor query_37_pad_0 = const()[name = tensor("query_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_37_dilations_0 = const()[name = tensor("query_37_dilations_0"), val = tensor([1, 1])]; + tensor query_37_groups_0 = const()[name = tensor("query_37_groups_0"), val = tensor(1)]; + tensor layers_18_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_18_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(463312384)))]; + tensor layers_18_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_18_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(465409600)))]; + tensor query_37_cast_fp16 = conv(bias = layers_18_self_attn_q_proj_bias_to_fp16, dilations = query_37_dilations_0, groups = query_37_groups_0, pad = query_37_pad_0, pad_type = query_37_pad_type_0, strides = query_37_strides_0, weight = layers_18_self_attn_q_proj_weight_to_fp16, x = obj_73_cast_fp16)[name = tensor("query_37_cast_fp16")]; + tensor key_37_pad_type_0 = const()[name = tensor("key_37_pad_type_0"), val = tensor("valid")]; + tensor key_37_strides_0 = const()[name = tensor("key_37_strides_0"), val = tensor([1, 1])]; + tensor key_37_pad_0 = const()[name = tensor("key_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_37_dilations_0 = const()[name = tensor("key_37_dilations_0"), val = tensor([1, 1])]; + tensor key_37_groups_0 = const()[name = tensor("key_37_groups_0"), val = tensor(1)]; + tensor layers_18_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_18_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(465411712)))]; + tensor key_37_cast_fp16 = conv(dilations = key_37_dilations_0, groups = key_37_groups_0, pad = key_37_pad_0, pad_type = key_37_pad_type_0, strides = key_37_strides_0, weight = layers_18_self_attn_k_proj_weight_to_fp16, x = obj_73_cast_fp16)[name = tensor("key_37_cast_fp16")]; + tensor value_37_pad_type_0 = const()[name = tensor("value_37_pad_type_0"), val = tensor("valid")]; + tensor value_37_strides_0 = const()[name = tensor("value_37_strides_0"), val = tensor([1, 1])]; + tensor value_37_pad_0 = const()[name = tensor("value_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_37_dilations_0 = const()[name = tensor("value_37_dilations_0"), val = tensor([1, 1])]; + tensor value_37_groups_0 = const()[name = tensor("value_37_groups_0"), val = tensor(1)]; + tensor layers_18_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_18_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(467508928)))]; + tensor layers_18_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_18_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(469606144)))]; + tensor value_37_cast_fp16 = conv(bias = layers_18_self_attn_v_proj_bias_to_fp16, dilations = value_37_dilations_0, groups = value_37_groups_0, pad = value_37_pad_0, pad_type = value_37_pad_type_0, strides = value_37_strides_0, weight = layers_18_self_attn_v_proj_weight_to_fp16, x = obj_73_cast_fp16)[name = tensor("value_37_cast_fp16")]; + tensor var_2376 = const()[name = tensor("op_2376"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_37_cast_fp16 = reshape(shape = var_2376, x = query_37_cast_fp16)[name = tensor("mh_q_37_cast_fp16")]; + tensor var_2378_to_fp16 = const()[name = tensor("op_2378_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2379_cast_fp16 = mul(x = mh_q_37_cast_fp16, y = var_2378_to_fp16)[name = tensor("op_2379_cast_fp16")]; + tensor var_2382 = const()[name = tensor("op_2382"), val = tensor([1, 16, 64, 1500])]; + tensor var_2383_cast_fp16 = reshape(shape = var_2382, x = key_37_cast_fp16)[name = tensor("op_2383_cast_fp16")]; + tensor mh_w_37_transpose_x_0 = const()[name = tensor("mh_w_37_transpose_x_0"), val = tensor(true)]; + tensor mh_w_37_transpose_y_0 = const()[name = tensor("mh_w_37_transpose_y_0"), val = tensor(false)]; + tensor mh_w_37_cast_fp16 = matmul(transpose_x = mh_w_37_transpose_x_0, transpose_y = mh_w_37_transpose_y_0, x = var_2379_cast_fp16, y = var_2383_cast_fp16)[name = tensor("mh_w_37_cast_fp16")]; + tensor var_2386_cast_fp16 = softmax(axis = var_2318, x = mh_w_37_cast_fp16)[name = tensor("op_2386_cast_fp16")]; + tensor var_2387 = const()[name = tensor("op_2387"), val = tensor([1, 16, 64, 1500])]; + tensor var_2388_cast_fp16 = reshape(shape = var_2387, x = value_37_cast_fp16)[name = tensor("op_2388_cast_fp16")]; + tensor attn_37_transpose_x_0 = const()[name = tensor("attn_37_transpose_x_0"), val = tensor(false)]; + tensor attn_37_transpose_y_0 = const()[name = tensor("attn_37_transpose_y_0"), val = tensor(true)]; + tensor attn_37_cast_fp16 = matmul(transpose_x = attn_37_transpose_x_0, transpose_y = attn_37_transpose_y_0, x = var_2388_cast_fp16, y = var_2386_cast_fp16)[name = tensor("attn_37_cast_fp16")]; + tensor var_2391 = const()[name = tensor("op_2391"), val = tensor([1, 1024, 1, 1500])]; + tensor input_145_cast_fp16 = reshape(shape = var_2391, x = attn_37_cast_fp16)[name = tensor("input_145_cast_fp16")]; + tensor obj_75_pad_type_0 = const()[name = tensor("obj_75_pad_type_0"), val = tensor("valid")]; + tensor obj_75_strides_0 = const()[name = tensor("obj_75_strides_0"), val = tensor([1, 1])]; + tensor obj_75_pad_0 = const()[name = tensor("obj_75_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_75_dilations_0 = const()[name = tensor("obj_75_dilations_0"), val = tensor([1, 1])]; + tensor obj_75_groups_0 = const()[name = tensor("obj_75_groups_0"), val = tensor(1)]; + tensor layers_18_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_18_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(469608256)))]; + tensor layers_18_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_18_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(471705472)))]; + tensor obj_75_cast_fp16 = conv(bias = layers_18_self_attn_o_proj_bias_to_fp16, dilations = obj_75_dilations_0, groups = obj_75_groups_0, pad = obj_75_pad_0, pad_type = obj_75_pad_type_0, strides = obj_75_strides_0, weight = layers_18_self_attn_o_proj_weight_to_fp16, x = input_145_cast_fp16)[name = tensor("obj_75_cast_fp16")]; + tensor inputs_75_cast_fp16 = add(x = inputs_73_cast_fp16, y = obj_75_cast_fp16)[name = tensor("inputs_75_cast_fp16")]; + tensor out_75_axes_0 = const()[name = tensor("out_75_axes_0"), val = tensor([1])]; + tensor var_2409_to_fp16 = const()[name = tensor("op_2409_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_75_cast_fp16 = layer_norm(axes = out_75_axes_0, epsilon = var_2409_to_fp16, x = inputs_75_cast_fp16)[name = tensor("out_75_cast_fp16")]; + tensor input_147_gamma_0_to_fp16 = const()[name = tensor("input_147_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(471707584)))]; + tensor input_147_beta_0_to_fp16 = const()[name = tensor("input_147_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(471709696)))]; + tensor input_147_epsilon_0_to_fp16 = const()[name = tensor("input_147_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_147_cast_fp16 = batch_norm(beta = input_147_beta_0_to_fp16, epsilon = input_147_epsilon_0_to_fp16, gamma = input_147_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_75_cast_fp16)[name = tensor("input_147_cast_fp16")]; + tensor input_149_pad_type_0 = const()[name = tensor("input_149_pad_type_0"), val = tensor("valid")]; + tensor input_149_strides_0 = const()[name = tensor("input_149_strides_0"), val = tensor([1, 1])]; + tensor input_149_pad_0 = const()[name = tensor("input_149_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_149_dilations_0 = const()[name = tensor("input_149_dilations_0"), val = tensor([1, 1])]; + tensor input_149_groups_0 = const()[name = tensor("input_149_groups_0"), val = tensor(1)]; + tensor layers_18_fc1_weight_to_fp16 = const()[name = tensor("layers_18_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(471711808)))]; + tensor layers_18_fc1_bias_to_fp16 = const()[name = tensor("layers_18_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(480100480)))]; + tensor input_149_cast_fp16 = conv(bias = layers_18_fc1_bias_to_fp16, dilations = input_149_dilations_0, groups = input_149_groups_0, pad = input_149_pad_0, pad_type = input_149_pad_type_0, strides = input_149_strides_0, weight = layers_18_fc1_weight_to_fp16, x = input_147_cast_fp16)[name = tensor("input_149_cast_fp16")]; + tensor input_151_mode_0 = const()[name = tensor("input_151_mode_0"), val = tensor("EXACT")]; + tensor input_151_cast_fp16 = gelu(mode = input_151_mode_0, x = input_149_cast_fp16)[name = tensor("input_151_cast_fp16")]; + tensor hidden_states_41_pad_type_0 = const()[name = tensor("hidden_states_41_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_41_strides_0 = const()[name = tensor("hidden_states_41_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_41_pad_0 = const()[name = tensor("hidden_states_41_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_41_dilations_0 = const()[name = tensor("hidden_states_41_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_41_groups_0 = const()[name = tensor("hidden_states_41_groups_0"), val = tensor(1)]; + tensor layers_18_fc2_weight_to_fp16 = const()[name = tensor("layers_18_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(480108736)))]; + tensor layers_18_fc2_bias_to_fp16 = const()[name = tensor("layers_18_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(488497408)))]; + tensor hidden_states_41_cast_fp16 = conv(bias = layers_18_fc2_bias_to_fp16, dilations = hidden_states_41_dilations_0, groups = hidden_states_41_groups_0, pad = hidden_states_41_pad_0, pad_type = hidden_states_41_pad_type_0, strides = hidden_states_41_strides_0, weight = layers_18_fc2_weight_to_fp16, x = input_151_cast_fp16)[name = tensor("hidden_states_41_cast_fp16")]; + tensor inputs_77_cast_fp16 = add(x = inputs_75_cast_fp16, y = hidden_states_41_cast_fp16)[name = tensor("inputs_77_cast_fp16")]; + tensor var_2438 = const()[name = tensor("op_2438"), val = tensor(3)]; + tensor out_77_axes_0 = const()[name = tensor("out_77_axes_0"), val = tensor([1])]; + tensor var_2460_to_fp16 = const()[name = tensor("op_2460_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_77_cast_fp16 = layer_norm(axes = out_77_axes_0, epsilon = var_2460_to_fp16, x = inputs_77_cast_fp16)[name = tensor("out_77_cast_fp16")]; + tensor obj_77_gamma_0_to_fp16 = const()[name = tensor("obj_77_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(488499520)))]; + tensor obj_77_beta_0_to_fp16 = const()[name = tensor("obj_77_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(488501632)))]; + tensor obj_77_epsilon_0_to_fp16 = const()[name = tensor("obj_77_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_77_cast_fp16 = batch_norm(beta = obj_77_beta_0_to_fp16, epsilon = obj_77_epsilon_0_to_fp16, gamma = obj_77_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_77_cast_fp16)[name = tensor("obj_77_cast_fp16")]; + tensor query_39_pad_type_0 = const()[name = tensor("query_39_pad_type_0"), val = tensor("valid")]; + tensor query_39_strides_0 = const()[name = tensor("query_39_strides_0"), val = tensor([1, 1])]; + tensor query_39_pad_0 = const()[name = tensor("query_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_39_dilations_0 = const()[name = tensor("query_39_dilations_0"), val = tensor([1, 1])]; + tensor query_39_groups_0 = const()[name = tensor("query_39_groups_0"), val = tensor(1)]; + tensor layers_19_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_19_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(488503744)))]; + tensor layers_19_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_19_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(490600960)))]; + tensor query_39_cast_fp16 = conv(bias = layers_19_self_attn_q_proj_bias_to_fp16, dilations = query_39_dilations_0, groups = query_39_groups_0, pad = query_39_pad_0, pad_type = query_39_pad_type_0, strides = query_39_strides_0, weight = layers_19_self_attn_q_proj_weight_to_fp16, x = obj_77_cast_fp16)[name = tensor("query_39_cast_fp16")]; + tensor key_39_pad_type_0 = const()[name = tensor("key_39_pad_type_0"), val = tensor("valid")]; + tensor key_39_strides_0 = const()[name = tensor("key_39_strides_0"), val = tensor([1, 1])]; + tensor key_39_pad_0 = const()[name = tensor("key_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_39_dilations_0 = const()[name = tensor("key_39_dilations_0"), val = tensor([1, 1])]; + tensor key_39_groups_0 = const()[name = tensor("key_39_groups_0"), val = tensor(1)]; + tensor layers_19_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_19_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(490603072)))]; + tensor key_39_cast_fp16 = conv(dilations = key_39_dilations_0, groups = key_39_groups_0, pad = key_39_pad_0, pad_type = key_39_pad_type_0, strides = key_39_strides_0, weight = layers_19_self_attn_k_proj_weight_to_fp16, x = obj_77_cast_fp16)[name = tensor("key_39_cast_fp16")]; + tensor value_39_pad_type_0 = const()[name = tensor("value_39_pad_type_0"), val = tensor("valid")]; + tensor value_39_strides_0 = const()[name = tensor("value_39_strides_0"), val = tensor([1, 1])]; + tensor value_39_pad_0 = const()[name = tensor("value_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_39_dilations_0 = const()[name = tensor("value_39_dilations_0"), val = tensor([1, 1])]; + tensor value_39_groups_0 = const()[name = tensor("value_39_groups_0"), val = tensor(1)]; + tensor layers_19_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_19_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(492700288)))]; + tensor layers_19_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_19_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(494797504)))]; + tensor value_39_cast_fp16 = conv(bias = layers_19_self_attn_v_proj_bias_to_fp16, dilations = value_39_dilations_0, groups = value_39_groups_0, pad = value_39_pad_0, pad_type = value_39_pad_type_0, strides = value_39_strides_0, weight = layers_19_self_attn_v_proj_weight_to_fp16, x = obj_77_cast_fp16)[name = tensor("value_39_cast_fp16")]; + tensor var_2496 = const()[name = tensor("op_2496"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_39_cast_fp16 = reshape(shape = var_2496, x = query_39_cast_fp16)[name = tensor("mh_q_39_cast_fp16")]; + tensor var_2498_to_fp16 = const()[name = tensor("op_2498_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2499_cast_fp16 = mul(x = mh_q_39_cast_fp16, y = var_2498_to_fp16)[name = tensor("op_2499_cast_fp16")]; + tensor var_2502 = const()[name = tensor("op_2502"), val = tensor([1, 16, 64, 1500])]; + tensor var_2503_cast_fp16 = reshape(shape = var_2502, x = key_39_cast_fp16)[name = tensor("op_2503_cast_fp16")]; + tensor mh_w_39_transpose_x_0 = const()[name = tensor("mh_w_39_transpose_x_0"), val = tensor(true)]; + tensor mh_w_39_transpose_y_0 = const()[name = tensor("mh_w_39_transpose_y_0"), val = tensor(false)]; + tensor mh_w_39_cast_fp16 = matmul(transpose_x = mh_w_39_transpose_x_0, transpose_y = mh_w_39_transpose_y_0, x = var_2499_cast_fp16, y = var_2503_cast_fp16)[name = tensor("mh_w_39_cast_fp16")]; + tensor var_2506_cast_fp16 = softmax(axis = var_2438, x = mh_w_39_cast_fp16)[name = tensor("op_2506_cast_fp16")]; + tensor var_2507 = const()[name = tensor("op_2507"), val = tensor([1, 16, 64, 1500])]; + tensor var_2508_cast_fp16 = reshape(shape = var_2507, x = value_39_cast_fp16)[name = tensor("op_2508_cast_fp16")]; + tensor attn_39_transpose_x_0 = const()[name = tensor("attn_39_transpose_x_0"), val = tensor(false)]; + tensor attn_39_transpose_y_0 = const()[name = tensor("attn_39_transpose_y_0"), val = tensor(true)]; + tensor attn_39_cast_fp16 = matmul(transpose_x = attn_39_transpose_x_0, transpose_y = attn_39_transpose_y_0, x = var_2508_cast_fp16, y = var_2506_cast_fp16)[name = tensor("attn_39_cast_fp16")]; + tensor var_2511 = const()[name = tensor("op_2511"), val = tensor([1, 1024, 1, 1500])]; + tensor input_153_cast_fp16 = reshape(shape = var_2511, x = attn_39_cast_fp16)[name = tensor("input_153_cast_fp16")]; + tensor obj_79_pad_type_0 = const()[name = tensor("obj_79_pad_type_0"), val = tensor("valid")]; + tensor obj_79_strides_0 = const()[name = tensor("obj_79_strides_0"), val = tensor([1, 1])]; + tensor obj_79_pad_0 = const()[name = tensor("obj_79_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_79_dilations_0 = const()[name = tensor("obj_79_dilations_0"), val = tensor([1, 1])]; + tensor obj_79_groups_0 = const()[name = tensor("obj_79_groups_0"), val = tensor(1)]; + tensor layers_19_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_19_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(494799616)))]; + tensor layers_19_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_19_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(496896832)))]; + tensor obj_79_cast_fp16 = conv(bias = layers_19_self_attn_o_proj_bias_to_fp16, dilations = obj_79_dilations_0, groups = obj_79_groups_0, pad = obj_79_pad_0, pad_type = obj_79_pad_type_0, strides = obj_79_strides_0, weight = layers_19_self_attn_o_proj_weight_to_fp16, x = input_153_cast_fp16)[name = tensor("obj_79_cast_fp16")]; + tensor inputs_79_cast_fp16 = add(x = inputs_77_cast_fp16, y = obj_79_cast_fp16)[name = tensor("inputs_79_cast_fp16")]; + tensor out_79_axes_0 = const()[name = tensor("out_79_axes_0"), val = tensor([1])]; + tensor var_2529_to_fp16 = const()[name = tensor("op_2529_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_79_cast_fp16 = layer_norm(axes = out_79_axes_0, epsilon = var_2529_to_fp16, x = inputs_79_cast_fp16)[name = tensor("out_79_cast_fp16")]; + tensor input_155_gamma_0_to_fp16 = const()[name = tensor("input_155_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(496898944)))]; + tensor input_155_beta_0_to_fp16 = const()[name = tensor("input_155_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(496901056)))]; + tensor input_155_epsilon_0_to_fp16 = const()[name = tensor("input_155_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_155_cast_fp16 = batch_norm(beta = input_155_beta_0_to_fp16, epsilon = input_155_epsilon_0_to_fp16, gamma = input_155_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_79_cast_fp16)[name = tensor("input_155_cast_fp16")]; + tensor input_157_pad_type_0 = const()[name = tensor("input_157_pad_type_0"), val = tensor("valid")]; + tensor input_157_strides_0 = const()[name = tensor("input_157_strides_0"), val = tensor([1, 1])]; + tensor input_157_pad_0 = const()[name = tensor("input_157_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_157_dilations_0 = const()[name = tensor("input_157_dilations_0"), val = tensor([1, 1])]; + tensor input_157_groups_0 = const()[name = tensor("input_157_groups_0"), val = tensor(1)]; + tensor layers_19_fc1_weight_to_fp16 = const()[name = tensor("layers_19_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(496903168)))]; + tensor layers_19_fc1_bias_to_fp16 = const()[name = tensor("layers_19_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(505291840)))]; + tensor input_157_cast_fp16 = conv(bias = layers_19_fc1_bias_to_fp16, dilations = input_157_dilations_0, groups = input_157_groups_0, pad = input_157_pad_0, pad_type = input_157_pad_type_0, strides = input_157_strides_0, weight = layers_19_fc1_weight_to_fp16, x = input_155_cast_fp16)[name = tensor("input_157_cast_fp16")]; + tensor input_159_mode_0 = const()[name = tensor("input_159_mode_0"), val = tensor("EXACT")]; + tensor input_159_cast_fp16 = gelu(mode = input_159_mode_0, x = input_157_cast_fp16)[name = tensor("input_159_cast_fp16")]; + tensor hidden_states_43_pad_type_0 = const()[name = tensor("hidden_states_43_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_43_strides_0 = const()[name = tensor("hidden_states_43_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_43_pad_0 = const()[name = tensor("hidden_states_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_43_dilations_0 = const()[name = tensor("hidden_states_43_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_43_groups_0 = const()[name = tensor("hidden_states_43_groups_0"), val = tensor(1)]; + tensor layers_19_fc2_weight_to_fp16 = const()[name = tensor("layers_19_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(505300096)))]; + tensor layers_19_fc2_bias_to_fp16 = const()[name = tensor("layers_19_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(513688768)))]; + tensor hidden_states_43_cast_fp16 = conv(bias = layers_19_fc2_bias_to_fp16, dilations = hidden_states_43_dilations_0, groups = hidden_states_43_groups_0, pad = hidden_states_43_pad_0, pad_type = hidden_states_43_pad_type_0, strides = hidden_states_43_strides_0, weight = layers_19_fc2_weight_to_fp16, x = input_159_cast_fp16)[name = tensor("hidden_states_43_cast_fp16")]; + tensor inputs_81_cast_fp16 = add(x = inputs_79_cast_fp16, y = hidden_states_43_cast_fp16)[name = tensor("inputs_81_cast_fp16")]; + tensor var_2558 = const()[name = tensor("op_2558"), val = tensor(3)]; + tensor out_81_axes_0 = const()[name = tensor("out_81_axes_0"), val = tensor([1])]; + tensor var_2580_to_fp16 = const()[name = tensor("op_2580_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_81_cast_fp16 = layer_norm(axes = out_81_axes_0, epsilon = var_2580_to_fp16, x = inputs_81_cast_fp16)[name = tensor("out_81_cast_fp16")]; + tensor obj_81_gamma_0_to_fp16 = const()[name = tensor("obj_81_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(513690880)))]; + tensor obj_81_beta_0_to_fp16 = const()[name = tensor("obj_81_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(513692992)))]; + tensor obj_81_epsilon_0_to_fp16 = const()[name = tensor("obj_81_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_81_cast_fp16 = batch_norm(beta = obj_81_beta_0_to_fp16, epsilon = obj_81_epsilon_0_to_fp16, gamma = obj_81_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_81_cast_fp16)[name = tensor("obj_81_cast_fp16")]; + tensor query_41_pad_type_0 = const()[name = tensor("query_41_pad_type_0"), val = tensor("valid")]; + tensor query_41_strides_0 = const()[name = tensor("query_41_strides_0"), val = tensor([1, 1])]; + tensor query_41_pad_0 = const()[name = tensor("query_41_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_41_dilations_0 = const()[name = tensor("query_41_dilations_0"), val = tensor([1, 1])]; + tensor query_41_groups_0 = const()[name = tensor("query_41_groups_0"), val = tensor(1)]; + tensor layers_20_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_20_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(513695104)))]; + tensor layers_20_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_20_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(515792320)))]; + tensor query_41_cast_fp16 = conv(bias = layers_20_self_attn_q_proj_bias_to_fp16, dilations = query_41_dilations_0, groups = query_41_groups_0, pad = query_41_pad_0, pad_type = query_41_pad_type_0, strides = query_41_strides_0, weight = layers_20_self_attn_q_proj_weight_to_fp16, x = obj_81_cast_fp16)[name = tensor("query_41_cast_fp16")]; + tensor key_41_pad_type_0 = const()[name = tensor("key_41_pad_type_0"), val = tensor("valid")]; + tensor key_41_strides_0 = const()[name = tensor("key_41_strides_0"), val = tensor([1, 1])]; + tensor key_41_pad_0 = const()[name = tensor("key_41_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_41_dilations_0 = const()[name = tensor("key_41_dilations_0"), val = tensor([1, 1])]; + tensor key_41_groups_0 = const()[name = tensor("key_41_groups_0"), val = tensor(1)]; + tensor layers_20_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_20_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(515794432)))]; + tensor key_41_cast_fp16 = conv(dilations = key_41_dilations_0, groups = key_41_groups_0, pad = key_41_pad_0, pad_type = key_41_pad_type_0, strides = key_41_strides_0, weight = layers_20_self_attn_k_proj_weight_to_fp16, x = obj_81_cast_fp16)[name = tensor("key_41_cast_fp16")]; + tensor value_41_pad_type_0 = const()[name = tensor("value_41_pad_type_0"), val = tensor("valid")]; + tensor value_41_strides_0 = const()[name = tensor("value_41_strides_0"), val = tensor([1, 1])]; + tensor value_41_pad_0 = const()[name = tensor("value_41_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_41_dilations_0 = const()[name = tensor("value_41_dilations_0"), val = tensor([1, 1])]; + tensor value_41_groups_0 = const()[name = tensor("value_41_groups_0"), val = tensor(1)]; + tensor layers_20_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_20_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(517891648)))]; + tensor layers_20_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_20_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(519988864)))]; + tensor value_41_cast_fp16 = conv(bias = layers_20_self_attn_v_proj_bias_to_fp16, dilations = value_41_dilations_0, groups = value_41_groups_0, pad = value_41_pad_0, pad_type = value_41_pad_type_0, strides = value_41_strides_0, weight = layers_20_self_attn_v_proj_weight_to_fp16, x = obj_81_cast_fp16)[name = tensor("value_41_cast_fp16")]; + tensor var_2616 = const()[name = tensor("op_2616"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_41_cast_fp16 = reshape(shape = var_2616, x = query_41_cast_fp16)[name = tensor("mh_q_41_cast_fp16")]; + tensor var_2618_to_fp16 = const()[name = tensor("op_2618_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2619_cast_fp16 = mul(x = mh_q_41_cast_fp16, y = var_2618_to_fp16)[name = tensor("op_2619_cast_fp16")]; + tensor var_2622 = const()[name = tensor("op_2622"), val = tensor([1, 16, 64, 1500])]; + tensor var_2623_cast_fp16 = reshape(shape = var_2622, x = key_41_cast_fp16)[name = tensor("op_2623_cast_fp16")]; + tensor mh_w_41_transpose_x_0 = const()[name = tensor("mh_w_41_transpose_x_0"), val = tensor(true)]; + tensor mh_w_41_transpose_y_0 = const()[name = tensor("mh_w_41_transpose_y_0"), val = tensor(false)]; + tensor mh_w_41_cast_fp16 = matmul(transpose_x = mh_w_41_transpose_x_0, transpose_y = mh_w_41_transpose_y_0, x = var_2619_cast_fp16, y = var_2623_cast_fp16)[name = tensor("mh_w_41_cast_fp16")]; + tensor var_2626_cast_fp16 = softmax(axis = var_2558, x = mh_w_41_cast_fp16)[name = tensor("op_2626_cast_fp16")]; + tensor var_2627 = const()[name = tensor("op_2627"), val = tensor([1, 16, 64, 1500])]; + tensor var_2628_cast_fp16 = reshape(shape = var_2627, x = value_41_cast_fp16)[name = tensor("op_2628_cast_fp16")]; + tensor attn_41_transpose_x_0 = const()[name = tensor("attn_41_transpose_x_0"), val = tensor(false)]; + tensor attn_41_transpose_y_0 = const()[name = tensor("attn_41_transpose_y_0"), val = tensor(true)]; + tensor attn_41_cast_fp16 = matmul(transpose_x = attn_41_transpose_x_0, transpose_y = attn_41_transpose_y_0, x = var_2628_cast_fp16, y = var_2626_cast_fp16)[name = tensor("attn_41_cast_fp16")]; + tensor var_2631 = const()[name = tensor("op_2631"), val = tensor([1, 1024, 1, 1500])]; + tensor input_161_cast_fp16 = reshape(shape = var_2631, x = attn_41_cast_fp16)[name = tensor("input_161_cast_fp16")]; + tensor obj_83_pad_type_0 = const()[name = tensor("obj_83_pad_type_0"), val = tensor("valid")]; + tensor obj_83_strides_0 = const()[name = tensor("obj_83_strides_0"), val = tensor([1, 1])]; + tensor obj_83_pad_0 = const()[name = tensor("obj_83_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_83_dilations_0 = const()[name = tensor("obj_83_dilations_0"), val = tensor([1, 1])]; + tensor obj_83_groups_0 = const()[name = tensor("obj_83_groups_0"), val = tensor(1)]; + tensor layers_20_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_20_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(519990976)))]; + tensor layers_20_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_20_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(522088192)))]; + tensor obj_83_cast_fp16 = conv(bias = layers_20_self_attn_o_proj_bias_to_fp16, dilations = obj_83_dilations_0, groups = obj_83_groups_0, pad = obj_83_pad_0, pad_type = obj_83_pad_type_0, strides = obj_83_strides_0, weight = layers_20_self_attn_o_proj_weight_to_fp16, x = input_161_cast_fp16)[name = tensor("obj_83_cast_fp16")]; + tensor inputs_83_cast_fp16 = add(x = inputs_81_cast_fp16, y = obj_83_cast_fp16)[name = tensor("inputs_83_cast_fp16")]; + tensor out_83_axes_0 = const()[name = tensor("out_83_axes_0"), val = tensor([1])]; + tensor var_2649_to_fp16 = const()[name = tensor("op_2649_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_83_cast_fp16 = layer_norm(axes = out_83_axes_0, epsilon = var_2649_to_fp16, x = inputs_83_cast_fp16)[name = tensor("out_83_cast_fp16")]; + tensor input_163_gamma_0_to_fp16 = const()[name = tensor("input_163_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(522090304)))]; + tensor input_163_beta_0_to_fp16 = const()[name = tensor("input_163_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(522092416)))]; + tensor input_163_epsilon_0_to_fp16 = const()[name = tensor("input_163_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_163_cast_fp16 = batch_norm(beta = input_163_beta_0_to_fp16, epsilon = input_163_epsilon_0_to_fp16, gamma = input_163_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_83_cast_fp16)[name = tensor("input_163_cast_fp16")]; + tensor input_165_pad_type_0 = const()[name = tensor("input_165_pad_type_0"), val = tensor("valid")]; + tensor input_165_strides_0 = const()[name = tensor("input_165_strides_0"), val = tensor([1, 1])]; + tensor input_165_pad_0 = const()[name = tensor("input_165_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_165_dilations_0 = const()[name = tensor("input_165_dilations_0"), val = tensor([1, 1])]; + tensor input_165_groups_0 = const()[name = tensor("input_165_groups_0"), val = tensor(1)]; + tensor layers_20_fc1_weight_to_fp16 = const()[name = tensor("layers_20_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(522094528)))]; + tensor layers_20_fc1_bias_to_fp16 = const()[name = tensor("layers_20_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(530483200)))]; + tensor input_165_cast_fp16 = conv(bias = layers_20_fc1_bias_to_fp16, dilations = input_165_dilations_0, groups = input_165_groups_0, pad = input_165_pad_0, pad_type = input_165_pad_type_0, strides = input_165_strides_0, weight = layers_20_fc1_weight_to_fp16, x = input_163_cast_fp16)[name = tensor("input_165_cast_fp16")]; + tensor input_167_mode_0 = const()[name = tensor("input_167_mode_0"), val = tensor("EXACT")]; + tensor input_167_cast_fp16 = gelu(mode = input_167_mode_0, x = input_165_cast_fp16)[name = tensor("input_167_cast_fp16")]; + tensor hidden_states_45_pad_type_0 = const()[name = tensor("hidden_states_45_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_45_strides_0 = const()[name = tensor("hidden_states_45_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_45_pad_0 = const()[name = tensor("hidden_states_45_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_45_dilations_0 = const()[name = tensor("hidden_states_45_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_45_groups_0 = const()[name = tensor("hidden_states_45_groups_0"), val = tensor(1)]; + tensor layers_20_fc2_weight_to_fp16 = const()[name = tensor("layers_20_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(530491456)))]; + tensor layers_20_fc2_bias_to_fp16 = const()[name = tensor("layers_20_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(538880128)))]; + tensor hidden_states_45_cast_fp16 = conv(bias = layers_20_fc2_bias_to_fp16, dilations = hidden_states_45_dilations_0, groups = hidden_states_45_groups_0, pad = hidden_states_45_pad_0, pad_type = hidden_states_45_pad_type_0, strides = hidden_states_45_strides_0, weight = layers_20_fc2_weight_to_fp16, x = input_167_cast_fp16)[name = tensor("hidden_states_45_cast_fp16")]; + tensor inputs_85_cast_fp16 = add(x = inputs_83_cast_fp16, y = hidden_states_45_cast_fp16)[name = tensor("inputs_85_cast_fp16")]; + tensor var_2678 = const()[name = tensor("op_2678"), val = tensor(3)]; + tensor out_85_axes_0 = const()[name = tensor("out_85_axes_0"), val = tensor([1])]; + tensor var_2700_to_fp16 = const()[name = tensor("op_2700_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_85_cast_fp16 = layer_norm(axes = out_85_axes_0, epsilon = var_2700_to_fp16, x = inputs_85_cast_fp16)[name = tensor("out_85_cast_fp16")]; + tensor obj_85_gamma_0_to_fp16 = const()[name = tensor("obj_85_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(538882240)))]; + tensor obj_85_beta_0_to_fp16 = const()[name = tensor("obj_85_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(538884352)))]; + tensor obj_85_epsilon_0_to_fp16 = const()[name = tensor("obj_85_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_85_cast_fp16 = batch_norm(beta = obj_85_beta_0_to_fp16, epsilon = obj_85_epsilon_0_to_fp16, gamma = obj_85_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_85_cast_fp16)[name = tensor("obj_85_cast_fp16")]; + tensor query_43_pad_type_0 = const()[name = tensor("query_43_pad_type_0"), val = tensor("valid")]; + tensor query_43_strides_0 = const()[name = tensor("query_43_strides_0"), val = tensor([1, 1])]; + tensor query_43_pad_0 = const()[name = tensor("query_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_43_dilations_0 = const()[name = tensor("query_43_dilations_0"), val = tensor([1, 1])]; + tensor query_43_groups_0 = const()[name = tensor("query_43_groups_0"), val = tensor(1)]; + tensor layers_21_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_21_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(538886464)))]; + tensor layers_21_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_21_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(540983680)))]; + tensor query_43_cast_fp16 = conv(bias = layers_21_self_attn_q_proj_bias_to_fp16, dilations = query_43_dilations_0, groups = query_43_groups_0, pad = query_43_pad_0, pad_type = query_43_pad_type_0, strides = query_43_strides_0, weight = layers_21_self_attn_q_proj_weight_to_fp16, x = obj_85_cast_fp16)[name = tensor("query_43_cast_fp16")]; + tensor key_43_pad_type_0 = const()[name = tensor("key_43_pad_type_0"), val = tensor("valid")]; + tensor key_43_strides_0 = const()[name = tensor("key_43_strides_0"), val = tensor([1, 1])]; + tensor key_43_pad_0 = const()[name = tensor("key_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_43_dilations_0 = const()[name = tensor("key_43_dilations_0"), val = tensor([1, 1])]; + tensor key_43_groups_0 = const()[name = tensor("key_43_groups_0"), val = tensor(1)]; + tensor layers_21_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_21_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(540985792)))]; + tensor key_43_cast_fp16 = conv(dilations = key_43_dilations_0, groups = key_43_groups_0, pad = key_43_pad_0, pad_type = key_43_pad_type_0, strides = key_43_strides_0, weight = layers_21_self_attn_k_proj_weight_to_fp16, x = obj_85_cast_fp16)[name = tensor("key_43_cast_fp16")]; + tensor value_43_pad_type_0 = const()[name = tensor("value_43_pad_type_0"), val = tensor("valid")]; + tensor value_43_strides_0 = const()[name = tensor("value_43_strides_0"), val = tensor([1, 1])]; + tensor value_43_pad_0 = const()[name = tensor("value_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_43_dilations_0 = const()[name = tensor("value_43_dilations_0"), val = tensor([1, 1])]; + tensor value_43_groups_0 = const()[name = tensor("value_43_groups_0"), val = tensor(1)]; + tensor layers_21_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_21_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(543083008)))]; + tensor layers_21_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_21_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(545180224)))]; + tensor value_43_cast_fp16 = conv(bias = layers_21_self_attn_v_proj_bias_to_fp16, dilations = value_43_dilations_0, groups = value_43_groups_0, pad = value_43_pad_0, pad_type = value_43_pad_type_0, strides = value_43_strides_0, weight = layers_21_self_attn_v_proj_weight_to_fp16, x = obj_85_cast_fp16)[name = tensor("value_43_cast_fp16")]; + tensor var_2736 = const()[name = tensor("op_2736"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_43_cast_fp16 = reshape(shape = var_2736, x = query_43_cast_fp16)[name = tensor("mh_q_43_cast_fp16")]; + tensor var_2738_to_fp16 = const()[name = tensor("op_2738_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2739_cast_fp16 = mul(x = mh_q_43_cast_fp16, y = var_2738_to_fp16)[name = tensor("op_2739_cast_fp16")]; + tensor var_2742 = const()[name = tensor("op_2742"), val = tensor([1, 16, 64, 1500])]; + tensor var_2743_cast_fp16 = reshape(shape = var_2742, x = key_43_cast_fp16)[name = tensor("op_2743_cast_fp16")]; + tensor mh_w_43_transpose_x_0 = const()[name = tensor("mh_w_43_transpose_x_0"), val = tensor(true)]; + tensor mh_w_43_transpose_y_0 = const()[name = tensor("mh_w_43_transpose_y_0"), val = tensor(false)]; + tensor mh_w_43_cast_fp16 = matmul(transpose_x = mh_w_43_transpose_x_0, transpose_y = mh_w_43_transpose_y_0, x = var_2739_cast_fp16, y = var_2743_cast_fp16)[name = tensor("mh_w_43_cast_fp16")]; + tensor var_2746_cast_fp16 = softmax(axis = var_2678, x = mh_w_43_cast_fp16)[name = tensor("op_2746_cast_fp16")]; + tensor var_2747 = const()[name = tensor("op_2747"), val = tensor([1, 16, 64, 1500])]; + tensor var_2748_cast_fp16 = reshape(shape = var_2747, x = value_43_cast_fp16)[name = tensor("op_2748_cast_fp16")]; + tensor attn_43_transpose_x_0 = const()[name = tensor("attn_43_transpose_x_0"), val = tensor(false)]; + tensor attn_43_transpose_y_0 = const()[name = tensor("attn_43_transpose_y_0"), val = tensor(true)]; + tensor attn_43_cast_fp16 = matmul(transpose_x = attn_43_transpose_x_0, transpose_y = attn_43_transpose_y_0, x = var_2748_cast_fp16, y = var_2746_cast_fp16)[name = tensor("attn_43_cast_fp16")]; + tensor var_2751 = const()[name = tensor("op_2751"), val = tensor([1, 1024, 1, 1500])]; + tensor input_169_cast_fp16 = reshape(shape = var_2751, x = attn_43_cast_fp16)[name = tensor("input_169_cast_fp16")]; + tensor obj_87_pad_type_0 = const()[name = tensor("obj_87_pad_type_0"), val = tensor("valid")]; + tensor obj_87_strides_0 = const()[name = tensor("obj_87_strides_0"), val = tensor([1, 1])]; + tensor obj_87_pad_0 = const()[name = tensor("obj_87_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_87_dilations_0 = const()[name = tensor("obj_87_dilations_0"), val = tensor([1, 1])]; + tensor obj_87_groups_0 = const()[name = tensor("obj_87_groups_0"), val = tensor(1)]; + tensor layers_21_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_21_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(545182336)))]; + tensor layers_21_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_21_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(547279552)))]; + tensor obj_87_cast_fp16 = conv(bias = layers_21_self_attn_o_proj_bias_to_fp16, dilations = obj_87_dilations_0, groups = obj_87_groups_0, pad = obj_87_pad_0, pad_type = obj_87_pad_type_0, strides = obj_87_strides_0, weight = layers_21_self_attn_o_proj_weight_to_fp16, x = input_169_cast_fp16)[name = tensor("obj_87_cast_fp16")]; + tensor inputs_87_cast_fp16 = add(x = inputs_85_cast_fp16, y = obj_87_cast_fp16)[name = tensor("inputs_87_cast_fp16")]; + tensor out_87_axes_0 = const()[name = tensor("out_87_axes_0"), val = tensor([1])]; + tensor var_2769_to_fp16 = const()[name = tensor("op_2769_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_87_cast_fp16 = layer_norm(axes = out_87_axes_0, epsilon = var_2769_to_fp16, x = inputs_87_cast_fp16)[name = tensor("out_87_cast_fp16")]; + tensor input_171_gamma_0_to_fp16 = const()[name = tensor("input_171_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(547281664)))]; + tensor input_171_beta_0_to_fp16 = const()[name = tensor("input_171_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(547283776)))]; + tensor input_171_epsilon_0_to_fp16 = const()[name = tensor("input_171_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_171_cast_fp16 = batch_norm(beta = input_171_beta_0_to_fp16, epsilon = input_171_epsilon_0_to_fp16, gamma = input_171_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_87_cast_fp16)[name = tensor("input_171_cast_fp16")]; + tensor input_173_pad_type_0 = const()[name = tensor("input_173_pad_type_0"), val = tensor("valid")]; + tensor input_173_strides_0 = const()[name = tensor("input_173_strides_0"), val = tensor([1, 1])]; + tensor input_173_pad_0 = const()[name = tensor("input_173_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_173_dilations_0 = const()[name = tensor("input_173_dilations_0"), val = tensor([1, 1])]; + tensor input_173_groups_0 = const()[name = tensor("input_173_groups_0"), val = tensor(1)]; + tensor layers_21_fc1_weight_to_fp16 = const()[name = tensor("layers_21_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(547285888)))]; + tensor layers_21_fc1_bias_to_fp16 = const()[name = tensor("layers_21_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(555674560)))]; + tensor input_173_cast_fp16 = conv(bias = layers_21_fc1_bias_to_fp16, dilations = input_173_dilations_0, groups = input_173_groups_0, pad = input_173_pad_0, pad_type = input_173_pad_type_0, strides = input_173_strides_0, weight = layers_21_fc1_weight_to_fp16, x = input_171_cast_fp16)[name = tensor("input_173_cast_fp16")]; + tensor input_175_mode_0 = const()[name = tensor("input_175_mode_0"), val = tensor("EXACT")]; + tensor input_175_cast_fp16 = gelu(mode = input_175_mode_0, x = input_173_cast_fp16)[name = tensor("input_175_cast_fp16")]; + tensor hidden_states_47_pad_type_0 = const()[name = tensor("hidden_states_47_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_47_strides_0 = const()[name = tensor("hidden_states_47_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_47_pad_0 = const()[name = tensor("hidden_states_47_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_47_dilations_0 = const()[name = tensor("hidden_states_47_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_47_groups_0 = const()[name = tensor("hidden_states_47_groups_0"), val = tensor(1)]; + tensor layers_21_fc2_weight_to_fp16 = const()[name = tensor("layers_21_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(555682816)))]; + tensor layers_21_fc2_bias_to_fp16 = const()[name = tensor("layers_21_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(564071488)))]; + tensor hidden_states_47_cast_fp16 = conv(bias = layers_21_fc2_bias_to_fp16, dilations = hidden_states_47_dilations_0, groups = hidden_states_47_groups_0, pad = hidden_states_47_pad_0, pad_type = hidden_states_47_pad_type_0, strides = hidden_states_47_strides_0, weight = layers_21_fc2_weight_to_fp16, x = input_175_cast_fp16)[name = tensor("hidden_states_47_cast_fp16")]; + tensor inputs_89_cast_fp16 = add(x = inputs_87_cast_fp16, y = hidden_states_47_cast_fp16)[name = tensor("inputs_89_cast_fp16")]; + tensor var_2798 = const()[name = tensor("op_2798"), val = tensor(3)]; + tensor out_89_axes_0 = const()[name = tensor("out_89_axes_0"), val = tensor([1])]; + tensor var_2820_to_fp16 = const()[name = tensor("op_2820_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_89_cast_fp16 = layer_norm(axes = out_89_axes_0, epsilon = var_2820_to_fp16, x = inputs_89_cast_fp16)[name = tensor("out_89_cast_fp16")]; + tensor obj_89_gamma_0_to_fp16 = const()[name = tensor("obj_89_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(564073600)))]; + tensor obj_89_beta_0_to_fp16 = const()[name = tensor("obj_89_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(564075712)))]; + tensor obj_89_epsilon_0_to_fp16 = const()[name = tensor("obj_89_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_89_cast_fp16 = batch_norm(beta = obj_89_beta_0_to_fp16, epsilon = obj_89_epsilon_0_to_fp16, gamma = obj_89_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_89_cast_fp16)[name = tensor("obj_89_cast_fp16")]; + tensor query_45_pad_type_0 = const()[name = tensor("query_45_pad_type_0"), val = tensor("valid")]; + tensor query_45_strides_0 = const()[name = tensor("query_45_strides_0"), val = tensor([1, 1])]; + tensor query_45_pad_0 = const()[name = tensor("query_45_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_45_dilations_0 = const()[name = tensor("query_45_dilations_0"), val = tensor([1, 1])]; + tensor query_45_groups_0 = const()[name = tensor("query_45_groups_0"), val = tensor(1)]; + tensor layers_22_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_22_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(564077824)))]; + tensor layers_22_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_22_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(566175040)))]; + tensor query_45_cast_fp16 = conv(bias = layers_22_self_attn_q_proj_bias_to_fp16, dilations = query_45_dilations_0, groups = query_45_groups_0, pad = query_45_pad_0, pad_type = query_45_pad_type_0, strides = query_45_strides_0, weight = layers_22_self_attn_q_proj_weight_to_fp16, x = obj_89_cast_fp16)[name = tensor("query_45_cast_fp16")]; + tensor key_45_pad_type_0 = const()[name = tensor("key_45_pad_type_0"), val = tensor("valid")]; + tensor key_45_strides_0 = const()[name = tensor("key_45_strides_0"), val = tensor([1, 1])]; + tensor key_45_pad_0 = const()[name = tensor("key_45_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_45_dilations_0 = const()[name = tensor("key_45_dilations_0"), val = tensor([1, 1])]; + tensor key_45_groups_0 = const()[name = tensor("key_45_groups_0"), val = tensor(1)]; + tensor layers_22_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_22_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(566177152)))]; + tensor key_45_cast_fp16 = conv(dilations = key_45_dilations_0, groups = key_45_groups_0, pad = key_45_pad_0, pad_type = key_45_pad_type_0, strides = key_45_strides_0, weight = layers_22_self_attn_k_proj_weight_to_fp16, x = obj_89_cast_fp16)[name = tensor("key_45_cast_fp16")]; + tensor value_45_pad_type_0 = const()[name = tensor("value_45_pad_type_0"), val = tensor("valid")]; + tensor value_45_strides_0 = const()[name = tensor("value_45_strides_0"), val = tensor([1, 1])]; + tensor value_45_pad_0 = const()[name = tensor("value_45_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_45_dilations_0 = const()[name = tensor("value_45_dilations_0"), val = tensor([1, 1])]; + tensor value_45_groups_0 = const()[name = tensor("value_45_groups_0"), val = tensor(1)]; + tensor layers_22_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_22_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(568274368)))]; + tensor layers_22_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_22_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(570371584)))]; + tensor value_45_cast_fp16 = conv(bias = layers_22_self_attn_v_proj_bias_to_fp16, dilations = value_45_dilations_0, groups = value_45_groups_0, pad = value_45_pad_0, pad_type = value_45_pad_type_0, strides = value_45_strides_0, weight = layers_22_self_attn_v_proj_weight_to_fp16, x = obj_89_cast_fp16)[name = tensor("value_45_cast_fp16")]; + tensor var_2856 = const()[name = tensor("op_2856"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_45_cast_fp16 = reshape(shape = var_2856, x = query_45_cast_fp16)[name = tensor("mh_q_45_cast_fp16")]; + tensor var_2858_to_fp16 = const()[name = tensor("op_2858_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2859_cast_fp16 = mul(x = mh_q_45_cast_fp16, y = var_2858_to_fp16)[name = tensor("op_2859_cast_fp16")]; + tensor var_2862 = const()[name = tensor("op_2862"), val = tensor([1, 16, 64, 1500])]; + tensor var_2863_cast_fp16 = reshape(shape = var_2862, x = key_45_cast_fp16)[name = tensor("op_2863_cast_fp16")]; + tensor mh_w_45_transpose_x_0 = const()[name = tensor("mh_w_45_transpose_x_0"), val = tensor(true)]; + tensor mh_w_45_transpose_y_0 = const()[name = tensor("mh_w_45_transpose_y_0"), val = tensor(false)]; + tensor mh_w_45_cast_fp16 = matmul(transpose_x = mh_w_45_transpose_x_0, transpose_y = mh_w_45_transpose_y_0, x = var_2859_cast_fp16, y = var_2863_cast_fp16)[name = tensor("mh_w_45_cast_fp16")]; + tensor var_2866_cast_fp16 = softmax(axis = var_2798, x = mh_w_45_cast_fp16)[name = tensor("op_2866_cast_fp16")]; + tensor var_2867 = const()[name = tensor("op_2867"), val = tensor([1, 16, 64, 1500])]; + tensor var_2868_cast_fp16 = reshape(shape = var_2867, x = value_45_cast_fp16)[name = tensor("op_2868_cast_fp16")]; + tensor attn_45_transpose_x_0 = const()[name = tensor("attn_45_transpose_x_0"), val = tensor(false)]; + tensor attn_45_transpose_y_0 = const()[name = tensor("attn_45_transpose_y_0"), val = tensor(true)]; + tensor attn_45_cast_fp16 = matmul(transpose_x = attn_45_transpose_x_0, transpose_y = attn_45_transpose_y_0, x = var_2868_cast_fp16, y = var_2866_cast_fp16)[name = tensor("attn_45_cast_fp16")]; + tensor var_2871 = const()[name = tensor("op_2871"), val = tensor([1, 1024, 1, 1500])]; + tensor input_177_cast_fp16 = reshape(shape = var_2871, x = attn_45_cast_fp16)[name = tensor("input_177_cast_fp16")]; + tensor obj_91_pad_type_0 = const()[name = tensor("obj_91_pad_type_0"), val = tensor("valid")]; + tensor obj_91_strides_0 = const()[name = tensor("obj_91_strides_0"), val = tensor([1, 1])]; + tensor obj_91_pad_0 = const()[name = tensor("obj_91_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_91_dilations_0 = const()[name = tensor("obj_91_dilations_0"), val = tensor([1, 1])]; + tensor obj_91_groups_0 = const()[name = tensor("obj_91_groups_0"), val = tensor(1)]; + tensor layers_22_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_22_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(570373696)))]; + tensor layers_22_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_22_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(572470912)))]; + tensor obj_91_cast_fp16 = conv(bias = layers_22_self_attn_o_proj_bias_to_fp16, dilations = obj_91_dilations_0, groups = obj_91_groups_0, pad = obj_91_pad_0, pad_type = obj_91_pad_type_0, strides = obj_91_strides_0, weight = layers_22_self_attn_o_proj_weight_to_fp16, x = input_177_cast_fp16)[name = tensor("obj_91_cast_fp16")]; + tensor inputs_91_cast_fp16 = add(x = inputs_89_cast_fp16, y = obj_91_cast_fp16)[name = tensor("inputs_91_cast_fp16")]; + tensor out_91_axes_0 = const()[name = tensor("out_91_axes_0"), val = tensor([1])]; + tensor var_2889_to_fp16 = const()[name = tensor("op_2889_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_91_cast_fp16 = layer_norm(axes = out_91_axes_0, epsilon = var_2889_to_fp16, x = inputs_91_cast_fp16)[name = tensor("out_91_cast_fp16")]; + tensor input_179_gamma_0_to_fp16 = const()[name = tensor("input_179_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(572473024)))]; + tensor input_179_beta_0_to_fp16 = const()[name = tensor("input_179_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(572475136)))]; + tensor input_179_epsilon_0_to_fp16 = const()[name = tensor("input_179_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_179_cast_fp16 = batch_norm(beta = input_179_beta_0_to_fp16, epsilon = input_179_epsilon_0_to_fp16, gamma = input_179_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_91_cast_fp16)[name = tensor("input_179_cast_fp16")]; + tensor input_181_pad_type_0 = const()[name = tensor("input_181_pad_type_0"), val = tensor("valid")]; + tensor input_181_strides_0 = const()[name = tensor("input_181_strides_0"), val = tensor([1, 1])]; + tensor input_181_pad_0 = const()[name = tensor("input_181_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_181_dilations_0 = const()[name = tensor("input_181_dilations_0"), val = tensor([1, 1])]; + tensor input_181_groups_0 = const()[name = tensor("input_181_groups_0"), val = tensor(1)]; + tensor layers_22_fc1_weight_to_fp16 = const()[name = tensor("layers_22_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(572477248)))]; + tensor layers_22_fc1_bias_to_fp16 = const()[name = tensor("layers_22_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(580865920)))]; + tensor input_181_cast_fp16 = conv(bias = layers_22_fc1_bias_to_fp16, dilations = input_181_dilations_0, groups = input_181_groups_0, pad = input_181_pad_0, pad_type = input_181_pad_type_0, strides = input_181_strides_0, weight = layers_22_fc1_weight_to_fp16, x = input_179_cast_fp16)[name = tensor("input_181_cast_fp16")]; + tensor input_183_mode_0 = const()[name = tensor("input_183_mode_0"), val = tensor("EXACT")]; + tensor input_183_cast_fp16 = gelu(mode = input_183_mode_0, x = input_181_cast_fp16)[name = tensor("input_183_cast_fp16")]; + tensor hidden_states_49_pad_type_0 = const()[name = tensor("hidden_states_49_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_49_strides_0 = const()[name = tensor("hidden_states_49_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_49_pad_0 = const()[name = tensor("hidden_states_49_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_49_dilations_0 = const()[name = tensor("hidden_states_49_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_49_groups_0 = const()[name = tensor("hidden_states_49_groups_0"), val = tensor(1)]; + tensor layers_22_fc2_weight_to_fp16 = const()[name = tensor("layers_22_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(580874176)))]; + tensor layers_22_fc2_bias_to_fp16 = const()[name = tensor("layers_22_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(589262848)))]; + tensor hidden_states_49_cast_fp16 = conv(bias = layers_22_fc2_bias_to_fp16, dilations = hidden_states_49_dilations_0, groups = hidden_states_49_groups_0, pad = hidden_states_49_pad_0, pad_type = hidden_states_49_pad_type_0, strides = hidden_states_49_strides_0, weight = layers_22_fc2_weight_to_fp16, x = input_183_cast_fp16)[name = tensor("hidden_states_49_cast_fp16")]; + tensor inputs_93_cast_fp16 = add(x = inputs_91_cast_fp16, y = hidden_states_49_cast_fp16)[name = tensor("inputs_93_cast_fp16")]; + tensor var_2918 = const()[name = tensor("op_2918"), val = tensor(3)]; + tensor out_93_axes_0 = const()[name = tensor("out_93_axes_0"), val = tensor([1])]; + tensor var_2940_to_fp16 = const()[name = tensor("op_2940_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_93_cast_fp16 = layer_norm(axes = out_93_axes_0, epsilon = var_2940_to_fp16, x = inputs_93_cast_fp16)[name = tensor("out_93_cast_fp16")]; + tensor obj_93_gamma_0_to_fp16 = const()[name = tensor("obj_93_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(589264960)))]; + tensor obj_93_beta_0_to_fp16 = const()[name = tensor("obj_93_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(589267072)))]; + tensor obj_93_epsilon_0_to_fp16 = const()[name = tensor("obj_93_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_93_cast_fp16 = batch_norm(beta = obj_93_beta_0_to_fp16, epsilon = obj_93_epsilon_0_to_fp16, gamma = obj_93_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_93_cast_fp16)[name = tensor("obj_93_cast_fp16")]; + tensor query_pad_type_0 = const()[name = tensor("query_pad_type_0"), val = tensor("valid")]; + tensor query_strides_0 = const()[name = tensor("query_strides_0"), val = tensor([1, 1])]; + tensor query_pad_0 = const()[name = tensor("query_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_dilations_0 = const()[name = tensor("query_dilations_0"), val = tensor([1, 1])]; + tensor query_groups_0 = const()[name = tensor("query_groups_0"), val = tensor(1)]; + tensor layers_23_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_23_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(589269184)))]; + tensor layers_23_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_23_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(591366400)))]; + tensor query_cast_fp16 = conv(bias = layers_23_self_attn_q_proj_bias_to_fp16, dilations = query_dilations_0, groups = query_groups_0, pad = query_pad_0, pad_type = query_pad_type_0, strides = query_strides_0, weight = layers_23_self_attn_q_proj_weight_to_fp16, x = obj_93_cast_fp16)[name = tensor("query_cast_fp16")]; + tensor key_pad_type_0 = const()[name = tensor("key_pad_type_0"), val = tensor("valid")]; + tensor key_strides_0 = const()[name = tensor("key_strides_0"), val = tensor([1, 1])]; + tensor key_pad_0 = const()[name = tensor("key_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_dilations_0 = const()[name = tensor("key_dilations_0"), val = tensor([1, 1])]; + tensor key_groups_0 = const()[name = tensor("key_groups_0"), val = tensor(1)]; + tensor layers_23_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_23_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(591368512)))]; + tensor key_cast_fp16 = conv(dilations = key_dilations_0, groups = key_groups_0, pad = key_pad_0, pad_type = key_pad_type_0, strides = key_strides_0, weight = layers_23_self_attn_k_proj_weight_to_fp16, x = obj_93_cast_fp16)[name = tensor("key_cast_fp16")]; + tensor value_pad_type_0 = const()[name = tensor("value_pad_type_0"), val = tensor("valid")]; + tensor value_strides_0 = const()[name = tensor("value_strides_0"), val = tensor([1, 1])]; + tensor value_pad_0 = const()[name = tensor("value_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_dilations_0 = const()[name = tensor("value_dilations_0"), val = tensor([1, 1])]; + tensor value_groups_0 = const()[name = tensor("value_groups_0"), val = tensor(1)]; + tensor layers_23_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_23_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(593465728)))]; + tensor layers_23_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_23_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(595562944)))]; + tensor value_cast_fp16 = conv(bias = layers_23_self_attn_v_proj_bias_to_fp16, dilations = value_dilations_0, groups = value_groups_0, pad = value_pad_0, pad_type = value_pad_type_0, strides = value_strides_0, weight = layers_23_self_attn_v_proj_weight_to_fp16, x = obj_93_cast_fp16)[name = tensor("value_cast_fp16")]; + tensor var_2976 = const()[name = tensor("op_2976"), val = tensor([1, 16, 64, 1500])]; + tensor mh_q_cast_fp16 = reshape(shape = var_2976, x = query_cast_fp16)[name = tensor("mh_q_cast_fp16")]; + tensor var_2978_to_fp16 = const()[name = tensor("op_2978_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2979_cast_fp16 = mul(x = mh_q_cast_fp16, y = var_2978_to_fp16)[name = tensor("op_2979_cast_fp16")]; + tensor var_2982 = const()[name = tensor("op_2982"), val = tensor([1, 16, 64, 1500])]; + tensor var_2983_cast_fp16 = reshape(shape = var_2982, x = key_cast_fp16)[name = tensor("op_2983_cast_fp16")]; + tensor mh_w_transpose_x_0 = const()[name = tensor("mh_w_transpose_x_0"), val = tensor(true)]; + tensor mh_w_transpose_y_0 = const()[name = tensor("mh_w_transpose_y_0"), val = tensor(false)]; + tensor mh_w_cast_fp16 = matmul(transpose_x = mh_w_transpose_x_0, transpose_y = mh_w_transpose_y_0, x = var_2979_cast_fp16, y = var_2983_cast_fp16)[name = tensor("mh_w_cast_fp16")]; + tensor var_2986_cast_fp16 = softmax(axis = var_2918, x = mh_w_cast_fp16)[name = tensor("op_2986_cast_fp16")]; + tensor var_2987 = const()[name = tensor("op_2987"), val = tensor([1, 16, 64, 1500])]; + tensor var_2988_cast_fp16 = reshape(shape = var_2987, x = value_cast_fp16)[name = tensor("op_2988_cast_fp16")]; + tensor attn_transpose_x_0 = const()[name = tensor("attn_transpose_x_0"), val = tensor(false)]; + tensor attn_transpose_y_0 = const()[name = tensor("attn_transpose_y_0"), val = tensor(true)]; + tensor attn_cast_fp16 = matmul(transpose_x = attn_transpose_x_0, transpose_y = attn_transpose_y_0, x = var_2988_cast_fp16, y = var_2986_cast_fp16)[name = tensor("attn_cast_fp16")]; + tensor var_2991 = const()[name = tensor("op_2991"), val = tensor([1, 1024, 1, 1500])]; + tensor input_185_cast_fp16 = reshape(shape = var_2991, x = attn_cast_fp16)[name = tensor("input_185_cast_fp16")]; + tensor obj_pad_type_0 = const()[name = tensor("obj_pad_type_0"), val = tensor("valid")]; + tensor obj_strides_0 = const()[name = tensor("obj_strides_0"), val = tensor([1, 1])]; + tensor obj_pad_0 = const()[name = tensor("obj_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_dilations_0 = const()[name = tensor("obj_dilations_0"), val = tensor([1, 1])]; + tensor obj_groups_0 = const()[name = tensor("obj_groups_0"), val = tensor(1)]; + tensor layers_23_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_23_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(595565056)))]; + tensor layers_23_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_23_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(597662272)))]; + tensor obj_cast_fp16 = conv(bias = layers_23_self_attn_o_proj_bias_to_fp16, dilations = obj_dilations_0, groups = obj_groups_0, pad = obj_pad_0, pad_type = obj_pad_type_0, strides = obj_strides_0, weight = layers_23_self_attn_o_proj_weight_to_fp16, x = input_185_cast_fp16)[name = tensor("obj_cast_fp16")]; + tensor inputs_95_cast_fp16 = add(x = inputs_93_cast_fp16, y = obj_cast_fp16)[name = tensor("inputs_95_cast_fp16")]; + tensor out_95_axes_0 = const()[name = tensor("out_95_axes_0"), val = tensor([1])]; + tensor var_3009_to_fp16 = const()[name = tensor("op_3009_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_95_cast_fp16 = layer_norm(axes = out_95_axes_0, epsilon = var_3009_to_fp16, x = inputs_95_cast_fp16)[name = tensor("out_95_cast_fp16")]; + tensor input_187_gamma_0_to_fp16 = const()[name = tensor("input_187_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(597664384)))]; + tensor input_187_beta_0_to_fp16 = const()[name = tensor("input_187_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(597666496)))]; + tensor input_187_epsilon_0_to_fp16 = const()[name = tensor("input_187_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_187_cast_fp16 = batch_norm(beta = input_187_beta_0_to_fp16, epsilon = input_187_epsilon_0_to_fp16, gamma = input_187_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_95_cast_fp16)[name = tensor("input_187_cast_fp16")]; + tensor input_189_pad_type_0 = const()[name = tensor("input_189_pad_type_0"), val = tensor("valid")]; + tensor input_189_strides_0 = const()[name = tensor("input_189_strides_0"), val = tensor([1, 1])]; + tensor input_189_pad_0 = const()[name = tensor("input_189_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_189_dilations_0 = const()[name = tensor("input_189_dilations_0"), val = tensor([1, 1])]; + tensor input_189_groups_0 = const()[name = tensor("input_189_groups_0"), val = tensor(1)]; + tensor layers_23_fc1_weight_to_fp16 = const()[name = tensor("layers_23_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(597668608)))]; + tensor layers_23_fc1_bias_to_fp16 = const()[name = tensor("layers_23_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(606057280)))]; + tensor input_189_cast_fp16 = conv(bias = layers_23_fc1_bias_to_fp16, dilations = input_189_dilations_0, groups = input_189_groups_0, pad = input_189_pad_0, pad_type = input_189_pad_type_0, strides = input_189_strides_0, weight = layers_23_fc1_weight_to_fp16, x = input_187_cast_fp16)[name = tensor("input_189_cast_fp16")]; + tensor input_mode_0 = const()[name = tensor("input_mode_0"), val = tensor("EXACT")]; + tensor input_cast_fp16 = gelu(mode = input_mode_0, x = input_189_cast_fp16)[name = tensor("input_cast_fp16")]; + tensor hidden_states_pad_type_0 = const()[name = tensor("hidden_states_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_strides_0 = const()[name = tensor("hidden_states_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_pad_0 = const()[name = tensor("hidden_states_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_dilations_0 = const()[name = tensor("hidden_states_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_groups_0 = const()[name = tensor("hidden_states_groups_0"), val = tensor(1)]; + tensor layers_23_fc2_weight_to_fp16 = const()[name = tensor("layers_23_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(606065536)))]; + tensor layers_23_fc2_bias_to_fp16 = const()[name = tensor("layers_23_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(614454208)))]; + tensor hidden_states_cast_fp16 = conv(bias = layers_23_fc2_bias_to_fp16, dilations = hidden_states_dilations_0, groups = hidden_states_groups_0, pad = hidden_states_pad_0, pad_type = hidden_states_pad_type_0, strides = hidden_states_strides_0, weight = layers_23_fc2_weight_to_fp16, x = input_cast_fp16)[name = tensor("hidden_states_cast_fp16")]; + tensor inputs_cast_fp16 = add(x = inputs_95_cast_fp16, y = hidden_states_cast_fp16)[name = tensor("inputs_cast_fp16")]; + tensor out_axes_0 = const()[name = tensor("out_axes_0"), val = tensor([1])]; + tensor var_3047_to_fp16 = const()[name = tensor("op_3047_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_cast_fp16 = layer_norm(axes = out_axes_0, epsilon = var_3047_to_fp16, x = inputs_cast_fp16)[name = tensor("out_cast_fp16")]; + tensor encoder_output_embeds_type_fp32_gamma_0_to_fp16 = const()[name = tensor("encoder_output_embeds_type_fp32_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(614456320)))]; + tensor encoder_output_embeds_type_fp32_beta_0_to_fp16 = const()[name = tensor("encoder_output_embeds_type_fp32_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(614458432)))]; + tensor encoder_output_embeds_type_fp32_epsilon_0_to_fp16 = const()[name = tensor("encoder_output_embeds_type_fp32_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor encoder_output_embeds = batch_norm(beta = encoder_output_embeds_type_fp32_beta_0_to_fp16, epsilon = encoder_output_embeds_type_fp32_epsilon_0_to_fp16, gamma = encoder_output_embeds_type_fp32_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_cast_fp16)[name = tensor("encoder_output_embeds_type_fp32_cast_fp16")]; + } -> (encoder_output_embeds); +} \ No newline at end of file diff --git a/openai_whisper-medium/AudioEncoder.mlmodelc/weights/weight.bin b/openai_whisper-medium/AudioEncoder.mlmodelc/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..c8beb32179ea8db553721fbafdb7024f2bcb79a1 --- /dev/null +++ b/openai_whisper-medium/AudioEncoder.mlmodelc/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:577c78ed7e0ae71f9ed6fdb063dc74a0f4c0c44d04118111650458973f7ddae6 +size 614460544 diff --git a/openai_whisper-medium/MelSpectrogram.mlcomputeplan.json b/openai_whisper-medium/MelSpectrogram.mlcomputeplan.json new file mode 100644 index 0000000000000000000000000000000000000000..717cb6a9aa4e752c90d26b278ccbb65e900fe5a5 --- /dev/null +++ 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a/openai_whisper-medium/MelSpectrogram.mlmodelc/model.mil b/openai_whisper-medium/MelSpectrogram.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..20a1b38b6e6cf850afd0ba3614d7a4396bc8e4d9 --- /dev/null +++ b/openai_whisper-medium/MelSpectrogram.mlmodelc/model.mil @@ -0,0 +1,66 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3401.3.1"}, {"coremlc-version", "3401.4.1"}, {"coremltools-component-torch", "2.5.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.2"}})] +{ + func main(tensor audio) { + tensor var_10 = const()[name = tensor("op_10"), val = tensor([1, 1, 480000])]; + tensor input_1_cast_fp16 = reshape(shape = var_10, x = audio)[name = tensor("input_1_cast_fp16")]; + tensor input_3_pad_0 = const()[name = tensor("input_3_pad_0"), val = tensor([0, 0, 0, 0, 200, 200])]; + tensor input_3_mode_0 = const()[name = tensor("input_3_mode_0"), val = tensor("reflect")]; + tensor const_1_to_fp16 = const()[name = tensor("const_1_to_fp16"), val = tensor(0x0p+0)]; + tensor input_3_cast_fp16 = pad(constant_val = const_1_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = tensor("input_3_cast_fp16")]; + tensor var_22 = const()[name = tensor("op_22"), val = tensor([480400])]; + tensor input_cast_fp16 = reshape(shape = var_22, x = input_3_cast_fp16)[name = tensor("input_cast_fp16")]; + tensor expand_dims_0_axes_0 = const()[name = tensor("expand_dims_0_axes_0"), val = tensor([0])]; + tensor expand_dims_0_cast_fp16 = expand_dims(axes = expand_dims_0_axes_0, x = input_cast_fp16)[name = tensor("expand_dims_0_cast_fp16")]; + tensor expand_dims_3 = const()[name = tensor("expand_dims_3"), val = tensor([160])]; + tensor expand_dims_4_axes_0 = const()[name = tensor("expand_dims_4_axes_0"), val = tensor([1])]; + tensor expand_dims_4_cast_fp16 = expand_dims(axes = expand_dims_4_axes_0, x = expand_dims_0_cast_fp16)[name = tensor("expand_dims_4_cast_fp16")]; + tensor conv_0_pad_type_0 = const()[name = tensor("conv_0_pad_type_0"), val = tensor("valid")]; + tensor conv_0_pad_0 = const()[name = tensor("conv_0_pad_0"), val = tensor([0, 0])]; + tensor conv_0_dilations_0 = const()[name = tensor("conv_0_dilations_0"), val = tensor([1])]; + tensor conv_0_groups_0 = const()[name = tensor("conv_0_groups_0"), val = tensor(1)]; + tensor expand_dims_1_to_fp16 = const()[name = tensor("expand_dims_1_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor conv_0_cast_fp16 = conv(dilations = conv_0_dilations_0, groups = conv_0_groups_0, pad = conv_0_pad_0, pad_type = conv_0_pad_type_0, strides = expand_dims_3, weight = expand_dims_1_to_fp16, x = expand_dims_4_cast_fp16)[name = tensor("conv_0_cast_fp16")]; + tensor conv_1_pad_type_0 = const()[name = tensor("conv_1_pad_type_0"), val = tensor("valid")]; + tensor conv_1_pad_0 = const()[name = tensor("conv_1_pad_0"), val = tensor([0, 0])]; + tensor conv_1_dilations_0 = const()[name = tensor("conv_1_dilations_0"), val = tensor([1])]; + tensor conv_1_groups_0 = const()[name = tensor("conv_1_groups_0"), val = tensor(1)]; + tensor expand_dims_2_to_fp16 = const()[name = tensor("expand_dims_2_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160960)))]; + tensor conv_1_cast_fp16 = conv(dilations = conv_1_dilations_0, groups = conv_1_groups_0, pad = conv_1_pad_0, pad_type = conv_1_pad_type_0, strides = expand_dims_3, weight = expand_dims_2_to_fp16, x = expand_dims_4_cast_fp16)[name = tensor("conv_1_cast_fp16")]; + tensor squeeze_0_axes_0 = const()[name = tensor("squeeze_0_axes_0"), val = tensor([0])]; + tensor squeeze_0_cast_fp16 = squeeze(axes = squeeze_0_axes_0, x = conv_0_cast_fp16)[name = tensor("squeeze_0_cast_fp16")]; + tensor squeeze_1_axes_0 = const()[name = tensor("squeeze_1_axes_0"), val = tensor([0])]; + tensor squeeze_1_cast_fp16 = squeeze(axes = squeeze_1_axes_0, x = conv_1_cast_fp16)[name = tensor("squeeze_1_cast_fp16")]; + tensor square_0_cast_fp16 = square(x = squeeze_0_cast_fp16)[name = tensor("square_0_cast_fp16")]; + tensor square_1_cast_fp16 = square(x = squeeze_1_cast_fp16)[name = tensor("square_1_cast_fp16")]; + tensor add_1_cast_fp16 = add(x = square_0_cast_fp16, y = square_1_cast_fp16)[name = tensor("add_1_cast_fp16")]; + tensor magnitudes_1_cast_fp16 = identity(x = add_1_cast_fp16)[name = tensor("magnitudes_1_cast_fp16")]; + tensor magnitudes_begin_0 = const()[name = tensor("magnitudes_begin_0"), val = tensor([0, 0])]; + tensor magnitudes_end_0 = const()[name = tensor("magnitudes_end_0"), val = tensor([201, 3000])]; + tensor magnitudes_end_mask_0 = const()[name = tensor("magnitudes_end_mask_0"), val = tensor([true, false])]; + tensor magnitudes_cast_fp16 = slice_by_index(begin = magnitudes_begin_0, end = magnitudes_end_0, end_mask = magnitudes_end_mask_0, x = magnitudes_1_cast_fp16)[name = tensor("magnitudes_cast_fp16")]; + tensor mel_spec_1_transpose_x_0 = const()[name = tensor("mel_spec_1_transpose_x_0"), val = tensor(false)]; + tensor mel_spec_1_transpose_y_0 = const()[name = tensor("mel_spec_1_transpose_y_0"), val = tensor(false)]; + tensor mel_filters_to_fp16 = const()[name = tensor("mel_filters_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(321856)))]; + tensor mel_spec_1_cast_fp16 = matmul(transpose_x = mel_spec_1_transpose_x_0, transpose_y = mel_spec_1_transpose_y_0, x = mel_filters_to_fp16, y = magnitudes_cast_fp16)[name = tensor("mel_spec_1_cast_fp16")]; + tensor var_41_to_fp16 = const()[name = tensor("op_41_to_fp16"), val = tensor(0x1p-24)]; + tensor mel_spec_cast_fp16 = add(x = mel_spec_1_cast_fp16, y = var_41_to_fp16)[name = tensor("mel_spec_cast_fp16")]; + tensor log_0_epsilon_0_to_fp16 = const()[name = tensor("log_0_epsilon_0_to_fp16"), val = tensor(0x0p+0)]; + tensor log_0_cast_fp16 = log(epsilon = log_0_epsilon_0_to_fp16, x = mel_spec_cast_fp16)[name = tensor("log_0_cast_fp16")]; + tensor mul_0_y_0_to_fp16 = const()[name = tensor("mul_0_y_0_to_fp16"), val = tensor(0x1.bccp-2)]; + tensor mul_0_cast_fp16 = mul(x = log_0_cast_fp16, y = mul_0_y_0_to_fp16)[name = tensor("mul_0_cast_fp16")]; + tensor var_44_keep_dims_0 = const()[name = tensor("op_44_keep_dims_0"), val = tensor(false)]; + tensor var_44_cast_fp16 = reduce_max(keep_dims = var_44_keep_dims_0, x = mul_0_cast_fp16)[name = tensor("op_44_cast_fp16")]; + tensor var_46_to_fp16 = const()[name = tensor("op_46_to_fp16"), val = tensor(0x1p+3)]; + tensor var_47_cast_fp16 = sub(x = var_44_cast_fp16, y = var_46_to_fp16)[name = tensor("op_47_cast_fp16")]; + tensor log_spec_3_cast_fp16 = maximum(x = mul_0_cast_fp16, y = var_47_cast_fp16)[name = tensor("log_spec_3_cast_fp16")]; + tensor var_50_to_fp16 = const()[name = tensor("op_50_to_fp16"), val = tensor(0x1p+2)]; + tensor var_51_cast_fp16 = add(x = log_spec_3_cast_fp16, y = var_50_to_fp16)[name = tensor("op_51_cast_fp16")]; + tensor _inversed_log_spec_y_0_to_fp16 = const()[name = tensor("_inversed_log_spec_y_0_to_fp16"), val = tensor(0x1p-2)]; + tensor _inversed_log_spec_cast_fp16 = mul(x = var_51_cast_fp16, y = _inversed_log_spec_y_0_to_fp16)[name = tensor("_inversed_log_spec_cast_fp16")]; + tensor var_55_axes_0 = const()[name = tensor("op_55_axes_0"), val = tensor([0])]; + tensor var_55_cast_fp16 = expand_dims(axes = var_55_axes_0, x = _inversed_log_spec_cast_fp16)[name = tensor("op_55_cast_fp16")]; + tensor var_62_axes_0 = const()[name = tensor("op_62_axes_0"), val = tensor([2])]; + tensor melspectrogram_features = expand_dims(axes = var_62_axes_0, x = var_55_cast_fp16)[name = tensor("op_62_cast_fp16")]; + } -> (melspectrogram_features); +} \ No newline at end of file diff --git a/openai_whisper-medium/MelSpectrogram.mlmodelc/weights/weight.bin b/openai_whisper-medium/MelSpectrogram.mlmodelc/weights/weight.bin new file mode 100644 index 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"shortDescription" : "", + "shape" : "[1, 448]", + "name" : "decoder_key_padding_mask", + "type" : "MultiArray" + } + ], + "generatedClassName" : "TextDecoder", + "method" : "predict" + } +] \ No newline at end of file diff --git a/openai_whisper-medium/TextDecoder.mlmodelc/model.mil b/openai_whisper-medium/TextDecoder.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..510013572579213f5a6da9f945bca2098fb6a503 --- /dev/null +++ b/openai_whisper-medium/TextDecoder.mlmodelc/model.mil @@ -0,0 +1,3620 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3401.3.1"}, {"coremlc-version", "3401.4.1"}, {"coremltools-component-torch", "2.5.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.2"}})] +{ + func main(tensor cache_length, tensor decoder_key_padding_mask, tensor encoder_output_embeds, tensor input_ids, tensor key_cache, tensor kv_cache_update_mask, tensor value_cache) { + tensor var_64_axis_0 = const()[name = tensor("op_64_axis_0"), val = tensor(0)]; + tensor var_64_batch_dims_0 = const()[name = tensor("op_64_batch_dims_0"), val = tensor(0)]; + tensor embed_tokens_weight_to_fp16 = const()[name = tensor("embed_tokens_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor var_64_cast_fp16 = gather(axis = var_64_axis_0, batch_dims = var_64_batch_dims_0, indices = input_ids, x = embed_tokens_weight_to_fp16)[name = tensor("op_64_cast_fp16")]; + tensor var_68_axis_0 = const()[name = tensor("op_68_axis_0"), val = tensor(0)]; + tensor var_68_batch_dims_0 = const()[name = tensor("op_68_batch_dims_0"), val = tensor(0)]; + tensor embed_positions_weight_to_fp16 = const()[name = tensor("embed_positions_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106219648)))]; + tensor var_68_cast_fp16 = gather(axis = var_68_axis_0, batch_dims = var_68_batch_dims_0, indices = cache_length, x = embed_positions_weight_to_fp16)[name = tensor("op_68_cast_fp16")]; + tensor hidden_states_1_cast_fp16 = add(x = var_64_cast_fp16, y = var_68_cast_fp16)[name = tensor("hidden_states_1_cast_fp16")]; + tensor var_82_axes_0 = const()[name = tensor("op_82_axes_0"), val = tensor([2])]; + tensor var_82_cast_fp16 = expand_dims(axes = var_82_axes_0, x = hidden_states_1_cast_fp16)[name = tensor("op_82_cast_fp16")]; + tensor inputs_1_axes_0 = const()[name = tensor("inputs_1_axes_0"), val = tensor([3])]; + tensor inputs_1_cast_fp16 = expand_dims(axes = inputs_1_axes_0, x = var_82_cast_fp16)[name = tensor("inputs_1_cast_fp16")]; + tensor tile_0 = const()[name = tensor("tile_0"), val = tensor([1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024])]; + tensor var_87_axis_0 = const()[name = tensor("op_87_axis_0"), val = tensor(1)]; + tensor var_87_cast_fp16_0, tensor var_87_cast_fp16_1, tensor var_87_cast_fp16_2, tensor var_87_cast_fp16_3, tensor var_87_cast_fp16_4, tensor var_87_cast_fp16_5, tensor var_87_cast_fp16_6, tensor var_87_cast_fp16_7, tensor var_87_cast_fp16_8, tensor var_87_cast_fp16_9, tensor var_87_cast_fp16_10, tensor var_87_cast_fp16_11, tensor var_87_cast_fp16_12, tensor var_87_cast_fp16_13, tensor var_87_cast_fp16_14, tensor var_87_cast_fp16_15, tensor var_87_cast_fp16_16, tensor var_87_cast_fp16_17, tensor var_87_cast_fp16_18, tensor var_87_cast_fp16_19, tensor var_87_cast_fp16_20, tensor var_87_cast_fp16_21, tensor var_87_cast_fp16_22, tensor var_87_cast_fp16_23 = split(axis = var_87_axis_0, split_sizes = tile_0, x = key_cache)[name = tensor("op_87_cast_fp16")]; + tensor tile_1 = const()[name = tensor("tile_1"), val = tensor([1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024, 1024])]; + tensor var_114_axis_0 = const()[name = tensor("op_114_axis_0"), val = tensor(1)]; + tensor var_114_cast_fp16_0, tensor var_114_cast_fp16_1, tensor var_114_cast_fp16_2, tensor var_114_cast_fp16_3, tensor var_114_cast_fp16_4, tensor var_114_cast_fp16_5, tensor var_114_cast_fp16_6, tensor var_114_cast_fp16_7, tensor var_114_cast_fp16_8, tensor var_114_cast_fp16_9, tensor var_114_cast_fp16_10, tensor var_114_cast_fp16_11, tensor var_114_cast_fp16_12, tensor var_114_cast_fp16_13, tensor var_114_cast_fp16_14, tensor var_114_cast_fp16_15, tensor var_114_cast_fp16_16, tensor var_114_cast_fp16_17, tensor var_114_cast_fp16_18, tensor var_114_cast_fp16_19, tensor var_114_cast_fp16_20, tensor var_114_cast_fp16_21, tensor var_114_cast_fp16_22, tensor var_114_cast_fp16_23 = split(axis = var_114_axis_0, split_sizes = tile_1, x = value_cache)[name = tensor("op_114_cast_fp16")]; + tensor var_144 = const()[name = tensor("op_144"), val = tensor(3)]; + tensor out_1_axes_0 = const()[name = tensor("out_1_axes_0"), val = tensor([1])]; + tensor var_169_to_fp16 = const()[name = tensor("op_169_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_1_cast_fp16 = layer_norm(axes = out_1_axes_0, epsilon = var_169_to_fp16, x = inputs_1_cast_fp16)[name = tensor("out_1_cast_fp16")]; + tensor obj_1_mean_0_to_fp16 = const()[name = tensor("obj_1_mean_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107137216)))]; + tensor obj_1_variance_0_to_fp16 = const()[name = tensor("obj_1_variance_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107139328)))]; + tensor obj_1_gamma_0_to_fp16 = const()[name = tensor("obj_1_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107141440)))]; + tensor obj_1_beta_0_to_fp16 = const()[name = tensor("obj_1_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107143552)))]; + tensor obj_1_epsilon_0_to_fp16 = const()[name = tensor("obj_1_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_1_cast_fp16 = batch_norm(beta = obj_1_beta_0_to_fp16, epsilon = obj_1_epsilon_0_to_fp16, gamma = obj_1_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_1_cast_fp16)[name = tensor("obj_1_cast_fp16")]; + tensor query_1_pad_type_0 = const()[name = tensor("query_1_pad_type_0"), val = tensor("valid")]; + tensor query_1_strides_0 = const()[name = tensor("query_1_strides_0"), val = tensor([1, 1])]; + tensor query_1_pad_0 = const()[name = tensor("query_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_1_dilations_0 = const()[name = tensor("query_1_dilations_0"), val = tensor([1, 1])]; + tensor query_1_groups_0 = const()[name = tensor("query_1_groups_0"), val = tensor(1)]; + tensor layers_0_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107145664)))]; + tensor layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109242880)))]; + tensor query_1_cast_fp16 = conv(bias = layers_0_self_attn_q_proj_bias_to_fp16, dilations = query_1_dilations_0, groups = query_1_groups_0, pad = query_1_pad_0, pad_type = query_1_pad_type_0, strides = query_1_strides_0, weight = layers_0_self_attn_q_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("query_1_cast_fp16")]; + tensor current_key_1_pad_type_0 = const()[name = tensor("current_key_1_pad_type_0"), val = tensor("valid")]; + tensor current_key_1_strides_0 = const()[name = tensor("current_key_1_strides_0"), val = tensor([1, 1])]; + tensor current_key_1_pad_0 = const()[name = tensor("current_key_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_1_dilations_0 = const()[name = tensor("current_key_1_dilations_0"), val = tensor([1, 1])]; + tensor current_key_1_groups_0 = const()[name = tensor("current_key_1_groups_0"), val = tensor(1)]; + tensor layers_0_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109244992)))]; + tensor current_key_1_cast_fp16 = conv(dilations = current_key_1_dilations_0, groups = current_key_1_groups_0, pad = current_key_1_pad_0, pad_type = current_key_1_pad_type_0, strides = current_key_1_strides_0, weight = layers_0_self_attn_k_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("current_key_1_cast_fp16")]; + tensor current_value_1_pad_type_0 = const()[name = tensor("current_value_1_pad_type_0"), val = tensor("valid")]; + tensor current_value_1_strides_0 = const()[name = tensor("current_value_1_strides_0"), val = tensor([1, 1])]; + tensor current_value_1_pad_0 = const()[name = tensor("current_value_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_1_dilations_0 = const()[name = tensor("current_value_1_dilations_0"), val = tensor([1, 1])]; + tensor current_value_1_groups_0 = const()[name = tensor("current_value_1_groups_0"), val = tensor(1)]; + tensor layers_0_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111342208)))]; + tensor layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113439424)))]; + tensor current_value_1_cast_fp16 = conv(bias = layers_0_self_attn_v_proj_bias_to_fp16, dilations = current_value_1_dilations_0, groups = current_value_1_groups_0, pad = current_value_1_pad_0, pad_type = current_value_1_pad_type_0, strides = current_value_1_strides_0, weight = layers_0_self_attn_v_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("current_value_1_cast_fp16")]; + tensor var_204_axes_0 = const()[name = tensor("op_204_axes_0"), val = tensor([1])]; + tensor var_204_cast_fp16 = expand_dims(axes = var_204_axes_0, x = kv_cache_update_mask)[name = tensor("op_204_cast_fp16")]; + tensor var_205_axes_0 = const()[name = tensor("op_205_axes_0"), val = tensor([2])]; + tensor var_205_cast_fp16 = expand_dims(axes = var_205_axes_0, x = var_204_cast_fp16)[name = tensor("op_205_cast_fp16")]; + tensor var_145_to_fp16 = const()[name = tensor("op_145_to_fp16"), val = tensor(0x1p+0)]; + tensor var_207_cast_fp16 = sub(x = var_145_to_fp16, y = var_205_cast_fp16)[name = tensor("op_207_cast_fp16")]; + tensor var_208_cast_fp16 = mul(x = var_87_cast_fp16_0, y = var_207_cast_fp16)[name = tensor("op_208_cast_fp16")]; + tensor var_209_cast_fp16 = mul(x = current_key_1_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_209_cast_fp16")]; + tensor key_1_cast_fp16 = add(x = var_208_cast_fp16, y = var_209_cast_fp16)[name = tensor("key_1_cast_fp16")]; + tensor var_212_cast_fp16 = mul(x = var_114_cast_fp16_0, y = var_207_cast_fp16)[name = tensor("op_212_cast_fp16")]; + tensor var_213_cast_fp16 = mul(x = current_value_1_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_213_cast_fp16")]; + tensor value_1_cast_fp16 = add(x = var_212_cast_fp16, y = var_213_cast_fp16)[name = tensor("value_1_cast_fp16")]; + tensor var_217 = const()[name = tensor("op_217"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_1_cast_fp16 = reshape(shape = var_217, x = query_1_cast_fp16)[name = tensor("mh_q_1_cast_fp16")]; + tensor var_219_to_fp16 = const()[name = tensor("op_219_to_fp16"), val = tensor(0x1p-3)]; + tensor var_220_cast_fp16 = mul(x = mh_q_1_cast_fp16, y = var_219_to_fp16)[name = tensor("op_220_cast_fp16")]; + tensor var_223 = const()[name = tensor("op_223"), val = tensor([1, 16, 64, 448])]; + tensor var_224_cast_fp16 = reshape(shape = var_223, x = key_1_cast_fp16)[name = tensor("op_224_cast_fp16")]; + tensor mh_w_1_transpose_x_0 = const()[name = tensor("mh_w_1_transpose_x_0"), val = tensor(true)]; + tensor mh_w_1_transpose_y_0 = const()[name = tensor("mh_w_1_transpose_y_0"), val = tensor(false)]; + tensor mh_w_1_cast_fp16 = matmul(transpose_x = mh_w_1_transpose_x_0, transpose_y = mh_w_1_transpose_y_0, x = var_220_cast_fp16, y = var_224_cast_fp16)[name = tensor("mh_w_1_cast_fp16")]; + tensor var_228_axes_0 = const()[name = tensor("op_228_axes_0"), val = tensor([1])]; + tensor var_228_cast_fp16 = expand_dims(axes = var_228_axes_0, x = decoder_key_padding_mask)[name = tensor("op_228_cast_fp16")]; + tensor var_229_axes_0 = const()[name = tensor("op_229_axes_0"), val = tensor([2])]; + tensor var_229_cast_fp16 = expand_dims(axes = var_229_axes_0, x = var_228_cast_fp16)[name = tensor("op_229_cast_fp16")]; + tensor mh_w_3_cast_fp16 = add(x = mh_w_1_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_3_cast_fp16")]; + tensor var_232_cast_fp16 = softmax(axis = var_144, x = mh_w_3_cast_fp16)[name = tensor("op_232_cast_fp16")]; + tensor var_233 = const()[name = tensor("op_233"), val = tensor([1, 16, 64, 448])]; + tensor var_234_cast_fp16 = reshape(shape = var_233, x = value_1_cast_fp16)[name = tensor("op_234_cast_fp16")]; + tensor attn_1_transpose_x_0 = const()[name = tensor("attn_1_transpose_x_0"), val = tensor(false)]; + tensor attn_1_transpose_y_0 = const()[name = tensor("attn_1_transpose_y_0"), val = tensor(true)]; + tensor attn_1_cast_fp16 = matmul(transpose_x = attn_1_transpose_x_0, transpose_y = attn_1_transpose_y_0, x = var_234_cast_fp16, y = var_232_cast_fp16)[name = tensor("attn_1_cast_fp16")]; + tensor var_237 = const()[name = tensor("op_237"), val = tensor([1, 1024, 1, 1])]; + tensor input_1_cast_fp16 = reshape(shape = var_237, x = attn_1_cast_fp16)[name = tensor("input_1_cast_fp16")]; + tensor obj_7_pad_type_0 = const()[name = tensor("obj_7_pad_type_0"), val = tensor("valid")]; + tensor obj_7_strides_0 = const()[name = tensor("obj_7_strides_0"), val = tensor([1, 1])]; + tensor obj_7_pad_0 = const()[name = tensor("obj_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_7_dilations_0 = const()[name = tensor("obj_7_dilations_0"), val = tensor([1, 1])]; + tensor obj_7_groups_0 = const()[name = tensor("obj_7_groups_0"), val = tensor(1)]; + tensor layers_0_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113441536)))]; + tensor layers_0_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115538752)))]; + tensor obj_7_cast_fp16 = conv(bias = layers_0_self_attn_o_proj_bias_to_fp16, dilations = obj_7_dilations_0, groups = obj_7_groups_0, pad = obj_7_pad_0, pad_type = obj_7_pad_type_0, strides = obj_7_strides_0, weight = layers_0_self_attn_o_proj_weight_to_fp16, x = input_1_cast_fp16)[name = tensor("obj_7_cast_fp16")]; + tensor inputs_3_cast_fp16 = add(x = inputs_1_cast_fp16, y = obj_7_cast_fp16)[name = tensor("inputs_3_cast_fp16")]; + tensor out_3_axes_0 = const()[name = tensor("out_3_axes_0"), val = tensor([1])]; + tensor var_259_to_fp16 = const()[name = tensor("op_259_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_3_cast_fp16 = layer_norm(axes = out_3_axes_0, epsilon = var_259_to_fp16, x = inputs_3_cast_fp16)[name = tensor("out_3_cast_fp16")]; + tensor obj_9_gamma_0_to_fp16 = const()[name = tensor("obj_9_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115540864)))]; + tensor obj_9_beta_0_to_fp16 = const()[name = tensor("obj_9_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115542976)))]; + tensor obj_9_epsilon_0_to_fp16 = const()[name = tensor("obj_9_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_9_cast_fp16 = batch_norm(beta = obj_9_beta_0_to_fp16, epsilon = obj_9_epsilon_0_to_fp16, gamma = obj_9_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_3_cast_fp16)[name = tensor("obj_9_cast_fp16")]; + tensor query_3_pad_type_0 = const()[name = tensor("query_3_pad_type_0"), val = tensor("valid")]; + tensor query_3_strides_0 = const()[name = tensor("query_3_strides_0"), val = tensor([1, 1])]; + tensor query_3_pad_0 = const()[name = tensor("query_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_3_dilations_0 = const()[name = tensor("query_3_dilations_0"), val = tensor([1, 1])]; + tensor query_3_groups_0 = const()[name = tensor("query_3_groups_0"), val = tensor(1)]; + tensor layers_0_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115545088)))]; + tensor layers_0_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_0_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(117642304)))]; + tensor query_3_cast_fp16 = conv(bias = layers_0_encoder_attn_q_proj_bias_to_fp16, dilations = query_3_dilations_0, groups = query_3_groups_0, pad = query_3_pad_0, pad_type = query_3_pad_type_0, strides = query_3_strides_0, weight = layers_0_encoder_attn_q_proj_weight_to_fp16, x = obj_9_cast_fp16)[name = tensor("query_3_cast_fp16")]; + tensor key_3_pad_type_0 = const()[name = tensor("key_3_pad_type_0"), val = tensor("valid")]; + tensor key_3_strides_0 = const()[name = tensor("key_3_strides_0"), val = tensor([1, 1])]; + tensor key_3_pad_0 = const()[name = tensor("key_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_3_dilations_0 = const()[name = tensor("key_3_dilations_0"), val = tensor([1, 1])]; + tensor key_3_groups_0 = const()[name = tensor("key_3_groups_0"), val = tensor(1)]; + tensor layers_0_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(117644416)))]; + tensor key_3_cast_fp16 = conv(dilations = key_3_dilations_0, groups = key_3_groups_0, pad = key_3_pad_0, pad_type = key_3_pad_type_0, strides = key_3_strides_0, weight = layers_0_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_3_cast_fp16")]; + tensor value_3_pad_type_0 = const()[name = tensor("value_3_pad_type_0"), val = tensor("valid")]; + tensor value_3_strides_0 = const()[name = tensor("value_3_strides_0"), val = tensor([1, 1])]; + tensor value_3_pad_0 = const()[name = tensor("value_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_3_dilations_0 = const()[name = tensor("value_3_dilations_0"), val = tensor([1, 1])]; + tensor value_3_groups_0 = const()[name = tensor("value_3_groups_0"), val = tensor(1)]; + tensor layers_0_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119741632)))]; + tensor layers_0_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_0_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121838848)))]; + tensor value_3_cast_fp16 = conv(bias = layers_0_encoder_attn_v_proj_bias_to_fp16, dilations = value_3_dilations_0, groups = value_3_groups_0, pad = value_3_pad_0, pad_type = value_3_pad_type_0, strides = value_3_strides_0, weight = layers_0_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_3_cast_fp16")]; + tensor var_295 = const()[name = tensor("op_295"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_3_cast_fp16 = reshape(shape = var_295, x = query_3_cast_fp16)[name = tensor("mh_q_3_cast_fp16")]; + tensor var_297_to_fp16 = const()[name = tensor("op_297_to_fp16"), val = tensor(0x1p-3)]; + tensor var_298_cast_fp16 = mul(x = mh_q_3_cast_fp16, y = var_297_to_fp16)[name = tensor("op_298_cast_fp16")]; + tensor var_301 = const()[name = tensor("op_301"), val = tensor([1, 16, 64, 1500])]; + tensor var_302_cast_fp16 = reshape(shape = var_301, x = key_3_cast_fp16)[name = tensor("op_302_cast_fp16")]; + tensor mh_w_5_transpose_x_0 = const()[name = tensor("mh_w_5_transpose_x_0"), val = tensor(true)]; + tensor mh_w_5_transpose_y_0 = const()[name = tensor("mh_w_5_transpose_y_0"), val = tensor(false)]; + tensor mh_w_5_cast_fp16 = matmul(transpose_x = mh_w_5_transpose_x_0, transpose_y = mh_w_5_transpose_y_0, x = var_298_cast_fp16, y = var_302_cast_fp16)[name = tensor("mh_w_5_cast_fp16")]; + tensor obj_13_cast_fp16 = softmax(axis = var_144, x = mh_w_5_cast_fp16)[name = tensor("obj_13_cast_fp16")]; + tensor var_306 = const()[name = tensor("op_306"), val = tensor([1, 16, 64, 1500])]; + tensor var_307_cast_fp16 = reshape(shape = var_306, x = value_3_cast_fp16)[name = tensor("op_307_cast_fp16")]; + tensor attn_3_transpose_x_0 = const()[name = tensor("attn_3_transpose_x_0"), val = tensor(false)]; + tensor attn_3_transpose_y_0 = const()[name = tensor("attn_3_transpose_y_0"), val = tensor(true)]; + tensor attn_3_cast_fp16 = matmul(transpose_x = attn_3_transpose_x_0, transpose_y = attn_3_transpose_y_0, x = var_307_cast_fp16, y = obj_13_cast_fp16)[name = tensor("attn_3_cast_fp16")]; + tensor var_310 = const()[name = tensor("op_310"), val = tensor([1, 1024, 1, 1])]; + tensor input_3_cast_fp16 = reshape(shape = var_310, x = attn_3_cast_fp16)[name = tensor("input_3_cast_fp16")]; + tensor obj_11_pad_type_0 = const()[name = tensor("obj_11_pad_type_0"), val = tensor("valid")]; + tensor obj_11_strides_0 = const()[name = tensor("obj_11_strides_0"), val = tensor([1, 1])]; + tensor obj_11_pad_0 = const()[name = tensor("obj_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_11_dilations_0 = const()[name = tensor("obj_11_dilations_0"), val = tensor([1, 1])]; + tensor obj_11_groups_0 = const()[name = tensor("obj_11_groups_0"), val = tensor(1)]; + tensor layers_0_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121840960)))]; + tensor layers_0_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_0_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123938176)))]; + tensor obj_11_cast_fp16 = conv(bias = layers_0_encoder_attn_o_proj_bias_to_fp16, dilations = obj_11_dilations_0, groups = obj_11_groups_0, pad = obj_11_pad_0, pad_type = obj_11_pad_type_0, strides = obj_11_strides_0, weight = layers_0_encoder_attn_o_proj_weight_to_fp16, x = input_3_cast_fp16)[name = tensor("obj_11_cast_fp16")]; + tensor inputs_5_cast_fp16 = add(x = inputs_3_cast_fp16, y = obj_11_cast_fp16)[name = tensor("inputs_5_cast_fp16")]; + tensor out_5_axes_0 = const()[name = tensor("out_5_axes_0"), val = tensor([1])]; + tensor var_328_to_fp16 = const()[name = tensor("op_328_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_5_cast_fp16 = layer_norm(axes = out_5_axes_0, epsilon = var_328_to_fp16, x = inputs_5_cast_fp16)[name = tensor("out_5_cast_fp16")]; + tensor input_5_gamma_0_to_fp16 = const()[name = tensor("input_5_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123940288)))]; + tensor input_5_beta_0_to_fp16 = const()[name = tensor("input_5_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123942400)))]; + tensor input_5_epsilon_0_to_fp16 = const()[name = tensor("input_5_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_5_cast_fp16 = batch_norm(beta = input_5_beta_0_to_fp16, epsilon = input_5_epsilon_0_to_fp16, gamma = input_5_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_5_cast_fp16)[name = tensor("input_5_cast_fp16")]; + tensor input_7_pad_type_0 = const()[name = tensor("input_7_pad_type_0"), val = tensor("valid")]; + tensor input_7_strides_0 = const()[name = tensor("input_7_strides_0"), val = tensor([1, 1])]; + tensor input_7_pad_0 = const()[name = tensor("input_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_7_dilations_0 = const()[name = tensor("input_7_dilations_0"), val = tensor([1, 1])]; + tensor input_7_groups_0 = const()[name = tensor("input_7_groups_0"), val = tensor(1)]; + tensor layers_0_fc1_weight_to_fp16 = const()[name = tensor("layers_0_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123944512)))]; + tensor layers_0_fc1_bias_to_fp16 = const()[name = tensor("layers_0_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132333184)))]; + tensor input_7_cast_fp16 = conv(bias = layers_0_fc1_bias_to_fp16, dilations = input_7_dilations_0, groups = input_7_groups_0, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = input_7_strides_0, weight = layers_0_fc1_weight_to_fp16, x = input_5_cast_fp16)[name = tensor("input_7_cast_fp16")]; + tensor input_9_mode_0 = const()[name = tensor("input_9_mode_0"), val = tensor("EXACT")]; + tensor input_9_cast_fp16 = gelu(mode = input_9_mode_0, x = input_7_cast_fp16)[name = tensor("input_9_cast_fp16")]; + tensor hidden_states_3_pad_type_0 = const()[name = tensor("hidden_states_3_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_3_strides_0 = const()[name = tensor("hidden_states_3_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_3_pad_0 = const()[name = tensor("hidden_states_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_3_dilations_0 = const()[name = tensor("hidden_states_3_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_3_groups_0 = const()[name = tensor("hidden_states_3_groups_0"), val = tensor(1)]; + tensor layers_0_fc2_weight_to_fp16 = const()[name = tensor("layers_0_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132341440)))]; + tensor layers_0_fc2_bias_to_fp16 = const()[name = tensor("layers_0_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140730112)))]; + tensor hidden_states_3_cast_fp16 = conv(bias = layers_0_fc2_bias_to_fp16, dilations = hidden_states_3_dilations_0, groups = hidden_states_3_groups_0, pad = hidden_states_3_pad_0, pad_type = hidden_states_3_pad_type_0, strides = hidden_states_3_strides_0, weight = layers_0_fc2_weight_to_fp16, x = input_9_cast_fp16)[name = tensor("hidden_states_3_cast_fp16")]; + tensor inputs_7_cast_fp16 = add(x = inputs_5_cast_fp16, y = hidden_states_3_cast_fp16)[name = tensor("inputs_7_cast_fp16")]; + tensor var_363 = const()[name = tensor("op_363"), val = tensor(3)]; + tensor out_7_axes_0 = const()[name = tensor("out_7_axes_0"), val = tensor([1])]; + tensor var_388_to_fp16 = const()[name = tensor("op_388_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_7_cast_fp16 = layer_norm(axes = out_7_axes_0, epsilon = var_388_to_fp16, x = inputs_7_cast_fp16)[name = tensor("out_7_cast_fp16")]; + tensor obj_15_gamma_0_to_fp16 = const()[name = tensor("obj_15_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140732224)))]; + tensor obj_15_beta_0_to_fp16 = const()[name = tensor("obj_15_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140734336)))]; + tensor obj_15_epsilon_0_to_fp16 = const()[name = tensor("obj_15_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_15_cast_fp16 = batch_norm(beta = obj_15_beta_0_to_fp16, epsilon = obj_15_epsilon_0_to_fp16, gamma = obj_15_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_7_cast_fp16)[name = tensor("obj_15_cast_fp16")]; + tensor query_5_pad_type_0 = const()[name = tensor("query_5_pad_type_0"), val = tensor("valid")]; + tensor query_5_strides_0 = const()[name = tensor("query_5_strides_0"), val = tensor([1, 1])]; + tensor query_5_pad_0 = const()[name = tensor("query_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_5_dilations_0 = const()[name = tensor("query_5_dilations_0"), val = tensor([1, 1])]; + tensor query_5_groups_0 = const()[name = tensor("query_5_groups_0"), val = tensor(1)]; + tensor layers_1_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140736448)))]; + tensor layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142833664)))]; + tensor query_5_cast_fp16 = conv(bias = layers_1_self_attn_q_proj_bias_to_fp16, dilations = query_5_dilations_0, groups = query_5_groups_0, pad = query_5_pad_0, pad_type = query_5_pad_type_0, strides = query_5_strides_0, weight = layers_1_self_attn_q_proj_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor("query_5_cast_fp16")]; + tensor current_key_3_pad_type_0 = const()[name = tensor("current_key_3_pad_type_0"), val = tensor("valid")]; + tensor current_key_3_strides_0 = const()[name = tensor("current_key_3_strides_0"), val = tensor([1, 1])]; + tensor current_key_3_pad_0 = const()[name = tensor("current_key_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_3_dilations_0 = const()[name = tensor("current_key_3_dilations_0"), val = tensor([1, 1])]; + tensor current_key_3_groups_0 = const()[name = tensor("current_key_3_groups_0"), val = tensor(1)]; + tensor layers_1_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142835776)))]; + tensor current_key_3_cast_fp16 = conv(dilations = current_key_3_dilations_0, groups = current_key_3_groups_0, pad = current_key_3_pad_0, pad_type = current_key_3_pad_type_0, strides = current_key_3_strides_0, weight = layers_1_self_attn_k_proj_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor("current_key_3_cast_fp16")]; + tensor current_value_3_pad_type_0 = const()[name = tensor("current_value_3_pad_type_0"), val = tensor("valid")]; + tensor current_value_3_strides_0 = const()[name = tensor("current_value_3_strides_0"), val = tensor([1, 1])]; + tensor current_value_3_pad_0 = const()[name = tensor("current_value_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_3_dilations_0 = const()[name = tensor("current_value_3_dilations_0"), val = tensor([1, 1])]; + tensor current_value_3_groups_0 = const()[name = tensor("current_value_3_groups_0"), val = tensor(1)]; + tensor layers_1_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(144932992)))]; + tensor layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147030208)))]; + tensor current_value_3_cast_fp16 = conv(bias = layers_1_self_attn_v_proj_bias_to_fp16, dilations = current_value_3_dilations_0, groups = current_value_3_groups_0, pad = current_value_3_pad_0, pad_type = current_value_3_pad_type_0, strides = current_value_3_strides_0, weight = layers_1_self_attn_v_proj_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor("current_value_3_cast_fp16")]; + tensor var_427_cast_fp16 = mul(x = var_87_cast_fp16_1, y = var_207_cast_fp16)[name = tensor("op_427_cast_fp16")]; + tensor var_428_cast_fp16 = mul(x = current_key_3_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_428_cast_fp16")]; + tensor key_5_cast_fp16 = add(x = var_427_cast_fp16, y = var_428_cast_fp16)[name = tensor("key_5_cast_fp16")]; + tensor var_431_cast_fp16 = mul(x = var_114_cast_fp16_1, y = var_207_cast_fp16)[name = tensor("op_431_cast_fp16")]; + tensor var_432_cast_fp16 = mul(x = current_value_3_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_432_cast_fp16")]; + tensor value_5_cast_fp16 = add(x = var_431_cast_fp16, y = var_432_cast_fp16)[name = tensor("value_5_cast_fp16")]; + tensor var_436 = const()[name = tensor("op_436"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_5_cast_fp16 = reshape(shape = var_436, x = query_5_cast_fp16)[name = tensor("mh_q_5_cast_fp16")]; + tensor var_438_to_fp16 = const()[name = tensor("op_438_to_fp16"), val = tensor(0x1p-3)]; + tensor var_439_cast_fp16 = mul(x = mh_q_5_cast_fp16, y = var_438_to_fp16)[name = tensor("op_439_cast_fp16")]; + tensor var_442 = const()[name = tensor("op_442"), val = tensor([1, 16, 64, 448])]; + tensor var_443_cast_fp16 = reshape(shape = var_442, x = key_5_cast_fp16)[name = tensor("op_443_cast_fp16")]; + tensor mh_w_7_transpose_x_0 = const()[name = tensor("mh_w_7_transpose_x_0"), val = tensor(true)]; + tensor mh_w_7_transpose_y_0 = const()[name = tensor("mh_w_7_transpose_y_0"), val = tensor(false)]; + tensor mh_w_7_cast_fp16 = matmul(transpose_x = mh_w_7_transpose_x_0, transpose_y = mh_w_7_transpose_y_0, x = var_439_cast_fp16, y = var_443_cast_fp16)[name = tensor("mh_w_7_cast_fp16")]; + tensor mh_w_9_cast_fp16 = add(x = mh_w_7_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_9_cast_fp16")]; + tensor var_451_cast_fp16 = softmax(axis = var_363, x = mh_w_9_cast_fp16)[name = tensor("op_451_cast_fp16")]; + tensor var_452 = const()[name = tensor("op_452"), val = tensor([1, 16, 64, 448])]; + tensor var_453_cast_fp16 = reshape(shape = var_452, x = value_5_cast_fp16)[name = tensor("op_453_cast_fp16")]; + tensor attn_5_transpose_x_0 = const()[name = tensor("attn_5_transpose_x_0"), val = tensor(false)]; + tensor attn_5_transpose_y_0 = const()[name = tensor("attn_5_transpose_y_0"), val = tensor(true)]; + tensor attn_5_cast_fp16 = matmul(transpose_x = attn_5_transpose_x_0, transpose_y = attn_5_transpose_y_0, x = var_453_cast_fp16, y = var_451_cast_fp16)[name = tensor("attn_5_cast_fp16")]; + tensor var_456 = const()[name = tensor("op_456"), val = tensor([1, 1024, 1, 1])]; + tensor input_11_cast_fp16 = reshape(shape = var_456, x = attn_5_cast_fp16)[name = tensor("input_11_cast_fp16")]; + tensor obj_21_pad_type_0 = const()[name = tensor("obj_21_pad_type_0"), val = tensor("valid")]; + tensor obj_21_strides_0 = const()[name = tensor("obj_21_strides_0"), val = tensor([1, 1])]; + tensor obj_21_pad_0 = const()[name = tensor("obj_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_21_dilations_0 = const()[name = tensor("obj_21_dilations_0"), val = tensor([1, 1])]; + tensor obj_21_groups_0 = const()[name = tensor("obj_21_groups_0"), val = tensor(1)]; + tensor layers_1_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147032320)))]; + tensor layers_1_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149129536)))]; + tensor obj_21_cast_fp16 = conv(bias = layers_1_self_attn_o_proj_bias_to_fp16, dilations = obj_21_dilations_0, groups = obj_21_groups_0, pad = obj_21_pad_0, pad_type = obj_21_pad_type_0, strides = obj_21_strides_0, weight = layers_1_self_attn_o_proj_weight_to_fp16, x = input_11_cast_fp16)[name = tensor("obj_21_cast_fp16")]; + tensor inputs_9_cast_fp16 = add(x = inputs_7_cast_fp16, y = obj_21_cast_fp16)[name = tensor("inputs_9_cast_fp16")]; + tensor out_9_axes_0 = const()[name = tensor("out_9_axes_0"), val = tensor([1])]; + tensor var_478_to_fp16 = const()[name = tensor("op_478_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_9_cast_fp16 = layer_norm(axes = out_9_axes_0, epsilon = var_478_to_fp16, x = inputs_9_cast_fp16)[name = tensor("out_9_cast_fp16")]; + tensor obj_23_gamma_0_to_fp16 = const()[name = tensor("obj_23_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149131648)))]; + tensor obj_23_beta_0_to_fp16 = const()[name = tensor("obj_23_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149133760)))]; + tensor obj_23_epsilon_0_to_fp16 = const()[name = tensor("obj_23_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_23_cast_fp16 = batch_norm(beta = obj_23_beta_0_to_fp16, epsilon = obj_23_epsilon_0_to_fp16, gamma = obj_23_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_9_cast_fp16)[name = tensor("obj_23_cast_fp16")]; + tensor query_7_pad_type_0 = const()[name = tensor("query_7_pad_type_0"), val = tensor("valid")]; + tensor query_7_strides_0 = const()[name = tensor("query_7_strides_0"), val = tensor([1, 1])]; + tensor query_7_pad_0 = const()[name = tensor("query_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_7_dilations_0 = const()[name = tensor("query_7_dilations_0"), val = tensor([1, 1])]; + tensor query_7_groups_0 = const()[name = tensor("query_7_groups_0"), val = tensor(1)]; + tensor layers_1_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149135872)))]; + tensor layers_1_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_1_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151233088)))]; + tensor query_7_cast_fp16 = conv(bias = layers_1_encoder_attn_q_proj_bias_to_fp16, dilations = query_7_dilations_0, groups = query_7_groups_0, pad = query_7_pad_0, pad_type = query_7_pad_type_0, strides = query_7_strides_0, weight = layers_1_encoder_attn_q_proj_weight_to_fp16, x = obj_23_cast_fp16)[name = tensor("query_7_cast_fp16")]; + tensor key_7_pad_type_0 = const()[name = tensor("key_7_pad_type_0"), val = tensor("valid")]; + tensor key_7_strides_0 = const()[name = tensor("key_7_strides_0"), val = tensor([1, 1])]; + tensor key_7_pad_0 = const()[name = tensor("key_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_7_dilations_0 = const()[name = tensor("key_7_dilations_0"), val = tensor([1, 1])]; + tensor key_7_groups_0 = const()[name = tensor("key_7_groups_0"), val = tensor(1)]; + tensor layers_1_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151235200)))]; + tensor key_7_cast_fp16 = conv(dilations = key_7_dilations_0, groups = key_7_groups_0, pad = key_7_pad_0, pad_type = key_7_pad_type_0, strides = key_7_strides_0, weight = layers_1_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_7_cast_fp16")]; + tensor value_7_pad_type_0 = const()[name = tensor("value_7_pad_type_0"), val = tensor("valid")]; + tensor value_7_strides_0 = const()[name = tensor("value_7_strides_0"), val = tensor([1, 1])]; + tensor value_7_pad_0 = const()[name = tensor("value_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_7_dilations_0 = const()[name = tensor("value_7_dilations_0"), val = tensor([1, 1])]; + tensor value_7_groups_0 = const()[name = tensor("value_7_groups_0"), val = tensor(1)]; + tensor layers_1_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153332416)))]; + tensor layers_1_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_1_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155429632)))]; + tensor value_7_cast_fp16 = conv(bias = layers_1_encoder_attn_v_proj_bias_to_fp16, dilations = value_7_dilations_0, groups = value_7_groups_0, pad = value_7_pad_0, pad_type = value_7_pad_type_0, strides = value_7_strides_0, weight = layers_1_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_7_cast_fp16")]; + tensor var_514 = const()[name = tensor("op_514"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_7_cast_fp16 = reshape(shape = var_514, x = query_7_cast_fp16)[name = tensor("mh_q_7_cast_fp16")]; + tensor var_516_to_fp16 = const()[name = tensor("op_516_to_fp16"), val = tensor(0x1p-3)]; + tensor var_517_cast_fp16 = mul(x = mh_q_7_cast_fp16, y = var_516_to_fp16)[name = tensor("op_517_cast_fp16")]; + tensor var_520 = const()[name = tensor("op_520"), val = tensor([1, 16, 64, 1500])]; + tensor var_521_cast_fp16 = reshape(shape = var_520, x = key_7_cast_fp16)[name = tensor("op_521_cast_fp16")]; + tensor mh_w_11_transpose_x_0 = const()[name = tensor("mh_w_11_transpose_x_0"), val = tensor(true)]; + tensor mh_w_11_transpose_y_0 = const()[name = tensor("mh_w_11_transpose_y_0"), val = tensor(false)]; + tensor mh_w_11_cast_fp16 = matmul(transpose_x = mh_w_11_transpose_x_0, transpose_y = mh_w_11_transpose_y_0, x = var_517_cast_fp16, y = var_521_cast_fp16)[name = tensor("mh_w_11_cast_fp16")]; + tensor obj_27_cast_fp16 = softmax(axis = var_363, x = mh_w_11_cast_fp16)[name = tensor("obj_27_cast_fp16")]; + tensor var_525 = const()[name = tensor("op_525"), val = tensor([1, 16, 64, 1500])]; + tensor var_526_cast_fp16 = reshape(shape = var_525, x = value_7_cast_fp16)[name = tensor("op_526_cast_fp16")]; + tensor attn_7_transpose_x_0 = const()[name = tensor("attn_7_transpose_x_0"), val = tensor(false)]; + tensor attn_7_transpose_y_0 = const()[name = tensor("attn_7_transpose_y_0"), val = tensor(true)]; + tensor attn_7_cast_fp16 = matmul(transpose_x = attn_7_transpose_x_0, transpose_y = attn_7_transpose_y_0, x = var_526_cast_fp16, y = obj_27_cast_fp16)[name = tensor("attn_7_cast_fp16")]; + tensor var_529 = const()[name = tensor("op_529"), val = tensor([1, 1024, 1, 1])]; + tensor input_13_cast_fp16 = reshape(shape = var_529, x = attn_7_cast_fp16)[name = tensor("input_13_cast_fp16")]; + tensor obj_25_pad_type_0 = const()[name = tensor("obj_25_pad_type_0"), val = tensor("valid")]; + tensor obj_25_strides_0 = const()[name = tensor("obj_25_strides_0"), val = tensor([1, 1])]; + tensor obj_25_pad_0 = const()[name = tensor("obj_25_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_25_dilations_0 = const()[name = tensor("obj_25_dilations_0"), val = tensor([1, 1])]; + tensor obj_25_groups_0 = const()[name = tensor("obj_25_groups_0"), val = tensor(1)]; + tensor layers_1_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155431744)))]; + tensor layers_1_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_1_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(157528960)))]; + tensor obj_25_cast_fp16 = conv(bias = layers_1_encoder_attn_o_proj_bias_to_fp16, dilations = obj_25_dilations_0, groups = obj_25_groups_0, pad = obj_25_pad_0, pad_type = obj_25_pad_type_0, strides = obj_25_strides_0, weight = layers_1_encoder_attn_o_proj_weight_to_fp16, x = input_13_cast_fp16)[name = tensor("obj_25_cast_fp16")]; + tensor inputs_11_cast_fp16 = add(x = inputs_9_cast_fp16, y = obj_25_cast_fp16)[name = tensor("inputs_11_cast_fp16")]; + tensor out_11_axes_0 = const()[name = tensor("out_11_axes_0"), val = tensor([1])]; + tensor var_547_to_fp16 = const()[name = tensor("op_547_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_11_cast_fp16 = layer_norm(axes = out_11_axes_0, epsilon = var_547_to_fp16, x = inputs_11_cast_fp16)[name = tensor("out_11_cast_fp16")]; + tensor input_15_gamma_0_to_fp16 = const()[name = tensor("input_15_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(157531072)))]; + tensor input_15_beta_0_to_fp16 = const()[name = tensor("input_15_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(157533184)))]; + tensor input_15_epsilon_0_to_fp16 = const()[name = tensor("input_15_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_15_cast_fp16 = batch_norm(beta = input_15_beta_0_to_fp16, epsilon = input_15_epsilon_0_to_fp16, gamma = input_15_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_11_cast_fp16)[name = tensor("input_15_cast_fp16")]; + tensor input_17_pad_type_0 = const()[name = tensor("input_17_pad_type_0"), val = tensor("valid")]; + tensor input_17_strides_0 = const()[name = tensor("input_17_strides_0"), val = tensor([1, 1])]; + tensor input_17_pad_0 = const()[name = tensor("input_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_17_dilations_0 = const()[name = tensor("input_17_dilations_0"), val = tensor([1, 1])]; + tensor input_17_groups_0 = const()[name = tensor("input_17_groups_0"), val = tensor(1)]; + tensor layers_1_fc1_weight_to_fp16 = const()[name = tensor("layers_1_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(157535296)))]; + tensor layers_1_fc1_bias_to_fp16 = const()[name = tensor("layers_1_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165923968)))]; + tensor input_17_cast_fp16 = conv(bias = layers_1_fc1_bias_to_fp16, dilations = input_17_dilations_0, groups = input_17_groups_0, pad = input_17_pad_0, pad_type = input_17_pad_type_0, strides = input_17_strides_0, weight = layers_1_fc1_weight_to_fp16, x = input_15_cast_fp16)[name = tensor("input_17_cast_fp16")]; + tensor input_19_mode_0 = const()[name = tensor("input_19_mode_0"), val = tensor("EXACT")]; + tensor input_19_cast_fp16 = gelu(mode = input_19_mode_0, x = input_17_cast_fp16)[name = tensor("input_19_cast_fp16")]; + tensor hidden_states_5_pad_type_0 = const()[name = tensor("hidden_states_5_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_5_strides_0 = const()[name = tensor("hidden_states_5_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_5_pad_0 = const()[name = tensor("hidden_states_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_5_dilations_0 = const()[name = tensor("hidden_states_5_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_5_groups_0 = const()[name = tensor("hidden_states_5_groups_0"), val = tensor(1)]; + tensor layers_1_fc2_weight_to_fp16 = const()[name = tensor("layers_1_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165932224)))]; + tensor layers_1_fc2_bias_to_fp16 = const()[name = tensor("layers_1_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174320896)))]; + tensor hidden_states_5_cast_fp16 = conv(bias = layers_1_fc2_bias_to_fp16, dilations = hidden_states_5_dilations_0, groups = hidden_states_5_groups_0, pad = hidden_states_5_pad_0, pad_type = hidden_states_5_pad_type_0, strides = hidden_states_5_strides_0, weight = layers_1_fc2_weight_to_fp16, x = input_19_cast_fp16)[name = tensor("hidden_states_5_cast_fp16")]; + tensor inputs_13_cast_fp16 = add(x = inputs_11_cast_fp16, y = hidden_states_5_cast_fp16)[name = tensor("inputs_13_cast_fp16")]; + tensor var_582 = const()[name = tensor("op_582"), val = tensor(3)]; + tensor out_13_axes_0 = const()[name = tensor("out_13_axes_0"), val = tensor([1])]; + tensor var_607_to_fp16 = const()[name = tensor("op_607_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_13_cast_fp16 = layer_norm(axes = out_13_axes_0, epsilon = var_607_to_fp16, x = inputs_13_cast_fp16)[name = tensor("out_13_cast_fp16")]; + tensor obj_29_gamma_0_to_fp16 = const()[name = tensor("obj_29_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174323008)))]; + tensor obj_29_beta_0_to_fp16 = const()[name = tensor("obj_29_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174325120)))]; + tensor obj_29_epsilon_0_to_fp16 = const()[name = tensor("obj_29_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_29_cast_fp16 = batch_norm(beta = obj_29_beta_0_to_fp16, epsilon = obj_29_epsilon_0_to_fp16, gamma = obj_29_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_13_cast_fp16)[name = tensor("obj_29_cast_fp16")]; + tensor query_9_pad_type_0 = const()[name = tensor("query_9_pad_type_0"), val = tensor("valid")]; + tensor query_9_strides_0 = const()[name = tensor("query_9_strides_0"), val = tensor([1, 1])]; + tensor query_9_pad_0 = const()[name = tensor("query_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_9_dilations_0 = const()[name = tensor("query_9_dilations_0"), val = tensor([1, 1])]; + tensor query_9_groups_0 = const()[name = tensor("query_9_groups_0"), val = tensor(1)]; + tensor layers_2_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174327232)))]; + tensor layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176424448)))]; + tensor query_9_cast_fp16 = conv(bias = layers_2_self_attn_q_proj_bias_to_fp16, dilations = query_9_dilations_0, groups = query_9_groups_0, pad = query_9_pad_0, pad_type = query_9_pad_type_0, strides = query_9_strides_0, weight = layers_2_self_attn_q_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("query_9_cast_fp16")]; + tensor current_key_5_pad_type_0 = const()[name = tensor("current_key_5_pad_type_0"), val = tensor("valid")]; + tensor current_key_5_strides_0 = const()[name = tensor("current_key_5_strides_0"), val = tensor([1, 1])]; + tensor current_key_5_pad_0 = const()[name = tensor("current_key_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_5_dilations_0 = const()[name = tensor("current_key_5_dilations_0"), val = tensor([1, 1])]; + tensor current_key_5_groups_0 = const()[name = tensor("current_key_5_groups_0"), val = tensor(1)]; + tensor layers_2_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176426560)))]; + tensor current_key_5_cast_fp16 = conv(dilations = current_key_5_dilations_0, groups = current_key_5_groups_0, pad = current_key_5_pad_0, pad_type = current_key_5_pad_type_0, strides = current_key_5_strides_0, weight = layers_2_self_attn_k_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("current_key_5_cast_fp16")]; + tensor current_value_5_pad_type_0 = const()[name = tensor("current_value_5_pad_type_0"), val = tensor("valid")]; + tensor current_value_5_strides_0 = const()[name = tensor("current_value_5_strides_0"), val = tensor([1, 1])]; + tensor current_value_5_pad_0 = const()[name = tensor("current_value_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_5_dilations_0 = const()[name = tensor("current_value_5_dilations_0"), val = tensor([1, 1])]; + tensor current_value_5_groups_0 = const()[name = tensor("current_value_5_groups_0"), val = tensor(1)]; + tensor layers_2_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178523776)))]; + tensor layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180620992)))]; + tensor current_value_5_cast_fp16 = conv(bias = layers_2_self_attn_v_proj_bias_to_fp16, dilations = current_value_5_dilations_0, groups = current_value_5_groups_0, pad = current_value_5_pad_0, pad_type = current_value_5_pad_type_0, strides = current_value_5_strides_0, weight = layers_2_self_attn_v_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("current_value_5_cast_fp16")]; + tensor var_646_cast_fp16 = mul(x = var_87_cast_fp16_2, y = var_207_cast_fp16)[name = tensor("op_646_cast_fp16")]; + tensor var_647_cast_fp16 = mul(x = current_key_5_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_647_cast_fp16")]; + tensor key_9_cast_fp16 = add(x = var_646_cast_fp16, y = var_647_cast_fp16)[name = tensor("key_9_cast_fp16")]; + tensor var_650_cast_fp16 = mul(x = var_114_cast_fp16_2, y = var_207_cast_fp16)[name = tensor("op_650_cast_fp16")]; + tensor var_651_cast_fp16 = mul(x = current_value_5_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_651_cast_fp16")]; + tensor value_9_cast_fp16 = add(x = var_650_cast_fp16, y = var_651_cast_fp16)[name = tensor("value_9_cast_fp16")]; + tensor var_655 = const()[name = tensor("op_655"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_9_cast_fp16 = reshape(shape = var_655, x = query_9_cast_fp16)[name = tensor("mh_q_9_cast_fp16")]; + tensor var_657_to_fp16 = const()[name = tensor("op_657_to_fp16"), val = tensor(0x1p-3)]; + tensor var_658_cast_fp16 = mul(x = mh_q_9_cast_fp16, y = var_657_to_fp16)[name = tensor("op_658_cast_fp16")]; + tensor var_661 = const()[name = tensor("op_661"), val = tensor([1, 16, 64, 448])]; + tensor var_662_cast_fp16 = reshape(shape = var_661, x = key_9_cast_fp16)[name = tensor("op_662_cast_fp16")]; + tensor mh_w_13_transpose_x_0 = const()[name = tensor("mh_w_13_transpose_x_0"), val = tensor(true)]; + tensor mh_w_13_transpose_y_0 = const()[name = tensor("mh_w_13_transpose_y_0"), val = tensor(false)]; + tensor mh_w_13_cast_fp16 = matmul(transpose_x = mh_w_13_transpose_x_0, transpose_y = mh_w_13_transpose_y_0, x = var_658_cast_fp16, y = var_662_cast_fp16)[name = tensor("mh_w_13_cast_fp16")]; + tensor mh_w_15_cast_fp16 = add(x = mh_w_13_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_15_cast_fp16")]; + tensor var_670_cast_fp16 = softmax(axis = var_582, x = mh_w_15_cast_fp16)[name = tensor("op_670_cast_fp16")]; + tensor var_671 = const()[name = tensor("op_671"), val = tensor([1, 16, 64, 448])]; + tensor var_672_cast_fp16 = reshape(shape = var_671, x = value_9_cast_fp16)[name = tensor("op_672_cast_fp16")]; + tensor attn_9_transpose_x_0 = const()[name = tensor("attn_9_transpose_x_0"), val = tensor(false)]; + tensor attn_9_transpose_y_0 = const()[name = tensor("attn_9_transpose_y_0"), val = tensor(true)]; + tensor attn_9_cast_fp16 = matmul(transpose_x = attn_9_transpose_x_0, transpose_y = attn_9_transpose_y_0, x = var_672_cast_fp16, y = var_670_cast_fp16)[name = tensor("attn_9_cast_fp16")]; + tensor var_675 = const()[name = tensor("op_675"), val = tensor([1, 1024, 1, 1])]; + tensor input_21_cast_fp16 = reshape(shape = var_675, x = attn_9_cast_fp16)[name = tensor("input_21_cast_fp16")]; + tensor obj_35_pad_type_0 = const()[name = tensor("obj_35_pad_type_0"), val = tensor("valid")]; + tensor obj_35_strides_0 = const()[name = tensor("obj_35_strides_0"), val = tensor([1, 1])]; + tensor obj_35_pad_0 = const()[name = tensor("obj_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_35_dilations_0 = const()[name = tensor("obj_35_dilations_0"), val = tensor([1, 1])]; + tensor obj_35_groups_0 = const()[name = tensor("obj_35_groups_0"), val = tensor(1)]; + tensor layers_2_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180623104)))]; + tensor layers_2_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(182720320)))]; + tensor obj_35_cast_fp16 = conv(bias = layers_2_self_attn_o_proj_bias_to_fp16, dilations = obj_35_dilations_0, groups = obj_35_groups_0, pad = obj_35_pad_0, pad_type = obj_35_pad_type_0, strides = obj_35_strides_0, weight = layers_2_self_attn_o_proj_weight_to_fp16, x = input_21_cast_fp16)[name = tensor("obj_35_cast_fp16")]; + tensor inputs_15_cast_fp16 = add(x = inputs_13_cast_fp16, y = obj_35_cast_fp16)[name = tensor("inputs_15_cast_fp16")]; + tensor out_15_axes_0 = const()[name = tensor("out_15_axes_0"), val = tensor([1])]; + tensor var_697_to_fp16 = const()[name = tensor("op_697_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_15_cast_fp16 = layer_norm(axes = out_15_axes_0, epsilon = var_697_to_fp16, x = inputs_15_cast_fp16)[name = tensor("out_15_cast_fp16")]; + tensor obj_37_gamma_0_to_fp16 = const()[name = tensor("obj_37_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(182722432)))]; + tensor obj_37_beta_0_to_fp16 = const()[name = tensor("obj_37_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(182724544)))]; + tensor obj_37_epsilon_0_to_fp16 = const()[name = tensor("obj_37_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_37_cast_fp16 = batch_norm(beta = obj_37_beta_0_to_fp16, epsilon = obj_37_epsilon_0_to_fp16, gamma = obj_37_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_15_cast_fp16)[name = tensor("obj_37_cast_fp16")]; + tensor query_11_pad_type_0 = const()[name = tensor("query_11_pad_type_0"), val = tensor("valid")]; + tensor query_11_strides_0 = const()[name = tensor("query_11_strides_0"), val = tensor([1, 1])]; + tensor query_11_pad_0 = const()[name = tensor("query_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_11_dilations_0 = const()[name = tensor("query_11_dilations_0"), val = tensor([1, 1])]; + tensor query_11_groups_0 = const()[name = tensor("query_11_groups_0"), val = tensor(1)]; + tensor layers_2_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(182726656)))]; + tensor layers_2_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_2_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184823872)))]; + tensor query_11_cast_fp16 = conv(bias = layers_2_encoder_attn_q_proj_bias_to_fp16, dilations = query_11_dilations_0, groups = query_11_groups_0, pad = query_11_pad_0, pad_type = query_11_pad_type_0, strides = query_11_strides_0, weight = layers_2_encoder_attn_q_proj_weight_to_fp16, x = obj_37_cast_fp16)[name = tensor("query_11_cast_fp16")]; + tensor key_11_pad_type_0 = const()[name = tensor("key_11_pad_type_0"), val = tensor("valid")]; + tensor key_11_strides_0 = const()[name = tensor("key_11_strides_0"), val = tensor([1, 1])]; + tensor key_11_pad_0 = const()[name = tensor("key_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_11_dilations_0 = const()[name = tensor("key_11_dilations_0"), val = tensor([1, 1])]; + tensor key_11_groups_0 = const()[name = tensor("key_11_groups_0"), val = tensor(1)]; + tensor layers_2_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184825984)))]; + tensor key_11_cast_fp16 = conv(dilations = key_11_dilations_0, groups = key_11_groups_0, pad = key_11_pad_0, pad_type = key_11_pad_type_0, strides = key_11_strides_0, weight = layers_2_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_11_cast_fp16")]; + tensor value_11_pad_type_0 = const()[name = tensor("value_11_pad_type_0"), val = tensor("valid")]; + tensor value_11_strides_0 = const()[name = tensor("value_11_strides_0"), val = tensor([1, 1])]; + tensor value_11_pad_0 = const()[name = tensor("value_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_11_dilations_0 = const()[name = tensor("value_11_dilations_0"), val = tensor([1, 1])]; + tensor value_11_groups_0 = const()[name = tensor("value_11_groups_0"), val = tensor(1)]; + tensor layers_2_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186923200)))]; + tensor layers_2_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_2_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189020416)))]; + tensor value_11_cast_fp16 = conv(bias = layers_2_encoder_attn_v_proj_bias_to_fp16, dilations = value_11_dilations_0, groups = value_11_groups_0, pad = value_11_pad_0, pad_type = value_11_pad_type_0, strides = value_11_strides_0, weight = layers_2_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_11_cast_fp16")]; + tensor var_733 = const()[name = tensor("op_733"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_11_cast_fp16 = reshape(shape = var_733, x = query_11_cast_fp16)[name = tensor("mh_q_11_cast_fp16")]; + tensor var_735_to_fp16 = const()[name = tensor("op_735_to_fp16"), val = tensor(0x1p-3)]; + tensor var_736_cast_fp16 = mul(x = mh_q_11_cast_fp16, y = var_735_to_fp16)[name = tensor("op_736_cast_fp16")]; + tensor var_739 = const()[name = tensor("op_739"), val = tensor([1, 16, 64, 1500])]; + tensor var_740_cast_fp16 = reshape(shape = var_739, x = key_11_cast_fp16)[name = tensor("op_740_cast_fp16")]; + tensor mh_w_17_transpose_x_0 = const()[name = tensor("mh_w_17_transpose_x_0"), val = tensor(true)]; + tensor mh_w_17_transpose_y_0 = const()[name = tensor("mh_w_17_transpose_y_0"), val = tensor(false)]; + tensor mh_w_17_cast_fp16 = matmul(transpose_x = mh_w_17_transpose_x_0, transpose_y = mh_w_17_transpose_y_0, x = var_736_cast_fp16, y = var_740_cast_fp16)[name = tensor("mh_w_17_cast_fp16")]; + tensor obj_41_cast_fp16 = softmax(axis = var_582, x = mh_w_17_cast_fp16)[name = tensor("obj_41_cast_fp16")]; + tensor var_744 = const()[name = tensor("op_744"), val = tensor([1, 16, 64, 1500])]; + tensor var_745_cast_fp16 = reshape(shape = var_744, x = value_11_cast_fp16)[name = tensor("op_745_cast_fp16")]; + tensor attn_11_transpose_x_0 = const()[name = tensor("attn_11_transpose_x_0"), val = tensor(false)]; + tensor attn_11_transpose_y_0 = const()[name = tensor("attn_11_transpose_y_0"), val = tensor(true)]; + tensor attn_11_cast_fp16 = matmul(transpose_x = attn_11_transpose_x_0, transpose_y = attn_11_transpose_y_0, x = var_745_cast_fp16, y = obj_41_cast_fp16)[name = tensor("attn_11_cast_fp16")]; + tensor var_748 = const()[name = tensor("op_748"), val = tensor([1, 1024, 1, 1])]; + tensor input_23_cast_fp16 = reshape(shape = var_748, x = attn_11_cast_fp16)[name = tensor("input_23_cast_fp16")]; + tensor obj_39_pad_type_0 = const()[name = tensor("obj_39_pad_type_0"), val = tensor("valid")]; + tensor obj_39_strides_0 = const()[name = tensor("obj_39_strides_0"), val = tensor([1, 1])]; + tensor obj_39_pad_0 = const()[name = tensor("obj_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_39_dilations_0 = const()[name = tensor("obj_39_dilations_0"), val = tensor([1, 1])]; + tensor obj_39_groups_0 = const()[name = tensor("obj_39_groups_0"), val = tensor(1)]; + tensor layers_2_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189022528)))]; + tensor layers_2_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_2_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191119744)))]; + tensor obj_39_cast_fp16 = conv(bias = layers_2_encoder_attn_o_proj_bias_to_fp16, dilations = obj_39_dilations_0, groups = obj_39_groups_0, pad = obj_39_pad_0, pad_type = obj_39_pad_type_0, strides = obj_39_strides_0, weight = layers_2_encoder_attn_o_proj_weight_to_fp16, x = input_23_cast_fp16)[name = tensor("obj_39_cast_fp16")]; + tensor inputs_17_cast_fp16 = add(x = inputs_15_cast_fp16, y = obj_39_cast_fp16)[name = tensor("inputs_17_cast_fp16")]; + tensor out_17_axes_0 = const()[name = tensor("out_17_axes_0"), val = tensor([1])]; + tensor var_766_to_fp16 = const()[name = tensor("op_766_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_17_cast_fp16 = layer_norm(axes = out_17_axes_0, epsilon = var_766_to_fp16, x = inputs_17_cast_fp16)[name = tensor("out_17_cast_fp16")]; + tensor input_25_gamma_0_to_fp16 = const()[name = tensor("input_25_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191121856)))]; + tensor input_25_beta_0_to_fp16 = const()[name = tensor("input_25_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191123968)))]; + tensor input_25_epsilon_0_to_fp16 = const()[name = tensor("input_25_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_25_cast_fp16 = batch_norm(beta = input_25_beta_0_to_fp16, epsilon = input_25_epsilon_0_to_fp16, gamma = input_25_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_17_cast_fp16)[name = tensor("input_25_cast_fp16")]; + tensor input_27_pad_type_0 = const()[name = tensor("input_27_pad_type_0"), val = tensor("valid")]; + tensor input_27_strides_0 = const()[name = tensor("input_27_strides_0"), val = tensor([1, 1])]; + tensor input_27_pad_0 = const()[name = tensor("input_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_27_dilations_0 = const()[name = tensor("input_27_dilations_0"), val = tensor([1, 1])]; + tensor input_27_groups_0 = const()[name = tensor("input_27_groups_0"), val = tensor(1)]; + tensor layers_2_fc1_weight_to_fp16 = const()[name = tensor("layers_2_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191126080)))]; + tensor layers_2_fc1_bias_to_fp16 = const()[name = tensor("layers_2_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199514752)))]; + tensor input_27_cast_fp16 = conv(bias = layers_2_fc1_bias_to_fp16, dilations = input_27_dilations_0, groups = input_27_groups_0, pad = input_27_pad_0, pad_type = input_27_pad_type_0, strides = input_27_strides_0, weight = layers_2_fc1_weight_to_fp16, x = input_25_cast_fp16)[name = tensor("input_27_cast_fp16")]; + tensor input_29_mode_0 = const()[name = tensor("input_29_mode_0"), val = tensor("EXACT")]; + tensor input_29_cast_fp16 = gelu(mode = input_29_mode_0, x = input_27_cast_fp16)[name = tensor("input_29_cast_fp16")]; + tensor hidden_states_7_pad_type_0 = const()[name = tensor("hidden_states_7_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_7_strides_0 = const()[name = tensor("hidden_states_7_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_7_pad_0 = const()[name = tensor("hidden_states_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_7_dilations_0 = const()[name = tensor("hidden_states_7_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_7_groups_0 = const()[name = tensor("hidden_states_7_groups_0"), val = tensor(1)]; + tensor layers_2_fc2_weight_to_fp16 = const()[name = tensor("layers_2_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199523008)))]; + tensor layers_2_fc2_bias_to_fp16 = const()[name = tensor("layers_2_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(207911680)))]; + tensor hidden_states_7_cast_fp16 = conv(bias = layers_2_fc2_bias_to_fp16, dilations = hidden_states_7_dilations_0, groups = hidden_states_7_groups_0, pad = hidden_states_7_pad_0, pad_type = hidden_states_7_pad_type_0, strides = hidden_states_7_strides_0, weight = layers_2_fc2_weight_to_fp16, x = input_29_cast_fp16)[name = tensor("hidden_states_7_cast_fp16")]; + tensor inputs_19_cast_fp16 = add(x = inputs_17_cast_fp16, y = hidden_states_7_cast_fp16)[name = tensor("inputs_19_cast_fp16")]; + tensor var_801 = const()[name = tensor("op_801"), val = tensor(3)]; + tensor out_19_axes_0 = const()[name = tensor("out_19_axes_0"), val = tensor([1])]; + tensor var_826_to_fp16 = const()[name = tensor("op_826_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_19_cast_fp16 = layer_norm(axes = out_19_axes_0, epsilon = var_826_to_fp16, x = inputs_19_cast_fp16)[name = tensor("out_19_cast_fp16")]; + tensor obj_43_gamma_0_to_fp16 = const()[name = tensor("obj_43_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(207913792)))]; + tensor obj_43_beta_0_to_fp16 = const()[name = tensor("obj_43_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(207915904)))]; + tensor obj_43_epsilon_0_to_fp16 = const()[name = tensor("obj_43_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_43_cast_fp16 = batch_norm(beta = obj_43_beta_0_to_fp16, epsilon = obj_43_epsilon_0_to_fp16, gamma = obj_43_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_19_cast_fp16)[name = tensor("obj_43_cast_fp16")]; + tensor query_13_pad_type_0 = const()[name = tensor("query_13_pad_type_0"), val = tensor("valid")]; + tensor query_13_strides_0 = const()[name = tensor("query_13_strides_0"), val = tensor([1, 1])]; + tensor query_13_pad_0 = const()[name = tensor("query_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_13_dilations_0 = const()[name = tensor("query_13_dilations_0"), val = tensor([1, 1])]; + tensor query_13_groups_0 = const()[name = tensor("query_13_groups_0"), val = tensor(1)]; + tensor layers_3_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(207918016)))]; + tensor layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210015232)))]; + tensor query_13_cast_fp16 = conv(bias = layers_3_self_attn_q_proj_bias_to_fp16, dilations = query_13_dilations_0, groups = query_13_groups_0, pad = query_13_pad_0, pad_type = query_13_pad_type_0, strides = query_13_strides_0, weight = layers_3_self_attn_q_proj_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor("query_13_cast_fp16")]; + tensor current_key_7_pad_type_0 = const()[name = tensor("current_key_7_pad_type_0"), val = tensor("valid")]; + tensor current_key_7_strides_0 = const()[name = tensor("current_key_7_strides_0"), val = tensor([1, 1])]; + tensor current_key_7_pad_0 = const()[name = tensor("current_key_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_7_dilations_0 = const()[name = tensor("current_key_7_dilations_0"), val = tensor([1, 1])]; + tensor current_key_7_groups_0 = const()[name = tensor("current_key_7_groups_0"), val = tensor(1)]; + tensor layers_3_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210017344)))]; + tensor current_key_7_cast_fp16 = conv(dilations = current_key_7_dilations_0, groups = current_key_7_groups_0, pad = current_key_7_pad_0, pad_type = current_key_7_pad_type_0, strides = current_key_7_strides_0, weight = layers_3_self_attn_k_proj_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor("current_key_7_cast_fp16")]; + tensor current_value_7_pad_type_0 = const()[name = tensor("current_value_7_pad_type_0"), val = tensor("valid")]; + tensor current_value_7_strides_0 = const()[name = tensor("current_value_7_strides_0"), val = tensor([1, 1])]; + tensor current_value_7_pad_0 = const()[name = tensor("current_value_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_7_dilations_0 = const()[name = tensor("current_value_7_dilations_0"), val = tensor([1, 1])]; + tensor current_value_7_groups_0 = const()[name = tensor("current_value_7_groups_0"), val = tensor(1)]; + tensor layers_3_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(212114560)))]; + tensor layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214211776)))]; + tensor current_value_7_cast_fp16 = conv(bias = layers_3_self_attn_v_proj_bias_to_fp16, dilations = current_value_7_dilations_0, groups = current_value_7_groups_0, pad = current_value_7_pad_0, pad_type = current_value_7_pad_type_0, strides = current_value_7_strides_0, weight = layers_3_self_attn_v_proj_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor("current_value_7_cast_fp16")]; + tensor var_865_cast_fp16 = mul(x = var_87_cast_fp16_3, y = var_207_cast_fp16)[name = tensor("op_865_cast_fp16")]; + tensor var_866_cast_fp16 = mul(x = current_key_7_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_866_cast_fp16")]; + tensor key_13_cast_fp16 = add(x = var_865_cast_fp16, y = var_866_cast_fp16)[name = tensor("key_13_cast_fp16")]; + tensor var_869_cast_fp16 = mul(x = var_114_cast_fp16_3, y = var_207_cast_fp16)[name = tensor("op_869_cast_fp16")]; + tensor var_870_cast_fp16 = mul(x = current_value_7_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_870_cast_fp16")]; + tensor value_13_cast_fp16 = add(x = var_869_cast_fp16, y = var_870_cast_fp16)[name = tensor("value_13_cast_fp16")]; + tensor var_874 = const()[name = tensor("op_874"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_13_cast_fp16 = reshape(shape = var_874, x = query_13_cast_fp16)[name = tensor("mh_q_13_cast_fp16")]; + tensor var_876_to_fp16 = const()[name = tensor("op_876_to_fp16"), val = tensor(0x1p-3)]; + tensor var_877_cast_fp16 = mul(x = mh_q_13_cast_fp16, y = var_876_to_fp16)[name = tensor("op_877_cast_fp16")]; + tensor var_880 = const()[name = tensor("op_880"), val = tensor([1, 16, 64, 448])]; + tensor var_881_cast_fp16 = reshape(shape = var_880, x = key_13_cast_fp16)[name = tensor("op_881_cast_fp16")]; + tensor mh_w_19_transpose_x_0 = const()[name = tensor("mh_w_19_transpose_x_0"), val = tensor(true)]; + tensor mh_w_19_transpose_y_0 = const()[name = tensor("mh_w_19_transpose_y_0"), val = tensor(false)]; + tensor mh_w_19_cast_fp16 = matmul(transpose_x = mh_w_19_transpose_x_0, transpose_y = mh_w_19_transpose_y_0, x = var_877_cast_fp16, y = var_881_cast_fp16)[name = tensor("mh_w_19_cast_fp16")]; + tensor mh_w_21_cast_fp16 = add(x = mh_w_19_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_21_cast_fp16")]; + tensor var_889_cast_fp16 = softmax(axis = var_801, x = mh_w_21_cast_fp16)[name = tensor("op_889_cast_fp16")]; + tensor var_890 = const()[name = tensor("op_890"), val = tensor([1, 16, 64, 448])]; + tensor var_891_cast_fp16 = reshape(shape = var_890, x = value_13_cast_fp16)[name = tensor("op_891_cast_fp16")]; + tensor attn_13_transpose_x_0 = const()[name = tensor("attn_13_transpose_x_0"), val = tensor(false)]; + tensor attn_13_transpose_y_0 = const()[name = tensor("attn_13_transpose_y_0"), val = tensor(true)]; + tensor attn_13_cast_fp16 = matmul(transpose_x = attn_13_transpose_x_0, transpose_y = attn_13_transpose_y_0, x = var_891_cast_fp16, y = var_889_cast_fp16)[name = tensor("attn_13_cast_fp16")]; + tensor var_894 = const()[name = tensor("op_894"), val = tensor([1, 1024, 1, 1])]; + tensor input_31_cast_fp16 = reshape(shape = var_894, x = attn_13_cast_fp16)[name = tensor("input_31_cast_fp16")]; + tensor obj_49_pad_type_0 = const()[name = tensor("obj_49_pad_type_0"), val = tensor("valid")]; + tensor obj_49_strides_0 = const()[name = tensor("obj_49_strides_0"), val = tensor([1, 1])]; + tensor obj_49_pad_0 = const()[name = tensor("obj_49_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_49_dilations_0 = const()[name = tensor("obj_49_dilations_0"), val = tensor([1, 1])]; + tensor obj_49_groups_0 = const()[name = tensor("obj_49_groups_0"), val = tensor(1)]; + tensor layers_3_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214213888)))]; + tensor layers_3_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216311104)))]; + tensor obj_49_cast_fp16 = conv(bias = layers_3_self_attn_o_proj_bias_to_fp16, dilations = obj_49_dilations_0, groups = obj_49_groups_0, pad = obj_49_pad_0, pad_type = obj_49_pad_type_0, strides = obj_49_strides_0, weight = layers_3_self_attn_o_proj_weight_to_fp16, x = input_31_cast_fp16)[name = tensor("obj_49_cast_fp16")]; + tensor inputs_21_cast_fp16 = add(x = inputs_19_cast_fp16, y = obj_49_cast_fp16)[name = tensor("inputs_21_cast_fp16")]; + tensor out_21_axes_0 = const()[name = tensor("out_21_axes_0"), val = tensor([1])]; + tensor var_916_to_fp16 = const()[name = tensor("op_916_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_21_cast_fp16 = layer_norm(axes = out_21_axes_0, epsilon = var_916_to_fp16, x = inputs_21_cast_fp16)[name = tensor("out_21_cast_fp16")]; + tensor obj_51_gamma_0_to_fp16 = const()[name = tensor("obj_51_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216313216)))]; + tensor obj_51_beta_0_to_fp16 = const()[name = tensor("obj_51_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216315328)))]; + tensor obj_51_epsilon_0_to_fp16 = const()[name = tensor("obj_51_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_51_cast_fp16 = batch_norm(beta = obj_51_beta_0_to_fp16, epsilon = obj_51_epsilon_0_to_fp16, gamma = obj_51_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_21_cast_fp16)[name = tensor("obj_51_cast_fp16")]; + tensor query_15_pad_type_0 = const()[name = tensor("query_15_pad_type_0"), val = tensor("valid")]; + tensor query_15_strides_0 = const()[name = tensor("query_15_strides_0"), val = tensor([1, 1])]; + tensor query_15_pad_0 = const()[name = tensor("query_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_15_dilations_0 = const()[name = tensor("query_15_dilations_0"), val = tensor([1, 1])]; + tensor query_15_groups_0 = const()[name = tensor("query_15_groups_0"), val = tensor(1)]; + tensor layers_3_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216317440)))]; + tensor layers_3_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_3_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(218414656)))]; + tensor query_15_cast_fp16 = conv(bias = layers_3_encoder_attn_q_proj_bias_to_fp16, dilations = query_15_dilations_0, groups = query_15_groups_0, pad = query_15_pad_0, pad_type = query_15_pad_type_0, strides = query_15_strides_0, weight = layers_3_encoder_attn_q_proj_weight_to_fp16, x = obj_51_cast_fp16)[name = tensor("query_15_cast_fp16")]; + tensor key_15_pad_type_0 = const()[name = tensor("key_15_pad_type_0"), val = tensor("valid")]; + tensor key_15_strides_0 = const()[name = tensor("key_15_strides_0"), val = tensor([1, 1])]; + tensor key_15_pad_0 = const()[name = tensor("key_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_15_dilations_0 = const()[name = tensor("key_15_dilations_0"), val = tensor([1, 1])]; + tensor key_15_groups_0 = const()[name = tensor("key_15_groups_0"), val = tensor(1)]; + tensor layers_3_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(218416768)))]; + tensor key_15_cast_fp16 = conv(dilations = key_15_dilations_0, groups = key_15_groups_0, pad = key_15_pad_0, pad_type = key_15_pad_type_0, strides = key_15_strides_0, weight = layers_3_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_15_cast_fp16")]; + tensor value_15_pad_type_0 = const()[name = tensor("value_15_pad_type_0"), val = tensor("valid")]; + tensor value_15_strides_0 = const()[name = tensor("value_15_strides_0"), val = tensor([1, 1])]; + tensor value_15_pad_0 = const()[name = tensor("value_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_15_dilations_0 = const()[name = tensor("value_15_dilations_0"), val = tensor([1, 1])]; + tensor value_15_groups_0 = const()[name = tensor("value_15_groups_0"), val = tensor(1)]; + tensor layers_3_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(220513984)))]; + tensor layers_3_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_3_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222611200)))]; + tensor value_15_cast_fp16 = conv(bias = layers_3_encoder_attn_v_proj_bias_to_fp16, dilations = value_15_dilations_0, groups = value_15_groups_0, pad = value_15_pad_0, pad_type = value_15_pad_type_0, strides = value_15_strides_0, weight = layers_3_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_15_cast_fp16")]; + tensor var_952 = const()[name = tensor("op_952"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_15_cast_fp16 = reshape(shape = var_952, x = query_15_cast_fp16)[name = tensor("mh_q_15_cast_fp16")]; + tensor var_954_to_fp16 = const()[name = tensor("op_954_to_fp16"), val = tensor(0x1p-3)]; + tensor var_955_cast_fp16 = mul(x = mh_q_15_cast_fp16, y = var_954_to_fp16)[name = tensor("op_955_cast_fp16")]; + tensor var_958 = const()[name = tensor("op_958"), val = tensor([1, 16, 64, 1500])]; + tensor var_959_cast_fp16 = reshape(shape = var_958, x = key_15_cast_fp16)[name = tensor("op_959_cast_fp16")]; + tensor mh_w_23_transpose_x_0 = const()[name = tensor("mh_w_23_transpose_x_0"), val = tensor(true)]; + tensor mh_w_23_transpose_y_0 = const()[name = tensor("mh_w_23_transpose_y_0"), val = tensor(false)]; + tensor mh_w_23_cast_fp16 = matmul(transpose_x = mh_w_23_transpose_x_0, transpose_y = mh_w_23_transpose_y_0, x = var_955_cast_fp16, y = var_959_cast_fp16)[name = tensor("mh_w_23_cast_fp16")]; + tensor obj_55_cast_fp16 = softmax(axis = var_801, x = mh_w_23_cast_fp16)[name = tensor("obj_55_cast_fp16")]; + tensor var_963 = const()[name = tensor("op_963"), val = tensor([1, 16, 64, 1500])]; + tensor var_964_cast_fp16 = reshape(shape = var_963, x = value_15_cast_fp16)[name = tensor("op_964_cast_fp16")]; + tensor attn_15_transpose_x_0 = const()[name = tensor("attn_15_transpose_x_0"), val = tensor(false)]; + tensor attn_15_transpose_y_0 = const()[name = tensor("attn_15_transpose_y_0"), val = tensor(true)]; + tensor attn_15_cast_fp16 = matmul(transpose_x = attn_15_transpose_x_0, transpose_y = attn_15_transpose_y_0, x = var_964_cast_fp16, y = obj_55_cast_fp16)[name = tensor("attn_15_cast_fp16")]; + tensor var_967 = const()[name = tensor("op_967"), val = tensor([1, 1024, 1, 1])]; + tensor input_33_cast_fp16 = reshape(shape = var_967, x = attn_15_cast_fp16)[name = tensor("input_33_cast_fp16")]; + tensor obj_53_pad_type_0 = const()[name = tensor("obj_53_pad_type_0"), val = tensor("valid")]; + tensor obj_53_strides_0 = const()[name = tensor("obj_53_strides_0"), val = tensor([1, 1])]; + tensor obj_53_pad_0 = const()[name = tensor("obj_53_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_53_dilations_0 = const()[name = tensor("obj_53_dilations_0"), val = tensor([1, 1])]; + tensor obj_53_groups_0 = const()[name = tensor("obj_53_groups_0"), val = tensor(1)]; + tensor layers_3_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222613312)))]; + tensor layers_3_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_3_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(224710528)))]; + tensor obj_53_cast_fp16 = conv(bias = layers_3_encoder_attn_o_proj_bias_to_fp16, dilations = obj_53_dilations_0, groups = obj_53_groups_0, pad = obj_53_pad_0, pad_type = obj_53_pad_type_0, strides = obj_53_strides_0, weight = layers_3_encoder_attn_o_proj_weight_to_fp16, x = input_33_cast_fp16)[name = tensor("obj_53_cast_fp16")]; + tensor inputs_23_cast_fp16 = add(x = inputs_21_cast_fp16, y = obj_53_cast_fp16)[name = tensor("inputs_23_cast_fp16")]; + tensor out_23_axes_0 = const()[name = tensor("out_23_axes_0"), val = tensor([1])]; + tensor var_985_to_fp16 = const()[name = tensor("op_985_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_23_cast_fp16 = layer_norm(axes = out_23_axes_0, epsilon = var_985_to_fp16, x = inputs_23_cast_fp16)[name = tensor("out_23_cast_fp16")]; + tensor input_35_gamma_0_to_fp16 = const()[name = tensor("input_35_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(224712640)))]; + tensor input_35_beta_0_to_fp16 = const()[name = tensor("input_35_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(224714752)))]; + tensor input_35_epsilon_0_to_fp16 = const()[name = tensor("input_35_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_35_cast_fp16 = batch_norm(beta = input_35_beta_0_to_fp16, epsilon = input_35_epsilon_0_to_fp16, gamma = input_35_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_23_cast_fp16)[name = tensor("input_35_cast_fp16")]; + tensor input_37_pad_type_0 = const()[name = tensor("input_37_pad_type_0"), val = tensor("valid")]; + tensor input_37_strides_0 = const()[name = tensor("input_37_strides_0"), val = tensor([1, 1])]; + tensor input_37_pad_0 = const()[name = tensor("input_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_37_dilations_0 = const()[name = tensor("input_37_dilations_0"), val = tensor([1, 1])]; + tensor input_37_groups_0 = const()[name = tensor("input_37_groups_0"), val = tensor(1)]; + tensor layers_3_fc1_weight_to_fp16 = const()[name = tensor("layers_3_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(224716864)))]; + tensor layers_3_fc1_bias_to_fp16 = const()[name = tensor("layers_3_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233105536)))]; + tensor input_37_cast_fp16 = conv(bias = layers_3_fc1_bias_to_fp16, dilations = input_37_dilations_0, groups = input_37_groups_0, pad = input_37_pad_0, pad_type = input_37_pad_type_0, strides = input_37_strides_0, weight = layers_3_fc1_weight_to_fp16, x = input_35_cast_fp16)[name = tensor("input_37_cast_fp16")]; + tensor input_39_mode_0 = const()[name = tensor("input_39_mode_0"), val = tensor("EXACT")]; + tensor input_39_cast_fp16 = gelu(mode = input_39_mode_0, x = input_37_cast_fp16)[name = tensor("input_39_cast_fp16")]; + tensor hidden_states_9_pad_type_0 = const()[name = tensor("hidden_states_9_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_9_strides_0 = const()[name = tensor("hidden_states_9_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_9_pad_0 = const()[name = tensor("hidden_states_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_9_dilations_0 = const()[name = tensor("hidden_states_9_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_9_groups_0 = const()[name = tensor("hidden_states_9_groups_0"), val = tensor(1)]; + tensor layers_3_fc2_weight_to_fp16 = const()[name = tensor("layers_3_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233113792)))]; + tensor layers_3_fc2_bias_to_fp16 = const()[name = tensor("layers_3_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241502464)))]; + tensor hidden_states_9_cast_fp16 = conv(bias = layers_3_fc2_bias_to_fp16, dilations = hidden_states_9_dilations_0, groups = hidden_states_9_groups_0, pad = hidden_states_9_pad_0, pad_type = hidden_states_9_pad_type_0, strides = hidden_states_9_strides_0, weight = layers_3_fc2_weight_to_fp16, x = input_39_cast_fp16)[name = tensor("hidden_states_9_cast_fp16")]; + tensor inputs_25_cast_fp16 = add(x = inputs_23_cast_fp16, y = hidden_states_9_cast_fp16)[name = tensor("inputs_25_cast_fp16")]; + tensor var_1020 = const()[name = tensor("op_1020"), val = tensor(3)]; + tensor out_25_axes_0 = const()[name = tensor("out_25_axes_0"), val = tensor([1])]; + tensor var_1045_to_fp16 = const()[name = tensor("op_1045_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_25_cast_fp16 = layer_norm(axes = out_25_axes_0, epsilon = var_1045_to_fp16, x = inputs_25_cast_fp16)[name = tensor("out_25_cast_fp16")]; + tensor obj_57_gamma_0_to_fp16 = const()[name = tensor("obj_57_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241504576)))]; + tensor obj_57_beta_0_to_fp16 = const()[name = tensor("obj_57_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241506688)))]; + tensor obj_57_epsilon_0_to_fp16 = const()[name = tensor("obj_57_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_57_cast_fp16 = batch_norm(beta = obj_57_beta_0_to_fp16, epsilon = obj_57_epsilon_0_to_fp16, gamma = obj_57_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_25_cast_fp16)[name = tensor("obj_57_cast_fp16")]; + tensor query_17_pad_type_0 = const()[name = tensor("query_17_pad_type_0"), val = tensor("valid")]; + tensor query_17_strides_0 = const()[name = tensor("query_17_strides_0"), val = tensor([1, 1])]; + tensor query_17_pad_0 = const()[name = tensor("query_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_17_dilations_0 = const()[name = tensor("query_17_dilations_0"), val = tensor([1, 1])]; + tensor query_17_groups_0 = const()[name = tensor("query_17_groups_0"), val = tensor(1)]; + tensor layers_4_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241508800)))]; + tensor layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(243606016)))]; + tensor query_17_cast_fp16 = conv(bias = layers_4_self_attn_q_proj_bias_to_fp16, dilations = query_17_dilations_0, groups = query_17_groups_0, pad = query_17_pad_0, pad_type = query_17_pad_type_0, strides = query_17_strides_0, weight = layers_4_self_attn_q_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("query_17_cast_fp16")]; + tensor current_key_9_pad_type_0 = const()[name = tensor("current_key_9_pad_type_0"), val = tensor("valid")]; + tensor current_key_9_strides_0 = const()[name = tensor("current_key_9_strides_0"), val = tensor([1, 1])]; + tensor current_key_9_pad_0 = const()[name = tensor("current_key_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_9_dilations_0 = const()[name = tensor("current_key_9_dilations_0"), val = tensor([1, 1])]; + tensor current_key_9_groups_0 = const()[name = tensor("current_key_9_groups_0"), val = tensor(1)]; + tensor layers_4_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(243608128)))]; + tensor current_key_9_cast_fp16 = conv(dilations = current_key_9_dilations_0, groups = current_key_9_groups_0, pad = current_key_9_pad_0, pad_type = current_key_9_pad_type_0, strides = current_key_9_strides_0, weight = layers_4_self_attn_k_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("current_key_9_cast_fp16")]; + tensor current_value_9_pad_type_0 = const()[name = tensor("current_value_9_pad_type_0"), val = tensor("valid")]; + tensor current_value_9_strides_0 = const()[name = tensor("current_value_9_strides_0"), val = tensor([1, 1])]; + tensor current_value_9_pad_0 = const()[name = tensor("current_value_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_9_dilations_0 = const()[name = tensor("current_value_9_dilations_0"), val = tensor([1, 1])]; + tensor current_value_9_groups_0 = const()[name = tensor("current_value_9_groups_0"), val = tensor(1)]; + tensor layers_4_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(245705344)))]; + tensor layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(247802560)))]; + tensor current_value_9_cast_fp16 = conv(bias = layers_4_self_attn_v_proj_bias_to_fp16, dilations = current_value_9_dilations_0, groups = current_value_9_groups_0, pad = current_value_9_pad_0, pad_type = current_value_9_pad_type_0, strides = current_value_9_strides_0, weight = layers_4_self_attn_v_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("current_value_9_cast_fp16")]; + tensor var_1084_cast_fp16 = mul(x = var_87_cast_fp16_4, y = var_207_cast_fp16)[name = tensor("op_1084_cast_fp16")]; + tensor var_1085_cast_fp16 = mul(x = current_key_9_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_1085_cast_fp16")]; + tensor key_17_cast_fp16 = add(x = var_1084_cast_fp16, y = var_1085_cast_fp16)[name = tensor("key_17_cast_fp16")]; + tensor var_1088_cast_fp16 = mul(x = var_114_cast_fp16_4, y = var_207_cast_fp16)[name = tensor("op_1088_cast_fp16")]; + tensor var_1089_cast_fp16 = mul(x = current_value_9_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_1089_cast_fp16")]; + tensor value_17_cast_fp16 = add(x = var_1088_cast_fp16, y = var_1089_cast_fp16)[name = tensor("value_17_cast_fp16")]; + tensor var_1093 = const()[name = tensor("op_1093"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_17_cast_fp16 = reshape(shape = var_1093, x = query_17_cast_fp16)[name = tensor("mh_q_17_cast_fp16")]; + tensor var_1095_to_fp16 = const()[name = tensor("op_1095_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1096_cast_fp16 = mul(x = mh_q_17_cast_fp16, y = var_1095_to_fp16)[name = tensor("op_1096_cast_fp16")]; + tensor var_1099 = const()[name = tensor("op_1099"), val = tensor([1, 16, 64, 448])]; + tensor var_1100_cast_fp16 = reshape(shape = var_1099, x = key_17_cast_fp16)[name = tensor("op_1100_cast_fp16")]; + tensor mh_w_25_transpose_x_0 = const()[name = tensor("mh_w_25_transpose_x_0"), val = tensor(true)]; + tensor mh_w_25_transpose_y_0 = const()[name = tensor("mh_w_25_transpose_y_0"), val = tensor(false)]; + tensor mh_w_25_cast_fp16 = matmul(transpose_x = mh_w_25_transpose_x_0, transpose_y = mh_w_25_transpose_y_0, x = var_1096_cast_fp16, y = var_1100_cast_fp16)[name = tensor("mh_w_25_cast_fp16")]; + tensor mh_w_27_cast_fp16 = add(x = mh_w_25_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_27_cast_fp16")]; + tensor var_1108_cast_fp16 = softmax(axis = var_1020, x = mh_w_27_cast_fp16)[name = tensor("op_1108_cast_fp16")]; + tensor var_1109 = const()[name = tensor("op_1109"), val = tensor([1, 16, 64, 448])]; + tensor var_1110_cast_fp16 = reshape(shape = var_1109, x = value_17_cast_fp16)[name = tensor("op_1110_cast_fp16")]; + tensor attn_17_transpose_x_0 = const()[name = tensor("attn_17_transpose_x_0"), val = tensor(false)]; + tensor attn_17_transpose_y_0 = const()[name = tensor("attn_17_transpose_y_0"), val = tensor(true)]; + tensor attn_17_cast_fp16 = matmul(transpose_x = attn_17_transpose_x_0, transpose_y = attn_17_transpose_y_0, x = var_1110_cast_fp16, y = var_1108_cast_fp16)[name = tensor("attn_17_cast_fp16")]; + tensor var_1113 = const()[name = tensor("op_1113"), val = tensor([1, 1024, 1, 1])]; + tensor input_41_cast_fp16 = reshape(shape = var_1113, x = attn_17_cast_fp16)[name = tensor("input_41_cast_fp16")]; + tensor obj_63_pad_type_0 = const()[name = tensor("obj_63_pad_type_0"), val = tensor("valid")]; + tensor obj_63_strides_0 = const()[name = tensor("obj_63_strides_0"), val = tensor([1, 1])]; + tensor obj_63_pad_0 = const()[name = tensor("obj_63_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_63_dilations_0 = const()[name = tensor("obj_63_dilations_0"), val = tensor([1, 1])]; + tensor obj_63_groups_0 = const()[name = tensor("obj_63_groups_0"), val = tensor(1)]; + tensor layers_4_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(247804672)))]; + tensor layers_4_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249901888)))]; + tensor obj_63_cast_fp16 = conv(bias = layers_4_self_attn_o_proj_bias_to_fp16, dilations = obj_63_dilations_0, groups = obj_63_groups_0, pad = obj_63_pad_0, pad_type = obj_63_pad_type_0, strides = obj_63_strides_0, weight = layers_4_self_attn_o_proj_weight_to_fp16, x = input_41_cast_fp16)[name = tensor("obj_63_cast_fp16")]; + tensor inputs_27_cast_fp16 = add(x = inputs_25_cast_fp16, y = obj_63_cast_fp16)[name = tensor("inputs_27_cast_fp16")]; + tensor out_27_axes_0 = const()[name = tensor("out_27_axes_0"), val = tensor([1])]; + tensor var_1135_to_fp16 = const()[name = tensor("op_1135_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_27_cast_fp16 = layer_norm(axes = out_27_axes_0, epsilon = var_1135_to_fp16, x = inputs_27_cast_fp16)[name = tensor("out_27_cast_fp16")]; + tensor obj_65_gamma_0_to_fp16 = const()[name = tensor("obj_65_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249904000)))]; + tensor obj_65_beta_0_to_fp16 = const()[name = tensor("obj_65_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249906112)))]; + tensor obj_65_epsilon_0_to_fp16 = const()[name = tensor("obj_65_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_65_cast_fp16 = batch_norm(beta = obj_65_beta_0_to_fp16, epsilon = obj_65_epsilon_0_to_fp16, gamma = obj_65_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_27_cast_fp16)[name = tensor("obj_65_cast_fp16")]; + tensor query_19_pad_type_0 = const()[name = tensor("query_19_pad_type_0"), val = tensor("valid")]; + tensor query_19_strides_0 = const()[name = tensor("query_19_strides_0"), val = tensor([1, 1])]; + tensor query_19_pad_0 = const()[name = tensor("query_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_19_dilations_0 = const()[name = tensor("query_19_dilations_0"), val = tensor([1, 1])]; + tensor query_19_groups_0 = const()[name = tensor("query_19_groups_0"), val = tensor(1)]; + tensor layers_4_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249908224)))]; + tensor layers_4_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_4_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252005440)))]; + tensor query_19_cast_fp16 = conv(bias = layers_4_encoder_attn_q_proj_bias_to_fp16, dilations = query_19_dilations_0, groups = query_19_groups_0, pad = query_19_pad_0, pad_type = query_19_pad_type_0, strides = query_19_strides_0, weight = layers_4_encoder_attn_q_proj_weight_to_fp16, x = obj_65_cast_fp16)[name = tensor("query_19_cast_fp16")]; + tensor key_19_pad_type_0 = const()[name = tensor("key_19_pad_type_0"), val = tensor("valid")]; + tensor key_19_strides_0 = const()[name = tensor("key_19_strides_0"), val = tensor([1, 1])]; + tensor key_19_pad_0 = const()[name = tensor("key_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_19_dilations_0 = const()[name = tensor("key_19_dilations_0"), val = tensor([1, 1])]; + tensor key_19_groups_0 = const()[name = tensor("key_19_groups_0"), val = tensor(1)]; + tensor layers_4_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252007552)))]; + tensor key_19_cast_fp16 = conv(dilations = key_19_dilations_0, groups = key_19_groups_0, pad = key_19_pad_0, pad_type = key_19_pad_type_0, strides = key_19_strides_0, weight = layers_4_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_19_cast_fp16")]; + tensor value_19_pad_type_0 = const()[name = tensor("value_19_pad_type_0"), val = tensor("valid")]; + tensor value_19_strides_0 = const()[name = tensor("value_19_strides_0"), val = tensor([1, 1])]; + tensor value_19_pad_0 = const()[name = tensor("value_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_19_dilations_0 = const()[name = tensor("value_19_dilations_0"), val = tensor([1, 1])]; + tensor value_19_groups_0 = const()[name = tensor("value_19_groups_0"), val = tensor(1)]; + tensor layers_4_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254104768)))]; + tensor layers_4_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_4_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(256201984)))]; + tensor value_19_cast_fp16 = conv(bias = layers_4_encoder_attn_v_proj_bias_to_fp16, dilations = value_19_dilations_0, groups = value_19_groups_0, pad = value_19_pad_0, pad_type = value_19_pad_type_0, strides = value_19_strides_0, weight = layers_4_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_19_cast_fp16")]; + tensor var_1171 = const()[name = tensor("op_1171"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_19_cast_fp16 = reshape(shape = var_1171, x = query_19_cast_fp16)[name = tensor("mh_q_19_cast_fp16")]; + tensor var_1173_to_fp16 = const()[name = tensor("op_1173_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1174_cast_fp16 = mul(x = mh_q_19_cast_fp16, y = var_1173_to_fp16)[name = tensor("op_1174_cast_fp16")]; + tensor var_1177 = const()[name = tensor("op_1177"), val = tensor([1, 16, 64, 1500])]; + tensor var_1178_cast_fp16 = reshape(shape = var_1177, x = key_19_cast_fp16)[name = tensor("op_1178_cast_fp16")]; + tensor mh_w_29_transpose_x_0 = const()[name = tensor("mh_w_29_transpose_x_0"), val = tensor(true)]; + tensor mh_w_29_transpose_y_0 = const()[name = tensor("mh_w_29_transpose_y_0"), val = tensor(false)]; + tensor mh_w_29_cast_fp16 = matmul(transpose_x = mh_w_29_transpose_x_0, transpose_y = mh_w_29_transpose_y_0, x = var_1174_cast_fp16, y = var_1178_cast_fp16)[name = tensor("mh_w_29_cast_fp16")]; + tensor obj_69_cast_fp16 = softmax(axis = var_1020, x = mh_w_29_cast_fp16)[name = tensor("obj_69_cast_fp16")]; + tensor var_1182 = const()[name = tensor("op_1182"), val = tensor([1, 16, 64, 1500])]; + tensor var_1183_cast_fp16 = reshape(shape = var_1182, x = value_19_cast_fp16)[name = tensor("op_1183_cast_fp16")]; + tensor attn_19_transpose_x_0 = const()[name = tensor("attn_19_transpose_x_0"), val = tensor(false)]; + tensor attn_19_transpose_y_0 = const()[name = tensor("attn_19_transpose_y_0"), val = tensor(true)]; + tensor attn_19_cast_fp16 = matmul(transpose_x = attn_19_transpose_x_0, transpose_y = attn_19_transpose_y_0, x = var_1183_cast_fp16, y = obj_69_cast_fp16)[name = tensor("attn_19_cast_fp16")]; + tensor var_1186 = const()[name = tensor("op_1186"), val = tensor([1, 1024, 1, 1])]; + tensor input_43_cast_fp16 = reshape(shape = var_1186, x = attn_19_cast_fp16)[name = tensor("input_43_cast_fp16")]; + tensor obj_67_pad_type_0 = const()[name = tensor("obj_67_pad_type_0"), val = tensor("valid")]; + tensor obj_67_strides_0 = const()[name = tensor("obj_67_strides_0"), val = tensor([1, 1])]; + tensor obj_67_pad_0 = const()[name = tensor("obj_67_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_67_dilations_0 = const()[name = tensor("obj_67_dilations_0"), val = tensor([1, 1])]; + tensor obj_67_groups_0 = const()[name = tensor("obj_67_groups_0"), val = tensor(1)]; + tensor layers_4_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(256204096)))]; + tensor layers_4_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_4_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(258301312)))]; + tensor obj_67_cast_fp16 = conv(bias = layers_4_encoder_attn_o_proj_bias_to_fp16, dilations = obj_67_dilations_0, groups = obj_67_groups_0, pad = obj_67_pad_0, pad_type = obj_67_pad_type_0, strides = obj_67_strides_0, weight = layers_4_encoder_attn_o_proj_weight_to_fp16, x = input_43_cast_fp16)[name = tensor("obj_67_cast_fp16")]; + tensor inputs_29_cast_fp16 = add(x = inputs_27_cast_fp16, y = obj_67_cast_fp16)[name = tensor("inputs_29_cast_fp16")]; + tensor out_29_axes_0 = const()[name = tensor("out_29_axes_0"), val = tensor([1])]; + tensor var_1204_to_fp16 = const()[name = tensor("op_1204_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_29_cast_fp16 = layer_norm(axes = out_29_axes_0, epsilon = var_1204_to_fp16, x = inputs_29_cast_fp16)[name = tensor("out_29_cast_fp16")]; + tensor input_45_gamma_0_to_fp16 = const()[name = tensor("input_45_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(258303424)))]; + tensor input_45_beta_0_to_fp16 = const()[name = tensor("input_45_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(258305536)))]; + tensor input_45_epsilon_0_to_fp16 = const()[name = tensor("input_45_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_45_cast_fp16 = batch_norm(beta = input_45_beta_0_to_fp16, epsilon = input_45_epsilon_0_to_fp16, gamma = input_45_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_29_cast_fp16)[name = tensor("input_45_cast_fp16")]; + tensor input_47_pad_type_0 = const()[name = tensor("input_47_pad_type_0"), val = tensor("valid")]; + tensor input_47_strides_0 = const()[name = tensor("input_47_strides_0"), val = tensor([1, 1])]; + tensor input_47_pad_0 = const()[name = tensor("input_47_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_47_dilations_0 = const()[name = tensor("input_47_dilations_0"), val = tensor([1, 1])]; + tensor input_47_groups_0 = const()[name = tensor("input_47_groups_0"), val = tensor(1)]; + tensor layers_4_fc1_weight_to_fp16 = const()[name = tensor("layers_4_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(258307648)))]; + tensor layers_4_fc1_bias_to_fp16 = const()[name = tensor("layers_4_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(266696320)))]; + tensor input_47_cast_fp16 = conv(bias = layers_4_fc1_bias_to_fp16, dilations = input_47_dilations_0, groups = input_47_groups_0, pad = input_47_pad_0, pad_type = input_47_pad_type_0, strides = input_47_strides_0, weight = layers_4_fc1_weight_to_fp16, x = input_45_cast_fp16)[name = tensor("input_47_cast_fp16")]; + tensor input_49_mode_0 = const()[name = tensor("input_49_mode_0"), val = tensor("EXACT")]; + tensor input_49_cast_fp16 = gelu(mode = input_49_mode_0, x = input_47_cast_fp16)[name = tensor("input_49_cast_fp16")]; + tensor hidden_states_11_pad_type_0 = const()[name = tensor("hidden_states_11_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_11_strides_0 = const()[name = tensor("hidden_states_11_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_11_pad_0 = const()[name = tensor("hidden_states_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_11_dilations_0 = const()[name = tensor("hidden_states_11_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_11_groups_0 = const()[name = tensor("hidden_states_11_groups_0"), val = tensor(1)]; + tensor layers_4_fc2_weight_to_fp16 = const()[name = tensor("layers_4_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(266704576)))]; + tensor layers_4_fc2_bias_to_fp16 = const()[name = tensor("layers_4_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(275093248)))]; + tensor hidden_states_11_cast_fp16 = conv(bias = layers_4_fc2_bias_to_fp16, dilations = hidden_states_11_dilations_0, groups = hidden_states_11_groups_0, pad = hidden_states_11_pad_0, pad_type = hidden_states_11_pad_type_0, strides = hidden_states_11_strides_0, weight = layers_4_fc2_weight_to_fp16, x = input_49_cast_fp16)[name = tensor("hidden_states_11_cast_fp16")]; + tensor inputs_31_cast_fp16 = add(x = inputs_29_cast_fp16, y = hidden_states_11_cast_fp16)[name = tensor("inputs_31_cast_fp16")]; + tensor var_1239 = const()[name = tensor("op_1239"), val = tensor(3)]; + tensor out_31_axes_0 = const()[name = tensor("out_31_axes_0"), val = tensor([1])]; + tensor var_1264_to_fp16 = const()[name = tensor("op_1264_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_31_cast_fp16 = layer_norm(axes = out_31_axes_0, epsilon = var_1264_to_fp16, x = inputs_31_cast_fp16)[name = tensor("out_31_cast_fp16")]; + tensor obj_71_gamma_0_to_fp16 = const()[name = tensor("obj_71_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(275095360)))]; + tensor obj_71_beta_0_to_fp16 = const()[name = tensor("obj_71_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(275097472)))]; + tensor obj_71_epsilon_0_to_fp16 = const()[name = tensor("obj_71_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_71_cast_fp16 = batch_norm(beta = obj_71_beta_0_to_fp16, epsilon = obj_71_epsilon_0_to_fp16, gamma = obj_71_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_31_cast_fp16)[name = tensor("obj_71_cast_fp16")]; + tensor query_21_pad_type_0 = const()[name = tensor("query_21_pad_type_0"), val = tensor("valid")]; + tensor query_21_strides_0 = const()[name = tensor("query_21_strides_0"), val = tensor([1, 1])]; + tensor query_21_pad_0 = const()[name = tensor("query_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_21_dilations_0 = const()[name = tensor("query_21_dilations_0"), val = tensor([1, 1])]; + tensor query_21_groups_0 = const()[name = tensor("query_21_groups_0"), val = tensor(1)]; + tensor layers_5_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(275099584)))]; + tensor layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(277196800)))]; + tensor query_21_cast_fp16 = conv(bias = layers_5_self_attn_q_proj_bias_to_fp16, dilations = query_21_dilations_0, groups = query_21_groups_0, pad = query_21_pad_0, pad_type = query_21_pad_type_0, strides = query_21_strides_0, weight = layers_5_self_attn_q_proj_weight_to_fp16, x = obj_71_cast_fp16)[name = tensor("query_21_cast_fp16")]; + tensor current_key_11_pad_type_0 = const()[name = tensor("current_key_11_pad_type_0"), val = tensor("valid")]; + tensor current_key_11_strides_0 = const()[name = tensor("current_key_11_strides_0"), val = tensor([1, 1])]; + tensor current_key_11_pad_0 = const()[name = tensor("current_key_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_11_dilations_0 = const()[name = tensor("current_key_11_dilations_0"), val = tensor([1, 1])]; + tensor current_key_11_groups_0 = const()[name = tensor("current_key_11_groups_0"), val = tensor(1)]; + tensor layers_5_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(277198912)))]; + tensor current_key_11_cast_fp16 = conv(dilations = current_key_11_dilations_0, groups = current_key_11_groups_0, pad = current_key_11_pad_0, pad_type = current_key_11_pad_type_0, strides = current_key_11_strides_0, weight = layers_5_self_attn_k_proj_weight_to_fp16, x = obj_71_cast_fp16)[name = tensor("current_key_11_cast_fp16")]; + tensor current_value_11_pad_type_0 = const()[name = tensor("current_value_11_pad_type_0"), val = tensor("valid")]; + tensor current_value_11_strides_0 = const()[name = tensor("current_value_11_strides_0"), val = tensor([1, 1])]; + tensor current_value_11_pad_0 = const()[name = tensor("current_value_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_11_dilations_0 = const()[name = tensor("current_value_11_dilations_0"), val = tensor([1, 1])]; + tensor current_value_11_groups_0 = const()[name = tensor("current_value_11_groups_0"), val = tensor(1)]; + tensor layers_5_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279296128)))]; + tensor layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(281393344)))]; + tensor current_value_11_cast_fp16 = conv(bias = layers_5_self_attn_v_proj_bias_to_fp16, dilations = current_value_11_dilations_0, groups = current_value_11_groups_0, pad = current_value_11_pad_0, pad_type = current_value_11_pad_type_0, strides = current_value_11_strides_0, weight = layers_5_self_attn_v_proj_weight_to_fp16, x = obj_71_cast_fp16)[name = tensor("current_value_11_cast_fp16")]; + tensor var_1303_cast_fp16 = mul(x = var_87_cast_fp16_5, y = var_207_cast_fp16)[name = tensor("op_1303_cast_fp16")]; + tensor var_1304_cast_fp16 = mul(x = current_key_11_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_1304_cast_fp16")]; + tensor key_21_cast_fp16 = add(x = var_1303_cast_fp16, y = var_1304_cast_fp16)[name = tensor("key_21_cast_fp16")]; + tensor var_1307_cast_fp16 = mul(x = var_114_cast_fp16_5, y = var_207_cast_fp16)[name = tensor("op_1307_cast_fp16")]; + tensor var_1308_cast_fp16 = mul(x = current_value_11_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_1308_cast_fp16")]; + tensor value_21_cast_fp16 = add(x = var_1307_cast_fp16, y = var_1308_cast_fp16)[name = tensor("value_21_cast_fp16")]; + tensor var_1312 = const()[name = tensor("op_1312"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_21_cast_fp16 = reshape(shape = var_1312, x = query_21_cast_fp16)[name = tensor("mh_q_21_cast_fp16")]; + tensor var_1314_to_fp16 = const()[name = tensor("op_1314_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1315_cast_fp16 = mul(x = mh_q_21_cast_fp16, y = var_1314_to_fp16)[name = tensor("op_1315_cast_fp16")]; + tensor var_1318 = const()[name = tensor("op_1318"), val = tensor([1, 16, 64, 448])]; + tensor var_1319_cast_fp16 = reshape(shape = var_1318, x = key_21_cast_fp16)[name = tensor("op_1319_cast_fp16")]; + tensor mh_w_31_transpose_x_0 = const()[name = tensor("mh_w_31_transpose_x_0"), val = tensor(true)]; + tensor mh_w_31_transpose_y_0 = const()[name = tensor("mh_w_31_transpose_y_0"), val = tensor(false)]; + tensor mh_w_31_cast_fp16 = matmul(transpose_x = mh_w_31_transpose_x_0, transpose_y = mh_w_31_transpose_y_0, x = var_1315_cast_fp16, y = var_1319_cast_fp16)[name = tensor("mh_w_31_cast_fp16")]; + tensor mh_w_33_cast_fp16 = add(x = mh_w_31_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_33_cast_fp16")]; + tensor var_1327_cast_fp16 = softmax(axis = var_1239, x = mh_w_33_cast_fp16)[name = tensor("op_1327_cast_fp16")]; + tensor var_1328 = const()[name = tensor("op_1328"), val = tensor([1, 16, 64, 448])]; + tensor var_1329_cast_fp16 = reshape(shape = var_1328, x = value_21_cast_fp16)[name = tensor("op_1329_cast_fp16")]; + tensor attn_21_transpose_x_0 = const()[name = tensor("attn_21_transpose_x_0"), val = tensor(false)]; + tensor attn_21_transpose_y_0 = const()[name = tensor("attn_21_transpose_y_0"), val = tensor(true)]; + tensor attn_21_cast_fp16 = matmul(transpose_x = attn_21_transpose_x_0, transpose_y = attn_21_transpose_y_0, x = var_1329_cast_fp16, y = var_1327_cast_fp16)[name = tensor("attn_21_cast_fp16")]; + tensor var_1332 = const()[name = tensor("op_1332"), val = tensor([1, 1024, 1, 1])]; + tensor input_51_cast_fp16 = reshape(shape = var_1332, x = attn_21_cast_fp16)[name = tensor("input_51_cast_fp16")]; + tensor obj_77_pad_type_0 = const()[name = tensor("obj_77_pad_type_0"), val = tensor("valid")]; + tensor obj_77_strides_0 = const()[name = tensor("obj_77_strides_0"), val = tensor([1, 1])]; + tensor obj_77_pad_0 = const()[name = tensor("obj_77_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_77_dilations_0 = const()[name = tensor("obj_77_dilations_0"), val = tensor([1, 1])]; + tensor obj_77_groups_0 = const()[name = tensor("obj_77_groups_0"), val = tensor(1)]; + tensor layers_5_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(281395456)))]; + tensor layers_5_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(283492672)))]; + tensor obj_77_cast_fp16 = conv(bias = layers_5_self_attn_o_proj_bias_to_fp16, dilations = obj_77_dilations_0, groups = obj_77_groups_0, pad = obj_77_pad_0, pad_type = obj_77_pad_type_0, strides = obj_77_strides_0, weight = layers_5_self_attn_o_proj_weight_to_fp16, x = input_51_cast_fp16)[name = tensor("obj_77_cast_fp16")]; + tensor inputs_33_cast_fp16 = add(x = inputs_31_cast_fp16, y = obj_77_cast_fp16)[name = tensor("inputs_33_cast_fp16")]; + tensor out_33_axes_0 = const()[name = tensor("out_33_axes_0"), val = tensor([1])]; + tensor var_1354_to_fp16 = const()[name = tensor("op_1354_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_33_cast_fp16 = layer_norm(axes = out_33_axes_0, epsilon = var_1354_to_fp16, x = inputs_33_cast_fp16)[name = tensor("out_33_cast_fp16")]; + tensor obj_79_gamma_0_to_fp16 = const()[name = tensor("obj_79_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(283494784)))]; + tensor obj_79_beta_0_to_fp16 = const()[name = tensor("obj_79_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(283496896)))]; + tensor obj_79_epsilon_0_to_fp16 = const()[name = tensor("obj_79_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_79_cast_fp16 = batch_norm(beta = obj_79_beta_0_to_fp16, epsilon = obj_79_epsilon_0_to_fp16, gamma = obj_79_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_33_cast_fp16)[name = tensor("obj_79_cast_fp16")]; + tensor query_23_pad_type_0 = const()[name = tensor("query_23_pad_type_0"), val = tensor("valid")]; + tensor query_23_strides_0 = const()[name = tensor("query_23_strides_0"), val = tensor([1, 1])]; + tensor query_23_pad_0 = const()[name = tensor("query_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_23_dilations_0 = const()[name = tensor("query_23_dilations_0"), val = tensor([1, 1])]; + tensor query_23_groups_0 = const()[name = tensor("query_23_groups_0"), val = tensor(1)]; + tensor layers_5_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(283499008)))]; + tensor layers_5_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_5_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(285596224)))]; + tensor query_23_cast_fp16 = conv(bias = layers_5_encoder_attn_q_proj_bias_to_fp16, dilations = query_23_dilations_0, groups = query_23_groups_0, pad = query_23_pad_0, pad_type = query_23_pad_type_0, strides = query_23_strides_0, weight = layers_5_encoder_attn_q_proj_weight_to_fp16, x = obj_79_cast_fp16)[name = tensor("query_23_cast_fp16")]; + tensor key_23_pad_type_0 = const()[name = tensor("key_23_pad_type_0"), val = tensor("valid")]; + tensor key_23_strides_0 = const()[name = tensor("key_23_strides_0"), val = tensor([1, 1])]; + tensor key_23_pad_0 = const()[name = tensor("key_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_23_dilations_0 = const()[name = tensor("key_23_dilations_0"), val = tensor([1, 1])]; + tensor key_23_groups_0 = const()[name = tensor("key_23_groups_0"), val = tensor(1)]; + tensor layers_5_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(285598336)))]; + tensor key_23_cast_fp16 = conv(dilations = key_23_dilations_0, groups = key_23_groups_0, pad = key_23_pad_0, pad_type = key_23_pad_type_0, strides = key_23_strides_0, weight = layers_5_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_23_cast_fp16")]; + tensor value_23_pad_type_0 = const()[name = tensor("value_23_pad_type_0"), val = tensor("valid")]; + tensor value_23_strides_0 = const()[name = tensor("value_23_strides_0"), val = tensor([1, 1])]; + tensor value_23_pad_0 = const()[name = tensor("value_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_23_dilations_0 = const()[name = tensor("value_23_dilations_0"), val = tensor([1, 1])]; + tensor value_23_groups_0 = const()[name = tensor("value_23_groups_0"), val = tensor(1)]; + tensor layers_5_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(287695552)))]; + tensor layers_5_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_5_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289792768)))]; + tensor value_23_cast_fp16 = conv(bias = layers_5_encoder_attn_v_proj_bias_to_fp16, dilations = value_23_dilations_0, groups = value_23_groups_0, pad = value_23_pad_0, pad_type = value_23_pad_type_0, strides = value_23_strides_0, weight = layers_5_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_23_cast_fp16")]; + tensor var_1390 = const()[name = tensor("op_1390"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_23_cast_fp16 = reshape(shape = var_1390, x = query_23_cast_fp16)[name = tensor("mh_q_23_cast_fp16")]; + tensor var_1392_to_fp16 = const()[name = tensor("op_1392_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1393_cast_fp16 = mul(x = mh_q_23_cast_fp16, y = var_1392_to_fp16)[name = tensor("op_1393_cast_fp16")]; + tensor var_1396 = const()[name = tensor("op_1396"), val = tensor([1, 16, 64, 1500])]; + tensor var_1397_cast_fp16 = reshape(shape = var_1396, x = key_23_cast_fp16)[name = tensor("op_1397_cast_fp16")]; + tensor mh_w_35_transpose_x_0 = const()[name = tensor("mh_w_35_transpose_x_0"), val = tensor(true)]; + tensor mh_w_35_transpose_y_0 = const()[name = tensor("mh_w_35_transpose_y_0"), val = tensor(false)]; + tensor mh_w_35_cast_fp16 = matmul(transpose_x = mh_w_35_transpose_x_0, transpose_y = mh_w_35_transpose_y_0, x = var_1393_cast_fp16, y = var_1397_cast_fp16)[name = tensor("mh_w_35_cast_fp16")]; + tensor obj_83_cast_fp16 = softmax(axis = var_1239, x = mh_w_35_cast_fp16)[name = tensor("obj_83_cast_fp16")]; + tensor var_1401 = const()[name = tensor("op_1401"), val = tensor([1, 16, 64, 1500])]; + tensor var_1402_cast_fp16 = reshape(shape = var_1401, x = value_23_cast_fp16)[name = tensor("op_1402_cast_fp16")]; + tensor attn_23_transpose_x_0 = const()[name = tensor("attn_23_transpose_x_0"), val = tensor(false)]; + tensor attn_23_transpose_y_0 = const()[name = tensor("attn_23_transpose_y_0"), val = tensor(true)]; + tensor attn_23_cast_fp16 = matmul(transpose_x = attn_23_transpose_x_0, transpose_y = attn_23_transpose_y_0, x = var_1402_cast_fp16, y = obj_83_cast_fp16)[name = tensor("attn_23_cast_fp16")]; + tensor var_1405 = const()[name = tensor("op_1405"), val = tensor([1, 1024, 1, 1])]; + tensor input_53_cast_fp16 = reshape(shape = var_1405, x = attn_23_cast_fp16)[name = tensor("input_53_cast_fp16")]; + tensor obj_81_pad_type_0 = const()[name = tensor("obj_81_pad_type_0"), val = tensor("valid")]; + tensor obj_81_strides_0 = const()[name = tensor("obj_81_strides_0"), val = tensor([1, 1])]; + tensor obj_81_pad_0 = const()[name = tensor("obj_81_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_81_dilations_0 = const()[name = tensor("obj_81_dilations_0"), val = tensor([1, 1])]; + tensor obj_81_groups_0 = const()[name = tensor("obj_81_groups_0"), val = tensor(1)]; + tensor layers_5_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289794880)))]; + tensor layers_5_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_5_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291892096)))]; + tensor obj_81_cast_fp16 = conv(bias = layers_5_encoder_attn_o_proj_bias_to_fp16, dilations = obj_81_dilations_0, groups = obj_81_groups_0, pad = obj_81_pad_0, pad_type = obj_81_pad_type_0, strides = obj_81_strides_0, weight = layers_5_encoder_attn_o_proj_weight_to_fp16, x = input_53_cast_fp16)[name = tensor("obj_81_cast_fp16")]; + tensor inputs_35_cast_fp16 = add(x = inputs_33_cast_fp16, y = obj_81_cast_fp16)[name = tensor("inputs_35_cast_fp16")]; + tensor out_35_axes_0 = const()[name = tensor("out_35_axes_0"), val = tensor([1])]; + tensor var_1423_to_fp16 = const()[name = tensor("op_1423_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_35_cast_fp16 = layer_norm(axes = out_35_axes_0, epsilon = var_1423_to_fp16, x = inputs_35_cast_fp16)[name = tensor("out_35_cast_fp16")]; + tensor input_55_gamma_0_to_fp16 = const()[name = tensor("input_55_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291894208)))]; + tensor input_55_beta_0_to_fp16 = const()[name = tensor("input_55_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291896320)))]; + tensor input_55_epsilon_0_to_fp16 = const()[name = tensor("input_55_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_55_cast_fp16 = batch_norm(beta = input_55_beta_0_to_fp16, epsilon = input_55_epsilon_0_to_fp16, gamma = input_55_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_35_cast_fp16)[name = tensor("input_55_cast_fp16")]; + tensor input_57_pad_type_0 = const()[name = tensor("input_57_pad_type_0"), val = tensor("valid")]; + tensor input_57_strides_0 = const()[name = tensor("input_57_strides_0"), val = tensor([1, 1])]; + tensor input_57_pad_0 = const()[name = tensor("input_57_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_57_dilations_0 = const()[name = tensor("input_57_dilations_0"), val = tensor([1, 1])]; + tensor input_57_groups_0 = const()[name = tensor("input_57_groups_0"), val = tensor(1)]; + tensor layers_5_fc1_weight_to_fp16 = const()[name = tensor("layers_5_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291898432)))]; + tensor layers_5_fc1_bias_to_fp16 = const()[name = tensor("layers_5_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(300287104)))]; + tensor input_57_cast_fp16 = conv(bias = layers_5_fc1_bias_to_fp16, dilations = input_57_dilations_0, groups = input_57_groups_0, pad = input_57_pad_0, pad_type = input_57_pad_type_0, strides = input_57_strides_0, weight = layers_5_fc1_weight_to_fp16, x = input_55_cast_fp16)[name = tensor("input_57_cast_fp16")]; + tensor input_59_mode_0 = const()[name = tensor("input_59_mode_0"), val = tensor("EXACT")]; + tensor input_59_cast_fp16 = gelu(mode = input_59_mode_0, x = input_57_cast_fp16)[name = tensor("input_59_cast_fp16")]; + tensor hidden_states_13_pad_type_0 = const()[name = tensor("hidden_states_13_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_13_strides_0 = const()[name = tensor("hidden_states_13_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_13_pad_0 = const()[name = tensor("hidden_states_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_13_dilations_0 = const()[name = tensor("hidden_states_13_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_13_groups_0 = const()[name = tensor("hidden_states_13_groups_0"), val = tensor(1)]; + tensor layers_5_fc2_weight_to_fp16 = const()[name = tensor("layers_5_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(300295360)))]; + tensor layers_5_fc2_bias_to_fp16 = const()[name = tensor("layers_5_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(308684032)))]; + tensor hidden_states_13_cast_fp16 = conv(bias = layers_5_fc2_bias_to_fp16, dilations = hidden_states_13_dilations_0, groups = hidden_states_13_groups_0, pad = hidden_states_13_pad_0, pad_type = hidden_states_13_pad_type_0, strides = hidden_states_13_strides_0, weight = layers_5_fc2_weight_to_fp16, x = input_59_cast_fp16)[name = tensor("hidden_states_13_cast_fp16")]; + tensor inputs_37_cast_fp16 = add(x = inputs_35_cast_fp16, y = hidden_states_13_cast_fp16)[name = tensor("inputs_37_cast_fp16")]; + tensor var_1458 = const()[name = tensor("op_1458"), val = tensor(3)]; + tensor out_37_axes_0 = const()[name = tensor("out_37_axes_0"), val = tensor([1])]; + tensor var_1483_to_fp16 = const()[name = tensor("op_1483_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_37_cast_fp16 = layer_norm(axes = out_37_axes_0, epsilon = var_1483_to_fp16, x = inputs_37_cast_fp16)[name = tensor("out_37_cast_fp16")]; + tensor obj_85_gamma_0_to_fp16 = const()[name = tensor("obj_85_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(308686144)))]; + tensor obj_85_beta_0_to_fp16 = const()[name = tensor("obj_85_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(308688256)))]; + tensor obj_85_epsilon_0_to_fp16 = const()[name = tensor("obj_85_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_85_cast_fp16 = batch_norm(beta = obj_85_beta_0_to_fp16, epsilon = obj_85_epsilon_0_to_fp16, gamma = obj_85_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_37_cast_fp16)[name = tensor("obj_85_cast_fp16")]; + tensor query_25_pad_type_0 = const()[name = tensor("query_25_pad_type_0"), val = tensor("valid")]; + tensor query_25_strides_0 = const()[name = tensor("query_25_strides_0"), val = tensor([1, 1])]; + tensor query_25_pad_0 = const()[name = tensor("query_25_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_25_dilations_0 = const()[name = tensor("query_25_dilations_0"), val = tensor([1, 1])]; + tensor query_25_groups_0 = const()[name = tensor("query_25_groups_0"), val = tensor(1)]; + tensor layers_6_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(308690368)))]; + tensor layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(310787584)))]; + tensor query_25_cast_fp16 = conv(bias = layers_6_self_attn_q_proj_bias_to_fp16, dilations = query_25_dilations_0, groups = query_25_groups_0, pad = query_25_pad_0, pad_type = query_25_pad_type_0, strides = query_25_strides_0, weight = layers_6_self_attn_q_proj_weight_to_fp16, x = obj_85_cast_fp16)[name = tensor("query_25_cast_fp16")]; + tensor current_key_13_pad_type_0 = const()[name = tensor("current_key_13_pad_type_0"), val = tensor("valid")]; + tensor current_key_13_strides_0 = const()[name = tensor("current_key_13_strides_0"), val = tensor([1, 1])]; + tensor current_key_13_pad_0 = const()[name = tensor("current_key_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_13_dilations_0 = const()[name = tensor("current_key_13_dilations_0"), val = tensor([1, 1])]; + tensor current_key_13_groups_0 = const()[name = tensor("current_key_13_groups_0"), val = tensor(1)]; + tensor layers_6_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(310789696)))]; + tensor current_key_13_cast_fp16 = conv(dilations = current_key_13_dilations_0, groups = current_key_13_groups_0, pad = current_key_13_pad_0, pad_type = current_key_13_pad_type_0, strides = current_key_13_strides_0, weight = layers_6_self_attn_k_proj_weight_to_fp16, x = obj_85_cast_fp16)[name = tensor("current_key_13_cast_fp16")]; + tensor current_value_13_pad_type_0 = const()[name = tensor("current_value_13_pad_type_0"), val = tensor("valid")]; + tensor current_value_13_strides_0 = const()[name = tensor("current_value_13_strides_0"), val = tensor([1, 1])]; + tensor current_value_13_pad_0 = const()[name = tensor("current_value_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_13_dilations_0 = const()[name = tensor("current_value_13_dilations_0"), val = tensor([1, 1])]; + tensor current_value_13_groups_0 = const()[name = tensor("current_value_13_groups_0"), val = tensor(1)]; + tensor layers_6_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(312886912)))]; + tensor layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(314984128)))]; + tensor current_value_13_cast_fp16 = conv(bias = layers_6_self_attn_v_proj_bias_to_fp16, dilations = current_value_13_dilations_0, groups = current_value_13_groups_0, pad = current_value_13_pad_0, pad_type = current_value_13_pad_type_0, strides = current_value_13_strides_0, weight = layers_6_self_attn_v_proj_weight_to_fp16, x = obj_85_cast_fp16)[name = tensor("current_value_13_cast_fp16")]; + tensor var_1522_cast_fp16 = mul(x = var_87_cast_fp16_6, y = var_207_cast_fp16)[name = tensor("op_1522_cast_fp16")]; + tensor var_1523_cast_fp16 = mul(x = current_key_13_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_1523_cast_fp16")]; + tensor key_25_cast_fp16 = add(x = var_1522_cast_fp16, y = var_1523_cast_fp16)[name = tensor("key_25_cast_fp16")]; + tensor var_1526_cast_fp16 = mul(x = var_114_cast_fp16_6, y = var_207_cast_fp16)[name = tensor("op_1526_cast_fp16")]; + tensor var_1527_cast_fp16 = mul(x = current_value_13_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_1527_cast_fp16")]; + tensor value_25_cast_fp16 = add(x = var_1526_cast_fp16, y = var_1527_cast_fp16)[name = tensor("value_25_cast_fp16")]; + tensor var_1531 = const()[name = tensor("op_1531"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_25_cast_fp16 = reshape(shape = var_1531, x = query_25_cast_fp16)[name = tensor("mh_q_25_cast_fp16")]; + tensor var_1533_to_fp16 = const()[name = tensor("op_1533_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1534_cast_fp16 = mul(x = mh_q_25_cast_fp16, y = var_1533_to_fp16)[name = tensor("op_1534_cast_fp16")]; + tensor var_1537 = const()[name = tensor("op_1537"), val = tensor([1, 16, 64, 448])]; + tensor var_1538_cast_fp16 = reshape(shape = var_1537, x = key_25_cast_fp16)[name = tensor("op_1538_cast_fp16")]; + tensor mh_w_37_transpose_x_0 = const()[name = tensor("mh_w_37_transpose_x_0"), val = tensor(true)]; + tensor mh_w_37_transpose_y_0 = const()[name = tensor("mh_w_37_transpose_y_0"), val = tensor(false)]; + tensor mh_w_37_cast_fp16 = matmul(transpose_x = mh_w_37_transpose_x_0, transpose_y = mh_w_37_transpose_y_0, x = var_1534_cast_fp16, y = var_1538_cast_fp16)[name = tensor("mh_w_37_cast_fp16")]; + tensor mh_w_39_cast_fp16 = add(x = mh_w_37_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_39_cast_fp16")]; + tensor var_1546_cast_fp16 = softmax(axis = var_1458, x = mh_w_39_cast_fp16)[name = tensor("op_1546_cast_fp16")]; + tensor var_1547 = const()[name = tensor("op_1547"), val = tensor([1, 16, 64, 448])]; + tensor var_1548_cast_fp16 = reshape(shape = var_1547, x = value_25_cast_fp16)[name = tensor("op_1548_cast_fp16")]; + tensor attn_25_transpose_x_0 = const()[name = tensor("attn_25_transpose_x_0"), val = tensor(false)]; + tensor attn_25_transpose_y_0 = const()[name = tensor("attn_25_transpose_y_0"), val = tensor(true)]; + tensor attn_25_cast_fp16 = matmul(transpose_x = attn_25_transpose_x_0, transpose_y = attn_25_transpose_y_0, x = var_1548_cast_fp16, y = var_1546_cast_fp16)[name = tensor("attn_25_cast_fp16")]; + tensor var_1551 = const()[name = tensor("op_1551"), val = tensor([1, 1024, 1, 1])]; + tensor input_61_cast_fp16 = reshape(shape = var_1551, x = attn_25_cast_fp16)[name = tensor("input_61_cast_fp16")]; + tensor obj_91_pad_type_0 = const()[name = tensor("obj_91_pad_type_0"), val = tensor("valid")]; + tensor obj_91_strides_0 = const()[name = tensor("obj_91_strides_0"), val = tensor([1, 1])]; + tensor obj_91_pad_0 = const()[name = tensor("obj_91_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_91_dilations_0 = const()[name = tensor("obj_91_dilations_0"), val = tensor([1, 1])]; + tensor obj_91_groups_0 = const()[name = tensor("obj_91_groups_0"), val = tensor(1)]; + tensor layers_6_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(314986240)))]; + tensor layers_6_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(317083456)))]; + tensor obj_91_cast_fp16 = conv(bias = layers_6_self_attn_o_proj_bias_to_fp16, dilations = obj_91_dilations_0, groups = obj_91_groups_0, pad = obj_91_pad_0, pad_type = obj_91_pad_type_0, strides = obj_91_strides_0, weight = layers_6_self_attn_o_proj_weight_to_fp16, x = input_61_cast_fp16)[name = tensor("obj_91_cast_fp16")]; + tensor inputs_39_cast_fp16 = add(x = inputs_37_cast_fp16, y = obj_91_cast_fp16)[name = tensor("inputs_39_cast_fp16")]; + tensor out_39_axes_0 = const()[name = tensor("out_39_axes_0"), val = tensor([1])]; + tensor var_1573_to_fp16 = const()[name = tensor("op_1573_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_39_cast_fp16 = layer_norm(axes = out_39_axes_0, epsilon = var_1573_to_fp16, x = inputs_39_cast_fp16)[name = tensor("out_39_cast_fp16")]; + tensor obj_93_gamma_0_to_fp16 = const()[name = tensor("obj_93_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(317085568)))]; + tensor obj_93_beta_0_to_fp16 = const()[name = tensor("obj_93_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(317087680)))]; + tensor obj_93_epsilon_0_to_fp16 = const()[name = tensor("obj_93_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_93_cast_fp16 = batch_norm(beta = obj_93_beta_0_to_fp16, epsilon = obj_93_epsilon_0_to_fp16, gamma = obj_93_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_39_cast_fp16)[name = tensor("obj_93_cast_fp16")]; + tensor query_27_pad_type_0 = const()[name = tensor("query_27_pad_type_0"), val = tensor("valid")]; + tensor query_27_strides_0 = const()[name = tensor("query_27_strides_0"), val = tensor([1, 1])]; + tensor query_27_pad_0 = const()[name = tensor("query_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_27_dilations_0 = const()[name = tensor("query_27_dilations_0"), val = tensor([1, 1])]; + tensor query_27_groups_0 = const()[name = tensor("query_27_groups_0"), val = tensor(1)]; + tensor layers_6_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_6_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(317089792)))]; + tensor layers_6_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_6_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(319187008)))]; + tensor query_27_cast_fp16 = conv(bias = layers_6_encoder_attn_q_proj_bias_to_fp16, dilations = query_27_dilations_0, groups = query_27_groups_0, pad = query_27_pad_0, pad_type = query_27_pad_type_0, strides = query_27_strides_0, weight = layers_6_encoder_attn_q_proj_weight_to_fp16, x = obj_93_cast_fp16)[name = tensor("query_27_cast_fp16")]; + tensor key_27_pad_type_0 = const()[name = tensor("key_27_pad_type_0"), val = tensor("valid")]; + tensor key_27_strides_0 = const()[name = tensor("key_27_strides_0"), val = tensor([1, 1])]; + tensor key_27_pad_0 = const()[name = tensor("key_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_27_dilations_0 = const()[name = tensor("key_27_dilations_0"), val = tensor([1, 1])]; + tensor key_27_groups_0 = const()[name = tensor("key_27_groups_0"), val = tensor(1)]; + tensor layers_6_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_6_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(319189120)))]; + tensor key_27_cast_fp16 = conv(dilations = key_27_dilations_0, groups = key_27_groups_0, pad = key_27_pad_0, pad_type = key_27_pad_type_0, strides = key_27_strides_0, weight = layers_6_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_27_cast_fp16")]; + tensor value_27_pad_type_0 = const()[name = tensor("value_27_pad_type_0"), val = tensor("valid")]; + tensor value_27_strides_0 = const()[name = tensor("value_27_strides_0"), val = tensor([1, 1])]; + tensor value_27_pad_0 = const()[name = tensor("value_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_27_dilations_0 = const()[name = tensor("value_27_dilations_0"), val = tensor([1, 1])]; + tensor value_27_groups_0 = const()[name = tensor("value_27_groups_0"), val = tensor(1)]; + tensor layers_6_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_6_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(321286336)))]; + tensor layers_6_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_6_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(323383552)))]; + tensor value_27_cast_fp16 = conv(bias = layers_6_encoder_attn_v_proj_bias_to_fp16, dilations = value_27_dilations_0, groups = value_27_groups_0, pad = value_27_pad_0, pad_type = value_27_pad_type_0, strides = value_27_strides_0, weight = layers_6_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_27_cast_fp16")]; + tensor var_1609 = const()[name = tensor("op_1609"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_27_cast_fp16 = reshape(shape = var_1609, x = query_27_cast_fp16)[name = tensor("mh_q_27_cast_fp16")]; + tensor var_1611_to_fp16 = const()[name = tensor("op_1611_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1612_cast_fp16 = mul(x = mh_q_27_cast_fp16, y = var_1611_to_fp16)[name = tensor("op_1612_cast_fp16")]; + tensor var_1615 = const()[name = tensor("op_1615"), val = tensor([1, 16, 64, 1500])]; + tensor var_1616_cast_fp16 = reshape(shape = var_1615, x = key_27_cast_fp16)[name = tensor("op_1616_cast_fp16")]; + tensor mh_w_41_transpose_x_0 = const()[name = tensor("mh_w_41_transpose_x_0"), val = tensor(true)]; + tensor mh_w_41_transpose_y_0 = const()[name = tensor("mh_w_41_transpose_y_0"), val = tensor(false)]; + tensor mh_w_41_cast_fp16 = matmul(transpose_x = mh_w_41_transpose_x_0, transpose_y = mh_w_41_transpose_y_0, x = var_1612_cast_fp16, y = var_1616_cast_fp16)[name = tensor("mh_w_41_cast_fp16")]; + tensor obj_97_cast_fp16 = softmax(axis = var_1458, x = mh_w_41_cast_fp16)[name = tensor("obj_97_cast_fp16")]; + tensor var_1620 = const()[name = tensor("op_1620"), val = tensor([1, 16, 64, 1500])]; + tensor var_1621_cast_fp16 = reshape(shape = var_1620, x = value_27_cast_fp16)[name = tensor("op_1621_cast_fp16")]; + tensor attn_27_transpose_x_0 = const()[name = tensor("attn_27_transpose_x_0"), val = tensor(false)]; + tensor attn_27_transpose_y_0 = const()[name = tensor("attn_27_transpose_y_0"), val = tensor(true)]; + tensor attn_27_cast_fp16 = matmul(transpose_x = attn_27_transpose_x_0, transpose_y = attn_27_transpose_y_0, x = var_1621_cast_fp16, y = obj_97_cast_fp16)[name = tensor("attn_27_cast_fp16")]; + tensor var_1624 = const()[name = tensor("op_1624"), val = tensor([1, 1024, 1, 1])]; + tensor input_63_cast_fp16 = reshape(shape = var_1624, x = attn_27_cast_fp16)[name = tensor("input_63_cast_fp16")]; + tensor obj_95_pad_type_0 = const()[name = tensor("obj_95_pad_type_0"), val = tensor("valid")]; + tensor obj_95_strides_0 = const()[name = tensor("obj_95_strides_0"), val = tensor([1, 1])]; + tensor obj_95_pad_0 = const()[name = tensor("obj_95_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_95_dilations_0 = const()[name = tensor("obj_95_dilations_0"), val = tensor([1, 1])]; + tensor obj_95_groups_0 = const()[name = tensor("obj_95_groups_0"), val = tensor(1)]; + tensor layers_6_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_6_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(323385664)))]; + tensor layers_6_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_6_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(325482880)))]; + tensor obj_95_cast_fp16 = conv(bias = layers_6_encoder_attn_o_proj_bias_to_fp16, dilations = obj_95_dilations_0, groups = obj_95_groups_0, pad = obj_95_pad_0, pad_type = obj_95_pad_type_0, strides = obj_95_strides_0, weight = layers_6_encoder_attn_o_proj_weight_to_fp16, x = input_63_cast_fp16)[name = tensor("obj_95_cast_fp16")]; + tensor inputs_41_cast_fp16 = add(x = inputs_39_cast_fp16, y = obj_95_cast_fp16)[name = tensor("inputs_41_cast_fp16")]; + tensor out_41_axes_0 = const()[name = tensor("out_41_axes_0"), val = tensor([1])]; + tensor var_1642_to_fp16 = const()[name = tensor("op_1642_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_41_cast_fp16 = layer_norm(axes = out_41_axes_0, epsilon = var_1642_to_fp16, x = inputs_41_cast_fp16)[name = tensor("out_41_cast_fp16")]; + tensor input_65_gamma_0_to_fp16 = const()[name = tensor("input_65_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(325484992)))]; + tensor input_65_beta_0_to_fp16 = const()[name = tensor("input_65_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(325487104)))]; + tensor input_65_epsilon_0_to_fp16 = const()[name = tensor("input_65_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_65_cast_fp16 = batch_norm(beta = input_65_beta_0_to_fp16, epsilon = input_65_epsilon_0_to_fp16, gamma = input_65_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_41_cast_fp16)[name = tensor("input_65_cast_fp16")]; + tensor input_67_pad_type_0 = const()[name = tensor("input_67_pad_type_0"), val = tensor("valid")]; + tensor input_67_strides_0 = const()[name = tensor("input_67_strides_0"), val = tensor([1, 1])]; + tensor input_67_pad_0 = const()[name = tensor("input_67_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_67_dilations_0 = const()[name = tensor("input_67_dilations_0"), val = tensor([1, 1])]; + tensor input_67_groups_0 = const()[name = tensor("input_67_groups_0"), val = tensor(1)]; + tensor layers_6_fc1_weight_to_fp16 = const()[name = tensor("layers_6_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(325489216)))]; + tensor layers_6_fc1_bias_to_fp16 = const()[name = tensor("layers_6_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(333877888)))]; + tensor input_67_cast_fp16 = conv(bias = layers_6_fc1_bias_to_fp16, dilations = input_67_dilations_0, groups = input_67_groups_0, pad = input_67_pad_0, pad_type = input_67_pad_type_0, strides = input_67_strides_0, weight = layers_6_fc1_weight_to_fp16, x = input_65_cast_fp16)[name = tensor("input_67_cast_fp16")]; + tensor input_69_mode_0 = const()[name = tensor("input_69_mode_0"), val = tensor("EXACT")]; + tensor input_69_cast_fp16 = gelu(mode = input_69_mode_0, x = input_67_cast_fp16)[name = tensor("input_69_cast_fp16")]; + tensor hidden_states_15_pad_type_0 = const()[name = tensor("hidden_states_15_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_15_strides_0 = const()[name = tensor("hidden_states_15_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_15_pad_0 = const()[name = tensor("hidden_states_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_15_dilations_0 = const()[name = tensor("hidden_states_15_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_15_groups_0 = const()[name = tensor("hidden_states_15_groups_0"), val = tensor(1)]; + tensor layers_6_fc2_weight_to_fp16 = const()[name = tensor("layers_6_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(333886144)))]; + tensor layers_6_fc2_bias_to_fp16 = const()[name = tensor("layers_6_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(342274816)))]; + tensor hidden_states_15_cast_fp16 = conv(bias = layers_6_fc2_bias_to_fp16, dilations = hidden_states_15_dilations_0, groups = hidden_states_15_groups_0, pad = hidden_states_15_pad_0, pad_type = hidden_states_15_pad_type_0, strides = hidden_states_15_strides_0, weight = layers_6_fc2_weight_to_fp16, x = input_69_cast_fp16)[name = tensor("hidden_states_15_cast_fp16")]; + tensor inputs_43_cast_fp16 = add(x = inputs_41_cast_fp16, y = hidden_states_15_cast_fp16)[name = tensor("inputs_43_cast_fp16")]; + tensor var_1677 = const()[name = tensor("op_1677"), val = tensor(3)]; + tensor out_43_axes_0 = const()[name = tensor("out_43_axes_0"), val = tensor([1])]; + tensor var_1702_to_fp16 = const()[name = tensor("op_1702_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_43_cast_fp16 = layer_norm(axes = out_43_axes_0, epsilon = var_1702_to_fp16, x = inputs_43_cast_fp16)[name = tensor("out_43_cast_fp16")]; + tensor obj_99_gamma_0_to_fp16 = const()[name = tensor("obj_99_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(342276928)))]; + tensor obj_99_beta_0_to_fp16 = const()[name = tensor("obj_99_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(342279040)))]; + tensor obj_99_epsilon_0_to_fp16 = const()[name = tensor("obj_99_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_99_cast_fp16 = batch_norm(beta = obj_99_beta_0_to_fp16, epsilon = obj_99_epsilon_0_to_fp16, gamma = obj_99_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_43_cast_fp16)[name = tensor("obj_99_cast_fp16")]; + tensor query_29_pad_type_0 = const()[name = tensor("query_29_pad_type_0"), val = tensor("valid")]; + tensor query_29_strides_0 = const()[name = tensor("query_29_strides_0"), val = tensor([1, 1])]; + tensor query_29_pad_0 = const()[name = tensor("query_29_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_29_dilations_0 = const()[name = tensor("query_29_dilations_0"), val = tensor([1, 1])]; + tensor query_29_groups_0 = const()[name = tensor("query_29_groups_0"), val = tensor(1)]; + tensor layers_7_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(342281152)))]; + tensor layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(344378368)))]; + tensor query_29_cast_fp16 = conv(bias = layers_7_self_attn_q_proj_bias_to_fp16, dilations = query_29_dilations_0, groups = query_29_groups_0, pad = query_29_pad_0, pad_type = query_29_pad_type_0, strides = query_29_strides_0, weight = layers_7_self_attn_q_proj_weight_to_fp16, x = obj_99_cast_fp16)[name = tensor("query_29_cast_fp16")]; + tensor current_key_15_pad_type_0 = const()[name = tensor("current_key_15_pad_type_0"), val = tensor("valid")]; + tensor current_key_15_strides_0 = const()[name = tensor("current_key_15_strides_0"), val = tensor([1, 1])]; + tensor current_key_15_pad_0 = const()[name = tensor("current_key_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_15_dilations_0 = const()[name = tensor("current_key_15_dilations_0"), val = tensor([1, 1])]; + tensor current_key_15_groups_0 = const()[name = tensor("current_key_15_groups_0"), val = tensor(1)]; + tensor layers_7_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(344380480)))]; + tensor current_key_15_cast_fp16 = conv(dilations = current_key_15_dilations_0, groups = current_key_15_groups_0, pad = current_key_15_pad_0, pad_type = current_key_15_pad_type_0, strides = current_key_15_strides_0, weight = layers_7_self_attn_k_proj_weight_to_fp16, x = obj_99_cast_fp16)[name = tensor("current_key_15_cast_fp16")]; + tensor current_value_15_pad_type_0 = const()[name = tensor("current_value_15_pad_type_0"), val = tensor("valid")]; + tensor current_value_15_strides_0 = const()[name = tensor("current_value_15_strides_0"), val = tensor([1, 1])]; + tensor current_value_15_pad_0 = const()[name = tensor("current_value_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_15_dilations_0 = const()[name = tensor("current_value_15_dilations_0"), val = tensor([1, 1])]; + tensor current_value_15_groups_0 = const()[name = tensor("current_value_15_groups_0"), val = tensor(1)]; + tensor layers_7_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(346477696)))]; + tensor layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(348574912)))]; + tensor current_value_15_cast_fp16 = conv(bias = layers_7_self_attn_v_proj_bias_to_fp16, dilations = current_value_15_dilations_0, groups = current_value_15_groups_0, pad = current_value_15_pad_0, pad_type = current_value_15_pad_type_0, strides = current_value_15_strides_0, weight = layers_7_self_attn_v_proj_weight_to_fp16, x = obj_99_cast_fp16)[name = tensor("current_value_15_cast_fp16")]; + tensor var_1741_cast_fp16 = mul(x = var_87_cast_fp16_7, y = var_207_cast_fp16)[name = tensor("op_1741_cast_fp16")]; + tensor var_1742_cast_fp16 = mul(x = current_key_15_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_1742_cast_fp16")]; + tensor key_29_cast_fp16 = add(x = var_1741_cast_fp16, y = var_1742_cast_fp16)[name = tensor("key_29_cast_fp16")]; + tensor var_1745_cast_fp16 = mul(x = var_114_cast_fp16_7, y = var_207_cast_fp16)[name = tensor("op_1745_cast_fp16")]; + tensor var_1746_cast_fp16 = mul(x = current_value_15_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_1746_cast_fp16")]; + tensor value_29_cast_fp16 = add(x = var_1745_cast_fp16, y = var_1746_cast_fp16)[name = tensor("value_29_cast_fp16")]; + tensor var_1750 = const()[name = tensor("op_1750"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_29_cast_fp16 = reshape(shape = var_1750, x = query_29_cast_fp16)[name = tensor("mh_q_29_cast_fp16")]; + tensor var_1752_to_fp16 = const()[name = tensor("op_1752_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1753_cast_fp16 = mul(x = mh_q_29_cast_fp16, y = var_1752_to_fp16)[name = tensor("op_1753_cast_fp16")]; + tensor var_1756 = const()[name = tensor("op_1756"), val = tensor([1, 16, 64, 448])]; + tensor var_1757_cast_fp16 = reshape(shape = var_1756, x = key_29_cast_fp16)[name = tensor("op_1757_cast_fp16")]; + tensor mh_w_43_transpose_x_0 = const()[name = tensor("mh_w_43_transpose_x_0"), val = tensor(true)]; + tensor mh_w_43_transpose_y_0 = const()[name = tensor("mh_w_43_transpose_y_0"), val = tensor(false)]; + tensor mh_w_43_cast_fp16 = matmul(transpose_x = mh_w_43_transpose_x_0, transpose_y = mh_w_43_transpose_y_0, x = var_1753_cast_fp16, y = var_1757_cast_fp16)[name = tensor("mh_w_43_cast_fp16")]; + tensor mh_w_45_cast_fp16 = add(x = mh_w_43_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_45_cast_fp16")]; + tensor var_1765_cast_fp16 = softmax(axis = var_1677, x = mh_w_45_cast_fp16)[name = tensor("op_1765_cast_fp16")]; + tensor var_1766 = const()[name = tensor("op_1766"), val = tensor([1, 16, 64, 448])]; + tensor var_1767_cast_fp16 = reshape(shape = var_1766, x = value_29_cast_fp16)[name = tensor("op_1767_cast_fp16")]; + tensor attn_29_transpose_x_0 = const()[name = tensor("attn_29_transpose_x_0"), val = tensor(false)]; + tensor attn_29_transpose_y_0 = const()[name = tensor("attn_29_transpose_y_0"), val = tensor(true)]; + tensor attn_29_cast_fp16 = matmul(transpose_x = attn_29_transpose_x_0, transpose_y = attn_29_transpose_y_0, x = var_1767_cast_fp16, y = var_1765_cast_fp16)[name = tensor("attn_29_cast_fp16")]; + tensor var_1770 = const()[name = tensor("op_1770"), val = tensor([1, 1024, 1, 1])]; + tensor input_71_cast_fp16 = reshape(shape = var_1770, x = attn_29_cast_fp16)[name = tensor("input_71_cast_fp16")]; + tensor obj_105_pad_type_0 = const()[name = tensor("obj_105_pad_type_0"), val = tensor("valid")]; + tensor obj_105_strides_0 = const()[name = tensor("obj_105_strides_0"), val = tensor([1, 1])]; + tensor obj_105_pad_0 = const()[name = tensor("obj_105_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_105_dilations_0 = const()[name = tensor("obj_105_dilations_0"), val = tensor([1, 1])]; + tensor obj_105_groups_0 = const()[name = tensor("obj_105_groups_0"), val = tensor(1)]; + tensor layers_7_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(348577024)))]; + tensor layers_7_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(350674240)))]; + tensor obj_105_cast_fp16 = conv(bias = layers_7_self_attn_o_proj_bias_to_fp16, dilations = obj_105_dilations_0, groups = obj_105_groups_0, pad = obj_105_pad_0, pad_type = obj_105_pad_type_0, strides = obj_105_strides_0, weight = layers_7_self_attn_o_proj_weight_to_fp16, x = input_71_cast_fp16)[name = tensor("obj_105_cast_fp16")]; + tensor inputs_45_cast_fp16 = add(x = inputs_43_cast_fp16, y = obj_105_cast_fp16)[name = tensor("inputs_45_cast_fp16")]; + tensor out_45_axes_0 = const()[name = tensor("out_45_axes_0"), val = tensor([1])]; + tensor var_1792_to_fp16 = const()[name = tensor("op_1792_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_45_cast_fp16 = layer_norm(axes = out_45_axes_0, epsilon = var_1792_to_fp16, x = inputs_45_cast_fp16)[name = tensor("out_45_cast_fp16")]; + tensor obj_107_gamma_0_to_fp16 = const()[name = tensor("obj_107_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(350676352)))]; + tensor obj_107_beta_0_to_fp16 = const()[name = tensor("obj_107_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(350678464)))]; + tensor obj_107_epsilon_0_to_fp16 = const()[name = tensor("obj_107_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_107_cast_fp16 = batch_norm(beta = obj_107_beta_0_to_fp16, epsilon = obj_107_epsilon_0_to_fp16, gamma = obj_107_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_45_cast_fp16)[name = tensor("obj_107_cast_fp16")]; + tensor query_31_pad_type_0 = const()[name = tensor("query_31_pad_type_0"), val = tensor("valid")]; + tensor query_31_strides_0 = const()[name = tensor("query_31_strides_0"), val = tensor([1, 1])]; + tensor query_31_pad_0 = const()[name = tensor("query_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_31_dilations_0 = const()[name = tensor("query_31_dilations_0"), val = tensor([1, 1])]; + tensor query_31_groups_0 = const()[name = tensor("query_31_groups_0"), val = tensor(1)]; + tensor layers_7_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_7_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(350680576)))]; + tensor layers_7_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_7_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(352777792)))]; + tensor query_31_cast_fp16 = conv(bias = layers_7_encoder_attn_q_proj_bias_to_fp16, dilations = query_31_dilations_0, groups = query_31_groups_0, pad = query_31_pad_0, pad_type = query_31_pad_type_0, strides = query_31_strides_0, weight = layers_7_encoder_attn_q_proj_weight_to_fp16, x = obj_107_cast_fp16)[name = tensor("query_31_cast_fp16")]; + tensor key_31_pad_type_0 = const()[name = tensor("key_31_pad_type_0"), val = tensor("valid")]; + tensor key_31_strides_0 = const()[name = tensor("key_31_strides_0"), val = tensor([1, 1])]; + tensor key_31_pad_0 = const()[name = tensor("key_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_31_dilations_0 = const()[name = tensor("key_31_dilations_0"), val = tensor([1, 1])]; + tensor key_31_groups_0 = const()[name = tensor("key_31_groups_0"), val = tensor(1)]; + tensor layers_7_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_7_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(352779904)))]; + tensor key_31_cast_fp16 = conv(dilations = key_31_dilations_0, groups = key_31_groups_0, pad = key_31_pad_0, pad_type = key_31_pad_type_0, strides = key_31_strides_0, weight = layers_7_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_31_cast_fp16")]; + tensor value_31_pad_type_0 = const()[name = tensor("value_31_pad_type_0"), val = tensor("valid")]; + tensor value_31_strides_0 = const()[name = tensor("value_31_strides_0"), val = tensor([1, 1])]; + tensor value_31_pad_0 = const()[name = tensor("value_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_31_dilations_0 = const()[name = tensor("value_31_dilations_0"), val = tensor([1, 1])]; + tensor value_31_groups_0 = const()[name = tensor("value_31_groups_0"), val = tensor(1)]; + tensor layers_7_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_7_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(354877120)))]; + tensor layers_7_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_7_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(356974336)))]; + tensor value_31_cast_fp16 = conv(bias = layers_7_encoder_attn_v_proj_bias_to_fp16, dilations = value_31_dilations_0, groups = value_31_groups_0, pad = value_31_pad_0, pad_type = value_31_pad_type_0, strides = value_31_strides_0, weight = layers_7_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_31_cast_fp16")]; + tensor var_1828 = const()[name = tensor("op_1828"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_31_cast_fp16 = reshape(shape = var_1828, x = query_31_cast_fp16)[name = tensor("mh_q_31_cast_fp16")]; + tensor var_1830_to_fp16 = const()[name = tensor("op_1830_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1831_cast_fp16 = mul(x = mh_q_31_cast_fp16, y = var_1830_to_fp16)[name = tensor("op_1831_cast_fp16")]; + tensor var_1834 = const()[name = tensor("op_1834"), val = tensor([1, 16, 64, 1500])]; + tensor var_1835_cast_fp16 = reshape(shape = var_1834, x = key_31_cast_fp16)[name = tensor("op_1835_cast_fp16")]; + tensor mh_w_47_transpose_x_0 = const()[name = tensor("mh_w_47_transpose_x_0"), val = tensor(true)]; + tensor mh_w_47_transpose_y_0 = const()[name = tensor("mh_w_47_transpose_y_0"), val = tensor(false)]; + tensor mh_w_47_cast_fp16 = matmul(transpose_x = mh_w_47_transpose_x_0, transpose_y = mh_w_47_transpose_y_0, x = var_1831_cast_fp16, y = var_1835_cast_fp16)[name = tensor("mh_w_47_cast_fp16")]; + tensor obj_111_cast_fp16 = softmax(axis = var_1677, x = mh_w_47_cast_fp16)[name = tensor("obj_111_cast_fp16")]; + tensor var_1839 = const()[name = tensor("op_1839"), val = tensor([1, 16, 64, 1500])]; + tensor var_1840_cast_fp16 = reshape(shape = var_1839, x = value_31_cast_fp16)[name = tensor("op_1840_cast_fp16")]; + tensor attn_31_transpose_x_0 = const()[name = tensor("attn_31_transpose_x_0"), val = tensor(false)]; + tensor attn_31_transpose_y_0 = const()[name = tensor("attn_31_transpose_y_0"), val = tensor(true)]; + tensor attn_31_cast_fp16 = matmul(transpose_x = attn_31_transpose_x_0, transpose_y = attn_31_transpose_y_0, x = var_1840_cast_fp16, y = obj_111_cast_fp16)[name = tensor("attn_31_cast_fp16")]; + tensor var_1843 = const()[name = tensor("op_1843"), val = tensor([1, 1024, 1, 1])]; + tensor input_73_cast_fp16 = reshape(shape = var_1843, x = attn_31_cast_fp16)[name = tensor("input_73_cast_fp16")]; + tensor obj_109_pad_type_0 = const()[name = tensor("obj_109_pad_type_0"), val = tensor("valid")]; + tensor obj_109_strides_0 = const()[name = tensor("obj_109_strides_0"), val = tensor([1, 1])]; + tensor obj_109_pad_0 = const()[name = tensor("obj_109_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_109_dilations_0 = const()[name = tensor("obj_109_dilations_0"), val = tensor([1, 1])]; + tensor obj_109_groups_0 = const()[name = tensor("obj_109_groups_0"), val = tensor(1)]; + tensor layers_7_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_7_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(356976448)))]; + tensor layers_7_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_7_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(359073664)))]; + tensor obj_109_cast_fp16 = conv(bias = layers_7_encoder_attn_o_proj_bias_to_fp16, dilations = obj_109_dilations_0, groups = obj_109_groups_0, pad = obj_109_pad_0, pad_type = obj_109_pad_type_0, strides = obj_109_strides_0, weight = layers_7_encoder_attn_o_proj_weight_to_fp16, x = input_73_cast_fp16)[name = tensor("obj_109_cast_fp16")]; + tensor inputs_47_cast_fp16 = add(x = inputs_45_cast_fp16, y = obj_109_cast_fp16)[name = tensor("inputs_47_cast_fp16")]; + tensor out_47_axes_0 = const()[name = tensor("out_47_axes_0"), val = tensor([1])]; + tensor var_1861_to_fp16 = const()[name = tensor("op_1861_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_47_cast_fp16 = layer_norm(axes = out_47_axes_0, epsilon = var_1861_to_fp16, x = inputs_47_cast_fp16)[name = tensor("out_47_cast_fp16")]; + tensor input_75_gamma_0_to_fp16 = const()[name = tensor("input_75_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(359075776)))]; + tensor input_75_beta_0_to_fp16 = const()[name = tensor("input_75_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(359077888)))]; + tensor input_75_epsilon_0_to_fp16 = const()[name = tensor("input_75_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_75_cast_fp16 = batch_norm(beta = input_75_beta_0_to_fp16, epsilon = input_75_epsilon_0_to_fp16, gamma = input_75_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_47_cast_fp16)[name = tensor("input_75_cast_fp16")]; + tensor input_77_pad_type_0 = const()[name = tensor("input_77_pad_type_0"), val = tensor("valid")]; + tensor input_77_strides_0 = const()[name = tensor("input_77_strides_0"), val = tensor([1, 1])]; + tensor input_77_pad_0 = const()[name = tensor("input_77_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_77_dilations_0 = const()[name = tensor("input_77_dilations_0"), val = tensor([1, 1])]; + tensor input_77_groups_0 = const()[name = tensor("input_77_groups_0"), val = tensor(1)]; + tensor layers_7_fc1_weight_to_fp16 = const()[name = tensor("layers_7_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(359080000)))]; + tensor layers_7_fc1_bias_to_fp16 = const()[name = tensor("layers_7_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(367468672)))]; + tensor input_77_cast_fp16 = conv(bias = layers_7_fc1_bias_to_fp16, dilations = input_77_dilations_0, groups = input_77_groups_0, pad = input_77_pad_0, pad_type = input_77_pad_type_0, strides = input_77_strides_0, weight = layers_7_fc1_weight_to_fp16, x = input_75_cast_fp16)[name = tensor("input_77_cast_fp16")]; + tensor input_79_mode_0 = const()[name = tensor("input_79_mode_0"), val = tensor("EXACT")]; + tensor input_79_cast_fp16 = gelu(mode = input_79_mode_0, x = input_77_cast_fp16)[name = tensor("input_79_cast_fp16")]; + tensor hidden_states_17_pad_type_0 = const()[name = tensor("hidden_states_17_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_17_strides_0 = const()[name = tensor("hidden_states_17_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_17_pad_0 = const()[name = tensor("hidden_states_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_17_dilations_0 = const()[name = tensor("hidden_states_17_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_17_groups_0 = const()[name = tensor("hidden_states_17_groups_0"), val = tensor(1)]; + tensor layers_7_fc2_weight_to_fp16 = const()[name = tensor("layers_7_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(367476928)))]; + tensor layers_7_fc2_bias_to_fp16 = const()[name = tensor("layers_7_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(375865600)))]; + tensor hidden_states_17_cast_fp16 = conv(bias = layers_7_fc2_bias_to_fp16, dilations = hidden_states_17_dilations_0, groups = hidden_states_17_groups_0, pad = hidden_states_17_pad_0, pad_type = hidden_states_17_pad_type_0, strides = hidden_states_17_strides_0, weight = layers_7_fc2_weight_to_fp16, x = input_79_cast_fp16)[name = tensor("hidden_states_17_cast_fp16")]; + tensor inputs_49_cast_fp16 = add(x = inputs_47_cast_fp16, y = hidden_states_17_cast_fp16)[name = tensor("inputs_49_cast_fp16")]; + tensor var_1896 = const()[name = tensor("op_1896"), val = tensor(3)]; + tensor out_49_axes_0 = const()[name = tensor("out_49_axes_0"), val = tensor([1])]; + tensor var_1921_to_fp16 = const()[name = tensor("op_1921_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_49_cast_fp16 = layer_norm(axes = out_49_axes_0, epsilon = var_1921_to_fp16, x = inputs_49_cast_fp16)[name = tensor("out_49_cast_fp16")]; + tensor obj_113_gamma_0_to_fp16 = const()[name = tensor("obj_113_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(375867712)))]; + tensor obj_113_beta_0_to_fp16 = const()[name = tensor("obj_113_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(375869824)))]; + tensor obj_113_epsilon_0_to_fp16 = const()[name = tensor("obj_113_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_113_cast_fp16 = batch_norm(beta = obj_113_beta_0_to_fp16, epsilon = obj_113_epsilon_0_to_fp16, gamma = obj_113_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_49_cast_fp16)[name = tensor("obj_113_cast_fp16")]; + tensor query_33_pad_type_0 = const()[name = tensor("query_33_pad_type_0"), val = tensor("valid")]; + tensor query_33_strides_0 = const()[name = tensor("query_33_strides_0"), val = tensor([1, 1])]; + tensor query_33_pad_0 = const()[name = tensor("query_33_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_33_dilations_0 = const()[name = tensor("query_33_dilations_0"), val = tensor([1, 1])]; + tensor query_33_groups_0 = const()[name = tensor("query_33_groups_0"), val = tensor(1)]; + tensor layers_8_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(375871936)))]; + tensor layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(377969152)))]; + tensor query_33_cast_fp16 = conv(bias = layers_8_self_attn_q_proj_bias_to_fp16, dilations = query_33_dilations_0, groups = query_33_groups_0, pad = query_33_pad_0, pad_type = query_33_pad_type_0, strides = query_33_strides_0, weight = layers_8_self_attn_q_proj_weight_to_fp16, x = obj_113_cast_fp16)[name = tensor("query_33_cast_fp16")]; + tensor current_key_17_pad_type_0 = const()[name = tensor("current_key_17_pad_type_0"), val = tensor("valid")]; + tensor current_key_17_strides_0 = const()[name = tensor("current_key_17_strides_0"), val = tensor([1, 1])]; + tensor current_key_17_pad_0 = const()[name = tensor("current_key_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_17_dilations_0 = const()[name = tensor("current_key_17_dilations_0"), val = tensor([1, 1])]; + tensor current_key_17_groups_0 = const()[name = tensor("current_key_17_groups_0"), val = tensor(1)]; + tensor layers_8_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(377971264)))]; + tensor current_key_17_cast_fp16 = conv(dilations = current_key_17_dilations_0, groups = current_key_17_groups_0, pad = current_key_17_pad_0, pad_type = current_key_17_pad_type_0, strides = current_key_17_strides_0, weight = layers_8_self_attn_k_proj_weight_to_fp16, x = obj_113_cast_fp16)[name = tensor("current_key_17_cast_fp16")]; + tensor current_value_17_pad_type_0 = const()[name = tensor("current_value_17_pad_type_0"), val = tensor("valid")]; + tensor current_value_17_strides_0 = const()[name = tensor("current_value_17_strides_0"), val = tensor([1, 1])]; + tensor current_value_17_pad_0 = const()[name = tensor("current_value_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_17_dilations_0 = const()[name = tensor("current_value_17_dilations_0"), val = tensor([1, 1])]; + tensor current_value_17_groups_0 = const()[name = tensor("current_value_17_groups_0"), val = tensor(1)]; + tensor layers_8_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(380068480)))]; + tensor layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(382165696)))]; + tensor current_value_17_cast_fp16 = conv(bias = layers_8_self_attn_v_proj_bias_to_fp16, dilations = current_value_17_dilations_0, groups = current_value_17_groups_0, pad = current_value_17_pad_0, pad_type = current_value_17_pad_type_0, strides = current_value_17_strides_0, weight = layers_8_self_attn_v_proj_weight_to_fp16, x = obj_113_cast_fp16)[name = tensor("current_value_17_cast_fp16")]; + tensor var_1960_cast_fp16 = mul(x = var_87_cast_fp16_8, y = var_207_cast_fp16)[name = tensor("op_1960_cast_fp16")]; + tensor var_1961_cast_fp16 = mul(x = current_key_17_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_1961_cast_fp16")]; + tensor key_33_cast_fp16 = add(x = var_1960_cast_fp16, y = var_1961_cast_fp16)[name = tensor("key_33_cast_fp16")]; + tensor var_1964_cast_fp16 = mul(x = var_114_cast_fp16_8, y = var_207_cast_fp16)[name = tensor("op_1964_cast_fp16")]; + tensor var_1965_cast_fp16 = mul(x = current_value_17_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_1965_cast_fp16")]; + tensor value_33_cast_fp16 = add(x = var_1964_cast_fp16, y = var_1965_cast_fp16)[name = tensor("value_33_cast_fp16")]; + tensor var_1969 = const()[name = tensor("op_1969"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_33_cast_fp16 = reshape(shape = var_1969, x = query_33_cast_fp16)[name = tensor("mh_q_33_cast_fp16")]; + tensor var_1971_to_fp16 = const()[name = tensor("op_1971_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1972_cast_fp16 = mul(x = mh_q_33_cast_fp16, y = var_1971_to_fp16)[name = tensor("op_1972_cast_fp16")]; + tensor var_1975 = const()[name = tensor("op_1975"), val = tensor([1, 16, 64, 448])]; + tensor var_1976_cast_fp16 = reshape(shape = var_1975, x = key_33_cast_fp16)[name = tensor("op_1976_cast_fp16")]; + tensor mh_w_49_transpose_x_0 = const()[name = tensor("mh_w_49_transpose_x_0"), val = tensor(true)]; + tensor mh_w_49_transpose_y_0 = const()[name = tensor("mh_w_49_transpose_y_0"), val = tensor(false)]; + tensor mh_w_49_cast_fp16 = matmul(transpose_x = mh_w_49_transpose_x_0, transpose_y = mh_w_49_transpose_y_0, x = var_1972_cast_fp16, y = var_1976_cast_fp16)[name = tensor("mh_w_49_cast_fp16")]; + tensor mh_w_51_cast_fp16 = add(x = mh_w_49_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_51_cast_fp16")]; + tensor var_1984_cast_fp16 = softmax(axis = var_1896, x = mh_w_51_cast_fp16)[name = tensor("op_1984_cast_fp16")]; + tensor var_1985 = const()[name = tensor("op_1985"), val = tensor([1, 16, 64, 448])]; + tensor var_1986_cast_fp16 = reshape(shape = var_1985, x = value_33_cast_fp16)[name = tensor("op_1986_cast_fp16")]; + tensor attn_33_transpose_x_0 = const()[name = tensor("attn_33_transpose_x_0"), val = tensor(false)]; + tensor attn_33_transpose_y_0 = const()[name = tensor("attn_33_transpose_y_0"), val = tensor(true)]; + tensor attn_33_cast_fp16 = matmul(transpose_x = attn_33_transpose_x_0, transpose_y = attn_33_transpose_y_0, x = var_1986_cast_fp16, y = var_1984_cast_fp16)[name = tensor("attn_33_cast_fp16")]; + tensor var_1989 = const()[name = tensor("op_1989"), val = tensor([1, 1024, 1, 1])]; + tensor input_81_cast_fp16 = reshape(shape = var_1989, x = attn_33_cast_fp16)[name = tensor("input_81_cast_fp16")]; + tensor obj_119_pad_type_0 = const()[name = tensor("obj_119_pad_type_0"), val = tensor("valid")]; + tensor obj_119_strides_0 = const()[name = tensor("obj_119_strides_0"), val = tensor([1, 1])]; + tensor obj_119_pad_0 = const()[name = tensor("obj_119_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_119_dilations_0 = const()[name = tensor("obj_119_dilations_0"), val = tensor([1, 1])]; + tensor obj_119_groups_0 = const()[name = tensor("obj_119_groups_0"), val = tensor(1)]; + tensor layers_8_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(382167808)))]; + tensor layers_8_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(384265024)))]; + tensor obj_119_cast_fp16 = conv(bias = layers_8_self_attn_o_proj_bias_to_fp16, dilations = obj_119_dilations_0, groups = obj_119_groups_0, pad = obj_119_pad_0, pad_type = obj_119_pad_type_0, strides = obj_119_strides_0, weight = layers_8_self_attn_o_proj_weight_to_fp16, x = input_81_cast_fp16)[name = tensor("obj_119_cast_fp16")]; + tensor inputs_51_cast_fp16 = add(x = inputs_49_cast_fp16, y = obj_119_cast_fp16)[name = tensor("inputs_51_cast_fp16")]; + tensor out_51_axes_0 = const()[name = tensor("out_51_axes_0"), val = tensor([1])]; + tensor var_2011_to_fp16 = const()[name = tensor("op_2011_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_51_cast_fp16 = layer_norm(axes = out_51_axes_0, epsilon = var_2011_to_fp16, x = inputs_51_cast_fp16)[name = tensor("out_51_cast_fp16")]; + tensor obj_121_gamma_0_to_fp16 = const()[name = tensor("obj_121_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(384267136)))]; + tensor obj_121_beta_0_to_fp16 = const()[name = tensor("obj_121_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(384269248)))]; + tensor obj_121_epsilon_0_to_fp16 = const()[name = tensor("obj_121_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_121_cast_fp16 = batch_norm(beta = obj_121_beta_0_to_fp16, epsilon = obj_121_epsilon_0_to_fp16, gamma = obj_121_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_51_cast_fp16)[name = tensor("obj_121_cast_fp16")]; + tensor query_35_pad_type_0 = const()[name = tensor("query_35_pad_type_0"), val = tensor("valid")]; + tensor query_35_strides_0 = const()[name = tensor("query_35_strides_0"), val = tensor([1, 1])]; + tensor query_35_pad_0 = const()[name = tensor("query_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_35_dilations_0 = const()[name = tensor("query_35_dilations_0"), val = tensor([1, 1])]; + tensor query_35_groups_0 = const()[name = tensor("query_35_groups_0"), val = tensor(1)]; + tensor layers_8_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_8_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(384271360)))]; + tensor layers_8_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_8_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(386368576)))]; + tensor query_35_cast_fp16 = conv(bias = layers_8_encoder_attn_q_proj_bias_to_fp16, dilations = query_35_dilations_0, groups = query_35_groups_0, pad = query_35_pad_0, pad_type = query_35_pad_type_0, strides = query_35_strides_0, weight = layers_8_encoder_attn_q_proj_weight_to_fp16, x = obj_121_cast_fp16)[name = tensor("query_35_cast_fp16")]; + tensor key_35_pad_type_0 = const()[name = tensor("key_35_pad_type_0"), val = tensor("valid")]; + tensor key_35_strides_0 = const()[name = tensor("key_35_strides_0"), val = tensor([1, 1])]; + tensor key_35_pad_0 = const()[name = tensor("key_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_35_dilations_0 = const()[name = tensor("key_35_dilations_0"), val = tensor([1, 1])]; + tensor key_35_groups_0 = const()[name = tensor("key_35_groups_0"), val = tensor(1)]; + tensor layers_8_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_8_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(386370688)))]; + tensor key_35_cast_fp16 = conv(dilations = key_35_dilations_0, groups = key_35_groups_0, pad = key_35_pad_0, pad_type = key_35_pad_type_0, strides = key_35_strides_0, weight = layers_8_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_35_cast_fp16")]; + tensor value_35_pad_type_0 = const()[name = tensor("value_35_pad_type_0"), val = tensor("valid")]; + tensor value_35_strides_0 = const()[name = tensor("value_35_strides_0"), val = tensor([1, 1])]; + tensor value_35_pad_0 = const()[name = tensor("value_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_35_dilations_0 = const()[name = tensor("value_35_dilations_0"), val = tensor([1, 1])]; + tensor value_35_groups_0 = const()[name = tensor("value_35_groups_0"), val = tensor(1)]; + tensor layers_8_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_8_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(388467904)))]; + tensor layers_8_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_8_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(390565120)))]; + tensor value_35_cast_fp16 = conv(bias = layers_8_encoder_attn_v_proj_bias_to_fp16, dilations = value_35_dilations_0, groups = value_35_groups_0, pad = value_35_pad_0, pad_type = value_35_pad_type_0, strides = value_35_strides_0, weight = layers_8_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_35_cast_fp16")]; + tensor var_2047 = const()[name = tensor("op_2047"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_35_cast_fp16 = reshape(shape = var_2047, x = query_35_cast_fp16)[name = tensor("mh_q_35_cast_fp16")]; + tensor var_2049_to_fp16 = const()[name = tensor("op_2049_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2050_cast_fp16 = mul(x = mh_q_35_cast_fp16, y = var_2049_to_fp16)[name = tensor("op_2050_cast_fp16")]; + tensor var_2053 = const()[name = tensor("op_2053"), val = tensor([1, 16, 64, 1500])]; + tensor var_2054_cast_fp16 = reshape(shape = var_2053, x = key_35_cast_fp16)[name = tensor("op_2054_cast_fp16")]; + tensor mh_w_53_transpose_x_0 = const()[name = tensor("mh_w_53_transpose_x_0"), val = tensor(true)]; + tensor mh_w_53_transpose_y_0 = const()[name = tensor("mh_w_53_transpose_y_0"), val = tensor(false)]; + tensor mh_w_53_cast_fp16 = matmul(transpose_x = mh_w_53_transpose_x_0, transpose_y = mh_w_53_transpose_y_0, x = var_2050_cast_fp16, y = var_2054_cast_fp16)[name = tensor("mh_w_53_cast_fp16")]; + tensor obj_125_cast_fp16 = softmax(axis = var_1896, x = mh_w_53_cast_fp16)[name = tensor("obj_125_cast_fp16")]; + tensor var_2058 = const()[name = tensor("op_2058"), val = tensor([1, 16, 64, 1500])]; + tensor var_2059_cast_fp16 = reshape(shape = var_2058, x = value_35_cast_fp16)[name = tensor("op_2059_cast_fp16")]; + tensor attn_35_transpose_x_0 = const()[name = tensor("attn_35_transpose_x_0"), val = tensor(false)]; + tensor attn_35_transpose_y_0 = const()[name = tensor("attn_35_transpose_y_0"), val = tensor(true)]; + tensor attn_35_cast_fp16 = matmul(transpose_x = attn_35_transpose_x_0, transpose_y = attn_35_transpose_y_0, x = var_2059_cast_fp16, y = obj_125_cast_fp16)[name = tensor("attn_35_cast_fp16")]; + tensor var_2062 = const()[name = tensor("op_2062"), val = tensor([1, 1024, 1, 1])]; + tensor input_83_cast_fp16 = reshape(shape = var_2062, x = attn_35_cast_fp16)[name = tensor("input_83_cast_fp16")]; + tensor obj_123_pad_type_0 = const()[name = tensor("obj_123_pad_type_0"), val = tensor("valid")]; + tensor obj_123_strides_0 = const()[name = tensor("obj_123_strides_0"), val = tensor([1, 1])]; + tensor obj_123_pad_0 = const()[name = tensor("obj_123_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_123_dilations_0 = const()[name = tensor("obj_123_dilations_0"), val = tensor([1, 1])]; + tensor obj_123_groups_0 = const()[name = tensor("obj_123_groups_0"), val = tensor(1)]; + tensor layers_8_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_8_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(390567232)))]; + tensor layers_8_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_8_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(392664448)))]; + tensor obj_123_cast_fp16 = conv(bias = layers_8_encoder_attn_o_proj_bias_to_fp16, dilations = obj_123_dilations_0, groups = obj_123_groups_0, pad = obj_123_pad_0, pad_type = obj_123_pad_type_0, strides = obj_123_strides_0, weight = layers_8_encoder_attn_o_proj_weight_to_fp16, x = input_83_cast_fp16)[name = tensor("obj_123_cast_fp16")]; + tensor inputs_53_cast_fp16 = add(x = inputs_51_cast_fp16, y = obj_123_cast_fp16)[name = tensor("inputs_53_cast_fp16")]; + tensor out_53_axes_0 = const()[name = tensor("out_53_axes_0"), val = tensor([1])]; + tensor var_2080_to_fp16 = const()[name = tensor("op_2080_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_53_cast_fp16 = layer_norm(axes = out_53_axes_0, epsilon = var_2080_to_fp16, x = inputs_53_cast_fp16)[name = tensor("out_53_cast_fp16")]; + tensor input_85_gamma_0_to_fp16 = const()[name = tensor("input_85_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(392666560)))]; + tensor input_85_beta_0_to_fp16 = const()[name = tensor("input_85_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(392668672)))]; + tensor input_85_epsilon_0_to_fp16 = const()[name = tensor("input_85_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_85_cast_fp16 = batch_norm(beta = input_85_beta_0_to_fp16, epsilon = input_85_epsilon_0_to_fp16, gamma = input_85_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_53_cast_fp16)[name = tensor("input_85_cast_fp16")]; + tensor input_87_pad_type_0 = const()[name = tensor("input_87_pad_type_0"), val = tensor("valid")]; + tensor input_87_strides_0 = const()[name = tensor("input_87_strides_0"), val = tensor([1, 1])]; + tensor input_87_pad_0 = const()[name = tensor("input_87_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_87_dilations_0 = const()[name = tensor("input_87_dilations_0"), val = tensor([1, 1])]; + tensor input_87_groups_0 = const()[name = tensor("input_87_groups_0"), val = tensor(1)]; + tensor layers_8_fc1_weight_to_fp16 = const()[name = tensor("layers_8_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(392670784)))]; + tensor layers_8_fc1_bias_to_fp16 = const()[name = tensor("layers_8_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(401059456)))]; + tensor input_87_cast_fp16 = conv(bias = layers_8_fc1_bias_to_fp16, dilations = input_87_dilations_0, groups = input_87_groups_0, pad = input_87_pad_0, pad_type = input_87_pad_type_0, strides = input_87_strides_0, weight = layers_8_fc1_weight_to_fp16, x = input_85_cast_fp16)[name = tensor("input_87_cast_fp16")]; + tensor input_89_mode_0 = const()[name = tensor("input_89_mode_0"), val = tensor("EXACT")]; + tensor input_89_cast_fp16 = gelu(mode = input_89_mode_0, x = input_87_cast_fp16)[name = tensor("input_89_cast_fp16")]; + tensor hidden_states_19_pad_type_0 = const()[name = tensor("hidden_states_19_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_19_strides_0 = const()[name = tensor("hidden_states_19_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_19_pad_0 = const()[name = tensor("hidden_states_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_19_dilations_0 = const()[name = tensor("hidden_states_19_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_19_groups_0 = const()[name = tensor("hidden_states_19_groups_0"), val = tensor(1)]; + tensor layers_8_fc2_weight_to_fp16 = const()[name = tensor("layers_8_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(401067712)))]; + tensor layers_8_fc2_bias_to_fp16 = const()[name = tensor("layers_8_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(409456384)))]; + tensor hidden_states_19_cast_fp16 = conv(bias = layers_8_fc2_bias_to_fp16, dilations = hidden_states_19_dilations_0, groups = hidden_states_19_groups_0, pad = hidden_states_19_pad_0, pad_type = hidden_states_19_pad_type_0, strides = hidden_states_19_strides_0, weight = layers_8_fc2_weight_to_fp16, x = input_89_cast_fp16)[name = tensor("hidden_states_19_cast_fp16")]; + tensor inputs_55_cast_fp16 = add(x = inputs_53_cast_fp16, y = hidden_states_19_cast_fp16)[name = tensor("inputs_55_cast_fp16")]; + tensor var_2115 = const()[name = tensor("op_2115"), val = tensor(3)]; + tensor out_55_axes_0 = const()[name = tensor("out_55_axes_0"), val = tensor([1])]; + tensor var_2140_to_fp16 = const()[name = tensor("op_2140_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_55_cast_fp16 = layer_norm(axes = out_55_axes_0, epsilon = var_2140_to_fp16, x = inputs_55_cast_fp16)[name = tensor("out_55_cast_fp16")]; + tensor obj_127_gamma_0_to_fp16 = const()[name = tensor("obj_127_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(409458496)))]; + tensor obj_127_beta_0_to_fp16 = const()[name = tensor("obj_127_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(409460608)))]; + tensor obj_127_epsilon_0_to_fp16 = const()[name = tensor("obj_127_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_127_cast_fp16 = batch_norm(beta = obj_127_beta_0_to_fp16, epsilon = obj_127_epsilon_0_to_fp16, gamma = obj_127_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_55_cast_fp16)[name = tensor("obj_127_cast_fp16")]; + tensor query_37_pad_type_0 = const()[name = tensor("query_37_pad_type_0"), val = tensor("valid")]; + tensor query_37_strides_0 = const()[name = tensor("query_37_strides_0"), val = tensor([1, 1])]; + tensor query_37_pad_0 = const()[name = tensor("query_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_37_dilations_0 = const()[name = tensor("query_37_dilations_0"), val = tensor([1, 1])]; + tensor query_37_groups_0 = const()[name = tensor("query_37_groups_0"), val = tensor(1)]; + tensor layers_9_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(409462720)))]; + tensor layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(411559936)))]; + tensor query_37_cast_fp16 = conv(bias = layers_9_self_attn_q_proj_bias_to_fp16, dilations = query_37_dilations_0, groups = query_37_groups_0, pad = query_37_pad_0, pad_type = query_37_pad_type_0, strides = query_37_strides_0, weight = layers_9_self_attn_q_proj_weight_to_fp16, x = obj_127_cast_fp16)[name = tensor("query_37_cast_fp16")]; + tensor current_key_19_pad_type_0 = const()[name = tensor("current_key_19_pad_type_0"), val = tensor("valid")]; + tensor current_key_19_strides_0 = const()[name = tensor("current_key_19_strides_0"), val = tensor([1, 1])]; + tensor current_key_19_pad_0 = const()[name = tensor("current_key_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_19_dilations_0 = const()[name = tensor("current_key_19_dilations_0"), val = tensor([1, 1])]; + tensor current_key_19_groups_0 = const()[name = tensor("current_key_19_groups_0"), val = tensor(1)]; + tensor layers_9_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(411562048)))]; + tensor current_key_19_cast_fp16 = conv(dilations = current_key_19_dilations_0, groups = current_key_19_groups_0, pad = current_key_19_pad_0, pad_type = current_key_19_pad_type_0, strides = current_key_19_strides_0, weight = layers_9_self_attn_k_proj_weight_to_fp16, x = obj_127_cast_fp16)[name = tensor("current_key_19_cast_fp16")]; + tensor current_value_19_pad_type_0 = const()[name = tensor("current_value_19_pad_type_0"), val = tensor("valid")]; + tensor current_value_19_strides_0 = const()[name = tensor("current_value_19_strides_0"), val = tensor([1, 1])]; + tensor current_value_19_pad_0 = const()[name = tensor("current_value_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_19_dilations_0 = const()[name = tensor("current_value_19_dilations_0"), val = tensor([1, 1])]; + tensor current_value_19_groups_0 = const()[name = tensor("current_value_19_groups_0"), val = tensor(1)]; + tensor layers_9_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(413659264)))]; + tensor layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(415756480)))]; + tensor current_value_19_cast_fp16 = conv(bias = layers_9_self_attn_v_proj_bias_to_fp16, dilations = current_value_19_dilations_0, groups = current_value_19_groups_0, pad = current_value_19_pad_0, pad_type = current_value_19_pad_type_0, strides = current_value_19_strides_0, weight = layers_9_self_attn_v_proj_weight_to_fp16, x = obj_127_cast_fp16)[name = tensor("current_value_19_cast_fp16")]; + tensor var_2179_cast_fp16 = mul(x = var_87_cast_fp16_9, y = var_207_cast_fp16)[name = tensor("op_2179_cast_fp16")]; + tensor var_2180_cast_fp16 = mul(x = current_key_19_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_2180_cast_fp16")]; + tensor key_37_cast_fp16 = add(x = var_2179_cast_fp16, y = var_2180_cast_fp16)[name = tensor("key_37_cast_fp16")]; + tensor var_2183_cast_fp16 = mul(x = var_114_cast_fp16_9, y = var_207_cast_fp16)[name = tensor("op_2183_cast_fp16")]; + tensor var_2184_cast_fp16 = mul(x = current_value_19_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_2184_cast_fp16")]; + tensor value_37_cast_fp16 = add(x = var_2183_cast_fp16, y = var_2184_cast_fp16)[name = tensor("value_37_cast_fp16")]; + tensor var_2188 = const()[name = tensor("op_2188"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_37_cast_fp16 = reshape(shape = var_2188, x = query_37_cast_fp16)[name = tensor("mh_q_37_cast_fp16")]; + tensor var_2190_to_fp16 = const()[name = tensor("op_2190_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2191_cast_fp16 = mul(x = mh_q_37_cast_fp16, y = var_2190_to_fp16)[name = tensor("op_2191_cast_fp16")]; + tensor var_2194 = const()[name = tensor("op_2194"), val = tensor([1, 16, 64, 448])]; + tensor var_2195_cast_fp16 = reshape(shape = var_2194, x = key_37_cast_fp16)[name = tensor("op_2195_cast_fp16")]; + tensor mh_w_55_transpose_x_0 = const()[name = tensor("mh_w_55_transpose_x_0"), val = tensor(true)]; + tensor mh_w_55_transpose_y_0 = const()[name = tensor("mh_w_55_transpose_y_0"), val = tensor(false)]; + tensor mh_w_55_cast_fp16 = matmul(transpose_x = mh_w_55_transpose_x_0, transpose_y = mh_w_55_transpose_y_0, x = var_2191_cast_fp16, y = var_2195_cast_fp16)[name = tensor("mh_w_55_cast_fp16")]; + tensor mh_w_57_cast_fp16 = add(x = mh_w_55_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_57_cast_fp16")]; + tensor var_2203_cast_fp16 = softmax(axis = var_2115, x = mh_w_57_cast_fp16)[name = tensor("op_2203_cast_fp16")]; + tensor var_2204 = const()[name = tensor("op_2204"), val = tensor([1, 16, 64, 448])]; + tensor var_2205_cast_fp16 = reshape(shape = var_2204, x = value_37_cast_fp16)[name = tensor("op_2205_cast_fp16")]; + tensor attn_37_transpose_x_0 = const()[name = tensor("attn_37_transpose_x_0"), val = tensor(false)]; + tensor attn_37_transpose_y_0 = const()[name = tensor("attn_37_transpose_y_0"), val = tensor(true)]; + tensor attn_37_cast_fp16 = matmul(transpose_x = attn_37_transpose_x_0, transpose_y = attn_37_transpose_y_0, x = var_2205_cast_fp16, y = var_2203_cast_fp16)[name = tensor("attn_37_cast_fp16")]; + tensor var_2208 = const()[name = tensor("op_2208"), val = tensor([1, 1024, 1, 1])]; + tensor input_91_cast_fp16 = reshape(shape = var_2208, x = attn_37_cast_fp16)[name = tensor("input_91_cast_fp16")]; + tensor obj_133_pad_type_0 = const()[name = tensor("obj_133_pad_type_0"), val = tensor("valid")]; + tensor obj_133_strides_0 = const()[name = tensor("obj_133_strides_0"), val = tensor([1, 1])]; + tensor obj_133_pad_0 = const()[name = tensor("obj_133_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_133_dilations_0 = const()[name = tensor("obj_133_dilations_0"), val = tensor([1, 1])]; + tensor obj_133_groups_0 = const()[name = tensor("obj_133_groups_0"), val = tensor(1)]; + tensor layers_9_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(415758592)))]; + tensor layers_9_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417855808)))]; + tensor obj_133_cast_fp16 = conv(bias = layers_9_self_attn_o_proj_bias_to_fp16, dilations = obj_133_dilations_0, groups = obj_133_groups_0, pad = obj_133_pad_0, pad_type = obj_133_pad_type_0, strides = obj_133_strides_0, weight = layers_9_self_attn_o_proj_weight_to_fp16, x = input_91_cast_fp16)[name = tensor("obj_133_cast_fp16")]; + tensor inputs_57_cast_fp16 = add(x = inputs_55_cast_fp16, y = obj_133_cast_fp16)[name = tensor("inputs_57_cast_fp16")]; + tensor out_57_axes_0 = const()[name = tensor("out_57_axes_0"), val = tensor([1])]; + tensor var_2230_to_fp16 = const()[name = tensor("op_2230_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_57_cast_fp16 = layer_norm(axes = out_57_axes_0, epsilon = var_2230_to_fp16, x = inputs_57_cast_fp16)[name = tensor("out_57_cast_fp16")]; + tensor obj_135_gamma_0_to_fp16 = const()[name = tensor("obj_135_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417857920)))]; + tensor obj_135_beta_0_to_fp16 = const()[name = tensor("obj_135_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417860032)))]; + tensor obj_135_epsilon_0_to_fp16 = const()[name = tensor("obj_135_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_135_cast_fp16 = batch_norm(beta = obj_135_beta_0_to_fp16, epsilon = obj_135_epsilon_0_to_fp16, gamma = obj_135_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_57_cast_fp16)[name = tensor("obj_135_cast_fp16")]; + tensor query_39_pad_type_0 = const()[name = tensor("query_39_pad_type_0"), val = tensor("valid")]; + tensor query_39_strides_0 = const()[name = tensor("query_39_strides_0"), val = tensor([1, 1])]; + tensor query_39_pad_0 = const()[name = tensor("query_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_39_dilations_0 = const()[name = tensor("query_39_dilations_0"), val = tensor([1, 1])]; + tensor query_39_groups_0 = const()[name = tensor("query_39_groups_0"), val = tensor(1)]; + tensor layers_9_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_9_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417862144)))]; + tensor layers_9_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_9_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(419959360)))]; + tensor query_39_cast_fp16 = conv(bias = layers_9_encoder_attn_q_proj_bias_to_fp16, dilations = query_39_dilations_0, groups = query_39_groups_0, pad = query_39_pad_0, pad_type = query_39_pad_type_0, strides = query_39_strides_0, weight = layers_9_encoder_attn_q_proj_weight_to_fp16, x = obj_135_cast_fp16)[name = tensor("query_39_cast_fp16")]; + tensor key_39_pad_type_0 = const()[name = tensor("key_39_pad_type_0"), val = tensor("valid")]; + tensor key_39_strides_0 = const()[name = tensor("key_39_strides_0"), val = tensor([1, 1])]; + tensor key_39_pad_0 = const()[name = tensor("key_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_39_dilations_0 = const()[name = tensor("key_39_dilations_0"), val = tensor([1, 1])]; + tensor key_39_groups_0 = const()[name = tensor("key_39_groups_0"), val = tensor(1)]; + tensor layers_9_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_9_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(419961472)))]; + tensor key_39_cast_fp16 = conv(dilations = key_39_dilations_0, groups = key_39_groups_0, pad = key_39_pad_0, pad_type = key_39_pad_type_0, strides = key_39_strides_0, weight = layers_9_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_39_cast_fp16")]; + tensor value_39_pad_type_0 = const()[name = tensor("value_39_pad_type_0"), val = tensor("valid")]; + tensor value_39_strides_0 = const()[name = tensor("value_39_strides_0"), val = tensor([1, 1])]; + tensor value_39_pad_0 = const()[name = tensor("value_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_39_dilations_0 = const()[name = tensor("value_39_dilations_0"), val = tensor([1, 1])]; + tensor value_39_groups_0 = const()[name = tensor("value_39_groups_0"), val = tensor(1)]; + tensor layers_9_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_9_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(422058688)))]; + tensor layers_9_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_9_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(424155904)))]; + tensor value_39_cast_fp16 = conv(bias = layers_9_encoder_attn_v_proj_bias_to_fp16, dilations = value_39_dilations_0, groups = value_39_groups_0, pad = value_39_pad_0, pad_type = value_39_pad_type_0, strides = value_39_strides_0, weight = layers_9_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_39_cast_fp16")]; + tensor var_2266 = const()[name = tensor("op_2266"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_39_cast_fp16 = reshape(shape = var_2266, x = query_39_cast_fp16)[name = tensor("mh_q_39_cast_fp16")]; + tensor var_2268_to_fp16 = const()[name = tensor("op_2268_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2269_cast_fp16 = mul(x = mh_q_39_cast_fp16, y = var_2268_to_fp16)[name = tensor("op_2269_cast_fp16")]; + tensor var_2272 = const()[name = tensor("op_2272"), val = tensor([1, 16, 64, 1500])]; + tensor var_2273_cast_fp16 = reshape(shape = var_2272, x = key_39_cast_fp16)[name = tensor("op_2273_cast_fp16")]; + tensor mh_w_59_transpose_x_0 = const()[name = tensor("mh_w_59_transpose_x_0"), val = tensor(true)]; + tensor mh_w_59_transpose_y_0 = const()[name = tensor("mh_w_59_transpose_y_0"), val = tensor(false)]; + tensor mh_w_59_cast_fp16 = matmul(transpose_x = mh_w_59_transpose_x_0, transpose_y = mh_w_59_transpose_y_0, x = var_2269_cast_fp16, y = var_2273_cast_fp16)[name = tensor("mh_w_59_cast_fp16")]; + tensor obj_139_cast_fp16 = softmax(axis = var_2115, x = mh_w_59_cast_fp16)[name = tensor("obj_139_cast_fp16")]; + tensor var_2277 = const()[name = tensor("op_2277"), val = tensor([1, 16, 64, 1500])]; + tensor var_2278_cast_fp16 = reshape(shape = var_2277, x = value_39_cast_fp16)[name = tensor("op_2278_cast_fp16")]; + tensor attn_39_transpose_x_0 = const()[name = tensor("attn_39_transpose_x_0"), val = tensor(false)]; + tensor attn_39_transpose_y_0 = const()[name = tensor("attn_39_transpose_y_0"), val = tensor(true)]; + tensor attn_39_cast_fp16 = matmul(transpose_x = attn_39_transpose_x_0, transpose_y = attn_39_transpose_y_0, x = var_2278_cast_fp16, y = obj_139_cast_fp16)[name = tensor("attn_39_cast_fp16")]; + tensor var_2281 = const()[name = tensor("op_2281"), val = tensor([1, 1024, 1, 1])]; + tensor input_93_cast_fp16 = reshape(shape = var_2281, x = attn_39_cast_fp16)[name = tensor("input_93_cast_fp16")]; + tensor obj_137_pad_type_0 = const()[name = tensor("obj_137_pad_type_0"), val = tensor("valid")]; + tensor obj_137_strides_0 = const()[name = tensor("obj_137_strides_0"), val = tensor([1, 1])]; + tensor obj_137_pad_0 = const()[name = tensor("obj_137_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_137_dilations_0 = const()[name = tensor("obj_137_dilations_0"), val = tensor([1, 1])]; + tensor obj_137_groups_0 = const()[name = tensor("obj_137_groups_0"), val = tensor(1)]; + tensor layers_9_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_9_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(424158016)))]; + tensor layers_9_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_9_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(426255232)))]; + tensor obj_137_cast_fp16 = conv(bias = layers_9_encoder_attn_o_proj_bias_to_fp16, dilations = obj_137_dilations_0, groups = obj_137_groups_0, pad = obj_137_pad_0, pad_type = obj_137_pad_type_0, strides = obj_137_strides_0, weight = layers_9_encoder_attn_o_proj_weight_to_fp16, x = input_93_cast_fp16)[name = tensor("obj_137_cast_fp16")]; + tensor inputs_59_cast_fp16 = add(x = inputs_57_cast_fp16, y = obj_137_cast_fp16)[name = tensor("inputs_59_cast_fp16")]; + tensor out_59_axes_0 = const()[name = tensor("out_59_axes_0"), val = tensor([1])]; + tensor var_2299_to_fp16 = const()[name = tensor("op_2299_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_59_cast_fp16 = layer_norm(axes = out_59_axes_0, epsilon = var_2299_to_fp16, x = inputs_59_cast_fp16)[name = tensor("out_59_cast_fp16")]; + tensor input_95_gamma_0_to_fp16 = const()[name = tensor("input_95_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(426257344)))]; + tensor input_95_beta_0_to_fp16 = const()[name = tensor("input_95_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(426259456)))]; + tensor input_95_epsilon_0_to_fp16 = const()[name = tensor("input_95_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_95_cast_fp16 = batch_norm(beta = input_95_beta_0_to_fp16, epsilon = input_95_epsilon_0_to_fp16, gamma = input_95_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_59_cast_fp16)[name = tensor("input_95_cast_fp16")]; + tensor input_97_pad_type_0 = const()[name = tensor("input_97_pad_type_0"), val = tensor("valid")]; + tensor input_97_strides_0 = const()[name = tensor("input_97_strides_0"), val = tensor([1, 1])]; + tensor input_97_pad_0 = const()[name = tensor("input_97_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_97_dilations_0 = const()[name = tensor("input_97_dilations_0"), val = tensor([1, 1])]; + tensor input_97_groups_0 = const()[name = tensor("input_97_groups_0"), val = tensor(1)]; + tensor layers_9_fc1_weight_to_fp16 = const()[name = tensor("layers_9_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(426261568)))]; + tensor layers_9_fc1_bias_to_fp16 = const()[name = tensor("layers_9_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(434650240)))]; + tensor input_97_cast_fp16 = conv(bias = layers_9_fc1_bias_to_fp16, dilations = input_97_dilations_0, groups = input_97_groups_0, pad = input_97_pad_0, pad_type = input_97_pad_type_0, strides = input_97_strides_0, weight = layers_9_fc1_weight_to_fp16, x = input_95_cast_fp16)[name = tensor("input_97_cast_fp16")]; + tensor input_99_mode_0 = const()[name = tensor("input_99_mode_0"), val = tensor("EXACT")]; + tensor input_99_cast_fp16 = gelu(mode = input_99_mode_0, x = input_97_cast_fp16)[name = tensor("input_99_cast_fp16")]; + tensor hidden_states_21_pad_type_0 = const()[name = tensor("hidden_states_21_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_21_strides_0 = const()[name = tensor("hidden_states_21_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_21_pad_0 = const()[name = tensor("hidden_states_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_21_dilations_0 = const()[name = tensor("hidden_states_21_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_21_groups_0 = const()[name = tensor("hidden_states_21_groups_0"), val = tensor(1)]; + tensor layers_9_fc2_weight_to_fp16 = const()[name = tensor("layers_9_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(434658496)))]; + tensor layers_9_fc2_bias_to_fp16 = const()[name = tensor("layers_9_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(443047168)))]; + tensor hidden_states_21_cast_fp16 = conv(bias = layers_9_fc2_bias_to_fp16, dilations = hidden_states_21_dilations_0, groups = hidden_states_21_groups_0, pad = hidden_states_21_pad_0, pad_type = hidden_states_21_pad_type_0, strides = hidden_states_21_strides_0, weight = layers_9_fc2_weight_to_fp16, x = input_99_cast_fp16)[name = tensor("hidden_states_21_cast_fp16")]; + tensor inputs_61_cast_fp16 = add(x = inputs_59_cast_fp16, y = hidden_states_21_cast_fp16)[name = tensor("inputs_61_cast_fp16")]; + tensor var_2334 = const()[name = tensor("op_2334"), val = tensor(3)]; + tensor out_61_axes_0 = const()[name = tensor("out_61_axes_0"), val = tensor([1])]; + tensor var_2359_to_fp16 = const()[name = tensor("op_2359_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_61_cast_fp16 = layer_norm(axes = out_61_axes_0, epsilon = var_2359_to_fp16, x = inputs_61_cast_fp16)[name = tensor("out_61_cast_fp16")]; + tensor obj_141_gamma_0_to_fp16 = const()[name = tensor("obj_141_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(443049280)))]; + tensor obj_141_beta_0_to_fp16 = const()[name = tensor("obj_141_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(443051392)))]; + tensor obj_141_epsilon_0_to_fp16 = const()[name = tensor("obj_141_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_141_cast_fp16 = batch_norm(beta = obj_141_beta_0_to_fp16, epsilon = obj_141_epsilon_0_to_fp16, gamma = obj_141_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_61_cast_fp16)[name = tensor("obj_141_cast_fp16")]; + tensor query_41_pad_type_0 = const()[name = tensor("query_41_pad_type_0"), val = tensor("valid")]; + tensor query_41_strides_0 = const()[name = tensor("query_41_strides_0"), val = tensor([1, 1])]; + tensor query_41_pad_0 = const()[name = tensor("query_41_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_41_dilations_0 = const()[name = tensor("query_41_dilations_0"), val = tensor([1, 1])]; + tensor query_41_groups_0 = const()[name = tensor("query_41_groups_0"), val = tensor(1)]; + tensor layers_10_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(443053504)))]; + tensor layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(445150720)))]; + tensor query_41_cast_fp16 = conv(bias = layers_10_self_attn_q_proj_bias_to_fp16, dilations = query_41_dilations_0, groups = query_41_groups_0, pad = query_41_pad_0, pad_type = query_41_pad_type_0, strides = query_41_strides_0, weight = layers_10_self_attn_q_proj_weight_to_fp16, x = obj_141_cast_fp16)[name = tensor("query_41_cast_fp16")]; + tensor current_key_21_pad_type_0 = const()[name = tensor("current_key_21_pad_type_0"), val = tensor("valid")]; + tensor current_key_21_strides_0 = const()[name = tensor("current_key_21_strides_0"), val = tensor([1, 1])]; + tensor current_key_21_pad_0 = const()[name = tensor("current_key_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_21_dilations_0 = const()[name = tensor("current_key_21_dilations_0"), val = tensor([1, 1])]; + tensor current_key_21_groups_0 = const()[name = tensor("current_key_21_groups_0"), val = tensor(1)]; + tensor layers_10_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(445152832)))]; + tensor current_key_21_cast_fp16 = conv(dilations = current_key_21_dilations_0, groups = current_key_21_groups_0, pad = current_key_21_pad_0, pad_type = current_key_21_pad_type_0, strides = current_key_21_strides_0, weight = layers_10_self_attn_k_proj_weight_to_fp16, x = obj_141_cast_fp16)[name = tensor("current_key_21_cast_fp16")]; + tensor current_value_21_pad_type_0 = const()[name = tensor("current_value_21_pad_type_0"), val = tensor("valid")]; + tensor current_value_21_strides_0 = const()[name = tensor("current_value_21_strides_0"), val = tensor([1, 1])]; + tensor current_value_21_pad_0 = const()[name = tensor("current_value_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_21_dilations_0 = const()[name = tensor("current_value_21_dilations_0"), val = tensor([1, 1])]; + tensor current_value_21_groups_0 = const()[name = tensor("current_value_21_groups_0"), val = tensor(1)]; + tensor layers_10_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(447250048)))]; + tensor layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(449347264)))]; + tensor current_value_21_cast_fp16 = conv(bias = layers_10_self_attn_v_proj_bias_to_fp16, dilations = current_value_21_dilations_0, groups = current_value_21_groups_0, pad = current_value_21_pad_0, pad_type = current_value_21_pad_type_0, strides = current_value_21_strides_0, weight = layers_10_self_attn_v_proj_weight_to_fp16, x = obj_141_cast_fp16)[name = tensor("current_value_21_cast_fp16")]; + tensor var_2398_cast_fp16 = mul(x = var_87_cast_fp16_10, y = var_207_cast_fp16)[name = tensor("op_2398_cast_fp16")]; + tensor var_2399_cast_fp16 = mul(x = current_key_21_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_2399_cast_fp16")]; + tensor key_41_cast_fp16 = add(x = var_2398_cast_fp16, y = var_2399_cast_fp16)[name = tensor("key_41_cast_fp16")]; + tensor var_2402_cast_fp16 = mul(x = var_114_cast_fp16_10, y = var_207_cast_fp16)[name = tensor("op_2402_cast_fp16")]; + tensor var_2403_cast_fp16 = mul(x = current_value_21_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_2403_cast_fp16")]; + tensor value_41_cast_fp16 = add(x = var_2402_cast_fp16, y = var_2403_cast_fp16)[name = tensor("value_41_cast_fp16")]; + tensor var_2407 = const()[name = tensor("op_2407"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_41_cast_fp16 = reshape(shape = var_2407, x = query_41_cast_fp16)[name = tensor("mh_q_41_cast_fp16")]; + tensor var_2409_to_fp16 = const()[name = tensor("op_2409_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2410_cast_fp16 = mul(x = mh_q_41_cast_fp16, y = var_2409_to_fp16)[name = tensor("op_2410_cast_fp16")]; + tensor var_2413 = const()[name = tensor("op_2413"), val = tensor([1, 16, 64, 448])]; + tensor var_2414_cast_fp16 = reshape(shape = var_2413, x = key_41_cast_fp16)[name = tensor("op_2414_cast_fp16")]; + tensor mh_w_61_transpose_x_0 = const()[name = tensor("mh_w_61_transpose_x_0"), val = tensor(true)]; + tensor mh_w_61_transpose_y_0 = const()[name = tensor("mh_w_61_transpose_y_0"), val = tensor(false)]; + tensor mh_w_61_cast_fp16 = matmul(transpose_x = mh_w_61_transpose_x_0, transpose_y = mh_w_61_transpose_y_0, x = var_2410_cast_fp16, y = var_2414_cast_fp16)[name = tensor("mh_w_61_cast_fp16")]; + tensor mh_w_63_cast_fp16 = add(x = mh_w_61_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_63_cast_fp16")]; + tensor var_2422_cast_fp16 = softmax(axis = var_2334, x = mh_w_63_cast_fp16)[name = tensor("op_2422_cast_fp16")]; + tensor var_2423 = const()[name = tensor("op_2423"), val = tensor([1, 16, 64, 448])]; + tensor var_2424_cast_fp16 = reshape(shape = var_2423, x = value_41_cast_fp16)[name = tensor("op_2424_cast_fp16")]; + tensor attn_41_transpose_x_0 = const()[name = tensor("attn_41_transpose_x_0"), val = tensor(false)]; + tensor attn_41_transpose_y_0 = const()[name = tensor("attn_41_transpose_y_0"), val = tensor(true)]; + tensor attn_41_cast_fp16 = matmul(transpose_x = attn_41_transpose_x_0, transpose_y = attn_41_transpose_y_0, x = var_2424_cast_fp16, y = var_2422_cast_fp16)[name = tensor("attn_41_cast_fp16")]; + tensor var_2427 = const()[name = tensor("op_2427"), val = tensor([1, 1024, 1, 1])]; + tensor input_101_cast_fp16 = reshape(shape = var_2427, x = attn_41_cast_fp16)[name = tensor("input_101_cast_fp16")]; + tensor obj_147_pad_type_0 = const()[name = tensor("obj_147_pad_type_0"), val = tensor("valid")]; + tensor obj_147_strides_0 = const()[name = tensor("obj_147_strides_0"), val = tensor([1, 1])]; + tensor obj_147_pad_0 = const()[name = tensor("obj_147_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_147_dilations_0 = const()[name = tensor("obj_147_dilations_0"), val = tensor([1, 1])]; + tensor obj_147_groups_0 = const()[name = tensor("obj_147_groups_0"), val = tensor(1)]; + tensor layers_10_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(449349376)))]; + tensor layers_10_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(451446592)))]; + tensor obj_147_cast_fp16 = conv(bias = layers_10_self_attn_o_proj_bias_to_fp16, dilations = obj_147_dilations_0, groups = obj_147_groups_0, pad = obj_147_pad_0, pad_type = obj_147_pad_type_0, strides = obj_147_strides_0, weight = layers_10_self_attn_o_proj_weight_to_fp16, x = input_101_cast_fp16)[name = tensor("obj_147_cast_fp16")]; + tensor inputs_63_cast_fp16 = add(x = inputs_61_cast_fp16, y = obj_147_cast_fp16)[name = tensor("inputs_63_cast_fp16")]; + tensor out_63_axes_0 = const()[name = tensor("out_63_axes_0"), val = tensor([1])]; + tensor var_2449_to_fp16 = const()[name = tensor("op_2449_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_63_cast_fp16 = layer_norm(axes = out_63_axes_0, epsilon = var_2449_to_fp16, x = inputs_63_cast_fp16)[name = tensor("out_63_cast_fp16")]; + tensor obj_149_gamma_0_to_fp16 = const()[name = tensor("obj_149_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(451448704)))]; + tensor obj_149_beta_0_to_fp16 = const()[name = tensor("obj_149_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(451450816)))]; + tensor obj_149_epsilon_0_to_fp16 = const()[name = tensor("obj_149_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_149_cast_fp16 = batch_norm(beta = obj_149_beta_0_to_fp16, epsilon = obj_149_epsilon_0_to_fp16, gamma = obj_149_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_63_cast_fp16)[name = tensor("obj_149_cast_fp16")]; + tensor query_43_pad_type_0 = const()[name = tensor("query_43_pad_type_0"), val = tensor("valid")]; + tensor query_43_strides_0 = const()[name = tensor("query_43_strides_0"), val = tensor([1, 1])]; + tensor query_43_pad_0 = const()[name = tensor("query_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_43_dilations_0 = const()[name = tensor("query_43_dilations_0"), val = tensor([1, 1])]; + tensor query_43_groups_0 = const()[name = tensor("query_43_groups_0"), val = tensor(1)]; + tensor layers_10_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_10_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(451452928)))]; + tensor layers_10_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_10_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(453550144)))]; + tensor query_43_cast_fp16 = conv(bias = layers_10_encoder_attn_q_proj_bias_to_fp16, dilations = query_43_dilations_0, groups = query_43_groups_0, pad = query_43_pad_0, pad_type = query_43_pad_type_0, strides = query_43_strides_0, weight = layers_10_encoder_attn_q_proj_weight_to_fp16, x = obj_149_cast_fp16)[name = tensor("query_43_cast_fp16")]; + tensor key_43_pad_type_0 = const()[name = tensor("key_43_pad_type_0"), val = tensor("valid")]; + tensor key_43_strides_0 = const()[name = tensor("key_43_strides_0"), val = tensor([1, 1])]; + tensor key_43_pad_0 = const()[name = tensor("key_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_43_dilations_0 = const()[name = tensor("key_43_dilations_0"), val = tensor([1, 1])]; + tensor key_43_groups_0 = const()[name = tensor("key_43_groups_0"), val = tensor(1)]; + tensor layers_10_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_10_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(453552256)))]; + tensor key_43_cast_fp16 = conv(dilations = key_43_dilations_0, groups = key_43_groups_0, pad = key_43_pad_0, pad_type = key_43_pad_type_0, strides = key_43_strides_0, weight = layers_10_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_43_cast_fp16")]; + tensor value_43_pad_type_0 = const()[name = tensor("value_43_pad_type_0"), val = tensor("valid")]; + tensor value_43_strides_0 = const()[name = tensor("value_43_strides_0"), val = tensor([1, 1])]; + tensor value_43_pad_0 = const()[name = tensor("value_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_43_dilations_0 = const()[name = tensor("value_43_dilations_0"), val = tensor([1, 1])]; + tensor value_43_groups_0 = const()[name = tensor("value_43_groups_0"), val = tensor(1)]; + tensor layers_10_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_10_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(455649472)))]; + tensor layers_10_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_10_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(457746688)))]; + tensor value_43_cast_fp16 = conv(bias = layers_10_encoder_attn_v_proj_bias_to_fp16, dilations = value_43_dilations_0, groups = value_43_groups_0, pad = value_43_pad_0, pad_type = value_43_pad_type_0, strides = value_43_strides_0, weight = layers_10_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_43_cast_fp16")]; + tensor var_2485 = const()[name = tensor("op_2485"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_43_cast_fp16 = reshape(shape = var_2485, x = query_43_cast_fp16)[name = tensor("mh_q_43_cast_fp16")]; + tensor var_2487_to_fp16 = const()[name = tensor("op_2487_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2488_cast_fp16 = mul(x = mh_q_43_cast_fp16, y = var_2487_to_fp16)[name = tensor("op_2488_cast_fp16")]; + tensor var_2491 = const()[name = tensor("op_2491"), val = tensor([1, 16, 64, 1500])]; + tensor var_2492_cast_fp16 = reshape(shape = var_2491, x = key_43_cast_fp16)[name = tensor("op_2492_cast_fp16")]; + tensor mh_w_65_transpose_x_0 = const()[name = tensor("mh_w_65_transpose_x_0"), val = tensor(true)]; + tensor mh_w_65_transpose_y_0 = const()[name = tensor("mh_w_65_transpose_y_0"), val = tensor(false)]; + tensor mh_w_65_cast_fp16 = matmul(transpose_x = mh_w_65_transpose_x_0, transpose_y = mh_w_65_transpose_y_0, x = var_2488_cast_fp16, y = var_2492_cast_fp16)[name = tensor("mh_w_65_cast_fp16")]; + tensor obj_153_cast_fp16 = softmax(axis = var_2334, x = mh_w_65_cast_fp16)[name = tensor("obj_153_cast_fp16")]; + tensor var_2496 = const()[name = tensor("op_2496"), val = tensor([1, 16, 64, 1500])]; + tensor var_2497_cast_fp16 = reshape(shape = var_2496, x = value_43_cast_fp16)[name = tensor("op_2497_cast_fp16")]; + tensor attn_43_transpose_x_0 = const()[name = tensor("attn_43_transpose_x_0"), val = tensor(false)]; + tensor attn_43_transpose_y_0 = const()[name = tensor("attn_43_transpose_y_0"), val = tensor(true)]; + tensor attn_43_cast_fp16 = matmul(transpose_x = attn_43_transpose_x_0, transpose_y = attn_43_transpose_y_0, x = var_2497_cast_fp16, y = obj_153_cast_fp16)[name = tensor("attn_43_cast_fp16")]; + tensor var_2500 = const()[name = tensor("op_2500"), val = tensor([1, 1024, 1, 1])]; + tensor input_103_cast_fp16 = reshape(shape = var_2500, x = attn_43_cast_fp16)[name = tensor("input_103_cast_fp16")]; + tensor obj_151_pad_type_0 = const()[name = tensor("obj_151_pad_type_0"), val = tensor("valid")]; + tensor obj_151_strides_0 = const()[name = tensor("obj_151_strides_0"), val = tensor([1, 1])]; + tensor obj_151_pad_0 = const()[name = tensor("obj_151_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_151_dilations_0 = const()[name = tensor("obj_151_dilations_0"), val = tensor([1, 1])]; + tensor obj_151_groups_0 = const()[name = tensor("obj_151_groups_0"), val = tensor(1)]; + tensor layers_10_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_10_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(457748800)))]; + tensor layers_10_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_10_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(459846016)))]; + tensor obj_151_cast_fp16 = conv(bias = layers_10_encoder_attn_o_proj_bias_to_fp16, dilations = obj_151_dilations_0, groups = obj_151_groups_0, pad = obj_151_pad_0, pad_type = obj_151_pad_type_0, strides = obj_151_strides_0, weight = layers_10_encoder_attn_o_proj_weight_to_fp16, x = input_103_cast_fp16)[name = tensor("obj_151_cast_fp16")]; + tensor inputs_65_cast_fp16 = add(x = inputs_63_cast_fp16, y = obj_151_cast_fp16)[name = tensor("inputs_65_cast_fp16")]; + tensor out_65_axes_0 = const()[name = tensor("out_65_axes_0"), val = tensor([1])]; + tensor var_2518_to_fp16 = const()[name = tensor("op_2518_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_65_cast_fp16 = layer_norm(axes = out_65_axes_0, epsilon = var_2518_to_fp16, x = inputs_65_cast_fp16)[name = tensor("out_65_cast_fp16")]; + tensor input_105_gamma_0_to_fp16 = const()[name = tensor("input_105_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(459848128)))]; + tensor input_105_beta_0_to_fp16 = const()[name = tensor("input_105_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(459850240)))]; + tensor input_105_epsilon_0_to_fp16 = const()[name = tensor("input_105_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_105_cast_fp16 = batch_norm(beta = input_105_beta_0_to_fp16, epsilon = input_105_epsilon_0_to_fp16, gamma = input_105_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_65_cast_fp16)[name = tensor("input_105_cast_fp16")]; + tensor input_107_pad_type_0 = const()[name = tensor("input_107_pad_type_0"), val = tensor("valid")]; + tensor input_107_strides_0 = const()[name = tensor("input_107_strides_0"), val = tensor([1, 1])]; + tensor input_107_pad_0 = const()[name = tensor("input_107_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_107_dilations_0 = const()[name = tensor("input_107_dilations_0"), val = tensor([1, 1])]; + tensor input_107_groups_0 = const()[name = tensor("input_107_groups_0"), val = tensor(1)]; + tensor layers_10_fc1_weight_to_fp16 = const()[name = tensor("layers_10_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(459852352)))]; + tensor layers_10_fc1_bias_to_fp16 = const()[name = tensor("layers_10_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(468241024)))]; + tensor input_107_cast_fp16 = conv(bias = layers_10_fc1_bias_to_fp16, dilations = input_107_dilations_0, groups = input_107_groups_0, pad = input_107_pad_0, pad_type = input_107_pad_type_0, strides = input_107_strides_0, weight = layers_10_fc1_weight_to_fp16, x = input_105_cast_fp16)[name = tensor("input_107_cast_fp16")]; + tensor input_109_mode_0 = const()[name = tensor("input_109_mode_0"), val = tensor("EXACT")]; + tensor input_109_cast_fp16 = gelu(mode = input_109_mode_0, x = input_107_cast_fp16)[name = tensor("input_109_cast_fp16")]; + tensor hidden_states_23_pad_type_0 = const()[name = tensor("hidden_states_23_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_23_strides_0 = const()[name = tensor("hidden_states_23_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_23_pad_0 = const()[name = tensor("hidden_states_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_23_dilations_0 = const()[name = tensor("hidden_states_23_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_23_groups_0 = const()[name = tensor("hidden_states_23_groups_0"), val = tensor(1)]; + tensor layers_10_fc2_weight_to_fp16 = const()[name = tensor("layers_10_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(468249280)))]; + tensor layers_10_fc2_bias_to_fp16 = const()[name = tensor("layers_10_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(476637952)))]; + tensor hidden_states_23_cast_fp16 = conv(bias = layers_10_fc2_bias_to_fp16, dilations = hidden_states_23_dilations_0, groups = hidden_states_23_groups_0, pad = hidden_states_23_pad_0, pad_type = hidden_states_23_pad_type_0, strides = hidden_states_23_strides_0, weight = layers_10_fc2_weight_to_fp16, x = input_109_cast_fp16)[name = tensor("hidden_states_23_cast_fp16")]; + tensor inputs_67_cast_fp16 = add(x = inputs_65_cast_fp16, y = hidden_states_23_cast_fp16)[name = tensor("inputs_67_cast_fp16")]; + tensor var_2553 = const()[name = tensor("op_2553"), val = tensor(3)]; + tensor out_67_axes_0 = const()[name = tensor("out_67_axes_0"), val = tensor([1])]; + tensor var_2578_to_fp16 = const()[name = tensor("op_2578_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_67_cast_fp16 = layer_norm(axes = out_67_axes_0, epsilon = var_2578_to_fp16, x = inputs_67_cast_fp16)[name = tensor("out_67_cast_fp16")]; + tensor obj_155_gamma_0_to_fp16 = const()[name = tensor("obj_155_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(476640064)))]; + tensor obj_155_beta_0_to_fp16 = const()[name = tensor("obj_155_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(476642176)))]; + tensor obj_155_epsilon_0_to_fp16 = const()[name = tensor("obj_155_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_155_cast_fp16 = batch_norm(beta = obj_155_beta_0_to_fp16, epsilon = obj_155_epsilon_0_to_fp16, gamma = obj_155_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_67_cast_fp16)[name = tensor("obj_155_cast_fp16")]; + tensor query_45_pad_type_0 = const()[name = tensor("query_45_pad_type_0"), val = tensor("valid")]; + tensor query_45_strides_0 = const()[name = tensor("query_45_strides_0"), val = tensor([1, 1])]; + tensor query_45_pad_0 = const()[name = tensor("query_45_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_45_dilations_0 = const()[name = tensor("query_45_dilations_0"), val = tensor([1, 1])]; + tensor query_45_groups_0 = const()[name = tensor("query_45_groups_0"), val = tensor(1)]; + tensor layers_11_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(476644288)))]; + tensor layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(478741504)))]; + tensor query_45_cast_fp16 = conv(bias = layers_11_self_attn_q_proj_bias_to_fp16, dilations = query_45_dilations_0, groups = query_45_groups_0, pad = query_45_pad_0, pad_type = query_45_pad_type_0, strides = query_45_strides_0, weight = layers_11_self_attn_q_proj_weight_to_fp16, x = obj_155_cast_fp16)[name = tensor("query_45_cast_fp16")]; + tensor current_key_23_pad_type_0 = const()[name = tensor("current_key_23_pad_type_0"), val = tensor("valid")]; + tensor current_key_23_strides_0 = const()[name = tensor("current_key_23_strides_0"), val = tensor([1, 1])]; + tensor current_key_23_pad_0 = const()[name = tensor("current_key_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_23_dilations_0 = const()[name = tensor("current_key_23_dilations_0"), val = tensor([1, 1])]; + tensor current_key_23_groups_0 = const()[name = tensor("current_key_23_groups_0"), val = tensor(1)]; + tensor layers_11_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(478743616)))]; + tensor current_key_23_cast_fp16 = conv(dilations = current_key_23_dilations_0, groups = current_key_23_groups_0, pad = current_key_23_pad_0, pad_type = current_key_23_pad_type_0, strides = current_key_23_strides_0, weight = layers_11_self_attn_k_proj_weight_to_fp16, x = obj_155_cast_fp16)[name = tensor("current_key_23_cast_fp16")]; + tensor current_value_23_pad_type_0 = const()[name = tensor("current_value_23_pad_type_0"), val = tensor("valid")]; + tensor current_value_23_strides_0 = const()[name = tensor("current_value_23_strides_0"), val = tensor([1, 1])]; + tensor current_value_23_pad_0 = const()[name = tensor("current_value_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_23_dilations_0 = const()[name = tensor("current_value_23_dilations_0"), val = tensor([1, 1])]; + tensor current_value_23_groups_0 = const()[name = tensor("current_value_23_groups_0"), val = tensor(1)]; + tensor layers_11_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(480840832)))]; + tensor layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(482938048)))]; + tensor current_value_23_cast_fp16 = conv(bias = layers_11_self_attn_v_proj_bias_to_fp16, dilations = current_value_23_dilations_0, groups = current_value_23_groups_0, pad = current_value_23_pad_0, pad_type = current_value_23_pad_type_0, strides = current_value_23_strides_0, weight = layers_11_self_attn_v_proj_weight_to_fp16, x = obj_155_cast_fp16)[name = tensor("current_value_23_cast_fp16")]; + tensor var_2617_cast_fp16 = mul(x = var_87_cast_fp16_11, y = var_207_cast_fp16)[name = tensor("op_2617_cast_fp16")]; + tensor var_2618_cast_fp16 = mul(x = current_key_23_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_2618_cast_fp16")]; + tensor key_45_cast_fp16 = add(x = var_2617_cast_fp16, y = var_2618_cast_fp16)[name = tensor("key_45_cast_fp16")]; + tensor var_2621_cast_fp16 = mul(x = var_114_cast_fp16_11, y = var_207_cast_fp16)[name = tensor("op_2621_cast_fp16")]; + tensor var_2622_cast_fp16 = mul(x = current_value_23_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_2622_cast_fp16")]; + tensor value_45_cast_fp16 = add(x = var_2621_cast_fp16, y = var_2622_cast_fp16)[name = tensor("value_45_cast_fp16")]; + tensor var_2626 = const()[name = tensor("op_2626"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_45_cast_fp16 = reshape(shape = var_2626, x = query_45_cast_fp16)[name = tensor("mh_q_45_cast_fp16")]; + tensor var_2628_to_fp16 = const()[name = tensor("op_2628_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2629_cast_fp16 = mul(x = mh_q_45_cast_fp16, y = var_2628_to_fp16)[name = tensor("op_2629_cast_fp16")]; + tensor var_2632 = const()[name = tensor("op_2632"), val = tensor([1, 16, 64, 448])]; + tensor var_2633_cast_fp16 = reshape(shape = var_2632, x = key_45_cast_fp16)[name = tensor("op_2633_cast_fp16")]; + tensor mh_w_67_transpose_x_0 = const()[name = tensor("mh_w_67_transpose_x_0"), val = tensor(true)]; + tensor mh_w_67_transpose_y_0 = const()[name = tensor("mh_w_67_transpose_y_0"), val = tensor(false)]; + tensor mh_w_67_cast_fp16 = matmul(transpose_x = mh_w_67_transpose_x_0, transpose_y = mh_w_67_transpose_y_0, x = var_2629_cast_fp16, y = var_2633_cast_fp16)[name = tensor("mh_w_67_cast_fp16")]; + tensor mh_w_69_cast_fp16 = add(x = mh_w_67_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_69_cast_fp16")]; + tensor var_2641_cast_fp16 = softmax(axis = var_2553, x = mh_w_69_cast_fp16)[name = tensor("op_2641_cast_fp16")]; + tensor var_2642 = const()[name = tensor("op_2642"), val = tensor([1, 16, 64, 448])]; + tensor var_2643_cast_fp16 = reshape(shape = var_2642, x = value_45_cast_fp16)[name = tensor("op_2643_cast_fp16")]; + tensor attn_45_transpose_x_0 = const()[name = tensor("attn_45_transpose_x_0"), val = tensor(false)]; + tensor attn_45_transpose_y_0 = const()[name = tensor("attn_45_transpose_y_0"), val = tensor(true)]; + tensor attn_45_cast_fp16 = matmul(transpose_x = attn_45_transpose_x_0, transpose_y = attn_45_transpose_y_0, x = var_2643_cast_fp16, y = var_2641_cast_fp16)[name = tensor("attn_45_cast_fp16")]; + tensor var_2646 = const()[name = tensor("op_2646"), val = tensor([1, 1024, 1, 1])]; + tensor input_111_cast_fp16 = reshape(shape = var_2646, x = attn_45_cast_fp16)[name = tensor("input_111_cast_fp16")]; + tensor obj_161_pad_type_0 = const()[name = tensor("obj_161_pad_type_0"), val = tensor("valid")]; + tensor obj_161_strides_0 = const()[name = tensor("obj_161_strides_0"), val = tensor([1, 1])]; + tensor obj_161_pad_0 = const()[name = tensor("obj_161_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_161_dilations_0 = const()[name = tensor("obj_161_dilations_0"), val = tensor([1, 1])]; + tensor obj_161_groups_0 = const()[name = tensor("obj_161_groups_0"), val = tensor(1)]; + tensor layers_11_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(482940160)))]; + tensor layers_11_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(485037376)))]; + tensor obj_161_cast_fp16 = conv(bias = layers_11_self_attn_o_proj_bias_to_fp16, dilations = obj_161_dilations_0, groups = obj_161_groups_0, pad = obj_161_pad_0, pad_type = obj_161_pad_type_0, strides = obj_161_strides_0, weight = layers_11_self_attn_o_proj_weight_to_fp16, x = input_111_cast_fp16)[name = tensor("obj_161_cast_fp16")]; + tensor inputs_69_cast_fp16 = add(x = inputs_67_cast_fp16, y = obj_161_cast_fp16)[name = tensor("inputs_69_cast_fp16")]; + tensor out_69_axes_0 = const()[name = tensor("out_69_axes_0"), val = tensor([1])]; + tensor var_2668_to_fp16 = const()[name = tensor("op_2668_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_69_cast_fp16 = layer_norm(axes = out_69_axes_0, epsilon = var_2668_to_fp16, x = inputs_69_cast_fp16)[name = tensor("out_69_cast_fp16")]; + tensor obj_163_gamma_0_to_fp16 = const()[name = tensor("obj_163_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(485039488)))]; + tensor obj_163_beta_0_to_fp16 = const()[name = tensor("obj_163_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(485041600)))]; + tensor obj_163_epsilon_0_to_fp16 = const()[name = tensor("obj_163_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_163_cast_fp16 = batch_norm(beta = obj_163_beta_0_to_fp16, epsilon = obj_163_epsilon_0_to_fp16, gamma = obj_163_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_69_cast_fp16)[name = tensor("obj_163_cast_fp16")]; + tensor query_47_pad_type_0 = const()[name = tensor("query_47_pad_type_0"), val = tensor("valid")]; + tensor query_47_strides_0 = const()[name = tensor("query_47_strides_0"), val = tensor([1, 1])]; + tensor query_47_pad_0 = const()[name = tensor("query_47_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_47_dilations_0 = const()[name = tensor("query_47_dilations_0"), val = tensor([1, 1])]; + tensor query_47_groups_0 = const()[name = tensor("query_47_groups_0"), val = tensor(1)]; + tensor layers_11_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_11_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(485043712)))]; + tensor layers_11_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_11_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(487140928)))]; + tensor query_47_cast_fp16 = conv(bias = layers_11_encoder_attn_q_proj_bias_to_fp16, dilations = query_47_dilations_0, groups = query_47_groups_0, pad = query_47_pad_0, pad_type = query_47_pad_type_0, strides = query_47_strides_0, weight = layers_11_encoder_attn_q_proj_weight_to_fp16, x = obj_163_cast_fp16)[name = tensor("query_47_cast_fp16")]; + tensor key_47_pad_type_0 = const()[name = tensor("key_47_pad_type_0"), val = tensor("valid")]; + tensor key_47_strides_0 = const()[name = tensor("key_47_strides_0"), val = tensor([1, 1])]; + tensor key_47_pad_0 = const()[name = tensor("key_47_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_47_dilations_0 = const()[name = tensor("key_47_dilations_0"), val = tensor([1, 1])]; + tensor key_47_groups_0 = const()[name = tensor("key_47_groups_0"), val = tensor(1)]; + tensor layers_11_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_11_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(487143040)))]; + tensor key_47_cast_fp16 = conv(dilations = key_47_dilations_0, groups = key_47_groups_0, pad = key_47_pad_0, pad_type = key_47_pad_type_0, strides = key_47_strides_0, weight = layers_11_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_47_cast_fp16")]; + tensor value_47_pad_type_0 = const()[name = tensor("value_47_pad_type_0"), val = tensor("valid")]; + tensor value_47_strides_0 = const()[name = tensor("value_47_strides_0"), val = tensor([1, 1])]; + tensor value_47_pad_0 = const()[name = tensor("value_47_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_47_dilations_0 = const()[name = tensor("value_47_dilations_0"), val = tensor([1, 1])]; + tensor value_47_groups_0 = const()[name = tensor("value_47_groups_0"), val = tensor(1)]; + tensor layers_11_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_11_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(489240256)))]; + tensor layers_11_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_11_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(491337472)))]; + tensor value_47_cast_fp16 = conv(bias = layers_11_encoder_attn_v_proj_bias_to_fp16, dilations = value_47_dilations_0, groups = value_47_groups_0, pad = value_47_pad_0, pad_type = value_47_pad_type_0, strides = value_47_strides_0, weight = layers_11_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_47_cast_fp16")]; + tensor var_2704 = const()[name = tensor("op_2704"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_47_cast_fp16 = reshape(shape = var_2704, x = query_47_cast_fp16)[name = tensor("mh_q_47_cast_fp16")]; + tensor var_2706_to_fp16 = const()[name = tensor("op_2706_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2707_cast_fp16 = mul(x = mh_q_47_cast_fp16, y = var_2706_to_fp16)[name = tensor("op_2707_cast_fp16")]; + tensor var_2710 = const()[name = tensor("op_2710"), val = tensor([1, 16, 64, 1500])]; + tensor var_2711_cast_fp16 = reshape(shape = var_2710, x = key_47_cast_fp16)[name = tensor("op_2711_cast_fp16")]; + tensor mh_w_71_transpose_x_0 = const()[name = tensor("mh_w_71_transpose_x_0"), val = tensor(true)]; + tensor mh_w_71_transpose_y_0 = const()[name = tensor("mh_w_71_transpose_y_0"), val = tensor(false)]; + tensor mh_w_71_cast_fp16 = matmul(transpose_x = mh_w_71_transpose_x_0, transpose_y = mh_w_71_transpose_y_0, x = var_2707_cast_fp16, y = var_2711_cast_fp16)[name = tensor("mh_w_71_cast_fp16")]; + tensor obj_167_cast_fp16 = softmax(axis = var_2553, x = mh_w_71_cast_fp16)[name = tensor("obj_167_cast_fp16")]; + tensor var_2715 = const()[name = tensor("op_2715"), val = tensor([1, 16, 64, 1500])]; + tensor var_2716_cast_fp16 = reshape(shape = var_2715, x = value_47_cast_fp16)[name = tensor("op_2716_cast_fp16")]; + tensor attn_47_transpose_x_0 = const()[name = tensor("attn_47_transpose_x_0"), val = tensor(false)]; + tensor attn_47_transpose_y_0 = const()[name = tensor("attn_47_transpose_y_0"), val = tensor(true)]; + tensor attn_47_cast_fp16 = matmul(transpose_x = attn_47_transpose_x_0, transpose_y = attn_47_transpose_y_0, x = var_2716_cast_fp16, y = obj_167_cast_fp16)[name = tensor("attn_47_cast_fp16")]; + tensor var_2719 = const()[name = tensor("op_2719"), val = tensor([1, 1024, 1, 1])]; + tensor input_113_cast_fp16 = reshape(shape = var_2719, x = attn_47_cast_fp16)[name = tensor("input_113_cast_fp16")]; + tensor obj_165_pad_type_0 = const()[name = tensor("obj_165_pad_type_0"), val = tensor("valid")]; + tensor obj_165_strides_0 = const()[name = tensor("obj_165_strides_0"), val = tensor([1, 1])]; + tensor obj_165_pad_0 = const()[name = tensor("obj_165_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_165_dilations_0 = const()[name = tensor("obj_165_dilations_0"), val = tensor([1, 1])]; + tensor obj_165_groups_0 = const()[name = tensor("obj_165_groups_0"), val = tensor(1)]; + tensor layers_11_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_11_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(491339584)))]; + tensor layers_11_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_11_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(493436800)))]; + tensor obj_165_cast_fp16 = conv(bias = layers_11_encoder_attn_o_proj_bias_to_fp16, dilations = obj_165_dilations_0, groups = obj_165_groups_0, pad = obj_165_pad_0, pad_type = obj_165_pad_type_0, strides = obj_165_strides_0, weight = layers_11_encoder_attn_o_proj_weight_to_fp16, x = input_113_cast_fp16)[name = tensor("obj_165_cast_fp16")]; + tensor inputs_71_cast_fp16 = add(x = inputs_69_cast_fp16, y = obj_165_cast_fp16)[name = tensor("inputs_71_cast_fp16")]; + tensor out_71_axes_0 = const()[name = tensor("out_71_axes_0"), val = tensor([1])]; + tensor var_2737_to_fp16 = const()[name = tensor("op_2737_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_71_cast_fp16 = layer_norm(axes = out_71_axes_0, epsilon = var_2737_to_fp16, x = inputs_71_cast_fp16)[name = tensor("out_71_cast_fp16")]; + tensor input_115_gamma_0_to_fp16 = const()[name = tensor("input_115_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(493438912)))]; + tensor input_115_beta_0_to_fp16 = const()[name = tensor("input_115_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(493441024)))]; + tensor input_115_epsilon_0_to_fp16 = const()[name = tensor("input_115_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_115_cast_fp16 = batch_norm(beta = input_115_beta_0_to_fp16, epsilon = input_115_epsilon_0_to_fp16, gamma = input_115_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_71_cast_fp16)[name = tensor("input_115_cast_fp16")]; + tensor input_117_pad_type_0 = const()[name = tensor("input_117_pad_type_0"), val = tensor("valid")]; + tensor input_117_strides_0 = const()[name = tensor("input_117_strides_0"), val = tensor([1, 1])]; + tensor input_117_pad_0 = const()[name = tensor("input_117_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_117_dilations_0 = const()[name = tensor("input_117_dilations_0"), val = tensor([1, 1])]; + tensor input_117_groups_0 = const()[name = tensor("input_117_groups_0"), val = tensor(1)]; + tensor layers_11_fc1_weight_to_fp16 = const()[name = tensor("layers_11_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(493443136)))]; + tensor layers_11_fc1_bias_to_fp16 = const()[name = tensor("layers_11_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(501831808)))]; + tensor input_117_cast_fp16 = conv(bias = layers_11_fc1_bias_to_fp16, dilations = input_117_dilations_0, groups = input_117_groups_0, pad = input_117_pad_0, pad_type = input_117_pad_type_0, strides = input_117_strides_0, weight = layers_11_fc1_weight_to_fp16, x = input_115_cast_fp16)[name = tensor("input_117_cast_fp16")]; + tensor input_119_mode_0 = const()[name = tensor("input_119_mode_0"), val = tensor("EXACT")]; + tensor input_119_cast_fp16 = gelu(mode = input_119_mode_0, x = input_117_cast_fp16)[name = tensor("input_119_cast_fp16")]; + tensor hidden_states_25_pad_type_0 = const()[name = tensor("hidden_states_25_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_25_strides_0 = const()[name = tensor("hidden_states_25_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_25_pad_0 = const()[name = tensor("hidden_states_25_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_25_dilations_0 = const()[name = tensor("hidden_states_25_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_25_groups_0 = const()[name = tensor("hidden_states_25_groups_0"), val = tensor(1)]; + tensor layers_11_fc2_weight_to_fp16 = const()[name = tensor("layers_11_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(501840064)))]; + tensor layers_11_fc2_bias_to_fp16 = const()[name = tensor("layers_11_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(510228736)))]; + tensor hidden_states_25_cast_fp16 = conv(bias = layers_11_fc2_bias_to_fp16, dilations = hidden_states_25_dilations_0, groups = hidden_states_25_groups_0, pad = hidden_states_25_pad_0, pad_type = hidden_states_25_pad_type_0, strides = hidden_states_25_strides_0, weight = layers_11_fc2_weight_to_fp16, x = input_119_cast_fp16)[name = tensor("hidden_states_25_cast_fp16")]; + tensor inputs_73_cast_fp16 = add(x = inputs_71_cast_fp16, y = hidden_states_25_cast_fp16)[name = tensor("inputs_73_cast_fp16")]; + tensor var_2772 = const()[name = tensor("op_2772"), val = tensor(3)]; + tensor out_73_axes_0 = const()[name = tensor("out_73_axes_0"), val = tensor([1])]; + tensor var_2797_to_fp16 = const()[name = tensor("op_2797_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_73_cast_fp16 = layer_norm(axes = out_73_axes_0, epsilon = var_2797_to_fp16, x = inputs_73_cast_fp16)[name = tensor("out_73_cast_fp16")]; + tensor obj_169_gamma_0_to_fp16 = const()[name = tensor("obj_169_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(510230848)))]; + tensor obj_169_beta_0_to_fp16 = const()[name = tensor("obj_169_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(510232960)))]; + tensor obj_169_epsilon_0_to_fp16 = const()[name = tensor("obj_169_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_169_cast_fp16 = batch_norm(beta = obj_169_beta_0_to_fp16, epsilon = obj_169_epsilon_0_to_fp16, gamma = obj_169_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_73_cast_fp16)[name = tensor("obj_169_cast_fp16")]; + tensor query_49_pad_type_0 = const()[name = tensor("query_49_pad_type_0"), val = tensor("valid")]; + tensor query_49_strides_0 = const()[name = tensor("query_49_strides_0"), val = tensor([1, 1])]; + tensor query_49_pad_0 = const()[name = tensor("query_49_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_49_dilations_0 = const()[name = tensor("query_49_dilations_0"), val = tensor([1, 1])]; + tensor query_49_groups_0 = const()[name = tensor("query_49_groups_0"), val = tensor(1)]; + tensor layers_12_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_12_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(510235072)))]; + tensor layers_12_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_12_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(512332288)))]; + tensor query_49_cast_fp16 = conv(bias = layers_12_self_attn_q_proj_bias_to_fp16, dilations = query_49_dilations_0, groups = query_49_groups_0, pad = query_49_pad_0, pad_type = query_49_pad_type_0, strides = query_49_strides_0, weight = layers_12_self_attn_q_proj_weight_to_fp16, x = obj_169_cast_fp16)[name = tensor("query_49_cast_fp16")]; + tensor current_key_25_pad_type_0 = const()[name = tensor("current_key_25_pad_type_0"), val = tensor("valid")]; + tensor current_key_25_strides_0 = const()[name = tensor("current_key_25_strides_0"), val = tensor([1, 1])]; + tensor current_key_25_pad_0 = const()[name = tensor("current_key_25_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_25_dilations_0 = const()[name = tensor("current_key_25_dilations_0"), val = tensor([1, 1])]; + tensor current_key_25_groups_0 = const()[name = tensor("current_key_25_groups_0"), val = tensor(1)]; + tensor layers_12_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_12_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(512334400)))]; + tensor current_key_25_cast_fp16 = conv(dilations = current_key_25_dilations_0, groups = current_key_25_groups_0, pad = current_key_25_pad_0, pad_type = current_key_25_pad_type_0, strides = current_key_25_strides_0, weight = layers_12_self_attn_k_proj_weight_to_fp16, x = obj_169_cast_fp16)[name = tensor("current_key_25_cast_fp16")]; + tensor current_value_25_pad_type_0 = const()[name = tensor("current_value_25_pad_type_0"), val = tensor("valid")]; + tensor current_value_25_strides_0 = const()[name = tensor("current_value_25_strides_0"), val = tensor([1, 1])]; + tensor current_value_25_pad_0 = const()[name = tensor("current_value_25_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_25_dilations_0 = const()[name = tensor("current_value_25_dilations_0"), val = tensor([1, 1])]; + tensor current_value_25_groups_0 = const()[name = tensor("current_value_25_groups_0"), val = tensor(1)]; + tensor layers_12_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_12_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(514431616)))]; + tensor layers_12_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_12_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(516528832)))]; + tensor current_value_25_cast_fp16 = conv(bias = layers_12_self_attn_v_proj_bias_to_fp16, dilations = current_value_25_dilations_0, groups = current_value_25_groups_0, pad = current_value_25_pad_0, pad_type = current_value_25_pad_type_0, strides = current_value_25_strides_0, weight = layers_12_self_attn_v_proj_weight_to_fp16, x = obj_169_cast_fp16)[name = tensor("current_value_25_cast_fp16")]; + tensor var_2836_cast_fp16 = mul(x = var_87_cast_fp16_12, y = var_207_cast_fp16)[name = tensor("op_2836_cast_fp16")]; + tensor var_2837_cast_fp16 = mul(x = current_key_25_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_2837_cast_fp16")]; + tensor key_49_cast_fp16 = add(x = var_2836_cast_fp16, y = var_2837_cast_fp16)[name = tensor("key_49_cast_fp16")]; + tensor var_2840_cast_fp16 = mul(x = var_114_cast_fp16_12, y = var_207_cast_fp16)[name = tensor("op_2840_cast_fp16")]; + tensor var_2841_cast_fp16 = mul(x = current_value_25_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_2841_cast_fp16")]; + tensor value_49_cast_fp16 = add(x = var_2840_cast_fp16, y = var_2841_cast_fp16)[name = tensor("value_49_cast_fp16")]; + tensor var_2845 = const()[name = tensor("op_2845"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_49_cast_fp16 = reshape(shape = var_2845, x = query_49_cast_fp16)[name = tensor("mh_q_49_cast_fp16")]; + tensor var_2847_to_fp16 = const()[name = tensor("op_2847_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2848_cast_fp16 = mul(x = mh_q_49_cast_fp16, y = var_2847_to_fp16)[name = tensor("op_2848_cast_fp16")]; + tensor var_2851 = const()[name = tensor("op_2851"), val = tensor([1, 16, 64, 448])]; + tensor var_2852_cast_fp16 = reshape(shape = var_2851, x = key_49_cast_fp16)[name = tensor("op_2852_cast_fp16")]; + tensor mh_w_73_transpose_x_0 = const()[name = tensor("mh_w_73_transpose_x_0"), val = tensor(true)]; + tensor mh_w_73_transpose_y_0 = const()[name = tensor("mh_w_73_transpose_y_0"), val = tensor(false)]; + tensor mh_w_73_cast_fp16 = matmul(transpose_x = mh_w_73_transpose_x_0, transpose_y = mh_w_73_transpose_y_0, x = var_2848_cast_fp16, y = var_2852_cast_fp16)[name = tensor("mh_w_73_cast_fp16")]; + tensor mh_w_75_cast_fp16 = add(x = mh_w_73_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_75_cast_fp16")]; + tensor var_2860_cast_fp16 = softmax(axis = var_2772, x = mh_w_75_cast_fp16)[name = tensor("op_2860_cast_fp16")]; + tensor var_2861 = const()[name = tensor("op_2861"), val = tensor([1, 16, 64, 448])]; + tensor var_2862_cast_fp16 = reshape(shape = var_2861, x = value_49_cast_fp16)[name = tensor("op_2862_cast_fp16")]; + tensor attn_49_transpose_x_0 = const()[name = tensor("attn_49_transpose_x_0"), val = tensor(false)]; + tensor attn_49_transpose_y_0 = const()[name = tensor("attn_49_transpose_y_0"), val = tensor(true)]; + tensor attn_49_cast_fp16 = matmul(transpose_x = attn_49_transpose_x_0, transpose_y = attn_49_transpose_y_0, x = var_2862_cast_fp16, y = var_2860_cast_fp16)[name = tensor("attn_49_cast_fp16")]; + tensor var_2865 = const()[name = tensor("op_2865"), val = tensor([1, 1024, 1, 1])]; + tensor input_121_cast_fp16 = reshape(shape = var_2865, x = attn_49_cast_fp16)[name = tensor("input_121_cast_fp16")]; + tensor obj_175_pad_type_0 = const()[name = tensor("obj_175_pad_type_0"), val = tensor("valid")]; + tensor obj_175_strides_0 = const()[name = tensor("obj_175_strides_0"), val = tensor([1, 1])]; + tensor obj_175_pad_0 = const()[name = tensor("obj_175_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_175_dilations_0 = const()[name = tensor("obj_175_dilations_0"), val = tensor([1, 1])]; + tensor obj_175_groups_0 = const()[name = tensor("obj_175_groups_0"), val = tensor(1)]; + tensor layers_12_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_12_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(516530944)))]; + tensor layers_12_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_12_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(518628160)))]; + tensor obj_175_cast_fp16 = conv(bias = layers_12_self_attn_o_proj_bias_to_fp16, dilations = obj_175_dilations_0, groups = obj_175_groups_0, pad = obj_175_pad_0, pad_type = obj_175_pad_type_0, strides = obj_175_strides_0, weight = layers_12_self_attn_o_proj_weight_to_fp16, x = input_121_cast_fp16)[name = tensor("obj_175_cast_fp16")]; + tensor inputs_75_cast_fp16 = add(x = inputs_73_cast_fp16, y = obj_175_cast_fp16)[name = tensor("inputs_75_cast_fp16")]; + tensor out_75_axes_0 = const()[name = tensor("out_75_axes_0"), val = tensor([1])]; + tensor var_2887_to_fp16 = const()[name = tensor("op_2887_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_75_cast_fp16 = layer_norm(axes = out_75_axes_0, epsilon = var_2887_to_fp16, x = inputs_75_cast_fp16)[name = tensor("out_75_cast_fp16")]; + tensor obj_177_gamma_0_to_fp16 = const()[name = tensor("obj_177_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(518630272)))]; + tensor obj_177_beta_0_to_fp16 = const()[name = tensor("obj_177_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(518632384)))]; + tensor obj_177_epsilon_0_to_fp16 = const()[name = tensor("obj_177_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_177_cast_fp16 = batch_norm(beta = obj_177_beta_0_to_fp16, epsilon = obj_177_epsilon_0_to_fp16, gamma = obj_177_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_75_cast_fp16)[name = tensor("obj_177_cast_fp16")]; + tensor query_51_pad_type_0 = const()[name = tensor("query_51_pad_type_0"), val = tensor("valid")]; + tensor query_51_strides_0 = const()[name = tensor("query_51_strides_0"), val = tensor([1, 1])]; + tensor query_51_pad_0 = const()[name = tensor("query_51_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_51_dilations_0 = const()[name = tensor("query_51_dilations_0"), val = tensor([1, 1])]; + tensor query_51_groups_0 = const()[name = tensor("query_51_groups_0"), val = tensor(1)]; + tensor layers_12_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_12_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(518634496)))]; + tensor layers_12_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_12_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(520731712)))]; + tensor query_51_cast_fp16 = conv(bias = layers_12_encoder_attn_q_proj_bias_to_fp16, dilations = query_51_dilations_0, groups = query_51_groups_0, pad = query_51_pad_0, pad_type = query_51_pad_type_0, strides = query_51_strides_0, weight = layers_12_encoder_attn_q_proj_weight_to_fp16, x = obj_177_cast_fp16)[name = tensor("query_51_cast_fp16")]; + tensor key_51_pad_type_0 = const()[name = tensor("key_51_pad_type_0"), val = tensor("valid")]; + tensor key_51_strides_0 = const()[name = tensor("key_51_strides_0"), val = tensor([1, 1])]; + tensor key_51_pad_0 = const()[name = tensor("key_51_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_51_dilations_0 = const()[name = tensor("key_51_dilations_0"), val = tensor([1, 1])]; + tensor key_51_groups_0 = const()[name = tensor("key_51_groups_0"), val = tensor(1)]; + tensor layers_12_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_12_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(520733824)))]; + tensor key_51_cast_fp16 = conv(dilations = key_51_dilations_0, groups = key_51_groups_0, pad = key_51_pad_0, pad_type = key_51_pad_type_0, strides = key_51_strides_0, weight = layers_12_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_51_cast_fp16")]; + tensor value_51_pad_type_0 = const()[name = tensor("value_51_pad_type_0"), val = tensor("valid")]; + tensor value_51_strides_0 = const()[name = tensor("value_51_strides_0"), val = tensor([1, 1])]; + tensor value_51_pad_0 = const()[name = tensor("value_51_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_51_dilations_0 = const()[name = tensor("value_51_dilations_0"), val = tensor([1, 1])]; + tensor value_51_groups_0 = const()[name = tensor("value_51_groups_0"), val = tensor(1)]; + tensor layers_12_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_12_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(522831040)))]; + tensor layers_12_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_12_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(524928256)))]; + tensor value_51_cast_fp16 = conv(bias = layers_12_encoder_attn_v_proj_bias_to_fp16, dilations = value_51_dilations_0, groups = value_51_groups_0, pad = value_51_pad_0, pad_type = value_51_pad_type_0, strides = value_51_strides_0, weight = layers_12_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_51_cast_fp16")]; + tensor var_2923 = const()[name = tensor("op_2923"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_51_cast_fp16 = reshape(shape = var_2923, x = query_51_cast_fp16)[name = tensor("mh_q_51_cast_fp16")]; + tensor var_2925_to_fp16 = const()[name = tensor("op_2925_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2926_cast_fp16 = mul(x = mh_q_51_cast_fp16, y = var_2925_to_fp16)[name = tensor("op_2926_cast_fp16")]; + tensor var_2929 = const()[name = tensor("op_2929"), val = tensor([1, 16, 64, 1500])]; + tensor var_2930_cast_fp16 = reshape(shape = var_2929, x = key_51_cast_fp16)[name = tensor("op_2930_cast_fp16")]; + tensor mh_w_77_transpose_x_0 = const()[name = tensor("mh_w_77_transpose_x_0"), val = tensor(true)]; + tensor mh_w_77_transpose_y_0 = const()[name = tensor("mh_w_77_transpose_y_0"), val = tensor(false)]; + tensor mh_w_77_cast_fp16 = matmul(transpose_x = mh_w_77_transpose_x_0, transpose_y = mh_w_77_transpose_y_0, x = var_2926_cast_fp16, y = var_2930_cast_fp16)[name = tensor("mh_w_77_cast_fp16")]; + tensor obj_181_cast_fp16 = softmax(axis = var_2772, x = mh_w_77_cast_fp16)[name = tensor("obj_181_cast_fp16")]; + tensor var_2934 = const()[name = tensor("op_2934"), val = tensor([1, 16, 64, 1500])]; + tensor var_2935_cast_fp16 = reshape(shape = var_2934, x = value_51_cast_fp16)[name = tensor("op_2935_cast_fp16")]; + tensor attn_51_transpose_x_0 = const()[name = tensor("attn_51_transpose_x_0"), val = tensor(false)]; + tensor attn_51_transpose_y_0 = const()[name = tensor("attn_51_transpose_y_0"), val = tensor(true)]; + tensor attn_51_cast_fp16 = matmul(transpose_x = attn_51_transpose_x_0, transpose_y = attn_51_transpose_y_0, x = var_2935_cast_fp16, y = obj_181_cast_fp16)[name = tensor("attn_51_cast_fp16")]; + tensor var_2938 = const()[name = tensor("op_2938"), val = tensor([1, 1024, 1, 1])]; + tensor input_123_cast_fp16 = reshape(shape = var_2938, x = attn_51_cast_fp16)[name = tensor("input_123_cast_fp16")]; + tensor obj_179_pad_type_0 = const()[name = tensor("obj_179_pad_type_0"), val = tensor("valid")]; + tensor obj_179_strides_0 = const()[name = tensor("obj_179_strides_0"), val = tensor([1, 1])]; + tensor obj_179_pad_0 = const()[name = tensor("obj_179_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_179_dilations_0 = const()[name = tensor("obj_179_dilations_0"), val = tensor([1, 1])]; + tensor obj_179_groups_0 = const()[name = tensor("obj_179_groups_0"), val = tensor(1)]; + tensor layers_12_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_12_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(524930368)))]; + tensor layers_12_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_12_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(527027584)))]; + tensor obj_179_cast_fp16 = conv(bias = layers_12_encoder_attn_o_proj_bias_to_fp16, dilations = obj_179_dilations_0, groups = obj_179_groups_0, pad = obj_179_pad_0, pad_type = obj_179_pad_type_0, strides = obj_179_strides_0, weight = layers_12_encoder_attn_o_proj_weight_to_fp16, x = input_123_cast_fp16)[name = tensor("obj_179_cast_fp16")]; + tensor inputs_77_cast_fp16 = add(x = inputs_75_cast_fp16, y = obj_179_cast_fp16)[name = tensor("inputs_77_cast_fp16")]; + tensor out_77_axes_0 = const()[name = tensor("out_77_axes_0"), val = tensor([1])]; + tensor var_2956_to_fp16 = const()[name = tensor("op_2956_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_77_cast_fp16 = layer_norm(axes = out_77_axes_0, epsilon = var_2956_to_fp16, x = inputs_77_cast_fp16)[name = tensor("out_77_cast_fp16")]; + tensor input_125_gamma_0_to_fp16 = const()[name = tensor("input_125_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(527029696)))]; + tensor input_125_beta_0_to_fp16 = const()[name = tensor("input_125_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(527031808)))]; + tensor input_125_epsilon_0_to_fp16 = const()[name = tensor("input_125_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_125_cast_fp16 = batch_norm(beta = input_125_beta_0_to_fp16, epsilon = input_125_epsilon_0_to_fp16, gamma = input_125_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_77_cast_fp16)[name = tensor("input_125_cast_fp16")]; + tensor input_127_pad_type_0 = const()[name = tensor("input_127_pad_type_0"), val = tensor("valid")]; + tensor input_127_strides_0 = const()[name = tensor("input_127_strides_0"), val = tensor([1, 1])]; + tensor input_127_pad_0 = const()[name = tensor("input_127_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_127_dilations_0 = const()[name = tensor("input_127_dilations_0"), val = tensor([1, 1])]; + tensor input_127_groups_0 = const()[name = tensor("input_127_groups_0"), val = tensor(1)]; + tensor layers_12_fc1_weight_to_fp16 = const()[name = tensor("layers_12_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(527033920)))]; + tensor layers_12_fc1_bias_to_fp16 = const()[name = tensor("layers_12_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(535422592)))]; + tensor input_127_cast_fp16 = conv(bias = layers_12_fc1_bias_to_fp16, dilations = input_127_dilations_0, groups = input_127_groups_0, pad = input_127_pad_0, pad_type = input_127_pad_type_0, strides = input_127_strides_0, weight = layers_12_fc1_weight_to_fp16, x = input_125_cast_fp16)[name = tensor("input_127_cast_fp16")]; + tensor input_129_mode_0 = const()[name = tensor("input_129_mode_0"), val = tensor("EXACT")]; + tensor input_129_cast_fp16 = gelu(mode = input_129_mode_0, x = input_127_cast_fp16)[name = tensor("input_129_cast_fp16")]; + tensor hidden_states_27_pad_type_0 = const()[name = tensor("hidden_states_27_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_27_strides_0 = const()[name = tensor("hidden_states_27_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_27_pad_0 = const()[name = tensor("hidden_states_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_27_dilations_0 = const()[name = tensor("hidden_states_27_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_27_groups_0 = const()[name = tensor("hidden_states_27_groups_0"), val = tensor(1)]; + tensor layers_12_fc2_weight_to_fp16 = const()[name = tensor("layers_12_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(535430848)))]; + tensor layers_12_fc2_bias_to_fp16 = const()[name = tensor("layers_12_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(543819520)))]; + tensor hidden_states_27_cast_fp16 = conv(bias = layers_12_fc2_bias_to_fp16, dilations = hidden_states_27_dilations_0, groups = hidden_states_27_groups_0, pad = hidden_states_27_pad_0, pad_type = hidden_states_27_pad_type_0, strides = hidden_states_27_strides_0, weight = layers_12_fc2_weight_to_fp16, x = input_129_cast_fp16)[name = tensor("hidden_states_27_cast_fp16")]; + tensor inputs_79_cast_fp16 = add(x = inputs_77_cast_fp16, y = hidden_states_27_cast_fp16)[name = tensor("inputs_79_cast_fp16")]; + tensor var_2991 = const()[name = tensor("op_2991"), val = tensor(3)]; + tensor out_79_axes_0 = const()[name = tensor("out_79_axes_0"), val = tensor([1])]; + tensor var_3016_to_fp16 = const()[name = tensor("op_3016_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_79_cast_fp16 = layer_norm(axes = out_79_axes_0, epsilon = var_3016_to_fp16, x = inputs_79_cast_fp16)[name = tensor("out_79_cast_fp16")]; + tensor obj_183_gamma_0_to_fp16 = const()[name = tensor("obj_183_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(543821632)))]; + tensor obj_183_beta_0_to_fp16 = const()[name = tensor("obj_183_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(543823744)))]; + tensor obj_183_epsilon_0_to_fp16 = const()[name = tensor("obj_183_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_183_cast_fp16 = batch_norm(beta = obj_183_beta_0_to_fp16, epsilon = obj_183_epsilon_0_to_fp16, gamma = obj_183_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_79_cast_fp16)[name = tensor("obj_183_cast_fp16")]; + tensor query_53_pad_type_0 = const()[name = tensor("query_53_pad_type_0"), val = tensor("valid")]; + tensor query_53_strides_0 = const()[name = tensor("query_53_strides_0"), val = tensor([1, 1])]; + tensor query_53_pad_0 = const()[name = tensor("query_53_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_53_dilations_0 = const()[name = tensor("query_53_dilations_0"), val = tensor([1, 1])]; + tensor query_53_groups_0 = const()[name = tensor("query_53_groups_0"), val = tensor(1)]; + tensor layers_13_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_13_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(543825856)))]; + tensor layers_13_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_13_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(545923072)))]; + tensor query_53_cast_fp16 = conv(bias = layers_13_self_attn_q_proj_bias_to_fp16, dilations = query_53_dilations_0, groups = query_53_groups_0, pad = query_53_pad_0, pad_type = query_53_pad_type_0, strides = query_53_strides_0, weight = layers_13_self_attn_q_proj_weight_to_fp16, x = obj_183_cast_fp16)[name = tensor("query_53_cast_fp16")]; + tensor current_key_27_pad_type_0 = const()[name = tensor("current_key_27_pad_type_0"), val = tensor("valid")]; + tensor current_key_27_strides_0 = const()[name = tensor("current_key_27_strides_0"), val = tensor([1, 1])]; + tensor current_key_27_pad_0 = const()[name = tensor("current_key_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_27_dilations_0 = const()[name = tensor("current_key_27_dilations_0"), val = tensor([1, 1])]; + tensor current_key_27_groups_0 = const()[name = tensor("current_key_27_groups_0"), val = tensor(1)]; + tensor layers_13_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_13_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(545925184)))]; + tensor current_key_27_cast_fp16 = conv(dilations = current_key_27_dilations_0, groups = current_key_27_groups_0, pad = current_key_27_pad_0, pad_type = current_key_27_pad_type_0, strides = current_key_27_strides_0, weight = layers_13_self_attn_k_proj_weight_to_fp16, x = obj_183_cast_fp16)[name = tensor("current_key_27_cast_fp16")]; + tensor current_value_27_pad_type_0 = const()[name = tensor("current_value_27_pad_type_0"), val = tensor("valid")]; + tensor current_value_27_strides_0 = const()[name = tensor("current_value_27_strides_0"), val = tensor([1, 1])]; + tensor current_value_27_pad_0 = const()[name = tensor("current_value_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_27_dilations_0 = const()[name = tensor("current_value_27_dilations_0"), val = tensor([1, 1])]; + tensor current_value_27_groups_0 = const()[name = tensor("current_value_27_groups_0"), val = tensor(1)]; + tensor layers_13_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_13_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(548022400)))]; + tensor layers_13_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_13_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(550119616)))]; + tensor current_value_27_cast_fp16 = conv(bias = layers_13_self_attn_v_proj_bias_to_fp16, dilations = current_value_27_dilations_0, groups = current_value_27_groups_0, pad = current_value_27_pad_0, pad_type = current_value_27_pad_type_0, strides = current_value_27_strides_0, weight = layers_13_self_attn_v_proj_weight_to_fp16, x = obj_183_cast_fp16)[name = tensor("current_value_27_cast_fp16")]; + tensor var_3055_cast_fp16 = mul(x = var_87_cast_fp16_13, y = var_207_cast_fp16)[name = tensor("op_3055_cast_fp16")]; + tensor var_3056_cast_fp16 = mul(x = current_key_27_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_3056_cast_fp16")]; + tensor key_53_cast_fp16 = add(x = var_3055_cast_fp16, y = var_3056_cast_fp16)[name = tensor("key_53_cast_fp16")]; + tensor var_3059_cast_fp16 = mul(x = var_114_cast_fp16_13, y = var_207_cast_fp16)[name = tensor("op_3059_cast_fp16")]; + tensor var_3060_cast_fp16 = mul(x = current_value_27_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_3060_cast_fp16")]; + tensor value_53_cast_fp16 = add(x = var_3059_cast_fp16, y = var_3060_cast_fp16)[name = tensor("value_53_cast_fp16")]; + tensor var_3064 = const()[name = tensor("op_3064"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_53_cast_fp16 = reshape(shape = var_3064, x = query_53_cast_fp16)[name = tensor("mh_q_53_cast_fp16")]; + tensor var_3066_to_fp16 = const()[name = tensor("op_3066_to_fp16"), val = tensor(0x1p-3)]; + tensor var_3067_cast_fp16 = mul(x = mh_q_53_cast_fp16, y = var_3066_to_fp16)[name = tensor("op_3067_cast_fp16")]; + tensor var_3070 = const()[name = tensor("op_3070"), val = tensor([1, 16, 64, 448])]; + tensor var_3071_cast_fp16 = reshape(shape = var_3070, x = key_53_cast_fp16)[name = tensor("op_3071_cast_fp16")]; + tensor mh_w_79_transpose_x_0 = const()[name = tensor("mh_w_79_transpose_x_0"), val = tensor(true)]; + tensor mh_w_79_transpose_y_0 = const()[name = tensor("mh_w_79_transpose_y_0"), val = tensor(false)]; + tensor mh_w_79_cast_fp16 = matmul(transpose_x = mh_w_79_transpose_x_0, transpose_y = mh_w_79_transpose_y_0, x = var_3067_cast_fp16, y = var_3071_cast_fp16)[name = tensor("mh_w_79_cast_fp16")]; + tensor mh_w_81_cast_fp16 = add(x = mh_w_79_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_81_cast_fp16")]; + tensor var_3079_cast_fp16 = softmax(axis = var_2991, x = mh_w_81_cast_fp16)[name = tensor("op_3079_cast_fp16")]; + tensor var_3080 = const()[name = tensor("op_3080"), val = tensor([1, 16, 64, 448])]; + tensor var_3081_cast_fp16 = reshape(shape = var_3080, x = value_53_cast_fp16)[name = tensor("op_3081_cast_fp16")]; + tensor attn_53_transpose_x_0 = const()[name = tensor("attn_53_transpose_x_0"), val = tensor(false)]; + tensor attn_53_transpose_y_0 = const()[name = tensor("attn_53_transpose_y_0"), val = tensor(true)]; + tensor attn_53_cast_fp16 = matmul(transpose_x = attn_53_transpose_x_0, transpose_y = attn_53_transpose_y_0, x = var_3081_cast_fp16, y = var_3079_cast_fp16)[name = tensor("attn_53_cast_fp16")]; + tensor var_3084 = const()[name = tensor("op_3084"), val = tensor([1, 1024, 1, 1])]; + tensor input_131_cast_fp16 = reshape(shape = var_3084, x = attn_53_cast_fp16)[name = tensor("input_131_cast_fp16")]; + tensor obj_189_pad_type_0 = const()[name = tensor("obj_189_pad_type_0"), val = tensor("valid")]; + tensor obj_189_strides_0 = const()[name = tensor("obj_189_strides_0"), val = tensor([1, 1])]; + tensor obj_189_pad_0 = const()[name = tensor("obj_189_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_189_dilations_0 = const()[name = tensor("obj_189_dilations_0"), val = tensor([1, 1])]; + tensor obj_189_groups_0 = const()[name = tensor("obj_189_groups_0"), val = tensor(1)]; + tensor layers_13_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_13_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(550121728)))]; + tensor layers_13_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_13_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(552218944)))]; + tensor obj_189_cast_fp16 = conv(bias = layers_13_self_attn_o_proj_bias_to_fp16, dilations = obj_189_dilations_0, groups = obj_189_groups_0, pad = obj_189_pad_0, pad_type = obj_189_pad_type_0, strides = obj_189_strides_0, weight = layers_13_self_attn_o_proj_weight_to_fp16, x = input_131_cast_fp16)[name = tensor("obj_189_cast_fp16")]; + tensor inputs_81_cast_fp16 = add(x = inputs_79_cast_fp16, y = obj_189_cast_fp16)[name = tensor("inputs_81_cast_fp16")]; + tensor out_81_axes_0 = const()[name = tensor("out_81_axes_0"), val = tensor([1])]; + tensor var_3106_to_fp16 = const()[name = tensor("op_3106_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_81_cast_fp16 = layer_norm(axes = out_81_axes_0, epsilon = var_3106_to_fp16, x = inputs_81_cast_fp16)[name = tensor("out_81_cast_fp16")]; + tensor obj_191_gamma_0_to_fp16 = const()[name = tensor("obj_191_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(552221056)))]; + tensor obj_191_beta_0_to_fp16 = const()[name = tensor("obj_191_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(552223168)))]; + tensor obj_191_epsilon_0_to_fp16 = const()[name = tensor("obj_191_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_191_cast_fp16 = batch_norm(beta = obj_191_beta_0_to_fp16, epsilon = obj_191_epsilon_0_to_fp16, gamma = obj_191_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_81_cast_fp16)[name = tensor("obj_191_cast_fp16")]; + tensor query_55_pad_type_0 = const()[name = tensor("query_55_pad_type_0"), val = tensor("valid")]; + tensor query_55_strides_0 = const()[name = tensor("query_55_strides_0"), val = tensor([1, 1])]; + tensor query_55_pad_0 = const()[name = tensor("query_55_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_55_dilations_0 = const()[name = tensor("query_55_dilations_0"), val = tensor([1, 1])]; + tensor query_55_groups_0 = const()[name = tensor("query_55_groups_0"), val = tensor(1)]; + tensor layers_13_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_13_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(552225280)))]; + tensor layers_13_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_13_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(554322496)))]; + tensor query_55_cast_fp16 = conv(bias = layers_13_encoder_attn_q_proj_bias_to_fp16, dilations = query_55_dilations_0, groups = query_55_groups_0, pad = query_55_pad_0, pad_type = query_55_pad_type_0, strides = query_55_strides_0, weight = layers_13_encoder_attn_q_proj_weight_to_fp16, x = obj_191_cast_fp16)[name = tensor("query_55_cast_fp16")]; + tensor key_55_pad_type_0 = const()[name = tensor("key_55_pad_type_0"), val = tensor("valid")]; + tensor key_55_strides_0 = const()[name = tensor("key_55_strides_0"), val = tensor([1, 1])]; + tensor key_55_pad_0 = const()[name = tensor("key_55_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_55_dilations_0 = const()[name = tensor("key_55_dilations_0"), val = tensor([1, 1])]; + tensor key_55_groups_0 = const()[name = tensor("key_55_groups_0"), val = tensor(1)]; + tensor layers_13_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_13_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(554324608)))]; + tensor key_55_cast_fp16 = conv(dilations = key_55_dilations_0, groups = key_55_groups_0, pad = key_55_pad_0, pad_type = key_55_pad_type_0, strides = key_55_strides_0, weight = layers_13_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_55_cast_fp16")]; + tensor value_55_pad_type_0 = const()[name = tensor("value_55_pad_type_0"), val = tensor("valid")]; + tensor value_55_strides_0 = const()[name = tensor("value_55_strides_0"), val = tensor([1, 1])]; + tensor value_55_pad_0 = const()[name = tensor("value_55_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_55_dilations_0 = const()[name = tensor("value_55_dilations_0"), val = tensor([1, 1])]; + tensor value_55_groups_0 = const()[name = tensor("value_55_groups_0"), val = tensor(1)]; + tensor layers_13_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_13_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(556421824)))]; + tensor layers_13_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_13_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(558519040)))]; + tensor value_55_cast_fp16 = conv(bias = layers_13_encoder_attn_v_proj_bias_to_fp16, dilations = value_55_dilations_0, groups = value_55_groups_0, pad = value_55_pad_0, pad_type = value_55_pad_type_0, strides = value_55_strides_0, weight = layers_13_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_55_cast_fp16")]; + tensor var_3142 = const()[name = tensor("op_3142"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_55_cast_fp16 = reshape(shape = var_3142, x = query_55_cast_fp16)[name = tensor("mh_q_55_cast_fp16")]; + tensor var_3144_to_fp16 = const()[name = tensor("op_3144_to_fp16"), val = tensor(0x1p-3)]; + tensor var_3145_cast_fp16 = mul(x = mh_q_55_cast_fp16, y = var_3144_to_fp16)[name = tensor("op_3145_cast_fp16")]; + tensor var_3148 = const()[name = tensor("op_3148"), val = tensor([1, 16, 64, 1500])]; + tensor var_3149_cast_fp16 = reshape(shape = var_3148, x = key_55_cast_fp16)[name = tensor("op_3149_cast_fp16")]; + tensor mh_w_83_transpose_x_0 = const()[name = tensor("mh_w_83_transpose_x_0"), val = tensor(true)]; + tensor mh_w_83_transpose_y_0 = const()[name = tensor("mh_w_83_transpose_y_0"), val = tensor(false)]; + tensor mh_w_83_cast_fp16 = matmul(transpose_x = mh_w_83_transpose_x_0, transpose_y = mh_w_83_transpose_y_0, x = var_3145_cast_fp16, y = var_3149_cast_fp16)[name = tensor("mh_w_83_cast_fp16")]; + tensor obj_195_cast_fp16 = softmax(axis = var_2991, x = mh_w_83_cast_fp16)[name = tensor("obj_195_cast_fp16")]; + tensor var_3153 = const()[name = tensor("op_3153"), val = tensor([1, 16, 64, 1500])]; + tensor var_3154_cast_fp16 = reshape(shape = var_3153, x = value_55_cast_fp16)[name = tensor("op_3154_cast_fp16")]; + tensor attn_55_transpose_x_0 = const()[name = tensor("attn_55_transpose_x_0"), val = tensor(false)]; + tensor attn_55_transpose_y_0 = const()[name = tensor("attn_55_transpose_y_0"), val = tensor(true)]; + tensor attn_55_cast_fp16 = matmul(transpose_x = attn_55_transpose_x_0, transpose_y = attn_55_transpose_y_0, x = var_3154_cast_fp16, y = obj_195_cast_fp16)[name = tensor("attn_55_cast_fp16")]; + tensor var_3157 = const()[name = tensor("op_3157"), val = tensor([1, 1024, 1, 1])]; + tensor input_133_cast_fp16 = reshape(shape = var_3157, x = attn_55_cast_fp16)[name = tensor("input_133_cast_fp16")]; + tensor obj_193_pad_type_0 = const()[name = tensor("obj_193_pad_type_0"), val = tensor("valid")]; + tensor obj_193_strides_0 = const()[name = tensor("obj_193_strides_0"), val = tensor([1, 1])]; + tensor obj_193_pad_0 = const()[name = tensor("obj_193_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_193_dilations_0 = const()[name = tensor("obj_193_dilations_0"), val = tensor([1, 1])]; + tensor obj_193_groups_0 = const()[name = tensor("obj_193_groups_0"), val = tensor(1)]; + tensor layers_13_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_13_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(558521152)))]; + tensor layers_13_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_13_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(560618368)))]; + tensor obj_193_cast_fp16 = conv(bias = layers_13_encoder_attn_o_proj_bias_to_fp16, dilations = obj_193_dilations_0, groups = obj_193_groups_0, pad = obj_193_pad_0, pad_type = obj_193_pad_type_0, strides = obj_193_strides_0, weight = layers_13_encoder_attn_o_proj_weight_to_fp16, x = input_133_cast_fp16)[name = tensor("obj_193_cast_fp16")]; + tensor inputs_83_cast_fp16 = add(x = inputs_81_cast_fp16, y = obj_193_cast_fp16)[name = tensor("inputs_83_cast_fp16")]; + tensor out_83_axes_0 = const()[name = tensor("out_83_axes_0"), val = tensor([1])]; + tensor var_3178_to_fp16 = const()[name = tensor("op_3178_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_83_cast_fp16 = layer_norm(axes = out_83_axes_0, epsilon = var_3178_to_fp16, x = inputs_83_cast_fp16)[name = tensor("out_83_cast_fp16")]; + tensor input_135_gamma_0_to_fp16 = const()[name = tensor("input_135_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(560620480)))]; + tensor input_135_beta_0_to_fp16 = const()[name = tensor("input_135_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(560622592)))]; + tensor input_135_epsilon_0_to_fp16 = const()[name = tensor("input_135_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_135_cast_fp16 = batch_norm(beta = input_135_beta_0_to_fp16, epsilon = input_135_epsilon_0_to_fp16, gamma = input_135_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_83_cast_fp16)[name = tensor("input_135_cast_fp16")]; + tensor input_137_pad_type_0 = const()[name = tensor("input_137_pad_type_0"), val = tensor("valid")]; + tensor input_137_strides_0 = const()[name = tensor("input_137_strides_0"), val = tensor([1, 1])]; + tensor input_137_pad_0 = const()[name = tensor("input_137_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_137_dilations_0 = const()[name = tensor("input_137_dilations_0"), val = tensor([1, 1])]; + tensor input_137_groups_0 = const()[name = tensor("input_137_groups_0"), val = tensor(1)]; + tensor layers_13_fc1_weight_to_fp16 = const()[name = tensor("layers_13_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(560624704)))]; + tensor layers_13_fc1_bias_to_fp16 = const()[name = tensor("layers_13_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(569013376)))]; + tensor input_137_cast_fp16 = conv(bias = layers_13_fc1_bias_to_fp16, dilations = input_137_dilations_0, groups = input_137_groups_0, pad = input_137_pad_0, pad_type = input_137_pad_type_0, strides = input_137_strides_0, weight = layers_13_fc1_weight_to_fp16, x = input_135_cast_fp16)[name = tensor("input_137_cast_fp16")]; + tensor input_139_mode_0 = const()[name = tensor("input_139_mode_0"), val = tensor("EXACT")]; + tensor input_139_cast_fp16 = gelu(mode = input_139_mode_0, x = input_137_cast_fp16)[name = tensor("input_139_cast_fp16")]; + tensor hidden_states_29_pad_type_0 = const()[name = tensor("hidden_states_29_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_29_strides_0 = const()[name = tensor("hidden_states_29_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_29_pad_0 = const()[name = tensor("hidden_states_29_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_29_dilations_0 = const()[name = tensor("hidden_states_29_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_29_groups_0 = const()[name = tensor("hidden_states_29_groups_0"), val = tensor(1)]; + tensor layers_13_fc2_weight_to_fp16 = const()[name = tensor("layers_13_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(569021632)))]; + tensor layers_13_fc2_bias_to_fp16 = const()[name = tensor("layers_13_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(577410304)))]; + tensor hidden_states_29_cast_fp16 = conv(bias = layers_13_fc2_bias_to_fp16, dilations = hidden_states_29_dilations_0, groups = hidden_states_29_groups_0, pad = hidden_states_29_pad_0, pad_type = hidden_states_29_pad_type_0, strides = hidden_states_29_strides_0, weight = layers_13_fc2_weight_to_fp16, x = input_139_cast_fp16)[name = tensor("hidden_states_29_cast_fp16")]; + tensor inputs_85_cast_fp16 = add(x = inputs_83_cast_fp16, y = hidden_states_29_cast_fp16)[name = tensor("inputs_85_cast_fp16")]; + tensor var_3214 = const()[name = tensor("op_3214"), val = tensor(3)]; + tensor out_85_axes_0 = const()[name = tensor("out_85_axes_0"), val = tensor([1])]; + tensor var_3239_to_fp16 = const()[name = tensor("op_3239_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_85_cast_fp16 = layer_norm(axes = out_85_axes_0, epsilon = var_3239_to_fp16, x = inputs_85_cast_fp16)[name = tensor("out_85_cast_fp16")]; + tensor obj_197_gamma_0_to_fp16 = const()[name = tensor("obj_197_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(577412416)))]; + tensor obj_197_beta_0_to_fp16 = const()[name = tensor("obj_197_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(577414528)))]; + tensor obj_197_epsilon_0_to_fp16 = const()[name = tensor("obj_197_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_197_cast_fp16 = batch_norm(beta = obj_197_beta_0_to_fp16, epsilon = obj_197_epsilon_0_to_fp16, gamma = obj_197_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_85_cast_fp16)[name = tensor("obj_197_cast_fp16")]; + tensor query_57_pad_type_0 = const()[name = tensor("query_57_pad_type_0"), val = tensor("valid")]; + tensor query_57_strides_0 = const()[name = tensor("query_57_strides_0"), val = tensor([1, 1])]; + tensor query_57_pad_0 = const()[name = tensor("query_57_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_57_dilations_0 = const()[name = tensor("query_57_dilations_0"), val = tensor([1, 1])]; + tensor query_57_groups_0 = const()[name = tensor("query_57_groups_0"), val = tensor(1)]; + tensor layers_14_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_14_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(577416640)))]; + tensor layers_14_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_14_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(579513856)))]; + tensor query_57_cast_fp16 = conv(bias = layers_14_self_attn_q_proj_bias_to_fp16, dilations = query_57_dilations_0, groups = query_57_groups_0, pad = query_57_pad_0, pad_type = query_57_pad_type_0, strides = query_57_strides_0, weight = layers_14_self_attn_q_proj_weight_to_fp16, x = obj_197_cast_fp16)[name = tensor("query_57_cast_fp16")]; + tensor current_key_29_pad_type_0 = const()[name = tensor("current_key_29_pad_type_0"), val = tensor("valid")]; + tensor current_key_29_strides_0 = const()[name = tensor("current_key_29_strides_0"), val = tensor([1, 1])]; + tensor current_key_29_pad_0 = const()[name = tensor("current_key_29_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_29_dilations_0 = const()[name = tensor("current_key_29_dilations_0"), val = tensor([1, 1])]; + tensor current_key_29_groups_0 = const()[name = tensor("current_key_29_groups_0"), val = tensor(1)]; + tensor layers_14_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_14_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(579515968)))]; + tensor current_key_29_cast_fp16 = conv(dilations = current_key_29_dilations_0, groups = current_key_29_groups_0, pad = current_key_29_pad_0, pad_type = current_key_29_pad_type_0, strides = current_key_29_strides_0, weight = layers_14_self_attn_k_proj_weight_to_fp16, x = obj_197_cast_fp16)[name = tensor("current_key_29_cast_fp16")]; + tensor current_value_29_pad_type_0 = const()[name = tensor("current_value_29_pad_type_0"), val = tensor("valid")]; + tensor current_value_29_strides_0 = const()[name = tensor("current_value_29_strides_0"), val = tensor([1, 1])]; + tensor current_value_29_pad_0 = const()[name = tensor("current_value_29_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_29_dilations_0 = const()[name = tensor("current_value_29_dilations_0"), val = tensor([1, 1])]; + tensor current_value_29_groups_0 = const()[name = tensor("current_value_29_groups_0"), val = tensor(1)]; + tensor layers_14_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_14_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(581613184)))]; + tensor layers_14_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_14_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(583710400)))]; + tensor current_value_29_cast_fp16 = conv(bias = layers_14_self_attn_v_proj_bias_to_fp16, dilations = current_value_29_dilations_0, groups = current_value_29_groups_0, pad = current_value_29_pad_0, pad_type = current_value_29_pad_type_0, strides = current_value_29_strides_0, weight = layers_14_self_attn_v_proj_weight_to_fp16, x = obj_197_cast_fp16)[name = tensor("current_value_29_cast_fp16")]; + tensor var_3278_cast_fp16 = mul(x = var_87_cast_fp16_14, y = var_207_cast_fp16)[name = tensor("op_3278_cast_fp16")]; + tensor var_3279_cast_fp16 = mul(x = current_key_29_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_3279_cast_fp16")]; + tensor key_57_cast_fp16 = add(x = var_3278_cast_fp16, y = var_3279_cast_fp16)[name = tensor("key_57_cast_fp16")]; + tensor var_3282_cast_fp16 = mul(x = var_114_cast_fp16_14, y = var_207_cast_fp16)[name = tensor("op_3282_cast_fp16")]; + tensor var_3283_cast_fp16 = mul(x = current_value_29_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_3283_cast_fp16")]; + tensor value_57_cast_fp16 = add(x = var_3282_cast_fp16, y = var_3283_cast_fp16)[name = tensor("value_57_cast_fp16")]; + tensor var_3287 = const()[name = tensor("op_3287"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_57_cast_fp16 = reshape(shape = var_3287, x = query_57_cast_fp16)[name = tensor("mh_q_57_cast_fp16")]; + tensor var_3289_to_fp16 = const()[name = tensor("op_3289_to_fp16"), val = tensor(0x1p-3)]; + tensor var_3290_cast_fp16 = mul(x = mh_q_57_cast_fp16, y = var_3289_to_fp16)[name = tensor("op_3290_cast_fp16")]; + tensor var_3293 = const()[name = tensor("op_3293"), val = tensor([1, 16, 64, 448])]; + tensor var_3294_cast_fp16 = reshape(shape = var_3293, x = key_57_cast_fp16)[name = tensor("op_3294_cast_fp16")]; + tensor mh_w_85_transpose_x_0 = const()[name = tensor("mh_w_85_transpose_x_0"), val = tensor(true)]; + tensor mh_w_85_transpose_y_0 = const()[name = tensor("mh_w_85_transpose_y_0"), val = tensor(false)]; + tensor mh_w_85_cast_fp16 = matmul(transpose_x = mh_w_85_transpose_x_0, transpose_y = mh_w_85_transpose_y_0, x = var_3290_cast_fp16, y = var_3294_cast_fp16)[name = tensor("mh_w_85_cast_fp16")]; + tensor mh_w_87_cast_fp16 = add(x = mh_w_85_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_87_cast_fp16")]; + tensor var_3302_cast_fp16 = softmax(axis = var_3214, x = mh_w_87_cast_fp16)[name = tensor("op_3302_cast_fp16")]; + tensor var_3303 = const()[name = tensor("op_3303"), val = tensor([1, 16, 64, 448])]; + tensor var_3304_cast_fp16 = reshape(shape = var_3303, x = value_57_cast_fp16)[name = tensor("op_3304_cast_fp16")]; + tensor attn_57_transpose_x_0 = const()[name = tensor("attn_57_transpose_x_0"), val = tensor(false)]; + tensor attn_57_transpose_y_0 = const()[name = tensor("attn_57_transpose_y_0"), val = tensor(true)]; + tensor attn_57_cast_fp16 = matmul(transpose_x = attn_57_transpose_x_0, transpose_y = attn_57_transpose_y_0, x = var_3304_cast_fp16, y = var_3302_cast_fp16)[name = tensor("attn_57_cast_fp16")]; + tensor var_3307 = const()[name = tensor("op_3307"), val = tensor([1, 1024, 1, 1])]; + tensor input_141_cast_fp16 = reshape(shape = var_3307, x = attn_57_cast_fp16)[name = tensor("input_141_cast_fp16")]; + tensor obj_203_pad_type_0 = const()[name = tensor("obj_203_pad_type_0"), val = tensor("valid")]; + tensor obj_203_strides_0 = const()[name = tensor("obj_203_strides_0"), val = tensor([1, 1])]; + tensor obj_203_pad_0 = const()[name = tensor("obj_203_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_203_dilations_0 = const()[name = tensor("obj_203_dilations_0"), val = tensor([1, 1])]; + tensor obj_203_groups_0 = const()[name = tensor("obj_203_groups_0"), val = tensor(1)]; + tensor layers_14_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_14_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(583712512)))]; + tensor layers_14_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_14_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(585809728)))]; + tensor obj_203_cast_fp16 = conv(bias = layers_14_self_attn_o_proj_bias_to_fp16, dilations = obj_203_dilations_0, groups = obj_203_groups_0, pad = obj_203_pad_0, pad_type = obj_203_pad_type_0, strides = obj_203_strides_0, weight = layers_14_self_attn_o_proj_weight_to_fp16, x = input_141_cast_fp16)[name = tensor("obj_203_cast_fp16")]; + tensor inputs_87_cast_fp16 = add(x = inputs_85_cast_fp16, y = obj_203_cast_fp16)[name = tensor("inputs_87_cast_fp16")]; + tensor out_87_axes_0 = const()[name = tensor("out_87_axes_0"), val = tensor([1])]; + tensor var_3329_to_fp16 = const()[name = tensor("op_3329_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_87_cast_fp16 = layer_norm(axes = out_87_axes_0, epsilon = var_3329_to_fp16, x = inputs_87_cast_fp16)[name = tensor("out_87_cast_fp16")]; + tensor obj_205_gamma_0_to_fp16 = const()[name = tensor("obj_205_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(585811840)))]; + tensor obj_205_beta_0_to_fp16 = const()[name = tensor("obj_205_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(585813952)))]; + tensor obj_205_epsilon_0_to_fp16 = const()[name = tensor("obj_205_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_205_cast_fp16 = batch_norm(beta = obj_205_beta_0_to_fp16, epsilon = obj_205_epsilon_0_to_fp16, gamma = obj_205_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_87_cast_fp16)[name = tensor("obj_205_cast_fp16")]; + tensor query_59_pad_type_0 = const()[name = tensor("query_59_pad_type_0"), val = tensor("valid")]; + tensor query_59_strides_0 = const()[name = tensor("query_59_strides_0"), val = tensor([1, 1])]; + tensor query_59_pad_0 = const()[name = tensor("query_59_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_59_dilations_0 = const()[name = tensor("query_59_dilations_0"), val = tensor([1, 1])]; + tensor query_59_groups_0 = const()[name = tensor("query_59_groups_0"), val = tensor(1)]; + tensor layers_14_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_14_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(585816064)))]; + tensor layers_14_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_14_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(587913280)))]; + tensor query_59_cast_fp16 = conv(bias = layers_14_encoder_attn_q_proj_bias_to_fp16, dilations = query_59_dilations_0, groups = query_59_groups_0, pad = query_59_pad_0, pad_type = query_59_pad_type_0, strides = query_59_strides_0, weight = layers_14_encoder_attn_q_proj_weight_to_fp16, x = obj_205_cast_fp16)[name = tensor("query_59_cast_fp16")]; + tensor key_59_pad_type_0 = const()[name = tensor("key_59_pad_type_0"), val = tensor("valid")]; + tensor key_59_strides_0 = const()[name = tensor("key_59_strides_0"), val = tensor([1, 1])]; + tensor key_59_pad_0 = const()[name = tensor("key_59_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_59_dilations_0 = const()[name = tensor("key_59_dilations_0"), val = tensor([1, 1])]; + tensor key_59_groups_0 = const()[name = tensor("key_59_groups_0"), val = tensor(1)]; + tensor layers_14_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_14_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(587915392)))]; + tensor key_59_cast_fp16 = conv(dilations = key_59_dilations_0, groups = key_59_groups_0, pad = key_59_pad_0, pad_type = key_59_pad_type_0, strides = key_59_strides_0, weight = layers_14_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_59_cast_fp16")]; + tensor value_59_pad_type_0 = const()[name = tensor("value_59_pad_type_0"), val = tensor("valid")]; + tensor value_59_strides_0 = const()[name = tensor("value_59_strides_0"), val = tensor([1, 1])]; + tensor value_59_pad_0 = const()[name = tensor("value_59_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_59_dilations_0 = const()[name = tensor("value_59_dilations_0"), val = tensor([1, 1])]; + tensor value_59_groups_0 = const()[name = tensor("value_59_groups_0"), val = tensor(1)]; + tensor layers_14_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_14_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(590012608)))]; + tensor layers_14_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_14_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(592109824)))]; + tensor value_59_cast_fp16 = conv(bias = layers_14_encoder_attn_v_proj_bias_to_fp16, dilations = value_59_dilations_0, groups = value_59_groups_0, pad = value_59_pad_0, pad_type = value_59_pad_type_0, strides = value_59_strides_0, weight = layers_14_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_59_cast_fp16")]; + tensor var_3365 = const()[name = tensor("op_3365"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_59_cast_fp16 = reshape(shape = var_3365, x = query_59_cast_fp16)[name = tensor("mh_q_59_cast_fp16")]; + tensor var_3367_to_fp16 = const()[name = tensor("op_3367_to_fp16"), val = tensor(0x1p-3)]; + tensor var_3368_cast_fp16 = mul(x = mh_q_59_cast_fp16, y = var_3367_to_fp16)[name = tensor("op_3368_cast_fp16")]; + tensor var_3371 = const()[name = tensor("op_3371"), val = tensor([1, 16, 64, 1500])]; + tensor var_3372_cast_fp16 = reshape(shape = var_3371, x = key_59_cast_fp16)[name = tensor("op_3372_cast_fp16")]; + tensor mh_w_89_transpose_x_0 = const()[name = tensor("mh_w_89_transpose_x_0"), val = tensor(true)]; + tensor mh_w_89_transpose_y_0 = const()[name = tensor("mh_w_89_transpose_y_0"), val = tensor(false)]; + tensor mh_w_89_cast_fp16 = matmul(transpose_x = mh_w_89_transpose_x_0, transpose_y = mh_w_89_transpose_y_0, x = var_3368_cast_fp16, y = var_3372_cast_fp16)[name = tensor("mh_w_89_cast_fp16")]; + tensor obj_209_cast_fp16 = softmax(axis = var_3214, x = mh_w_89_cast_fp16)[name = tensor("obj_209_cast_fp16")]; + tensor var_3376 = const()[name = tensor("op_3376"), val = tensor([1, 16, 64, 1500])]; + tensor var_3377_cast_fp16 = reshape(shape = var_3376, x = value_59_cast_fp16)[name = tensor("op_3377_cast_fp16")]; + tensor attn_59_transpose_x_0 = const()[name = tensor("attn_59_transpose_x_0"), val = tensor(false)]; + tensor attn_59_transpose_y_0 = const()[name = tensor("attn_59_transpose_y_0"), val = tensor(true)]; + tensor attn_59_cast_fp16 = matmul(transpose_x = attn_59_transpose_x_0, transpose_y = attn_59_transpose_y_0, x = var_3377_cast_fp16, y = obj_209_cast_fp16)[name = tensor("attn_59_cast_fp16")]; + tensor var_3380 = const()[name = tensor("op_3380"), val = tensor([1, 1024, 1, 1])]; + tensor input_143_cast_fp16 = reshape(shape = var_3380, x = attn_59_cast_fp16)[name = tensor("input_143_cast_fp16")]; + tensor obj_207_pad_type_0 = const()[name = tensor("obj_207_pad_type_0"), val = tensor("valid")]; + tensor obj_207_strides_0 = const()[name = tensor("obj_207_strides_0"), val = tensor([1, 1])]; + tensor obj_207_pad_0 = const()[name = tensor("obj_207_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_207_dilations_0 = const()[name = tensor("obj_207_dilations_0"), val = tensor([1, 1])]; + tensor obj_207_groups_0 = const()[name = tensor("obj_207_groups_0"), val = tensor(1)]; + tensor layers_14_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_14_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(592111936)))]; + tensor layers_14_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_14_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(594209152)))]; + tensor obj_207_cast_fp16 = conv(bias = layers_14_encoder_attn_o_proj_bias_to_fp16, dilations = obj_207_dilations_0, groups = obj_207_groups_0, pad = obj_207_pad_0, pad_type = obj_207_pad_type_0, strides = obj_207_strides_0, weight = layers_14_encoder_attn_o_proj_weight_to_fp16, x = input_143_cast_fp16)[name = tensor("obj_207_cast_fp16")]; + tensor inputs_89_cast_fp16 = add(x = inputs_87_cast_fp16, y = obj_207_cast_fp16)[name = tensor("inputs_89_cast_fp16")]; + tensor out_89_axes_0 = const()[name = tensor("out_89_axes_0"), val = tensor([1])]; + tensor var_3398_to_fp16 = const()[name = tensor("op_3398_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_89_cast_fp16 = layer_norm(axes = out_89_axes_0, epsilon = var_3398_to_fp16, x = inputs_89_cast_fp16)[name = tensor("out_89_cast_fp16")]; + tensor input_145_gamma_0_to_fp16 = const()[name = tensor("input_145_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(594211264)))]; + tensor input_145_beta_0_to_fp16 = const()[name = tensor("input_145_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(594213376)))]; + tensor input_145_epsilon_0_to_fp16 = const()[name = tensor("input_145_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_145_cast_fp16 = batch_norm(beta = input_145_beta_0_to_fp16, epsilon = input_145_epsilon_0_to_fp16, gamma = input_145_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_89_cast_fp16)[name = tensor("input_145_cast_fp16")]; + tensor input_147_pad_type_0 = const()[name = tensor("input_147_pad_type_0"), val = tensor("valid")]; + tensor input_147_strides_0 = const()[name = tensor("input_147_strides_0"), val = tensor([1, 1])]; + tensor input_147_pad_0 = const()[name = tensor("input_147_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_147_dilations_0 = const()[name = tensor("input_147_dilations_0"), val = tensor([1, 1])]; + tensor input_147_groups_0 = const()[name = tensor("input_147_groups_0"), val = tensor(1)]; + tensor layers_14_fc1_weight_to_fp16 = const()[name = tensor("layers_14_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(594215488)))]; + tensor layers_14_fc1_bias_to_fp16 = const()[name = tensor("layers_14_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(602604160)))]; + tensor input_147_cast_fp16 = conv(bias = layers_14_fc1_bias_to_fp16, dilations = input_147_dilations_0, groups = input_147_groups_0, pad = input_147_pad_0, pad_type = input_147_pad_type_0, strides = input_147_strides_0, weight = layers_14_fc1_weight_to_fp16, x = input_145_cast_fp16)[name = tensor("input_147_cast_fp16")]; + tensor input_149_mode_0 = const()[name = tensor("input_149_mode_0"), val = tensor("EXACT")]; + tensor input_149_cast_fp16 = gelu(mode = input_149_mode_0, x = input_147_cast_fp16)[name = tensor("input_149_cast_fp16")]; + tensor hidden_states_31_pad_type_0 = const()[name = tensor("hidden_states_31_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_31_strides_0 = const()[name = tensor("hidden_states_31_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_31_pad_0 = const()[name = tensor("hidden_states_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_31_dilations_0 = const()[name = tensor("hidden_states_31_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_31_groups_0 = const()[name = tensor("hidden_states_31_groups_0"), val = tensor(1)]; + tensor layers_14_fc2_weight_to_fp16 = const()[name = tensor("layers_14_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(602612416)))]; + tensor layers_14_fc2_bias_to_fp16 = const()[name = tensor("layers_14_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(611001088)))]; + tensor hidden_states_31_cast_fp16 = conv(bias = layers_14_fc2_bias_to_fp16, dilations = hidden_states_31_dilations_0, groups = hidden_states_31_groups_0, pad = hidden_states_31_pad_0, pad_type = hidden_states_31_pad_type_0, strides = hidden_states_31_strides_0, weight = layers_14_fc2_weight_to_fp16, x = input_149_cast_fp16)[name = tensor("hidden_states_31_cast_fp16")]; + tensor inputs_91_cast_fp16 = add(x = inputs_89_cast_fp16, y = hidden_states_31_cast_fp16)[name = tensor("inputs_91_cast_fp16")]; + tensor var_3433 = const()[name = tensor("op_3433"), val = tensor(3)]; + tensor out_91_axes_0 = const()[name = tensor("out_91_axes_0"), val = tensor([1])]; + tensor var_3458_to_fp16 = const()[name = tensor("op_3458_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_91_cast_fp16 = layer_norm(axes = out_91_axes_0, epsilon = var_3458_to_fp16, x = inputs_91_cast_fp16)[name = tensor("out_91_cast_fp16")]; + tensor obj_211_gamma_0_to_fp16 = const()[name = tensor("obj_211_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(611003200)))]; + tensor obj_211_beta_0_to_fp16 = const()[name = tensor("obj_211_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(611005312)))]; + tensor obj_211_epsilon_0_to_fp16 = const()[name = tensor("obj_211_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_211_cast_fp16 = batch_norm(beta = obj_211_beta_0_to_fp16, epsilon = obj_211_epsilon_0_to_fp16, gamma = obj_211_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_91_cast_fp16)[name = tensor("obj_211_cast_fp16")]; + tensor query_61_pad_type_0 = const()[name = tensor("query_61_pad_type_0"), val = tensor("valid")]; + tensor query_61_strides_0 = const()[name = tensor("query_61_strides_0"), val = tensor([1, 1])]; + tensor query_61_pad_0 = const()[name = tensor("query_61_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_61_dilations_0 = const()[name = tensor("query_61_dilations_0"), val = tensor([1, 1])]; + tensor query_61_groups_0 = const()[name = tensor("query_61_groups_0"), val = tensor(1)]; + tensor layers_15_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_15_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(611007424)))]; + tensor layers_15_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_15_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(613104640)))]; + tensor query_61_cast_fp16 = conv(bias = layers_15_self_attn_q_proj_bias_to_fp16, dilations = query_61_dilations_0, groups = query_61_groups_0, pad = query_61_pad_0, pad_type = query_61_pad_type_0, strides = query_61_strides_0, weight = layers_15_self_attn_q_proj_weight_to_fp16, x = obj_211_cast_fp16)[name = tensor("query_61_cast_fp16")]; + tensor current_key_31_pad_type_0 = const()[name = tensor("current_key_31_pad_type_0"), val = tensor("valid")]; + tensor current_key_31_strides_0 = const()[name = tensor("current_key_31_strides_0"), val = tensor([1, 1])]; + tensor current_key_31_pad_0 = const()[name = tensor("current_key_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_31_dilations_0 = const()[name = tensor("current_key_31_dilations_0"), val = tensor([1, 1])]; + tensor current_key_31_groups_0 = const()[name = tensor("current_key_31_groups_0"), val = tensor(1)]; + tensor layers_15_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_15_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(613106752)))]; + tensor current_key_31_cast_fp16 = conv(dilations = current_key_31_dilations_0, groups = current_key_31_groups_0, pad = current_key_31_pad_0, pad_type = current_key_31_pad_type_0, strides = current_key_31_strides_0, weight = layers_15_self_attn_k_proj_weight_to_fp16, x = obj_211_cast_fp16)[name = tensor("current_key_31_cast_fp16")]; + tensor current_value_31_pad_type_0 = const()[name = tensor("current_value_31_pad_type_0"), val = tensor("valid")]; + tensor current_value_31_strides_0 = const()[name = tensor("current_value_31_strides_0"), val = tensor([1, 1])]; + tensor current_value_31_pad_0 = const()[name = tensor("current_value_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_31_dilations_0 = const()[name = tensor("current_value_31_dilations_0"), val = tensor([1, 1])]; + tensor current_value_31_groups_0 = const()[name = tensor("current_value_31_groups_0"), val = tensor(1)]; + tensor layers_15_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_15_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(615203968)))]; + tensor layers_15_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_15_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(617301184)))]; + tensor current_value_31_cast_fp16 = conv(bias = layers_15_self_attn_v_proj_bias_to_fp16, dilations = current_value_31_dilations_0, groups = current_value_31_groups_0, pad = current_value_31_pad_0, pad_type = current_value_31_pad_type_0, strides = current_value_31_strides_0, weight = layers_15_self_attn_v_proj_weight_to_fp16, x = obj_211_cast_fp16)[name = tensor("current_value_31_cast_fp16")]; + tensor var_3497_cast_fp16 = mul(x = var_87_cast_fp16_15, y = var_207_cast_fp16)[name = tensor("op_3497_cast_fp16")]; + tensor var_3498_cast_fp16 = mul(x = current_key_31_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_3498_cast_fp16")]; + tensor key_61_cast_fp16 = add(x = var_3497_cast_fp16, y = var_3498_cast_fp16)[name = tensor("key_61_cast_fp16")]; + tensor var_3501_cast_fp16 = mul(x = var_114_cast_fp16_15, y = var_207_cast_fp16)[name = tensor("op_3501_cast_fp16")]; + tensor var_3502_cast_fp16 = mul(x = current_value_31_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_3502_cast_fp16")]; + tensor value_61_cast_fp16 = add(x = var_3501_cast_fp16, y = var_3502_cast_fp16)[name = tensor("value_61_cast_fp16")]; + tensor var_3506 = const()[name = tensor("op_3506"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_61_cast_fp16 = reshape(shape = var_3506, x = query_61_cast_fp16)[name = tensor("mh_q_61_cast_fp16")]; + tensor var_3508_to_fp16 = const()[name = tensor("op_3508_to_fp16"), val = tensor(0x1p-3)]; + tensor var_3509_cast_fp16 = mul(x = mh_q_61_cast_fp16, y = var_3508_to_fp16)[name = tensor("op_3509_cast_fp16")]; + tensor var_3512 = const()[name = tensor("op_3512"), val = tensor([1, 16, 64, 448])]; + tensor var_3513_cast_fp16 = reshape(shape = var_3512, x = key_61_cast_fp16)[name = tensor("op_3513_cast_fp16")]; + tensor mh_w_91_transpose_x_0 = const()[name = tensor("mh_w_91_transpose_x_0"), val = tensor(true)]; + tensor mh_w_91_transpose_y_0 = const()[name = tensor("mh_w_91_transpose_y_0"), val = tensor(false)]; + tensor mh_w_91_cast_fp16 = matmul(transpose_x = mh_w_91_transpose_x_0, transpose_y = mh_w_91_transpose_y_0, x = var_3509_cast_fp16, y = var_3513_cast_fp16)[name = tensor("mh_w_91_cast_fp16")]; + tensor mh_w_93_cast_fp16 = add(x = mh_w_91_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_93_cast_fp16")]; + tensor var_3521_cast_fp16 = softmax(axis = var_3433, x = mh_w_93_cast_fp16)[name = tensor("op_3521_cast_fp16")]; + tensor var_3522 = const()[name = tensor("op_3522"), val = tensor([1, 16, 64, 448])]; + tensor var_3523_cast_fp16 = reshape(shape = var_3522, x = value_61_cast_fp16)[name = tensor("op_3523_cast_fp16")]; + tensor attn_61_transpose_x_0 = const()[name = tensor("attn_61_transpose_x_0"), val = tensor(false)]; + tensor attn_61_transpose_y_0 = const()[name = tensor("attn_61_transpose_y_0"), val = tensor(true)]; + tensor attn_61_cast_fp16 = matmul(transpose_x = attn_61_transpose_x_0, transpose_y = attn_61_transpose_y_0, x = var_3523_cast_fp16, y = var_3521_cast_fp16)[name = tensor("attn_61_cast_fp16")]; + tensor var_3526 = const()[name = tensor("op_3526"), val = tensor([1, 1024, 1, 1])]; + tensor input_151_cast_fp16 = reshape(shape = var_3526, x = attn_61_cast_fp16)[name = tensor("input_151_cast_fp16")]; + tensor obj_217_pad_type_0 = const()[name = tensor("obj_217_pad_type_0"), val = tensor("valid")]; + tensor obj_217_strides_0 = const()[name = tensor("obj_217_strides_0"), val = tensor([1, 1])]; + tensor obj_217_pad_0 = const()[name = tensor("obj_217_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_217_dilations_0 = const()[name = tensor("obj_217_dilations_0"), val = tensor([1, 1])]; + tensor obj_217_groups_0 = const()[name = tensor("obj_217_groups_0"), val = tensor(1)]; + tensor layers_15_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_15_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(617303296)))]; + tensor layers_15_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_15_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(619400512)))]; + tensor obj_217_cast_fp16 = conv(bias = layers_15_self_attn_o_proj_bias_to_fp16, dilations = obj_217_dilations_0, groups = obj_217_groups_0, pad = obj_217_pad_0, pad_type = obj_217_pad_type_0, strides = obj_217_strides_0, weight = layers_15_self_attn_o_proj_weight_to_fp16, x = input_151_cast_fp16)[name = tensor("obj_217_cast_fp16")]; + tensor inputs_93_cast_fp16 = add(x = inputs_91_cast_fp16, y = obj_217_cast_fp16)[name = tensor("inputs_93_cast_fp16")]; + tensor out_93_axes_0 = const()[name = tensor("out_93_axes_0"), val = tensor([1])]; + tensor var_3548_to_fp16 = const()[name = tensor("op_3548_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_93_cast_fp16 = layer_norm(axes = out_93_axes_0, epsilon = var_3548_to_fp16, x = inputs_93_cast_fp16)[name = tensor("out_93_cast_fp16")]; + tensor obj_219_gamma_0_to_fp16 = const()[name = tensor("obj_219_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(619402624)))]; + tensor obj_219_beta_0_to_fp16 = const()[name = tensor("obj_219_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(619404736)))]; + tensor obj_219_epsilon_0_to_fp16 = const()[name = tensor("obj_219_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_219_cast_fp16 = batch_norm(beta = obj_219_beta_0_to_fp16, epsilon = obj_219_epsilon_0_to_fp16, gamma = obj_219_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_93_cast_fp16)[name = tensor("obj_219_cast_fp16")]; + tensor query_63_pad_type_0 = const()[name = tensor("query_63_pad_type_0"), val = tensor("valid")]; + tensor query_63_strides_0 = const()[name = tensor("query_63_strides_0"), val = tensor([1, 1])]; + tensor query_63_pad_0 = const()[name = tensor("query_63_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_63_dilations_0 = const()[name = tensor("query_63_dilations_0"), val = tensor([1, 1])]; + tensor query_63_groups_0 = const()[name = tensor("query_63_groups_0"), val = tensor(1)]; + tensor layers_15_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_15_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(619406848)))]; + tensor layers_15_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_15_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(621504064)))]; + tensor query_63_cast_fp16 = conv(bias = layers_15_encoder_attn_q_proj_bias_to_fp16, dilations = query_63_dilations_0, groups = query_63_groups_0, pad = query_63_pad_0, pad_type = query_63_pad_type_0, strides = query_63_strides_0, weight = layers_15_encoder_attn_q_proj_weight_to_fp16, x = obj_219_cast_fp16)[name = tensor("query_63_cast_fp16")]; + tensor key_63_pad_type_0 = const()[name = tensor("key_63_pad_type_0"), val = tensor("valid")]; + tensor key_63_strides_0 = const()[name = tensor("key_63_strides_0"), val = tensor([1, 1])]; + tensor key_63_pad_0 = const()[name = tensor("key_63_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_63_dilations_0 = const()[name = tensor("key_63_dilations_0"), val = tensor([1, 1])]; + tensor key_63_groups_0 = const()[name = tensor("key_63_groups_0"), val = tensor(1)]; + tensor layers_15_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_15_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(621506176)))]; + tensor key_63_cast_fp16 = conv(dilations = key_63_dilations_0, groups = key_63_groups_0, pad = key_63_pad_0, pad_type = key_63_pad_type_0, strides = key_63_strides_0, weight = layers_15_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_63_cast_fp16")]; + tensor value_63_pad_type_0 = const()[name = tensor("value_63_pad_type_0"), val = tensor("valid")]; + tensor value_63_strides_0 = const()[name = tensor("value_63_strides_0"), val = tensor([1, 1])]; + tensor value_63_pad_0 = const()[name = tensor("value_63_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_63_dilations_0 = const()[name = tensor("value_63_dilations_0"), val = tensor([1, 1])]; + tensor value_63_groups_0 = const()[name = tensor("value_63_groups_0"), val = tensor(1)]; + tensor layers_15_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_15_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(623603392)))]; + tensor layers_15_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_15_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(625700608)))]; + tensor value_63_cast_fp16 = conv(bias = layers_15_encoder_attn_v_proj_bias_to_fp16, dilations = value_63_dilations_0, groups = value_63_groups_0, pad = value_63_pad_0, pad_type = value_63_pad_type_0, strides = value_63_strides_0, weight = layers_15_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_63_cast_fp16")]; + tensor var_3584 = const()[name = tensor("op_3584"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_63_cast_fp16 = reshape(shape = var_3584, x = query_63_cast_fp16)[name = tensor("mh_q_63_cast_fp16")]; + tensor var_3586_to_fp16 = const()[name = tensor("op_3586_to_fp16"), val = tensor(0x1p-3)]; + tensor var_3587_cast_fp16 = mul(x = mh_q_63_cast_fp16, y = var_3586_to_fp16)[name = tensor("op_3587_cast_fp16")]; + tensor var_3590 = const()[name = tensor("op_3590"), val = tensor([1, 16, 64, 1500])]; + tensor var_3591_cast_fp16 = reshape(shape = var_3590, x = key_63_cast_fp16)[name = tensor("op_3591_cast_fp16")]; + tensor mh_w_95_transpose_x_0 = const()[name = tensor("mh_w_95_transpose_x_0"), val = tensor(true)]; + tensor mh_w_95_transpose_y_0 = const()[name = tensor("mh_w_95_transpose_y_0"), val = tensor(false)]; + tensor mh_w_95_cast_fp16 = matmul(transpose_x = mh_w_95_transpose_x_0, transpose_y = mh_w_95_transpose_y_0, x = var_3587_cast_fp16, y = var_3591_cast_fp16)[name = tensor("mh_w_95_cast_fp16")]; + tensor obj_223_cast_fp16 = softmax(axis = var_3433, x = mh_w_95_cast_fp16)[name = tensor("obj_223_cast_fp16")]; + tensor var_3595 = const()[name = tensor("op_3595"), val = tensor([1, 16, 64, 1500])]; + tensor var_3596_cast_fp16 = reshape(shape = var_3595, x = value_63_cast_fp16)[name = tensor("op_3596_cast_fp16")]; + tensor attn_63_transpose_x_0 = const()[name = tensor("attn_63_transpose_x_0"), val = tensor(false)]; + tensor attn_63_transpose_y_0 = const()[name = tensor("attn_63_transpose_y_0"), val = tensor(true)]; + tensor attn_63_cast_fp16 = matmul(transpose_x = attn_63_transpose_x_0, transpose_y = attn_63_transpose_y_0, x = var_3596_cast_fp16, y = obj_223_cast_fp16)[name = tensor("attn_63_cast_fp16")]; + tensor var_3599 = const()[name = tensor("op_3599"), val = tensor([1, 1024, 1, 1])]; + tensor input_153_cast_fp16 = reshape(shape = var_3599, x = attn_63_cast_fp16)[name = tensor("input_153_cast_fp16")]; + tensor obj_221_pad_type_0 = const()[name = tensor("obj_221_pad_type_0"), val = tensor("valid")]; + tensor obj_221_strides_0 = const()[name = tensor("obj_221_strides_0"), val = tensor([1, 1])]; + tensor obj_221_pad_0 = const()[name = tensor("obj_221_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_221_dilations_0 = const()[name = tensor("obj_221_dilations_0"), val = tensor([1, 1])]; + tensor obj_221_groups_0 = const()[name = tensor("obj_221_groups_0"), val = tensor(1)]; + tensor layers_15_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_15_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(625702720)))]; + tensor layers_15_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_15_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(627799936)))]; + tensor obj_221_cast_fp16 = conv(bias = layers_15_encoder_attn_o_proj_bias_to_fp16, dilations = obj_221_dilations_0, groups = obj_221_groups_0, pad = obj_221_pad_0, pad_type = obj_221_pad_type_0, strides = obj_221_strides_0, weight = layers_15_encoder_attn_o_proj_weight_to_fp16, x = input_153_cast_fp16)[name = tensor("obj_221_cast_fp16")]; + tensor inputs_95_cast_fp16 = add(x = inputs_93_cast_fp16, y = obj_221_cast_fp16)[name = tensor("inputs_95_cast_fp16")]; + tensor out_95_axes_0 = const()[name = tensor("out_95_axes_0"), val = tensor([1])]; + tensor var_3620_to_fp16 = const()[name = tensor("op_3620_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_95_cast_fp16 = layer_norm(axes = out_95_axes_0, epsilon = var_3620_to_fp16, x = inputs_95_cast_fp16)[name = tensor("out_95_cast_fp16")]; + tensor input_155_gamma_0_to_fp16 = const()[name = tensor("input_155_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(627802048)))]; + tensor input_155_beta_0_to_fp16 = const()[name = tensor("input_155_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(627804160)))]; + tensor input_155_epsilon_0_to_fp16 = const()[name = tensor("input_155_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_155_cast_fp16 = batch_norm(beta = input_155_beta_0_to_fp16, epsilon = input_155_epsilon_0_to_fp16, gamma = input_155_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_95_cast_fp16)[name = tensor("input_155_cast_fp16")]; + tensor input_157_pad_type_0 = const()[name = tensor("input_157_pad_type_0"), val = tensor("valid")]; + tensor input_157_strides_0 = const()[name = tensor("input_157_strides_0"), val = tensor([1, 1])]; + tensor input_157_pad_0 = const()[name = tensor("input_157_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_157_dilations_0 = const()[name = tensor("input_157_dilations_0"), val = tensor([1, 1])]; + tensor input_157_groups_0 = const()[name = tensor("input_157_groups_0"), val = tensor(1)]; + tensor layers_15_fc1_weight_to_fp16 = const()[name = tensor("layers_15_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(627806272)))]; + tensor layers_15_fc1_bias_to_fp16 = const()[name = tensor("layers_15_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(636194944)))]; + tensor input_157_cast_fp16 = conv(bias = layers_15_fc1_bias_to_fp16, dilations = input_157_dilations_0, groups = input_157_groups_0, pad = input_157_pad_0, pad_type = input_157_pad_type_0, strides = input_157_strides_0, weight = layers_15_fc1_weight_to_fp16, x = input_155_cast_fp16)[name = tensor("input_157_cast_fp16")]; + tensor input_159_mode_0 = const()[name = tensor("input_159_mode_0"), val = tensor("EXACT")]; + tensor input_159_cast_fp16 = gelu(mode = input_159_mode_0, x = input_157_cast_fp16)[name = tensor("input_159_cast_fp16")]; + tensor hidden_states_33_pad_type_0 = const()[name = tensor("hidden_states_33_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_33_strides_0 = const()[name = tensor("hidden_states_33_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_33_pad_0 = const()[name = tensor("hidden_states_33_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_33_dilations_0 = const()[name = tensor("hidden_states_33_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_33_groups_0 = const()[name = tensor("hidden_states_33_groups_0"), val = tensor(1)]; + tensor layers_15_fc2_weight_to_fp16 = const()[name = tensor("layers_15_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(636203200)))]; + tensor layers_15_fc2_bias_to_fp16 = const()[name = tensor("layers_15_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(644591872)))]; + tensor hidden_states_33_cast_fp16 = conv(bias = layers_15_fc2_bias_to_fp16, dilations = hidden_states_33_dilations_0, groups = hidden_states_33_groups_0, pad = hidden_states_33_pad_0, pad_type = hidden_states_33_pad_type_0, strides = hidden_states_33_strides_0, weight = layers_15_fc2_weight_to_fp16, x = input_159_cast_fp16)[name = tensor("hidden_states_33_cast_fp16")]; + tensor inputs_97_cast_fp16 = add(x = inputs_95_cast_fp16, y = hidden_states_33_cast_fp16)[name = tensor("inputs_97_cast_fp16")]; + tensor var_3656 = const()[name = tensor("op_3656"), val = tensor(3)]; + tensor out_97_axes_0 = const()[name = tensor("out_97_axes_0"), val = tensor([1])]; + tensor var_3681_to_fp16 = const()[name = tensor("op_3681_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_97_cast_fp16 = layer_norm(axes = out_97_axes_0, epsilon = var_3681_to_fp16, x = inputs_97_cast_fp16)[name = tensor("out_97_cast_fp16")]; + tensor obj_225_gamma_0_to_fp16 = const()[name = tensor("obj_225_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(644593984)))]; + tensor obj_225_beta_0_to_fp16 = const()[name = tensor("obj_225_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(644596096)))]; + tensor obj_225_epsilon_0_to_fp16 = const()[name = tensor("obj_225_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_225_cast_fp16 = batch_norm(beta = obj_225_beta_0_to_fp16, epsilon = obj_225_epsilon_0_to_fp16, gamma = obj_225_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_97_cast_fp16)[name = tensor("obj_225_cast_fp16")]; + tensor query_65_pad_type_0 = const()[name = tensor("query_65_pad_type_0"), val = tensor("valid")]; + tensor query_65_strides_0 = const()[name = tensor("query_65_strides_0"), val = tensor([1, 1])]; + tensor query_65_pad_0 = const()[name = tensor("query_65_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_65_dilations_0 = const()[name = tensor("query_65_dilations_0"), val = tensor([1, 1])]; + tensor query_65_groups_0 = const()[name = tensor("query_65_groups_0"), val = tensor(1)]; + tensor layers_16_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_16_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(644598208)))]; + tensor layers_16_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_16_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(646695424)))]; + tensor query_65_cast_fp16 = conv(bias = layers_16_self_attn_q_proj_bias_to_fp16, dilations = query_65_dilations_0, groups = query_65_groups_0, pad = query_65_pad_0, pad_type = query_65_pad_type_0, strides = query_65_strides_0, weight = layers_16_self_attn_q_proj_weight_to_fp16, x = obj_225_cast_fp16)[name = tensor("query_65_cast_fp16")]; + tensor current_key_33_pad_type_0 = const()[name = tensor("current_key_33_pad_type_0"), val = tensor("valid")]; + tensor current_key_33_strides_0 = const()[name = tensor("current_key_33_strides_0"), val = tensor([1, 1])]; + tensor current_key_33_pad_0 = const()[name = tensor("current_key_33_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_33_dilations_0 = const()[name = tensor("current_key_33_dilations_0"), val = tensor([1, 1])]; + tensor current_key_33_groups_0 = const()[name = tensor("current_key_33_groups_0"), val = tensor(1)]; + tensor layers_16_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_16_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(646697536)))]; + tensor current_key_33_cast_fp16 = conv(dilations = current_key_33_dilations_0, groups = current_key_33_groups_0, pad = current_key_33_pad_0, pad_type = current_key_33_pad_type_0, strides = current_key_33_strides_0, weight = layers_16_self_attn_k_proj_weight_to_fp16, x = obj_225_cast_fp16)[name = tensor("current_key_33_cast_fp16")]; + tensor current_value_33_pad_type_0 = const()[name = tensor("current_value_33_pad_type_0"), val = tensor("valid")]; + tensor current_value_33_strides_0 = const()[name = tensor("current_value_33_strides_0"), val = tensor([1, 1])]; + tensor current_value_33_pad_0 = const()[name = tensor("current_value_33_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_33_dilations_0 = const()[name = tensor("current_value_33_dilations_0"), val = tensor([1, 1])]; + tensor current_value_33_groups_0 = const()[name = tensor("current_value_33_groups_0"), val = tensor(1)]; + tensor layers_16_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_16_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(648794752)))]; + tensor layers_16_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_16_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(650891968)))]; + tensor current_value_33_cast_fp16 = conv(bias = layers_16_self_attn_v_proj_bias_to_fp16, dilations = current_value_33_dilations_0, groups = current_value_33_groups_0, pad = current_value_33_pad_0, pad_type = current_value_33_pad_type_0, strides = current_value_33_strides_0, weight = layers_16_self_attn_v_proj_weight_to_fp16, x = obj_225_cast_fp16)[name = tensor("current_value_33_cast_fp16")]; + tensor var_3720_cast_fp16 = mul(x = var_87_cast_fp16_16, y = var_207_cast_fp16)[name = tensor("op_3720_cast_fp16")]; + tensor var_3721_cast_fp16 = mul(x = current_key_33_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_3721_cast_fp16")]; + tensor key_65_cast_fp16 = add(x = var_3720_cast_fp16, y = var_3721_cast_fp16)[name = tensor("key_65_cast_fp16")]; + tensor var_3724_cast_fp16 = mul(x = var_114_cast_fp16_16, y = var_207_cast_fp16)[name = tensor("op_3724_cast_fp16")]; + tensor var_3725_cast_fp16 = mul(x = current_value_33_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_3725_cast_fp16")]; + tensor value_65_cast_fp16 = add(x = var_3724_cast_fp16, y = var_3725_cast_fp16)[name = tensor("value_65_cast_fp16")]; + tensor var_3729 = const()[name = tensor("op_3729"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_65_cast_fp16 = reshape(shape = var_3729, x = query_65_cast_fp16)[name = tensor("mh_q_65_cast_fp16")]; + tensor var_3731_to_fp16 = const()[name = tensor("op_3731_to_fp16"), val = tensor(0x1p-3)]; + tensor var_3732_cast_fp16 = mul(x = mh_q_65_cast_fp16, y = var_3731_to_fp16)[name = tensor("op_3732_cast_fp16")]; + tensor var_3735 = const()[name = tensor("op_3735"), val = tensor([1, 16, 64, 448])]; + tensor var_3736_cast_fp16 = reshape(shape = var_3735, x = key_65_cast_fp16)[name = tensor("op_3736_cast_fp16")]; + tensor mh_w_97_transpose_x_0 = const()[name = tensor("mh_w_97_transpose_x_0"), val = tensor(true)]; + tensor mh_w_97_transpose_y_0 = const()[name = tensor("mh_w_97_transpose_y_0"), val = tensor(false)]; + tensor mh_w_97_cast_fp16 = matmul(transpose_x = mh_w_97_transpose_x_0, transpose_y = mh_w_97_transpose_y_0, x = var_3732_cast_fp16, y = var_3736_cast_fp16)[name = tensor("mh_w_97_cast_fp16")]; + tensor mh_w_99_cast_fp16 = add(x = mh_w_97_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_99_cast_fp16")]; + tensor var_3744_cast_fp16 = softmax(axis = var_3656, x = mh_w_99_cast_fp16)[name = tensor("op_3744_cast_fp16")]; + tensor var_3745 = const()[name = tensor("op_3745"), val = tensor([1, 16, 64, 448])]; + tensor var_3746_cast_fp16 = reshape(shape = var_3745, x = value_65_cast_fp16)[name = tensor("op_3746_cast_fp16")]; + tensor attn_65_transpose_x_0 = const()[name = tensor("attn_65_transpose_x_0"), val = tensor(false)]; + tensor attn_65_transpose_y_0 = const()[name = tensor("attn_65_transpose_y_0"), val = tensor(true)]; + tensor attn_65_cast_fp16 = matmul(transpose_x = attn_65_transpose_x_0, transpose_y = attn_65_transpose_y_0, x = var_3746_cast_fp16, y = var_3744_cast_fp16)[name = tensor("attn_65_cast_fp16")]; + tensor var_3749 = const()[name = tensor("op_3749"), val = tensor([1, 1024, 1, 1])]; + tensor input_161_cast_fp16 = reshape(shape = var_3749, x = attn_65_cast_fp16)[name = tensor("input_161_cast_fp16")]; + tensor obj_231_pad_type_0 = const()[name = tensor("obj_231_pad_type_0"), val = tensor("valid")]; + tensor obj_231_strides_0 = const()[name = tensor("obj_231_strides_0"), val = tensor([1, 1])]; + tensor obj_231_pad_0 = const()[name = tensor("obj_231_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_231_dilations_0 = const()[name = tensor("obj_231_dilations_0"), val = tensor([1, 1])]; + tensor obj_231_groups_0 = const()[name = tensor("obj_231_groups_0"), val = tensor(1)]; + tensor layers_16_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_16_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(650894080)))]; + tensor layers_16_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_16_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(652991296)))]; + tensor obj_231_cast_fp16 = conv(bias = layers_16_self_attn_o_proj_bias_to_fp16, dilations = obj_231_dilations_0, groups = obj_231_groups_0, pad = obj_231_pad_0, pad_type = obj_231_pad_type_0, strides = obj_231_strides_0, weight = layers_16_self_attn_o_proj_weight_to_fp16, x = input_161_cast_fp16)[name = tensor("obj_231_cast_fp16")]; + tensor inputs_99_cast_fp16 = add(x = inputs_97_cast_fp16, y = obj_231_cast_fp16)[name = tensor("inputs_99_cast_fp16")]; + tensor out_99_axes_0 = const()[name = tensor("out_99_axes_0"), val = tensor([1])]; + tensor var_3771_to_fp16 = const()[name = tensor("op_3771_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_99_cast_fp16 = layer_norm(axes = out_99_axes_0, epsilon = var_3771_to_fp16, x = inputs_99_cast_fp16)[name = tensor("out_99_cast_fp16")]; + tensor obj_233_gamma_0_to_fp16 = const()[name = tensor("obj_233_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(652993408)))]; + tensor obj_233_beta_0_to_fp16 = const()[name = tensor("obj_233_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(652995520)))]; + tensor obj_233_epsilon_0_to_fp16 = const()[name = tensor("obj_233_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_233_cast_fp16 = batch_norm(beta = obj_233_beta_0_to_fp16, epsilon = obj_233_epsilon_0_to_fp16, gamma = obj_233_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_99_cast_fp16)[name = tensor("obj_233_cast_fp16")]; + tensor query_67_pad_type_0 = const()[name = tensor("query_67_pad_type_0"), val = tensor("valid")]; + tensor query_67_strides_0 = const()[name = tensor("query_67_strides_0"), val = tensor([1, 1])]; + tensor query_67_pad_0 = const()[name = tensor("query_67_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_67_dilations_0 = const()[name = tensor("query_67_dilations_0"), val = tensor([1, 1])]; + tensor query_67_groups_0 = const()[name = tensor("query_67_groups_0"), val = tensor(1)]; + tensor layers_16_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_16_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(652997632)))]; + tensor layers_16_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_16_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(655094848)))]; + tensor query_67_cast_fp16 = conv(bias = layers_16_encoder_attn_q_proj_bias_to_fp16, dilations = query_67_dilations_0, groups = query_67_groups_0, pad = query_67_pad_0, pad_type = query_67_pad_type_0, strides = query_67_strides_0, weight = layers_16_encoder_attn_q_proj_weight_to_fp16, x = obj_233_cast_fp16)[name = tensor("query_67_cast_fp16")]; + tensor key_67_pad_type_0 = const()[name = tensor("key_67_pad_type_0"), val = tensor("valid")]; + tensor key_67_strides_0 = const()[name = tensor("key_67_strides_0"), val = tensor([1, 1])]; + tensor key_67_pad_0 = const()[name = tensor("key_67_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_67_dilations_0 = const()[name = tensor("key_67_dilations_0"), val = tensor([1, 1])]; + tensor key_67_groups_0 = const()[name = tensor("key_67_groups_0"), val = tensor(1)]; + tensor layers_16_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_16_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(655096960)))]; + tensor key_67_cast_fp16 = conv(dilations = key_67_dilations_0, groups = key_67_groups_0, pad = key_67_pad_0, pad_type = key_67_pad_type_0, strides = key_67_strides_0, weight = layers_16_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_67_cast_fp16")]; + tensor value_67_pad_type_0 = const()[name = tensor("value_67_pad_type_0"), val = tensor("valid")]; + tensor value_67_strides_0 = const()[name = tensor("value_67_strides_0"), val = tensor([1, 1])]; + tensor value_67_pad_0 = const()[name = tensor("value_67_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_67_dilations_0 = const()[name = tensor("value_67_dilations_0"), val = tensor([1, 1])]; + tensor value_67_groups_0 = const()[name = tensor("value_67_groups_0"), val = tensor(1)]; + tensor layers_16_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_16_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(657194176)))]; + tensor layers_16_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_16_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(659291392)))]; + tensor value_67_cast_fp16 = conv(bias = layers_16_encoder_attn_v_proj_bias_to_fp16, dilations = value_67_dilations_0, groups = value_67_groups_0, pad = value_67_pad_0, pad_type = value_67_pad_type_0, strides = value_67_strides_0, weight = layers_16_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_67_cast_fp16")]; + tensor var_3807 = const()[name = tensor("op_3807"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_67_cast_fp16 = reshape(shape = var_3807, x = query_67_cast_fp16)[name = tensor("mh_q_67_cast_fp16")]; + tensor var_3809_to_fp16 = const()[name = tensor("op_3809_to_fp16"), val = tensor(0x1p-3)]; + tensor var_3810_cast_fp16 = mul(x = mh_q_67_cast_fp16, y = var_3809_to_fp16)[name = tensor("op_3810_cast_fp16")]; + tensor var_3813 = const()[name = tensor("op_3813"), val = tensor([1, 16, 64, 1500])]; + tensor var_3814_cast_fp16 = reshape(shape = var_3813, x = key_67_cast_fp16)[name = tensor("op_3814_cast_fp16")]; + tensor mh_w_101_transpose_x_0 = const()[name = tensor("mh_w_101_transpose_x_0"), val = tensor(true)]; + tensor mh_w_101_transpose_y_0 = const()[name = tensor("mh_w_101_transpose_y_0"), val = tensor(false)]; + tensor mh_w_101_cast_fp16 = matmul(transpose_x = mh_w_101_transpose_x_0, transpose_y = mh_w_101_transpose_y_0, x = var_3810_cast_fp16, y = var_3814_cast_fp16)[name = tensor("mh_w_101_cast_fp16")]; + tensor obj_237_cast_fp16 = softmax(axis = var_3656, x = mh_w_101_cast_fp16)[name = tensor("obj_237_cast_fp16")]; + tensor var_3818 = const()[name = tensor("op_3818"), val = tensor([1, 16, 64, 1500])]; + tensor var_3819_cast_fp16 = reshape(shape = var_3818, x = value_67_cast_fp16)[name = tensor("op_3819_cast_fp16")]; + tensor attn_67_transpose_x_0 = const()[name = tensor("attn_67_transpose_x_0"), val = tensor(false)]; + tensor attn_67_transpose_y_0 = const()[name = tensor("attn_67_transpose_y_0"), val = tensor(true)]; + tensor attn_67_cast_fp16 = matmul(transpose_x = attn_67_transpose_x_0, transpose_y = attn_67_transpose_y_0, x = var_3819_cast_fp16, y = obj_237_cast_fp16)[name = tensor("attn_67_cast_fp16")]; + tensor var_3822 = const()[name = tensor("op_3822"), val = tensor([1, 1024, 1, 1])]; + tensor input_163_cast_fp16 = reshape(shape = var_3822, x = attn_67_cast_fp16)[name = tensor("input_163_cast_fp16")]; + tensor obj_235_pad_type_0 = const()[name = tensor("obj_235_pad_type_0"), val = tensor("valid")]; + tensor obj_235_strides_0 = const()[name = tensor("obj_235_strides_0"), val = tensor([1, 1])]; + tensor obj_235_pad_0 = const()[name = tensor("obj_235_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_235_dilations_0 = const()[name = tensor("obj_235_dilations_0"), val = tensor([1, 1])]; + tensor obj_235_groups_0 = const()[name = tensor("obj_235_groups_0"), val = tensor(1)]; + tensor layers_16_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_16_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(659293504)))]; + tensor layers_16_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_16_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(661390720)))]; + tensor obj_235_cast_fp16 = conv(bias = layers_16_encoder_attn_o_proj_bias_to_fp16, dilations = obj_235_dilations_0, groups = obj_235_groups_0, pad = obj_235_pad_0, pad_type = obj_235_pad_type_0, strides = obj_235_strides_0, weight = layers_16_encoder_attn_o_proj_weight_to_fp16, x = input_163_cast_fp16)[name = tensor("obj_235_cast_fp16")]; + tensor inputs_101_cast_fp16 = add(x = inputs_99_cast_fp16, y = obj_235_cast_fp16)[name = tensor("inputs_101_cast_fp16")]; + tensor out_101_axes_0 = const()[name = tensor("out_101_axes_0"), val = tensor([1])]; + tensor var_3843_to_fp16 = const()[name = tensor("op_3843_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_101_cast_fp16 = layer_norm(axes = out_101_axes_0, epsilon = var_3843_to_fp16, x = inputs_101_cast_fp16)[name = tensor("out_101_cast_fp16")]; + tensor input_165_gamma_0_to_fp16 = const()[name = tensor("input_165_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(661392832)))]; + tensor input_165_beta_0_to_fp16 = const()[name = tensor("input_165_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(661394944)))]; + tensor input_165_epsilon_0_to_fp16 = const()[name = tensor("input_165_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_165_cast_fp16 = batch_norm(beta = input_165_beta_0_to_fp16, epsilon = input_165_epsilon_0_to_fp16, gamma = input_165_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_101_cast_fp16)[name = tensor("input_165_cast_fp16")]; + tensor input_167_pad_type_0 = const()[name = tensor("input_167_pad_type_0"), val = tensor("valid")]; + tensor input_167_strides_0 = const()[name = tensor("input_167_strides_0"), val = tensor([1, 1])]; + tensor input_167_pad_0 = const()[name = tensor("input_167_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_167_dilations_0 = const()[name = tensor("input_167_dilations_0"), val = tensor([1, 1])]; + tensor input_167_groups_0 = const()[name = tensor("input_167_groups_0"), val = tensor(1)]; + tensor layers_16_fc1_weight_to_fp16 = const()[name = tensor("layers_16_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(661397056)))]; + tensor layers_16_fc1_bias_to_fp16 = const()[name = tensor("layers_16_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(669785728)))]; + tensor input_167_cast_fp16 = conv(bias = layers_16_fc1_bias_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = layers_16_fc1_weight_to_fp16, x = input_165_cast_fp16)[name = tensor("input_167_cast_fp16")]; + tensor input_169_mode_0 = const()[name = tensor("input_169_mode_0"), val = tensor("EXACT")]; + tensor input_169_cast_fp16 = gelu(mode = input_169_mode_0, x = input_167_cast_fp16)[name = tensor("input_169_cast_fp16")]; + tensor hidden_states_35_pad_type_0 = const()[name = tensor("hidden_states_35_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_35_strides_0 = const()[name = tensor("hidden_states_35_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_35_pad_0 = const()[name = tensor("hidden_states_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_35_dilations_0 = const()[name = tensor("hidden_states_35_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_35_groups_0 = const()[name = tensor("hidden_states_35_groups_0"), val = tensor(1)]; + tensor layers_16_fc2_weight_to_fp16 = const()[name = tensor("layers_16_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(669793984)))]; + tensor layers_16_fc2_bias_to_fp16 = const()[name = tensor("layers_16_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(678182656)))]; + tensor hidden_states_35_cast_fp16 = conv(bias = layers_16_fc2_bias_to_fp16, dilations = hidden_states_35_dilations_0, groups = hidden_states_35_groups_0, pad = hidden_states_35_pad_0, pad_type = hidden_states_35_pad_type_0, strides = hidden_states_35_strides_0, weight = layers_16_fc2_weight_to_fp16, x = input_169_cast_fp16)[name = tensor("hidden_states_35_cast_fp16")]; + tensor inputs_103_cast_fp16 = add(x = inputs_101_cast_fp16, y = hidden_states_35_cast_fp16)[name = tensor("inputs_103_cast_fp16")]; + tensor var_3879 = const()[name = tensor("op_3879"), val = tensor(3)]; + tensor out_103_axes_0 = const()[name = tensor("out_103_axes_0"), val = tensor([1])]; + tensor var_3904_to_fp16 = const()[name = tensor("op_3904_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_103_cast_fp16 = layer_norm(axes = out_103_axes_0, epsilon = var_3904_to_fp16, x = inputs_103_cast_fp16)[name = tensor("out_103_cast_fp16")]; + tensor obj_239_gamma_0_to_fp16 = const()[name = tensor("obj_239_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(678184768)))]; + tensor obj_239_beta_0_to_fp16 = const()[name = tensor("obj_239_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(678186880)))]; + tensor obj_239_epsilon_0_to_fp16 = const()[name = tensor("obj_239_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_239_cast_fp16 = batch_norm(beta = obj_239_beta_0_to_fp16, epsilon = obj_239_epsilon_0_to_fp16, gamma = obj_239_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_103_cast_fp16)[name = tensor("obj_239_cast_fp16")]; + tensor query_69_pad_type_0 = const()[name = tensor("query_69_pad_type_0"), val = tensor("valid")]; + tensor query_69_strides_0 = const()[name = tensor("query_69_strides_0"), val = tensor([1, 1])]; + tensor query_69_pad_0 = const()[name = tensor("query_69_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_69_dilations_0 = const()[name = tensor("query_69_dilations_0"), val = tensor([1, 1])]; + tensor query_69_groups_0 = const()[name = tensor("query_69_groups_0"), val = tensor(1)]; + tensor layers_17_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_17_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(678188992)))]; + tensor layers_17_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_17_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(680286208)))]; + tensor query_69_cast_fp16 = conv(bias = layers_17_self_attn_q_proj_bias_to_fp16, dilations = query_69_dilations_0, groups = query_69_groups_0, pad = query_69_pad_0, pad_type = query_69_pad_type_0, strides = query_69_strides_0, weight = layers_17_self_attn_q_proj_weight_to_fp16, x = obj_239_cast_fp16)[name = tensor("query_69_cast_fp16")]; + tensor current_key_35_pad_type_0 = const()[name = tensor("current_key_35_pad_type_0"), val = tensor("valid")]; + tensor current_key_35_strides_0 = const()[name = tensor("current_key_35_strides_0"), val = tensor([1, 1])]; + tensor current_key_35_pad_0 = const()[name = tensor("current_key_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_35_dilations_0 = const()[name = tensor("current_key_35_dilations_0"), val = tensor([1, 1])]; + tensor current_key_35_groups_0 = const()[name = tensor("current_key_35_groups_0"), val = tensor(1)]; + tensor layers_17_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_17_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(680288320)))]; + tensor current_key_35_cast_fp16 = conv(dilations = current_key_35_dilations_0, groups = current_key_35_groups_0, pad = current_key_35_pad_0, pad_type = current_key_35_pad_type_0, strides = current_key_35_strides_0, weight = layers_17_self_attn_k_proj_weight_to_fp16, x = obj_239_cast_fp16)[name = tensor("current_key_35_cast_fp16")]; + tensor current_value_35_pad_type_0 = const()[name = tensor("current_value_35_pad_type_0"), val = tensor("valid")]; + tensor current_value_35_strides_0 = const()[name = tensor("current_value_35_strides_0"), val = tensor([1, 1])]; + tensor current_value_35_pad_0 = const()[name = tensor("current_value_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_35_dilations_0 = const()[name = tensor("current_value_35_dilations_0"), val = tensor([1, 1])]; + tensor current_value_35_groups_0 = const()[name = tensor("current_value_35_groups_0"), val = tensor(1)]; + tensor layers_17_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_17_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(682385536)))]; + tensor layers_17_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_17_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(684482752)))]; + tensor current_value_35_cast_fp16 = conv(bias = layers_17_self_attn_v_proj_bias_to_fp16, dilations = current_value_35_dilations_0, groups = current_value_35_groups_0, pad = current_value_35_pad_0, pad_type = current_value_35_pad_type_0, strides = current_value_35_strides_0, weight = layers_17_self_attn_v_proj_weight_to_fp16, x = obj_239_cast_fp16)[name = tensor("current_value_35_cast_fp16")]; + tensor var_3943_cast_fp16 = mul(x = var_87_cast_fp16_17, y = var_207_cast_fp16)[name = tensor("op_3943_cast_fp16")]; + tensor var_3944_cast_fp16 = mul(x = current_key_35_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_3944_cast_fp16")]; + tensor key_69_cast_fp16 = add(x = var_3943_cast_fp16, y = var_3944_cast_fp16)[name = tensor("key_69_cast_fp16")]; + tensor var_3947_cast_fp16 = mul(x = var_114_cast_fp16_17, y = var_207_cast_fp16)[name = tensor("op_3947_cast_fp16")]; + tensor var_3948_cast_fp16 = mul(x = current_value_35_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_3948_cast_fp16")]; + tensor value_69_cast_fp16 = add(x = var_3947_cast_fp16, y = var_3948_cast_fp16)[name = tensor("value_69_cast_fp16")]; + tensor var_3952 = const()[name = tensor("op_3952"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_69_cast_fp16 = reshape(shape = var_3952, x = query_69_cast_fp16)[name = tensor("mh_q_69_cast_fp16")]; + tensor var_3954_to_fp16 = const()[name = tensor("op_3954_to_fp16"), val = tensor(0x1p-3)]; + tensor var_3955_cast_fp16 = mul(x = mh_q_69_cast_fp16, y = var_3954_to_fp16)[name = tensor("op_3955_cast_fp16")]; + tensor var_3958 = const()[name = tensor("op_3958"), val = tensor([1, 16, 64, 448])]; + tensor var_3959_cast_fp16 = reshape(shape = var_3958, x = key_69_cast_fp16)[name = tensor("op_3959_cast_fp16")]; + tensor mh_w_103_transpose_x_0 = const()[name = tensor("mh_w_103_transpose_x_0"), val = tensor(true)]; + tensor mh_w_103_transpose_y_0 = const()[name = tensor("mh_w_103_transpose_y_0"), val = tensor(false)]; + tensor mh_w_103_cast_fp16 = matmul(transpose_x = mh_w_103_transpose_x_0, transpose_y = mh_w_103_transpose_y_0, x = var_3955_cast_fp16, y = var_3959_cast_fp16)[name = tensor("mh_w_103_cast_fp16")]; + tensor mh_w_105_cast_fp16 = add(x = mh_w_103_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_105_cast_fp16")]; + tensor var_3967_cast_fp16 = softmax(axis = var_3879, x = mh_w_105_cast_fp16)[name = tensor("op_3967_cast_fp16")]; + tensor var_3968 = const()[name = tensor("op_3968"), val = tensor([1, 16, 64, 448])]; + tensor var_3969_cast_fp16 = reshape(shape = var_3968, x = value_69_cast_fp16)[name = tensor("op_3969_cast_fp16")]; + tensor attn_69_transpose_x_0 = const()[name = tensor("attn_69_transpose_x_0"), val = tensor(false)]; + tensor attn_69_transpose_y_0 = const()[name = tensor("attn_69_transpose_y_0"), val = tensor(true)]; + tensor attn_69_cast_fp16 = matmul(transpose_x = attn_69_transpose_x_0, transpose_y = attn_69_transpose_y_0, x = var_3969_cast_fp16, y = var_3967_cast_fp16)[name = tensor("attn_69_cast_fp16")]; + tensor var_3972 = const()[name = tensor("op_3972"), val = tensor([1, 1024, 1, 1])]; + tensor input_171_cast_fp16 = reshape(shape = var_3972, x = attn_69_cast_fp16)[name = tensor("input_171_cast_fp16")]; + tensor obj_245_pad_type_0 = const()[name = tensor("obj_245_pad_type_0"), val = tensor("valid")]; + tensor obj_245_strides_0 = const()[name = tensor("obj_245_strides_0"), val = tensor([1, 1])]; + tensor obj_245_pad_0 = const()[name = tensor("obj_245_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_245_dilations_0 = const()[name = tensor("obj_245_dilations_0"), val = tensor([1, 1])]; + tensor obj_245_groups_0 = const()[name = tensor("obj_245_groups_0"), val = tensor(1)]; + tensor layers_17_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_17_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(684484864)))]; + tensor layers_17_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_17_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(686582080)))]; + tensor obj_245_cast_fp16 = conv(bias = layers_17_self_attn_o_proj_bias_to_fp16, dilations = obj_245_dilations_0, groups = obj_245_groups_0, pad = obj_245_pad_0, pad_type = obj_245_pad_type_0, strides = obj_245_strides_0, weight = layers_17_self_attn_o_proj_weight_to_fp16, x = input_171_cast_fp16)[name = tensor("obj_245_cast_fp16")]; + tensor inputs_105_cast_fp16 = add(x = inputs_103_cast_fp16, y = obj_245_cast_fp16)[name = tensor("inputs_105_cast_fp16")]; + tensor out_105_axes_0 = const()[name = tensor("out_105_axes_0"), val = tensor([1])]; + tensor var_3994_to_fp16 = const()[name = tensor("op_3994_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_105_cast_fp16 = layer_norm(axes = out_105_axes_0, epsilon = var_3994_to_fp16, x = inputs_105_cast_fp16)[name = tensor("out_105_cast_fp16")]; + tensor obj_247_gamma_0_to_fp16 = const()[name = tensor("obj_247_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(686584192)))]; + tensor obj_247_beta_0_to_fp16 = const()[name = tensor("obj_247_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(686586304)))]; + tensor obj_247_epsilon_0_to_fp16 = const()[name = tensor("obj_247_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_247_cast_fp16 = batch_norm(beta = obj_247_beta_0_to_fp16, epsilon = obj_247_epsilon_0_to_fp16, gamma = obj_247_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_105_cast_fp16)[name = tensor("obj_247_cast_fp16")]; + tensor query_71_pad_type_0 = const()[name = tensor("query_71_pad_type_0"), val = tensor("valid")]; + tensor query_71_strides_0 = const()[name = tensor("query_71_strides_0"), val = tensor([1, 1])]; + tensor query_71_pad_0 = const()[name = tensor("query_71_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_71_dilations_0 = const()[name = tensor("query_71_dilations_0"), val = tensor([1, 1])]; + tensor query_71_groups_0 = const()[name = tensor("query_71_groups_0"), val = tensor(1)]; + tensor layers_17_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_17_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(686588416)))]; + tensor layers_17_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_17_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(688685632)))]; + tensor query_71_cast_fp16 = conv(bias = layers_17_encoder_attn_q_proj_bias_to_fp16, dilations = query_71_dilations_0, groups = query_71_groups_0, pad = query_71_pad_0, pad_type = query_71_pad_type_0, strides = query_71_strides_0, weight = layers_17_encoder_attn_q_proj_weight_to_fp16, x = obj_247_cast_fp16)[name = tensor("query_71_cast_fp16")]; + tensor key_71_pad_type_0 = const()[name = tensor("key_71_pad_type_0"), val = tensor("valid")]; + tensor key_71_strides_0 = const()[name = tensor("key_71_strides_0"), val = tensor([1, 1])]; + tensor key_71_pad_0 = const()[name = tensor("key_71_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_71_dilations_0 = const()[name = tensor("key_71_dilations_0"), val = tensor([1, 1])]; + tensor key_71_groups_0 = const()[name = tensor("key_71_groups_0"), val = tensor(1)]; + tensor layers_17_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_17_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(688687744)))]; + tensor key_71_cast_fp16 = conv(dilations = key_71_dilations_0, groups = key_71_groups_0, pad = key_71_pad_0, pad_type = key_71_pad_type_0, strides = key_71_strides_0, weight = layers_17_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_71_cast_fp16")]; + tensor value_71_pad_type_0 = const()[name = tensor("value_71_pad_type_0"), val = tensor("valid")]; + tensor value_71_strides_0 = const()[name = tensor("value_71_strides_0"), val = tensor([1, 1])]; + tensor value_71_pad_0 = const()[name = tensor("value_71_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_71_dilations_0 = const()[name = tensor("value_71_dilations_0"), val = tensor([1, 1])]; + tensor value_71_groups_0 = const()[name = tensor("value_71_groups_0"), val = tensor(1)]; + tensor layers_17_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_17_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(690784960)))]; + tensor layers_17_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_17_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(692882176)))]; + tensor value_71_cast_fp16 = conv(bias = layers_17_encoder_attn_v_proj_bias_to_fp16, dilations = value_71_dilations_0, groups = value_71_groups_0, pad = value_71_pad_0, pad_type = value_71_pad_type_0, strides = value_71_strides_0, weight = layers_17_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_71_cast_fp16")]; + tensor var_4030 = const()[name = tensor("op_4030"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_71_cast_fp16 = reshape(shape = var_4030, x = query_71_cast_fp16)[name = tensor("mh_q_71_cast_fp16")]; + tensor var_4032_to_fp16 = const()[name = tensor("op_4032_to_fp16"), val = tensor(0x1p-3)]; + tensor var_4033_cast_fp16 = mul(x = mh_q_71_cast_fp16, y = var_4032_to_fp16)[name = tensor("op_4033_cast_fp16")]; + tensor var_4036 = const()[name = tensor("op_4036"), val = tensor([1, 16, 64, 1500])]; + tensor var_4037_cast_fp16 = reshape(shape = var_4036, x = key_71_cast_fp16)[name = tensor("op_4037_cast_fp16")]; + tensor mh_w_107_transpose_x_0 = const()[name = tensor("mh_w_107_transpose_x_0"), val = tensor(true)]; + tensor mh_w_107_transpose_y_0 = const()[name = tensor("mh_w_107_transpose_y_0"), val = tensor(false)]; + tensor mh_w_107_cast_fp16 = matmul(transpose_x = mh_w_107_transpose_x_0, transpose_y = mh_w_107_transpose_y_0, x = var_4033_cast_fp16, y = var_4037_cast_fp16)[name = tensor("mh_w_107_cast_fp16")]; + tensor obj_251_cast_fp16 = softmax(axis = var_3879, x = mh_w_107_cast_fp16)[name = tensor("obj_251_cast_fp16")]; + tensor var_4041 = const()[name = tensor("op_4041"), val = tensor([1, 16, 64, 1500])]; + tensor var_4042_cast_fp16 = reshape(shape = var_4041, x = value_71_cast_fp16)[name = tensor("op_4042_cast_fp16")]; + tensor attn_71_transpose_x_0 = const()[name = tensor("attn_71_transpose_x_0"), val = tensor(false)]; + tensor attn_71_transpose_y_0 = const()[name = tensor("attn_71_transpose_y_0"), val = tensor(true)]; + tensor attn_71_cast_fp16 = matmul(transpose_x = attn_71_transpose_x_0, transpose_y = attn_71_transpose_y_0, x = var_4042_cast_fp16, y = obj_251_cast_fp16)[name = tensor("attn_71_cast_fp16")]; + tensor var_4045 = const()[name = tensor("op_4045"), val = tensor([1, 1024, 1, 1])]; + tensor input_173_cast_fp16 = reshape(shape = var_4045, x = attn_71_cast_fp16)[name = tensor("input_173_cast_fp16")]; + tensor obj_249_pad_type_0 = const()[name = tensor("obj_249_pad_type_0"), val = tensor("valid")]; + tensor obj_249_strides_0 = const()[name = tensor("obj_249_strides_0"), val = tensor([1, 1])]; + tensor obj_249_pad_0 = const()[name = tensor("obj_249_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_249_dilations_0 = const()[name = tensor("obj_249_dilations_0"), val = tensor([1, 1])]; + tensor obj_249_groups_0 = const()[name = tensor("obj_249_groups_0"), val = tensor(1)]; + tensor layers_17_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_17_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(692884288)))]; + tensor layers_17_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_17_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(694981504)))]; + tensor obj_249_cast_fp16 = conv(bias = layers_17_encoder_attn_o_proj_bias_to_fp16, dilations = obj_249_dilations_0, groups = obj_249_groups_0, pad = obj_249_pad_0, pad_type = obj_249_pad_type_0, strides = obj_249_strides_0, weight = layers_17_encoder_attn_o_proj_weight_to_fp16, x = input_173_cast_fp16)[name = tensor("obj_249_cast_fp16")]; + tensor inputs_107_cast_fp16 = add(x = inputs_105_cast_fp16, y = obj_249_cast_fp16)[name = tensor("inputs_107_cast_fp16")]; + tensor out_107_axes_0 = const()[name = tensor("out_107_axes_0"), val = tensor([1])]; + tensor var_4063_to_fp16 = const()[name = tensor("op_4063_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_107_cast_fp16 = layer_norm(axes = out_107_axes_0, epsilon = var_4063_to_fp16, x = inputs_107_cast_fp16)[name = tensor("out_107_cast_fp16")]; + tensor input_175_gamma_0_to_fp16 = const()[name = tensor("input_175_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(694983616)))]; + tensor input_175_beta_0_to_fp16 = const()[name = tensor("input_175_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(694985728)))]; + tensor input_175_epsilon_0_to_fp16 = const()[name = tensor("input_175_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_175_cast_fp16 = batch_norm(beta = input_175_beta_0_to_fp16, epsilon = input_175_epsilon_0_to_fp16, gamma = input_175_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_107_cast_fp16)[name = tensor("input_175_cast_fp16")]; + tensor input_177_pad_type_0 = const()[name = tensor("input_177_pad_type_0"), val = tensor("valid")]; + tensor input_177_strides_0 = const()[name = tensor("input_177_strides_0"), val = tensor([1, 1])]; + tensor input_177_pad_0 = const()[name = tensor("input_177_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_177_dilations_0 = const()[name = tensor("input_177_dilations_0"), val = tensor([1, 1])]; + tensor input_177_groups_0 = const()[name = tensor("input_177_groups_0"), val = tensor(1)]; + tensor layers_17_fc1_weight_to_fp16 = const()[name = tensor("layers_17_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(694987840)))]; + tensor layers_17_fc1_bias_to_fp16 = const()[name = tensor("layers_17_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(703376512)))]; + tensor input_177_cast_fp16 = conv(bias = layers_17_fc1_bias_to_fp16, dilations = input_177_dilations_0, groups = input_177_groups_0, pad = input_177_pad_0, pad_type = input_177_pad_type_0, strides = input_177_strides_0, weight = layers_17_fc1_weight_to_fp16, x = input_175_cast_fp16)[name = tensor("input_177_cast_fp16")]; + tensor input_179_mode_0 = const()[name = tensor("input_179_mode_0"), val = tensor("EXACT")]; + tensor input_179_cast_fp16 = gelu(mode = input_179_mode_0, x = input_177_cast_fp16)[name = tensor("input_179_cast_fp16")]; + tensor hidden_states_37_pad_type_0 = const()[name = tensor("hidden_states_37_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_37_strides_0 = const()[name = tensor("hidden_states_37_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_37_pad_0 = const()[name = tensor("hidden_states_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_37_dilations_0 = const()[name = tensor("hidden_states_37_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_37_groups_0 = const()[name = tensor("hidden_states_37_groups_0"), val = tensor(1)]; + tensor layers_17_fc2_weight_to_fp16 = const()[name = tensor("layers_17_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(703384768)))]; + tensor layers_17_fc2_bias_to_fp16 = const()[name = tensor("layers_17_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(711773440)))]; + tensor hidden_states_37_cast_fp16 = conv(bias = layers_17_fc2_bias_to_fp16, dilations = hidden_states_37_dilations_0, groups = hidden_states_37_groups_0, pad = hidden_states_37_pad_0, pad_type = hidden_states_37_pad_type_0, strides = hidden_states_37_strides_0, weight = layers_17_fc2_weight_to_fp16, x = input_179_cast_fp16)[name = tensor("hidden_states_37_cast_fp16")]; + tensor inputs_109_cast_fp16 = add(x = inputs_107_cast_fp16, y = hidden_states_37_cast_fp16)[name = tensor("inputs_109_cast_fp16")]; + tensor var_4098 = const()[name = tensor("op_4098"), val = tensor(3)]; + tensor out_109_axes_0 = const()[name = tensor("out_109_axes_0"), val = tensor([1])]; + tensor var_4123_to_fp16 = const()[name = tensor("op_4123_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_109_cast_fp16 = layer_norm(axes = out_109_axes_0, epsilon = var_4123_to_fp16, x = inputs_109_cast_fp16)[name = tensor("out_109_cast_fp16")]; + tensor obj_253_gamma_0_to_fp16 = const()[name = tensor("obj_253_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(711775552)))]; + tensor obj_253_beta_0_to_fp16 = const()[name = tensor("obj_253_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(711777664)))]; + tensor obj_253_epsilon_0_to_fp16 = const()[name = tensor("obj_253_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_253_cast_fp16 = batch_norm(beta = obj_253_beta_0_to_fp16, epsilon = obj_253_epsilon_0_to_fp16, gamma = obj_253_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_109_cast_fp16)[name = tensor("obj_253_cast_fp16")]; + tensor query_73_pad_type_0 = const()[name = tensor("query_73_pad_type_0"), val = tensor("valid")]; + tensor query_73_strides_0 = const()[name = tensor("query_73_strides_0"), val = tensor([1, 1])]; + tensor query_73_pad_0 = const()[name = tensor("query_73_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_73_dilations_0 = const()[name = tensor("query_73_dilations_0"), val = tensor([1, 1])]; + tensor query_73_groups_0 = const()[name = tensor("query_73_groups_0"), val = tensor(1)]; + tensor layers_18_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_18_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(711779776)))]; + tensor layers_18_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_18_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(713876992)))]; + tensor query_73_cast_fp16 = conv(bias = layers_18_self_attn_q_proj_bias_to_fp16, dilations = query_73_dilations_0, groups = query_73_groups_0, pad = query_73_pad_0, pad_type = query_73_pad_type_0, strides = query_73_strides_0, weight = layers_18_self_attn_q_proj_weight_to_fp16, x = obj_253_cast_fp16)[name = tensor("query_73_cast_fp16")]; + tensor current_key_37_pad_type_0 = const()[name = tensor("current_key_37_pad_type_0"), val = tensor("valid")]; + tensor current_key_37_strides_0 = const()[name = tensor("current_key_37_strides_0"), val = tensor([1, 1])]; + tensor current_key_37_pad_0 = const()[name = tensor("current_key_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_37_dilations_0 = const()[name = tensor("current_key_37_dilations_0"), val = tensor([1, 1])]; + tensor current_key_37_groups_0 = const()[name = tensor("current_key_37_groups_0"), val = tensor(1)]; + tensor layers_18_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_18_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(713879104)))]; + tensor current_key_37_cast_fp16 = conv(dilations = current_key_37_dilations_0, groups = current_key_37_groups_0, pad = current_key_37_pad_0, pad_type = current_key_37_pad_type_0, strides = current_key_37_strides_0, weight = layers_18_self_attn_k_proj_weight_to_fp16, x = obj_253_cast_fp16)[name = tensor("current_key_37_cast_fp16")]; + tensor current_value_37_pad_type_0 = const()[name = tensor("current_value_37_pad_type_0"), val = tensor("valid")]; + tensor current_value_37_strides_0 = const()[name = tensor("current_value_37_strides_0"), val = tensor([1, 1])]; + tensor current_value_37_pad_0 = const()[name = tensor("current_value_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_37_dilations_0 = const()[name = tensor("current_value_37_dilations_0"), val = tensor([1, 1])]; + tensor current_value_37_groups_0 = const()[name = tensor("current_value_37_groups_0"), val = tensor(1)]; + tensor layers_18_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_18_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(715976320)))]; + tensor layers_18_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_18_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(718073536)))]; + tensor current_value_37_cast_fp16 = conv(bias = layers_18_self_attn_v_proj_bias_to_fp16, dilations = current_value_37_dilations_0, groups = current_value_37_groups_0, pad = current_value_37_pad_0, pad_type = current_value_37_pad_type_0, strides = current_value_37_strides_0, weight = layers_18_self_attn_v_proj_weight_to_fp16, x = obj_253_cast_fp16)[name = tensor("current_value_37_cast_fp16")]; + tensor var_4162_cast_fp16 = mul(x = var_87_cast_fp16_18, y = var_207_cast_fp16)[name = tensor("op_4162_cast_fp16")]; + tensor var_4163_cast_fp16 = mul(x = current_key_37_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_4163_cast_fp16")]; + tensor key_73_cast_fp16 = add(x = var_4162_cast_fp16, y = var_4163_cast_fp16)[name = tensor("key_73_cast_fp16")]; + tensor var_4166_cast_fp16 = mul(x = var_114_cast_fp16_18, y = var_207_cast_fp16)[name = tensor("op_4166_cast_fp16")]; + tensor var_4167_cast_fp16 = mul(x = current_value_37_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_4167_cast_fp16")]; + tensor value_73_cast_fp16 = add(x = var_4166_cast_fp16, y = var_4167_cast_fp16)[name = tensor("value_73_cast_fp16")]; + tensor var_4171 = const()[name = tensor("op_4171"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_73_cast_fp16 = reshape(shape = var_4171, x = query_73_cast_fp16)[name = tensor("mh_q_73_cast_fp16")]; + tensor var_4173_to_fp16 = const()[name = tensor("op_4173_to_fp16"), val = tensor(0x1p-3)]; + tensor var_4174_cast_fp16 = mul(x = mh_q_73_cast_fp16, y = var_4173_to_fp16)[name = tensor("op_4174_cast_fp16")]; + tensor var_4177 = const()[name = tensor("op_4177"), val = tensor([1, 16, 64, 448])]; + tensor var_4178_cast_fp16 = reshape(shape = var_4177, x = key_73_cast_fp16)[name = tensor("op_4178_cast_fp16")]; + tensor mh_w_109_transpose_x_0 = const()[name = tensor("mh_w_109_transpose_x_0"), val = tensor(true)]; + tensor mh_w_109_transpose_y_0 = const()[name = tensor("mh_w_109_transpose_y_0"), val = tensor(false)]; + tensor mh_w_109_cast_fp16 = matmul(transpose_x = mh_w_109_transpose_x_0, transpose_y = mh_w_109_transpose_y_0, x = var_4174_cast_fp16, y = var_4178_cast_fp16)[name = tensor("mh_w_109_cast_fp16")]; + tensor mh_w_111_cast_fp16 = add(x = mh_w_109_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_111_cast_fp16")]; + tensor var_4186_cast_fp16 = softmax(axis = var_4098, x = mh_w_111_cast_fp16)[name = tensor("op_4186_cast_fp16")]; + tensor var_4187 = const()[name = tensor("op_4187"), val = tensor([1, 16, 64, 448])]; + tensor var_4188_cast_fp16 = reshape(shape = var_4187, x = value_73_cast_fp16)[name = tensor("op_4188_cast_fp16")]; + tensor attn_73_transpose_x_0 = const()[name = tensor("attn_73_transpose_x_0"), val = tensor(false)]; + tensor attn_73_transpose_y_0 = const()[name = tensor("attn_73_transpose_y_0"), val = tensor(true)]; + tensor attn_73_cast_fp16 = matmul(transpose_x = attn_73_transpose_x_0, transpose_y = attn_73_transpose_y_0, x = var_4188_cast_fp16, y = var_4186_cast_fp16)[name = tensor("attn_73_cast_fp16")]; + tensor var_4191 = const()[name = tensor("op_4191"), val = tensor([1, 1024, 1, 1])]; + tensor input_181_cast_fp16 = reshape(shape = var_4191, x = attn_73_cast_fp16)[name = tensor("input_181_cast_fp16")]; + tensor obj_259_pad_type_0 = const()[name = tensor("obj_259_pad_type_0"), val = tensor("valid")]; + tensor obj_259_strides_0 = const()[name = tensor("obj_259_strides_0"), val = tensor([1, 1])]; + tensor obj_259_pad_0 = const()[name = tensor("obj_259_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_259_dilations_0 = const()[name = tensor("obj_259_dilations_0"), val = tensor([1, 1])]; + tensor obj_259_groups_0 = const()[name = tensor("obj_259_groups_0"), val = tensor(1)]; + tensor layers_18_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_18_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(718075648)))]; + tensor layers_18_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_18_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(720172864)))]; + tensor obj_259_cast_fp16 = conv(bias = layers_18_self_attn_o_proj_bias_to_fp16, dilations = obj_259_dilations_0, groups = obj_259_groups_0, pad = obj_259_pad_0, pad_type = obj_259_pad_type_0, strides = obj_259_strides_0, weight = layers_18_self_attn_o_proj_weight_to_fp16, x = input_181_cast_fp16)[name = tensor("obj_259_cast_fp16")]; + tensor inputs_111_cast_fp16 = add(x = inputs_109_cast_fp16, y = obj_259_cast_fp16)[name = tensor("inputs_111_cast_fp16")]; + tensor out_111_axes_0 = const()[name = tensor("out_111_axes_0"), val = tensor([1])]; + tensor var_4213_to_fp16 = const()[name = tensor("op_4213_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_111_cast_fp16 = layer_norm(axes = out_111_axes_0, epsilon = var_4213_to_fp16, x = inputs_111_cast_fp16)[name = tensor("out_111_cast_fp16")]; + tensor obj_261_gamma_0_to_fp16 = const()[name = tensor("obj_261_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(720174976)))]; + tensor obj_261_beta_0_to_fp16 = const()[name = tensor("obj_261_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(720177088)))]; + tensor obj_261_epsilon_0_to_fp16 = const()[name = tensor("obj_261_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_261_cast_fp16 = batch_norm(beta = obj_261_beta_0_to_fp16, epsilon = obj_261_epsilon_0_to_fp16, gamma = obj_261_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_111_cast_fp16)[name = tensor("obj_261_cast_fp16")]; + tensor query_75_pad_type_0 = const()[name = tensor("query_75_pad_type_0"), val = tensor("valid")]; + tensor query_75_strides_0 = const()[name = tensor("query_75_strides_0"), val = tensor([1, 1])]; + tensor query_75_pad_0 = const()[name = tensor("query_75_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_75_dilations_0 = const()[name = tensor("query_75_dilations_0"), val = tensor([1, 1])]; + tensor query_75_groups_0 = const()[name = tensor("query_75_groups_0"), val = tensor(1)]; + tensor layers_18_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_18_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(720179200)))]; + tensor layers_18_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_18_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(722276416)))]; + tensor query_75_cast_fp16 = conv(bias = layers_18_encoder_attn_q_proj_bias_to_fp16, dilations = query_75_dilations_0, groups = query_75_groups_0, pad = query_75_pad_0, pad_type = query_75_pad_type_0, strides = query_75_strides_0, weight = layers_18_encoder_attn_q_proj_weight_to_fp16, x = obj_261_cast_fp16)[name = tensor("query_75_cast_fp16")]; + tensor key_75_pad_type_0 = const()[name = tensor("key_75_pad_type_0"), val = tensor("valid")]; + tensor key_75_strides_0 = const()[name = tensor("key_75_strides_0"), val = tensor([1, 1])]; + tensor key_75_pad_0 = const()[name = tensor("key_75_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_75_dilations_0 = const()[name = tensor("key_75_dilations_0"), val = tensor([1, 1])]; + tensor key_75_groups_0 = const()[name = tensor("key_75_groups_0"), val = tensor(1)]; + tensor layers_18_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_18_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(722278528)))]; + tensor key_75_cast_fp16 = conv(dilations = key_75_dilations_0, groups = key_75_groups_0, pad = key_75_pad_0, pad_type = key_75_pad_type_0, strides = key_75_strides_0, weight = layers_18_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_75_cast_fp16")]; + tensor value_75_pad_type_0 = const()[name = tensor("value_75_pad_type_0"), val = tensor("valid")]; + tensor value_75_strides_0 = const()[name = tensor("value_75_strides_0"), val = tensor([1, 1])]; + tensor value_75_pad_0 = const()[name = tensor("value_75_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_75_dilations_0 = const()[name = tensor("value_75_dilations_0"), val = tensor([1, 1])]; + tensor value_75_groups_0 = const()[name = tensor("value_75_groups_0"), val = tensor(1)]; + tensor layers_18_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_18_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(724375744)))]; + tensor layers_18_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_18_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(726472960)))]; + tensor value_75_cast_fp16 = conv(bias = layers_18_encoder_attn_v_proj_bias_to_fp16, dilations = value_75_dilations_0, groups = value_75_groups_0, pad = value_75_pad_0, pad_type = value_75_pad_type_0, strides = value_75_strides_0, weight = layers_18_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_75_cast_fp16")]; + tensor var_4249 = const()[name = tensor("op_4249"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_75_cast_fp16 = reshape(shape = var_4249, x = query_75_cast_fp16)[name = tensor("mh_q_75_cast_fp16")]; + tensor var_4251_to_fp16 = const()[name = tensor("op_4251_to_fp16"), val = tensor(0x1p-3)]; + tensor var_4252_cast_fp16 = mul(x = mh_q_75_cast_fp16, y = var_4251_to_fp16)[name = tensor("op_4252_cast_fp16")]; + tensor var_4255 = const()[name = tensor("op_4255"), val = tensor([1, 16, 64, 1500])]; + tensor var_4256_cast_fp16 = reshape(shape = var_4255, x = key_75_cast_fp16)[name = tensor("op_4256_cast_fp16")]; + tensor mh_w_113_transpose_x_0 = const()[name = tensor("mh_w_113_transpose_x_0"), val = tensor(true)]; + tensor mh_w_113_transpose_y_0 = const()[name = tensor("mh_w_113_transpose_y_0"), val = tensor(false)]; + tensor mh_w_113_cast_fp16 = matmul(transpose_x = mh_w_113_transpose_x_0, transpose_y = mh_w_113_transpose_y_0, x = var_4252_cast_fp16, y = var_4256_cast_fp16)[name = tensor("mh_w_113_cast_fp16")]; + tensor obj_265_cast_fp16 = softmax(axis = var_4098, x = mh_w_113_cast_fp16)[name = tensor("obj_265_cast_fp16")]; + tensor var_4260 = const()[name = tensor("op_4260"), val = tensor([1, 16, 64, 1500])]; + tensor var_4261_cast_fp16 = reshape(shape = var_4260, x = value_75_cast_fp16)[name = tensor("op_4261_cast_fp16")]; + tensor attn_75_transpose_x_0 = const()[name = tensor("attn_75_transpose_x_0"), val = tensor(false)]; + tensor attn_75_transpose_y_0 = const()[name = tensor("attn_75_transpose_y_0"), val = tensor(true)]; + tensor attn_75_cast_fp16 = matmul(transpose_x = attn_75_transpose_x_0, transpose_y = attn_75_transpose_y_0, x = var_4261_cast_fp16, y = obj_265_cast_fp16)[name = tensor("attn_75_cast_fp16")]; + tensor var_4264 = const()[name = tensor("op_4264"), val = tensor([1, 1024, 1, 1])]; + tensor input_183_cast_fp16 = reshape(shape = var_4264, x = attn_75_cast_fp16)[name = tensor("input_183_cast_fp16")]; + tensor obj_263_pad_type_0 = const()[name = tensor("obj_263_pad_type_0"), val = tensor("valid")]; + tensor obj_263_strides_0 = const()[name = tensor("obj_263_strides_0"), val = tensor([1, 1])]; + tensor obj_263_pad_0 = const()[name = tensor("obj_263_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_263_dilations_0 = const()[name = tensor("obj_263_dilations_0"), val = tensor([1, 1])]; + tensor obj_263_groups_0 = const()[name = tensor("obj_263_groups_0"), val = tensor(1)]; + tensor layers_18_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_18_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(726475072)))]; + tensor layers_18_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_18_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(728572288)))]; + tensor obj_263_cast_fp16 = conv(bias = layers_18_encoder_attn_o_proj_bias_to_fp16, dilations = obj_263_dilations_0, groups = obj_263_groups_0, pad = obj_263_pad_0, pad_type = obj_263_pad_type_0, strides = obj_263_strides_0, weight = layers_18_encoder_attn_o_proj_weight_to_fp16, x = input_183_cast_fp16)[name = tensor("obj_263_cast_fp16")]; + tensor inputs_113_cast_fp16 = add(x = inputs_111_cast_fp16, y = obj_263_cast_fp16)[name = tensor("inputs_113_cast_fp16")]; + tensor out_113_axes_0 = const()[name = tensor("out_113_axes_0"), val = tensor([1])]; + tensor var_4282_to_fp16 = const()[name = tensor("op_4282_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_113_cast_fp16 = layer_norm(axes = out_113_axes_0, epsilon = var_4282_to_fp16, x = inputs_113_cast_fp16)[name = tensor("out_113_cast_fp16")]; + tensor input_185_gamma_0_to_fp16 = const()[name = tensor("input_185_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(728574400)))]; + tensor input_185_beta_0_to_fp16 = const()[name = tensor("input_185_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(728576512)))]; + tensor input_185_epsilon_0_to_fp16 = const()[name = tensor("input_185_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_185_cast_fp16 = batch_norm(beta = input_185_beta_0_to_fp16, epsilon = input_185_epsilon_0_to_fp16, gamma = input_185_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_113_cast_fp16)[name = tensor("input_185_cast_fp16")]; + tensor input_187_pad_type_0 = const()[name = tensor("input_187_pad_type_0"), val = tensor("valid")]; + tensor input_187_strides_0 = const()[name = tensor("input_187_strides_0"), val = tensor([1, 1])]; + tensor input_187_pad_0 = const()[name = tensor("input_187_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_187_dilations_0 = const()[name = tensor("input_187_dilations_0"), val = tensor([1, 1])]; + tensor input_187_groups_0 = const()[name = tensor("input_187_groups_0"), val = tensor(1)]; + tensor layers_18_fc1_weight_to_fp16 = const()[name = tensor("layers_18_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(728578624)))]; + tensor layers_18_fc1_bias_to_fp16 = const()[name = tensor("layers_18_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(736967296)))]; + tensor input_187_cast_fp16 = conv(bias = layers_18_fc1_bias_to_fp16, dilations = input_187_dilations_0, groups = input_187_groups_0, pad = input_187_pad_0, pad_type = input_187_pad_type_0, strides = input_187_strides_0, weight = layers_18_fc1_weight_to_fp16, x = input_185_cast_fp16)[name = tensor("input_187_cast_fp16")]; + tensor input_189_mode_0 = const()[name = tensor("input_189_mode_0"), val = tensor("EXACT")]; + tensor input_189_cast_fp16 = gelu(mode = input_189_mode_0, x = input_187_cast_fp16)[name = tensor("input_189_cast_fp16")]; + tensor hidden_states_39_pad_type_0 = const()[name = tensor("hidden_states_39_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_39_strides_0 = const()[name = tensor("hidden_states_39_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_39_pad_0 = const()[name = tensor("hidden_states_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_39_dilations_0 = const()[name = tensor("hidden_states_39_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_39_groups_0 = const()[name = tensor("hidden_states_39_groups_0"), val = tensor(1)]; + tensor layers_18_fc2_weight_to_fp16 = const()[name = tensor("layers_18_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(736975552)))]; + tensor layers_18_fc2_bias_to_fp16 = const()[name = tensor("layers_18_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(745364224)))]; + tensor hidden_states_39_cast_fp16 = conv(bias = layers_18_fc2_bias_to_fp16, dilations = hidden_states_39_dilations_0, groups = hidden_states_39_groups_0, pad = hidden_states_39_pad_0, pad_type = hidden_states_39_pad_type_0, strides = hidden_states_39_strides_0, weight = layers_18_fc2_weight_to_fp16, x = input_189_cast_fp16)[name = tensor("hidden_states_39_cast_fp16")]; + tensor inputs_115_cast_fp16 = add(x = inputs_113_cast_fp16, y = hidden_states_39_cast_fp16)[name = tensor("inputs_115_cast_fp16")]; + tensor var_4317 = const()[name = tensor("op_4317"), val = tensor(3)]; + tensor out_115_axes_0 = const()[name = tensor("out_115_axes_0"), val = tensor([1])]; + tensor var_4342_to_fp16 = const()[name = tensor("op_4342_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_115_cast_fp16 = layer_norm(axes = out_115_axes_0, epsilon = var_4342_to_fp16, x = inputs_115_cast_fp16)[name = tensor("out_115_cast_fp16")]; + tensor obj_267_gamma_0_to_fp16 = const()[name = tensor("obj_267_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(745366336)))]; + tensor obj_267_beta_0_to_fp16 = const()[name = tensor("obj_267_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(745368448)))]; + tensor obj_267_epsilon_0_to_fp16 = const()[name = tensor("obj_267_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_267_cast_fp16 = batch_norm(beta = obj_267_beta_0_to_fp16, epsilon = obj_267_epsilon_0_to_fp16, gamma = obj_267_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_115_cast_fp16)[name = tensor("obj_267_cast_fp16")]; + tensor query_77_pad_type_0 = const()[name = tensor("query_77_pad_type_0"), val = tensor("valid")]; + tensor query_77_strides_0 = const()[name = tensor("query_77_strides_0"), val = tensor([1, 1])]; + tensor query_77_pad_0 = const()[name = tensor("query_77_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_77_dilations_0 = const()[name = tensor("query_77_dilations_0"), val = tensor([1, 1])]; + tensor query_77_groups_0 = const()[name = tensor("query_77_groups_0"), val = tensor(1)]; + tensor layers_19_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_19_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(745370560)))]; + tensor layers_19_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_19_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(747467776)))]; + tensor query_77_cast_fp16 = conv(bias = layers_19_self_attn_q_proj_bias_to_fp16, dilations = query_77_dilations_0, groups = query_77_groups_0, pad = query_77_pad_0, pad_type = query_77_pad_type_0, strides = query_77_strides_0, weight = layers_19_self_attn_q_proj_weight_to_fp16, x = obj_267_cast_fp16)[name = tensor("query_77_cast_fp16")]; + tensor current_key_39_pad_type_0 = const()[name = tensor("current_key_39_pad_type_0"), val = tensor("valid")]; + tensor current_key_39_strides_0 = const()[name = tensor("current_key_39_strides_0"), val = tensor([1, 1])]; + tensor current_key_39_pad_0 = const()[name = tensor("current_key_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_39_dilations_0 = const()[name = tensor("current_key_39_dilations_0"), val = tensor([1, 1])]; + tensor current_key_39_groups_0 = const()[name = tensor("current_key_39_groups_0"), val = tensor(1)]; + tensor layers_19_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_19_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(747469888)))]; + tensor current_key_39_cast_fp16 = conv(dilations = current_key_39_dilations_0, groups = current_key_39_groups_0, pad = current_key_39_pad_0, pad_type = current_key_39_pad_type_0, strides = current_key_39_strides_0, weight = layers_19_self_attn_k_proj_weight_to_fp16, x = obj_267_cast_fp16)[name = tensor("current_key_39_cast_fp16")]; + tensor current_value_39_pad_type_0 = const()[name = tensor("current_value_39_pad_type_0"), val = tensor("valid")]; + tensor current_value_39_strides_0 = const()[name = tensor("current_value_39_strides_0"), val = tensor([1, 1])]; + tensor current_value_39_pad_0 = const()[name = tensor("current_value_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_39_dilations_0 = const()[name = tensor("current_value_39_dilations_0"), val = tensor([1, 1])]; + tensor current_value_39_groups_0 = const()[name = tensor("current_value_39_groups_0"), val = tensor(1)]; + tensor layers_19_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_19_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(749567104)))]; + tensor layers_19_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_19_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(751664320)))]; + tensor current_value_39_cast_fp16 = conv(bias = layers_19_self_attn_v_proj_bias_to_fp16, dilations = current_value_39_dilations_0, groups = current_value_39_groups_0, pad = current_value_39_pad_0, pad_type = current_value_39_pad_type_0, strides = current_value_39_strides_0, weight = layers_19_self_attn_v_proj_weight_to_fp16, x = obj_267_cast_fp16)[name = tensor("current_value_39_cast_fp16")]; + tensor var_4381_cast_fp16 = mul(x = var_87_cast_fp16_19, y = var_207_cast_fp16)[name = tensor("op_4381_cast_fp16")]; + tensor var_4382_cast_fp16 = mul(x = current_key_39_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_4382_cast_fp16")]; + tensor key_77_cast_fp16 = add(x = var_4381_cast_fp16, y = var_4382_cast_fp16)[name = tensor("key_77_cast_fp16")]; + tensor var_4385_cast_fp16 = mul(x = var_114_cast_fp16_19, y = var_207_cast_fp16)[name = tensor("op_4385_cast_fp16")]; + tensor var_4386_cast_fp16 = mul(x = current_value_39_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_4386_cast_fp16")]; + tensor value_77_cast_fp16 = add(x = var_4385_cast_fp16, y = var_4386_cast_fp16)[name = tensor("value_77_cast_fp16")]; + tensor var_4390 = const()[name = tensor("op_4390"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_77_cast_fp16 = reshape(shape = var_4390, x = query_77_cast_fp16)[name = tensor("mh_q_77_cast_fp16")]; + tensor var_4392_to_fp16 = const()[name = tensor("op_4392_to_fp16"), val = tensor(0x1p-3)]; + tensor var_4393_cast_fp16 = mul(x = mh_q_77_cast_fp16, y = var_4392_to_fp16)[name = tensor("op_4393_cast_fp16")]; + tensor var_4396 = const()[name = tensor("op_4396"), val = tensor([1, 16, 64, 448])]; + tensor var_4397_cast_fp16 = reshape(shape = var_4396, x = key_77_cast_fp16)[name = tensor("op_4397_cast_fp16")]; + tensor mh_w_115_transpose_x_0 = const()[name = tensor("mh_w_115_transpose_x_0"), val = tensor(true)]; + tensor mh_w_115_transpose_y_0 = const()[name = tensor("mh_w_115_transpose_y_0"), val = tensor(false)]; + tensor mh_w_115_cast_fp16 = matmul(transpose_x = mh_w_115_transpose_x_0, transpose_y = mh_w_115_transpose_y_0, x = var_4393_cast_fp16, y = var_4397_cast_fp16)[name = tensor("mh_w_115_cast_fp16")]; + tensor mh_w_117_cast_fp16 = add(x = mh_w_115_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_117_cast_fp16")]; + tensor var_4405_cast_fp16 = softmax(axis = var_4317, x = mh_w_117_cast_fp16)[name = tensor("op_4405_cast_fp16")]; + tensor var_4406 = const()[name = tensor("op_4406"), val = tensor([1, 16, 64, 448])]; + tensor var_4407_cast_fp16 = reshape(shape = var_4406, x = value_77_cast_fp16)[name = tensor("op_4407_cast_fp16")]; + tensor attn_77_transpose_x_0 = const()[name = tensor("attn_77_transpose_x_0"), val = tensor(false)]; + tensor attn_77_transpose_y_0 = const()[name = tensor("attn_77_transpose_y_0"), val = tensor(true)]; + tensor attn_77_cast_fp16 = matmul(transpose_x = attn_77_transpose_x_0, transpose_y = attn_77_transpose_y_0, x = var_4407_cast_fp16, y = var_4405_cast_fp16)[name = tensor("attn_77_cast_fp16")]; + tensor var_4410 = const()[name = tensor("op_4410"), val = tensor([1, 1024, 1, 1])]; + tensor input_191_cast_fp16 = reshape(shape = var_4410, x = attn_77_cast_fp16)[name = tensor("input_191_cast_fp16")]; + tensor obj_273_pad_type_0 = const()[name = tensor("obj_273_pad_type_0"), val = tensor("valid")]; + tensor obj_273_strides_0 = const()[name = tensor("obj_273_strides_0"), val = tensor([1, 1])]; + tensor obj_273_pad_0 = const()[name = tensor("obj_273_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_273_dilations_0 = const()[name = tensor("obj_273_dilations_0"), val = tensor([1, 1])]; + tensor obj_273_groups_0 = const()[name = tensor("obj_273_groups_0"), val = tensor(1)]; + tensor layers_19_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_19_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(751666432)))]; + tensor layers_19_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_19_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(753763648)))]; + tensor obj_273_cast_fp16 = conv(bias = layers_19_self_attn_o_proj_bias_to_fp16, dilations = obj_273_dilations_0, groups = obj_273_groups_0, pad = obj_273_pad_0, pad_type = obj_273_pad_type_0, strides = obj_273_strides_0, weight = layers_19_self_attn_o_proj_weight_to_fp16, x = input_191_cast_fp16)[name = tensor("obj_273_cast_fp16")]; + tensor inputs_117_cast_fp16 = add(x = inputs_115_cast_fp16, y = obj_273_cast_fp16)[name = tensor("inputs_117_cast_fp16")]; + tensor out_117_axes_0 = const()[name = tensor("out_117_axes_0"), val = tensor([1])]; + tensor var_4432_to_fp16 = const()[name = tensor("op_4432_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_117_cast_fp16 = layer_norm(axes = out_117_axes_0, epsilon = var_4432_to_fp16, x = inputs_117_cast_fp16)[name = tensor("out_117_cast_fp16")]; + tensor obj_275_gamma_0_to_fp16 = const()[name = tensor("obj_275_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(753765760)))]; + tensor obj_275_beta_0_to_fp16 = const()[name = tensor("obj_275_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(753767872)))]; + tensor obj_275_epsilon_0_to_fp16 = const()[name = tensor("obj_275_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_275_cast_fp16 = batch_norm(beta = obj_275_beta_0_to_fp16, epsilon = obj_275_epsilon_0_to_fp16, gamma = obj_275_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_117_cast_fp16)[name = tensor("obj_275_cast_fp16")]; + tensor query_79_pad_type_0 = const()[name = tensor("query_79_pad_type_0"), val = tensor("valid")]; + tensor query_79_strides_0 = const()[name = tensor("query_79_strides_0"), val = tensor([1, 1])]; + tensor query_79_pad_0 = const()[name = tensor("query_79_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_79_dilations_0 = const()[name = tensor("query_79_dilations_0"), val = tensor([1, 1])]; + tensor query_79_groups_0 = const()[name = tensor("query_79_groups_0"), val = tensor(1)]; + tensor layers_19_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_19_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(753769984)))]; + tensor layers_19_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_19_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(755867200)))]; + tensor query_79_cast_fp16 = conv(bias = layers_19_encoder_attn_q_proj_bias_to_fp16, dilations = query_79_dilations_0, groups = query_79_groups_0, pad = query_79_pad_0, pad_type = query_79_pad_type_0, strides = query_79_strides_0, weight = layers_19_encoder_attn_q_proj_weight_to_fp16, x = obj_275_cast_fp16)[name = tensor("query_79_cast_fp16")]; + tensor key_79_pad_type_0 = const()[name = tensor("key_79_pad_type_0"), val = tensor("valid")]; + tensor key_79_strides_0 = const()[name = tensor("key_79_strides_0"), val = tensor([1, 1])]; + tensor key_79_pad_0 = const()[name = tensor("key_79_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_79_dilations_0 = const()[name = tensor("key_79_dilations_0"), val = tensor([1, 1])]; + tensor key_79_groups_0 = const()[name = tensor("key_79_groups_0"), val = tensor(1)]; + tensor layers_19_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_19_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(755869312)))]; + tensor key_79_cast_fp16 = conv(dilations = key_79_dilations_0, groups = key_79_groups_0, pad = key_79_pad_0, pad_type = key_79_pad_type_0, strides = key_79_strides_0, weight = layers_19_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_79_cast_fp16")]; + tensor value_79_pad_type_0 = const()[name = tensor("value_79_pad_type_0"), val = tensor("valid")]; + tensor value_79_strides_0 = const()[name = tensor("value_79_strides_0"), val = tensor([1, 1])]; + tensor value_79_pad_0 = const()[name = tensor("value_79_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_79_dilations_0 = const()[name = tensor("value_79_dilations_0"), val = tensor([1, 1])]; + tensor value_79_groups_0 = const()[name = tensor("value_79_groups_0"), val = tensor(1)]; + tensor layers_19_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_19_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(757966528)))]; + tensor layers_19_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_19_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(760063744)))]; + tensor value_79_cast_fp16 = conv(bias = layers_19_encoder_attn_v_proj_bias_to_fp16, dilations = value_79_dilations_0, groups = value_79_groups_0, pad = value_79_pad_0, pad_type = value_79_pad_type_0, strides = value_79_strides_0, weight = layers_19_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_79_cast_fp16")]; + tensor var_4468 = const()[name = tensor("op_4468"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_79_cast_fp16 = reshape(shape = var_4468, x = query_79_cast_fp16)[name = tensor("mh_q_79_cast_fp16")]; + tensor var_4470_to_fp16 = const()[name = tensor("op_4470_to_fp16"), val = tensor(0x1p-3)]; + tensor var_4471_cast_fp16 = mul(x = mh_q_79_cast_fp16, y = var_4470_to_fp16)[name = tensor("op_4471_cast_fp16")]; + tensor var_4474 = const()[name = tensor("op_4474"), val = tensor([1, 16, 64, 1500])]; + tensor var_4475_cast_fp16 = reshape(shape = var_4474, x = key_79_cast_fp16)[name = tensor("op_4475_cast_fp16")]; + tensor mh_w_119_transpose_x_0 = const()[name = tensor("mh_w_119_transpose_x_0"), val = tensor(true)]; + tensor mh_w_119_transpose_y_0 = const()[name = tensor("mh_w_119_transpose_y_0"), val = tensor(false)]; + tensor mh_w_119_cast_fp16 = matmul(transpose_x = mh_w_119_transpose_x_0, transpose_y = mh_w_119_transpose_y_0, x = var_4471_cast_fp16, y = var_4475_cast_fp16)[name = tensor("mh_w_119_cast_fp16")]; + tensor obj_279_cast_fp16 = softmax(axis = var_4317, x = mh_w_119_cast_fp16)[name = tensor("obj_279_cast_fp16")]; + tensor var_4479 = const()[name = tensor("op_4479"), val = tensor([1, 16, 64, 1500])]; + tensor var_4480_cast_fp16 = reshape(shape = var_4479, x = value_79_cast_fp16)[name = tensor("op_4480_cast_fp16")]; + tensor attn_79_transpose_x_0 = const()[name = tensor("attn_79_transpose_x_0"), val = tensor(false)]; + tensor attn_79_transpose_y_0 = const()[name = tensor("attn_79_transpose_y_0"), val = tensor(true)]; + tensor attn_79_cast_fp16 = matmul(transpose_x = attn_79_transpose_x_0, transpose_y = attn_79_transpose_y_0, x = var_4480_cast_fp16, y = obj_279_cast_fp16)[name = tensor("attn_79_cast_fp16")]; + tensor var_4483 = const()[name = tensor("op_4483"), val = tensor([1, 1024, 1, 1])]; + tensor input_193_cast_fp16 = reshape(shape = var_4483, x = attn_79_cast_fp16)[name = tensor("input_193_cast_fp16")]; + tensor obj_277_pad_type_0 = const()[name = tensor("obj_277_pad_type_0"), val = tensor("valid")]; + tensor obj_277_strides_0 = const()[name = tensor("obj_277_strides_0"), val = tensor([1, 1])]; + tensor obj_277_pad_0 = const()[name = tensor("obj_277_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_277_dilations_0 = const()[name = tensor("obj_277_dilations_0"), val = tensor([1, 1])]; + tensor obj_277_groups_0 = const()[name = tensor("obj_277_groups_0"), val = tensor(1)]; + tensor layers_19_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_19_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(760065856)))]; + tensor layers_19_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_19_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(762163072)))]; + tensor obj_277_cast_fp16 = conv(bias = layers_19_encoder_attn_o_proj_bias_to_fp16, dilations = obj_277_dilations_0, groups = obj_277_groups_0, pad = obj_277_pad_0, pad_type = obj_277_pad_type_0, strides = obj_277_strides_0, weight = layers_19_encoder_attn_o_proj_weight_to_fp16, x = input_193_cast_fp16)[name = tensor("obj_277_cast_fp16")]; + tensor inputs_119_cast_fp16 = add(x = inputs_117_cast_fp16, y = obj_277_cast_fp16)[name = tensor("inputs_119_cast_fp16")]; + tensor out_119_axes_0 = const()[name = tensor("out_119_axes_0"), val = tensor([1])]; + tensor var_4501_to_fp16 = const()[name = tensor("op_4501_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_119_cast_fp16 = layer_norm(axes = out_119_axes_0, epsilon = var_4501_to_fp16, x = inputs_119_cast_fp16)[name = tensor("out_119_cast_fp16")]; + tensor input_195_gamma_0_to_fp16 = const()[name = tensor("input_195_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(762165184)))]; + tensor input_195_beta_0_to_fp16 = const()[name = tensor("input_195_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(762167296)))]; + tensor input_195_epsilon_0_to_fp16 = const()[name = tensor("input_195_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_195_cast_fp16 = batch_norm(beta = input_195_beta_0_to_fp16, epsilon = input_195_epsilon_0_to_fp16, gamma = input_195_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_119_cast_fp16)[name = tensor("input_195_cast_fp16")]; + tensor input_197_pad_type_0 = const()[name = tensor("input_197_pad_type_0"), val = tensor("valid")]; + tensor input_197_strides_0 = const()[name = tensor("input_197_strides_0"), val = tensor([1, 1])]; + tensor input_197_pad_0 = const()[name = tensor("input_197_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_197_dilations_0 = const()[name = tensor("input_197_dilations_0"), val = tensor([1, 1])]; + tensor input_197_groups_0 = const()[name = tensor("input_197_groups_0"), val = tensor(1)]; + tensor layers_19_fc1_weight_to_fp16 = const()[name = tensor("layers_19_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(762169408)))]; + tensor layers_19_fc1_bias_to_fp16 = const()[name = tensor("layers_19_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(770558080)))]; + tensor input_197_cast_fp16 = conv(bias = layers_19_fc1_bias_to_fp16, dilations = input_197_dilations_0, groups = input_197_groups_0, pad = input_197_pad_0, pad_type = input_197_pad_type_0, strides = input_197_strides_0, weight = layers_19_fc1_weight_to_fp16, x = input_195_cast_fp16)[name = tensor("input_197_cast_fp16")]; + tensor input_199_mode_0 = const()[name = tensor("input_199_mode_0"), val = tensor("EXACT")]; + tensor input_199_cast_fp16 = gelu(mode = input_199_mode_0, x = input_197_cast_fp16)[name = tensor("input_199_cast_fp16")]; + tensor hidden_states_41_pad_type_0 = const()[name = tensor("hidden_states_41_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_41_strides_0 = const()[name = tensor("hidden_states_41_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_41_pad_0 = const()[name = tensor("hidden_states_41_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_41_dilations_0 = const()[name = tensor("hidden_states_41_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_41_groups_0 = const()[name = tensor("hidden_states_41_groups_0"), val = tensor(1)]; + tensor layers_19_fc2_weight_to_fp16 = const()[name = tensor("layers_19_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(770566336)))]; + tensor layers_19_fc2_bias_to_fp16 = const()[name = tensor("layers_19_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(778955008)))]; + tensor hidden_states_41_cast_fp16 = conv(bias = layers_19_fc2_bias_to_fp16, dilations = hidden_states_41_dilations_0, groups = hidden_states_41_groups_0, pad = hidden_states_41_pad_0, pad_type = hidden_states_41_pad_type_0, strides = hidden_states_41_strides_0, weight = layers_19_fc2_weight_to_fp16, x = input_199_cast_fp16)[name = tensor("hidden_states_41_cast_fp16")]; + tensor inputs_121_cast_fp16 = add(x = inputs_119_cast_fp16, y = hidden_states_41_cast_fp16)[name = tensor("inputs_121_cast_fp16")]; + tensor var_4536 = const()[name = tensor("op_4536"), val = tensor(3)]; + tensor out_121_axes_0 = const()[name = tensor("out_121_axes_0"), val = tensor([1])]; + tensor var_4561_to_fp16 = const()[name = tensor("op_4561_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_121_cast_fp16 = layer_norm(axes = out_121_axes_0, epsilon = var_4561_to_fp16, x = inputs_121_cast_fp16)[name = tensor("out_121_cast_fp16")]; + tensor obj_281_gamma_0_to_fp16 = const()[name = tensor("obj_281_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(778957120)))]; + tensor obj_281_beta_0_to_fp16 = const()[name = tensor("obj_281_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(778959232)))]; + tensor obj_281_epsilon_0_to_fp16 = const()[name = tensor("obj_281_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_281_cast_fp16 = batch_norm(beta = obj_281_beta_0_to_fp16, epsilon = obj_281_epsilon_0_to_fp16, gamma = obj_281_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_121_cast_fp16)[name = tensor("obj_281_cast_fp16")]; + tensor query_81_pad_type_0 = const()[name = tensor("query_81_pad_type_0"), val = tensor("valid")]; + tensor query_81_strides_0 = const()[name = tensor("query_81_strides_0"), val = tensor([1, 1])]; + tensor query_81_pad_0 = const()[name = tensor("query_81_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_81_dilations_0 = const()[name = tensor("query_81_dilations_0"), val = tensor([1, 1])]; + tensor query_81_groups_0 = const()[name = tensor("query_81_groups_0"), val = tensor(1)]; + tensor layers_20_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_20_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(778961344)))]; + tensor layers_20_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_20_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(781058560)))]; + tensor query_81_cast_fp16 = conv(bias = layers_20_self_attn_q_proj_bias_to_fp16, dilations = query_81_dilations_0, groups = query_81_groups_0, pad = query_81_pad_0, pad_type = query_81_pad_type_0, strides = query_81_strides_0, weight = layers_20_self_attn_q_proj_weight_to_fp16, x = obj_281_cast_fp16)[name = tensor("query_81_cast_fp16")]; + tensor current_key_41_pad_type_0 = const()[name = tensor("current_key_41_pad_type_0"), val = tensor("valid")]; + tensor current_key_41_strides_0 = const()[name = tensor("current_key_41_strides_0"), val = tensor([1, 1])]; + tensor current_key_41_pad_0 = const()[name = tensor("current_key_41_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_41_dilations_0 = const()[name = tensor("current_key_41_dilations_0"), val = tensor([1, 1])]; + tensor current_key_41_groups_0 = const()[name = tensor("current_key_41_groups_0"), val = tensor(1)]; + tensor layers_20_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_20_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(781060672)))]; + tensor current_key_41_cast_fp16 = conv(dilations = current_key_41_dilations_0, groups = current_key_41_groups_0, pad = current_key_41_pad_0, pad_type = current_key_41_pad_type_0, strides = current_key_41_strides_0, weight = layers_20_self_attn_k_proj_weight_to_fp16, x = obj_281_cast_fp16)[name = tensor("current_key_41_cast_fp16")]; + tensor current_value_41_pad_type_0 = const()[name = tensor("current_value_41_pad_type_0"), val = tensor("valid")]; + tensor current_value_41_strides_0 = const()[name = tensor("current_value_41_strides_0"), val = tensor([1, 1])]; + tensor current_value_41_pad_0 = const()[name = tensor("current_value_41_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_41_dilations_0 = const()[name = tensor("current_value_41_dilations_0"), val = tensor([1, 1])]; + tensor current_value_41_groups_0 = const()[name = tensor("current_value_41_groups_0"), val = tensor(1)]; + tensor layers_20_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_20_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(783157888)))]; + tensor layers_20_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_20_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(785255104)))]; + tensor current_value_41_cast_fp16 = conv(bias = layers_20_self_attn_v_proj_bias_to_fp16, dilations = current_value_41_dilations_0, groups = current_value_41_groups_0, pad = current_value_41_pad_0, pad_type = current_value_41_pad_type_0, strides = current_value_41_strides_0, weight = layers_20_self_attn_v_proj_weight_to_fp16, x = obj_281_cast_fp16)[name = tensor("current_value_41_cast_fp16")]; + tensor var_4600_cast_fp16 = mul(x = var_87_cast_fp16_20, y = var_207_cast_fp16)[name = tensor("op_4600_cast_fp16")]; + tensor var_4601_cast_fp16 = mul(x = current_key_41_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_4601_cast_fp16")]; + tensor key_81_cast_fp16 = add(x = var_4600_cast_fp16, y = var_4601_cast_fp16)[name = tensor("key_81_cast_fp16")]; + tensor var_4604_cast_fp16 = mul(x = var_114_cast_fp16_20, y = var_207_cast_fp16)[name = tensor("op_4604_cast_fp16")]; + tensor var_4605_cast_fp16 = mul(x = current_value_41_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_4605_cast_fp16")]; + tensor value_81_cast_fp16 = add(x = var_4604_cast_fp16, y = var_4605_cast_fp16)[name = tensor("value_81_cast_fp16")]; + tensor var_4609 = const()[name = tensor("op_4609"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_81_cast_fp16 = reshape(shape = var_4609, x = query_81_cast_fp16)[name = tensor("mh_q_81_cast_fp16")]; + tensor var_4611_to_fp16 = const()[name = tensor("op_4611_to_fp16"), val = tensor(0x1p-3)]; + tensor var_4612_cast_fp16 = mul(x = mh_q_81_cast_fp16, y = var_4611_to_fp16)[name = tensor("op_4612_cast_fp16")]; + tensor var_4615 = const()[name = tensor("op_4615"), val = tensor([1, 16, 64, 448])]; + tensor var_4616_cast_fp16 = reshape(shape = var_4615, x = key_81_cast_fp16)[name = tensor("op_4616_cast_fp16")]; + tensor mh_w_121_transpose_x_0 = const()[name = tensor("mh_w_121_transpose_x_0"), val = tensor(true)]; + tensor mh_w_121_transpose_y_0 = const()[name = tensor("mh_w_121_transpose_y_0"), val = tensor(false)]; + tensor mh_w_121_cast_fp16 = matmul(transpose_x = mh_w_121_transpose_x_0, transpose_y = mh_w_121_transpose_y_0, x = var_4612_cast_fp16, y = var_4616_cast_fp16)[name = tensor("mh_w_121_cast_fp16")]; + tensor mh_w_123_cast_fp16 = add(x = mh_w_121_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_123_cast_fp16")]; + tensor var_4624_cast_fp16 = softmax(axis = var_4536, x = mh_w_123_cast_fp16)[name = tensor("op_4624_cast_fp16")]; + tensor var_4625 = const()[name = tensor("op_4625"), val = tensor([1, 16, 64, 448])]; + tensor var_4626_cast_fp16 = reshape(shape = var_4625, x = value_81_cast_fp16)[name = tensor("op_4626_cast_fp16")]; + tensor attn_81_transpose_x_0 = const()[name = tensor("attn_81_transpose_x_0"), val = tensor(false)]; + tensor attn_81_transpose_y_0 = const()[name = tensor("attn_81_transpose_y_0"), val = tensor(true)]; + tensor attn_81_cast_fp16 = matmul(transpose_x = attn_81_transpose_x_0, transpose_y = attn_81_transpose_y_0, x = var_4626_cast_fp16, y = var_4624_cast_fp16)[name = tensor("attn_81_cast_fp16")]; + tensor var_4629 = const()[name = tensor("op_4629"), val = tensor([1, 1024, 1, 1])]; + tensor input_201_cast_fp16 = reshape(shape = var_4629, x = attn_81_cast_fp16)[name = tensor("input_201_cast_fp16")]; + tensor obj_287_pad_type_0 = const()[name = tensor("obj_287_pad_type_0"), val = tensor("valid")]; + tensor obj_287_strides_0 = const()[name = tensor("obj_287_strides_0"), val = tensor([1, 1])]; + tensor obj_287_pad_0 = const()[name = tensor("obj_287_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_287_dilations_0 = const()[name = tensor("obj_287_dilations_0"), val = tensor([1, 1])]; + tensor obj_287_groups_0 = const()[name = tensor("obj_287_groups_0"), val = tensor(1)]; + tensor layers_20_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_20_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(785257216)))]; + tensor layers_20_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_20_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(787354432)))]; + tensor obj_287_cast_fp16 = conv(bias = layers_20_self_attn_o_proj_bias_to_fp16, dilations = obj_287_dilations_0, groups = obj_287_groups_0, pad = obj_287_pad_0, pad_type = obj_287_pad_type_0, strides = obj_287_strides_0, weight = layers_20_self_attn_o_proj_weight_to_fp16, x = input_201_cast_fp16)[name = tensor("obj_287_cast_fp16")]; + tensor inputs_123_cast_fp16 = add(x = inputs_121_cast_fp16, y = obj_287_cast_fp16)[name = tensor("inputs_123_cast_fp16")]; + tensor out_123_axes_0 = const()[name = tensor("out_123_axes_0"), val = tensor([1])]; + tensor var_4651_to_fp16 = const()[name = tensor("op_4651_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_123_cast_fp16 = layer_norm(axes = out_123_axes_0, epsilon = var_4651_to_fp16, x = inputs_123_cast_fp16)[name = tensor("out_123_cast_fp16")]; + tensor obj_289_gamma_0_to_fp16 = const()[name = tensor("obj_289_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(787356544)))]; + tensor obj_289_beta_0_to_fp16 = const()[name = tensor("obj_289_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(787358656)))]; + tensor obj_289_epsilon_0_to_fp16 = const()[name = tensor("obj_289_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_289_cast_fp16 = batch_norm(beta = obj_289_beta_0_to_fp16, epsilon = obj_289_epsilon_0_to_fp16, gamma = obj_289_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_123_cast_fp16)[name = tensor("obj_289_cast_fp16")]; + tensor query_83_pad_type_0 = const()[name = tensor("query_83_pad_type_0"), val = tensor("valid")]; + tensor query_83_strides_0 = const()[name = tensor("query_83_strides_0"), val = tensor([1, 1])]; + tensor query_83_pad_0 = const()[name = tensor("query_83_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_83_dilations_0 = const()[name = tensor("query_83_dilations_0"), val = tensor([1, 1])]; + tensor query_83_groups_0 = const()[name = tensor("query_83_groups_0"), val = tensor(1)]; + tensor layers_20_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_20_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(787360768)))]; + tensor layers_20_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_20_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(789457984)))]; + tensor query_83_cast_fp16 = conv(bias = layers_20_encoder_attn_q_proj_bias_to_fp16, dilations = query_83_dilations_0, groups = query_83_groups_0, pad = query_83_pad_0, pad_type = query_83_pad_type_0, strides = query_83_strides_0, weight = layers_20_encoder_attn_q_proj_weight_to_fp16, x = obj_289_cast_fp16)[name = tensor("query_83_cast_fp16")]; + tensor key_83_pad_type_0 = const()[name = tensor("key_83_pad_type_0"), val = tensor("valid")]; + tensor key_83_strides_0 = const()[name = tensor("key_83_strides_0"), val = tensor([1, 1])]; + tensor key_83_pad_0 = const()[name = tensor("key_83_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_83_dilations_0 = const()[name = tensor("key_83_dilations_0"), val = tensor([1, 1])]; + tensor key_83_groups_0 = const()[name = tensor("key_83_groups_0"), val = tensor(1)]; + tensor layers_20_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_20_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(789460096)))]; + tensor key_83_cast_fp16 = conv(dilations = key_83_dilations_0, groups = key_83_groups_0, pad = key_83_pad_0, pad_type = key_83_pad_type_0, strides = key_83_strides_0, weight = layers_20_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_83_cast_fp16")]; + tensor value_83_pad_type_0 = const()[name = tensor("value_83_pad_type_0"), val = tensor("valid")]; + tensor value_83_strides_0 = const()[name = tensor("value_83_strides_0"), val = tensor([1, 1])]; + tensor value_83_pad_0 = const()[name = tensor("value_83_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_83_dilations_0 = const()[name = tensor("value_83_dilations_0"), val = tensor([1, 1])]; + tensor value_83_groups_0 = const()[name = tensor("value_83_groups_0"), val = tensor(1)]; + tensor layers_20_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_20_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(791557312)))]; + tensor layers_20_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_20_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(793654528)))]; + tensor value_83_cast_fp16 = conv(bias = layers_20_encoder_attn_v_proj_bias_to_fp16, dilations = value_83_dilations_0, groups = value_83_groups_0, pad = value_83_pad_0, pad_type = value_83_pad_type_0, strides = value_83_strides_0, weight = layers_20_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_83_cast_fp16")]; + tensor var_4687 = const()[name = tensor("op_4687"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_83_cast_fp16 = reshape(shape = var_4687, x = query_83_cast_fp16)[name = tensor("mh_q_83_cast_fp16")]; + tensor var_4689_to_fp16 = const()[name = tensor("op_4689_to_fp16"), val = tensor(0x1p-3)]; + tensor var_4690_cast_fp16 = mul(x = mh_q_83_cast_fp16, y = var_4689_to_fp16)[name = tensor("op_4690_cast_fp16")]; + tensor var_4693 = const()[name = tensor("op_4693"), val = tensor([1, 16, 64, 1500])]; + tensor var_4694_cast_fp16 = reshape(shape = var_4693, x = key_83_cast_fp16)[name = tensor("op_4694_cast_fp16")]; + tensor mh_w_125_transpose_x_0 = const()[name = tensor("mh_w_125_transpose_x_0"), val = tensor(true)]; + tensor mh_w_125_transpose_y_0 = const()[name = tensor("mh_w_125_transpose_y_0"), val = tensor(false)]; + tensor mh_w_125_cast_fp16 = matmul(transpose_x = mh_w_125_transpose_x_0, transpose_y = mh_w_125_transpose_y_0, x = var_4690_cast_fp16, y = var_4694_cast_fp16)[name = tensor("mh_w_125_cast_fp16")]; + tensor obj_293_cast_fp16 = softmax(axis = var_4536, x = mh_w_125_cast_fp16)[name = tensor("obj_293_cast_fp16")]; + tensor var_4698 = const()[name = tensor("op_4698"), val = tensor([1, 16, 64, 1500])]; + tensor var_4699_cast_fp16 = reshape(shape = var_4698, x = value_83_cast_fp16)[name = tensor("op_4699_cast_fp16")]; + tensor attn_83_transpose_x_0 = const()[name = tensor("attn_83_transpose_x_0"), val = tensor(false)]; + tensor attn_83_transpose_y_0 = const()[name = tensor("attn_83_transpose_y_0"), val = tensor(true)]; + tensor attn_83_cast_fp16 = matmul(transpose_x = attn_83_transpose_x_0, transpose_y = attn_83_transpose_y_0, x = var_4699_cast_fp16, y = obj_293_cast_fp16)[name = tensor("attn_83_cast_fp16")]; + tensor var_4702 = const()[name = tensor("op_4702"), val = tensor([1, 1024, 1, 1])]; + tensor input_203_cast_fp16 = reshape(shape = var_4702, x = attn_83_cast_fp16)[name = tensor("input_203_cast_fp16")]; + tensor obj_291_pad_type_0 = const()[name = tensor("obj_291_pad_type_0"), val = tensor("valid")]; + tensor obj_291_strides_0 = const()[name = tensor("obj_291_strides_0"), val = tensor([1, 1])]; + tensor obj_291_pad_0 = const()[name = tensor("obj_291_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_291_dilations_0 = const()[name = tensor("obj_291_dilations_0"), val = tensor([1, 1])]; + tensor obj_291_groups_0 = const()[name = tensor("obj_291_groups_0"), val = tensor(1)]; + tensor layers_20_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_20_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(793656640)))]; + tensor layers_20_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_20_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(795753856)))]; + tensor obj_291_cast_fp16 = conv(bias = layers_20_encoder_attn_o_proj_bias_to_fp16, dilations = obj_291_dilations_0, groups = obj_291_groups_0, pad = obj_291_pad_0, pad_type = obj_291_pad_type_0, strides = obj_291_strides_0, weight = layers_20_encoder_attn_o_proj_weight_to_fp16, x = input_203_cast_fp16)[name = tensor("obj_291_cast_fp16")]; + tensor inputs_125_cast_fp16 = add(x = inputs_123_cast_fp16, y = obj_291_cast_fp16)[name = tensor("inputs_125_cast_fp16")]; + tensor out_125_axes_0 = const()[name = tensor("out_125_axes_0"), val = tensor([1])]; + tensor var_4723_to_fp16 = const()[name = tensor("op_4723_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_125_cast_fp16 = layer_norm(axes = out_125_axes_0, epsilon = var_4723_to_fp16, x = inputs_125_cast_fp16)[name = tensor("out_125_cast_fp16")]; + tensor input_205_gamma_0_to_fp16 = const()[name = tensor("input_205_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(795755968)))]; + tensor input_205_beta_0_to_fp16 = const()[name = tensor("input_205_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(795758080)))]; + tensor input_205_epsilon_0_to_fp16 = const()[name = tensor("input_205_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_205_cast_fp16 = batch_norm(beta = input_205_beta_0_to_fp16, epsilon = input_205_epsilon_0_to_fp16, gamma = input_205_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_125_cast_fp16)[name = tensor("input_205_cast_fp16")]; + tensor input_207_pad_type_0 = const()[name = tensor("input_207_pad_type_0"), val = tensor("valid")]; + tensor input_207_strides_0 = const()[name = tensor("input_207_strides_0"), val = tensor([1, 1])]; + tensor input_207_pad_0 = const()[name = tensor("input_207_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_207_dilations_0 = const()[name = tensor("input_207_dilations_0"), val = tensor([1, 1])]; + tensor input_207_groups_0 = const()[name = tensor("input_207_groups_0"), val = tensor(1)]; + tensor layers_20_fc1_weight_to_fp16 = const()[name = tensor("layers_20_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(795760192)))]; + tensor layers_20_fc1_bias_to_fp16 = const()[name = tensor("layers_20_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(804148864)))]; + tensor input_207_cast_fp16 = conv(bias = layers_20_fc1_bias_to_fp16, dilations = input_207_dilations_0, groups = input_207_groups_0, pad = input_207_pad_0, pad_type = input_207_pad_type_0, strides = input_207_strides_0, weight = layers_20_fc1_weight_to_fp16, x = input_205_cast_fp16)[name = tensor("input_207_cast_fp16")]; + tensor input_209_mode_0 = const()[name = tensor("input_209_mode_0"), val = tensor("EXACT")]; + tensor input_209_cast_fp16 = gelu(mode = input_209_mode_0, x = input_207_cast_fp16)[name = tensor("input_209_cast_fp16")]; + tensor hidden_states_43_pad_type_0 = const()[name = tensor("hidden_states_43_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_43_strides_0 = const()[name = tensor("hidden_states_43_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_43_pad_0 = const()[name = tensor("hidden_states_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_43_dilations_0 = const()[name = tensor("hidden_states_43_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_43_groups_0 = const()[name = tensor("hidden_states_43_groups_0"), val = tensor(1)]; + tensor layers_20_fc2_weight_to_fp16 = const()[name = tensor("layers_20_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(804157120)))]; + tensor layers_20_fc2_bias_to_fp16 = const()[name = tensor("layers_20_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(812545792)))]; + tensor hidden_states_43_cast_fp16 = conv(bias = layers_20_fc2_bias_to_fp16, dilations = hidden_states_43_dilations_0, groups = hidden_states_43_groups_0, pad = hidden_states_43_pad_0, pad_type = hidden_states_43_pad_type_0, strides = hidden_states_43_strides_0, weight = layers_20_fc2_weight_to_fp16, x = input_209_cast_fp16)[name = tensor("hidden_states_43_cast_fp16")]; + tensor inputs_127_cast_fp16 = add(x = inputs_125_cast_fp16, y = hidden_states_43_cast_fp16)[name = tensor("inputs_127_cast_fp16")]; + tensor var_4759 = const()[name = tensor("op_4759"), val = tensor(3)]; + tensor out_127_axes_0 = const()[name = tensor("out_127_axes_0"), val = tensor([1])]; + tensor var_4784_to_fp16 = const()[name = tensor("op_4784_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_127_cast_fp16 = layer_norm(axes = out_127_axes_0, epsilon = var_4784_to_fp16, x = inputs_127_cast_fp16)[name = tensor("out_127_cast_fp16")]; + tensor obj_295_gamma_0_to_fp16 = const()[name = tensor("obj_295_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(812547904)))]; + tensor obj_295_beta_0_to_fp16 = const()[name = tensor("obj_295_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(812550016)))]; + tensor obj_295_epsilon_0_to_fp16 = const()[name = tensor("obj_295_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_295_cast_fp16 = batch_norm(beta = obj_295_beta_0_to_fp16, epsilon = obj_295_epsilon_0_to_fp16, gamma = obj_295_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_127_cast_fp16)[name = tensor("obj_295_cast_fp16")]; + tensor query_85_pad_type_0 = const()[name = tensor("query_85_pad_type_0"), val = tensor("valid")]; + tensor query_85_strides_0 = const()[name = tensor("query_85_strides_0"), val = tensor([1, 1])]; + tensor query_85_pad_0 = const()[name = tensor("query_85_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_85_dilations_0 = const()[name = tensor("query_85_dilations_0"), val = tensor([1, 1])]; + tensor query_85_groups_0 = const()[name = tensor("query_85_groups_0"), val = tensor(1)]; + tensor layers_21_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_21_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(812552128)))]; + tensor layers_21_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_21_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(814649344)))]; + tensor query_85_cast_fp16 = conv(bias = layers_21_self_attn_q_proj_bias_to_fp16, dilations = query_85_dilations_0, groups = query_85_groups_0, pad = query_85_pad_0, pad_type = query_85_pad_type_0, strides = query_85_strides_0, weight = layers_21_self_attn_q_proj_weight_to_fp16, x = obj_295_cast_fp16)[name = tensor("query_85_cast_fp16")]; + tensor current_key_43_pad_type_0 = const()[name = tensor("current_key_43_pad_type_0"), val = tensor("valid")]; + tensor current_key_43_strides_0 = const()[name = tensor("current_key_43_strides_0"), val = tensor([1, 1])]; + tensor current_key_43_pad_0 = const()[name = tensor("current_key_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_43_dilations_0 = const()[name = tensor("current_key_43_dilations_0"), val = tensor([1, 1])]; + tensor current_key_43_groups_0 = const()[name = tensor("current_key_43_groups_0"), val = tensor(1)]; + tensor layers_21_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_21_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(814651456)))]; + tensor current_key_43_cast_fp16 = conv(dilations = current_key_43_dilations_0, groups = current_key_43_groups_0, pad = current_key_43_pad_0, pad_type = current_key_43_pad_type_0, strides = current_key_43_strides_0, weight = layers_21_self_attn_k_proj_weight_to_fp16, x = obj_295_cast_fp16)[name = tensor("current_key_43_cast_fp16")]; + tensor current_value_43_pad_type_0 = const()[name = tensor("current_value_43_pad_type_0"), val = tensor("valid")]; + tensor current_value_43_strides_0 = const()[name = tensor("current_value_43_strides_0"), val = tensor([1, 1])]; + tensor current_value_43_pad_0 = const()[name = tensor("current_value_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_43_dilations_0 = const()[name = tensor("current_value_43_dilations_0"), val = tensor([1, 1])]; + tensor current_value_43_groups_0 = const()[name = tensor("current_value_43_groups_0"), val = tensor(1)]; + tensor layers_21_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_21_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(816748672)))]; + tensor layers_21_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_21_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(818845888)))]; + tensor current_value_43_cast_fp16 = conv(bias = layers_21_self_attn_v_proj_bias_to_fp16, dilations = current_value_43_dilations_0, groups = current_value_43_groups_0, pad = current_value_43_pad_0, pad_type = current_value_43_pad_type_0, strides = current_value_43_strides_0, weight = layers_21_self_attn_v_proj_weight_to_fp16, x = obj_295_cast_fp16)[name = tensor("current_value_43_cast_fp16")]; + tensor var_4823_cast_fp16 = mul(x = var_87_cast_fp16_21, y = var_207_cast_fp16)[name = tensor("op_4823_cast_fp16")]; + tensor var_4824_cast_fp16 = mul(x = current_key_43_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_4824_cast_fp16")]; + tensor key_85_cast_fp16 = add(x = var_4823_cast_fp16, y = var_4824_cast_fp16)[name = tensor("key_85_cast_fp16")]; + tensor var_4827_cast_fp16 = mul(x = var_114_cast_fp16_21, y = var_207_cast_fp16)[name = tensor("op_4827_cast_fp16")]; + tensor var_4828_cast_fp16 = mul(x = current_value_43_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_4828_cast_fp16")]; + tensor value_85_cast_fp16 = add(x = var_4827_cast_fp16, y = var_4828_cast_fp16)[name = tensor("value_85_cast_fp16")]; + tensor var_4832 = const()[name = tensor("op_4832"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_85_cast_fp16 = reshape(shape = var_4832, x = query_85_cast_fp16)[name = tensor("mh_q_85_cast_fp16")]; + tensor var_4834_to_fp16 = const()[name = tensor("op_4834_to_fp16"), val = tensor(0x1p-3)]; + tensor var_4835_cast_fp16 = mul(x = mh_q_85_cast_fp16, y = var_4834_to_fp16)[name = tensor("op_4835_cast_fp16")]; + tensor var_4838 = const()[name = tensor("op_4838"), val = tensor([1, 16, 64, 448])]; + tensor var_4839_cast_fp16 = reshape(shape = var_4838, x = key_85_cast_fp16)[name = tensor("op_4839_cast_fp16")]; + tensor mh_w_127_transpose_x_0 = const()[name = tensor("mh_w_127_transpose_x_0"), val = tensor(true)]; + tensor mh_w_127_transpose_y_0 = const()[name = tensor("mh_w_127_transpose_y_0"), val = tensor(false)]; + tensor mh_w_127_cast_fp16 = matmul(transpose_x = mh_w_127_transpose_x_0, transpose_y = mh_w_127_transpose_y_0, x = var_4835_cast_fp16, y = var_4839_cast_fp16)[name = tensor("mh_w_127_cast_fp16")]; + tensor mh_w_129_cast_fp16 = add(x = mh_w_127_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_129_cast_fp16")]; + tensor var_4847_cast_fp16 = softmax(axis = var_4759, x = mh_w_129_cast_fp16)[name = tensor("op_4847_cast_fp16")]; + tensor var_4848 = const()[name = tensor("op_4848"), val = tensor([1, 16, 64, 448])]; + tensor var_4849_cast_fp16 = reshape(shape = var_4848, x = value_85_cast_fp16)[name = tensor("op_4849_cast_fp16")]; + tensor attn_85_transpose_x_0 = const()[name = tensor("attn_85_transpose_x_0"), val = tensor(false)]; + tensor attn_85_transpose_y_0 = const()[name = tensor("attn_85_transpose_y_0"), val = tensor(true)]; + tensor attn_85_cast_fp16 = matmul(transpose_x = attn_85_transpose_x_0, transpose_y = attn_85_transpose_y_0, x = var_4849_cast_fp16, y = var_4847_cast_fp16)[name = tensor("attn_85_cast_fp16")]; + tensor var_4852 = const()[name = tensor("op_4852"), val = tensor([1, 1024, 1, 1])]; + tensor input_211_cast_fp16 = reshape(shape = var_4852, x = attn_85_cast_fp16)[name = tensor("input_211_cast_fp16")]; + tensor obj_301_pad_type_0 = const()[name = tensor("obj_301_pad_type_0"), val = tensor("valid")]; + tensor obj_301_strides_0 = const()[name = tensor("obj_301_strides_0"), val = tensor([1, 1])]; + tensor obj_301_pad_0 = const()[name = tensor("obj_301_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_301_dilations_0 = const()[name = tensor("obj_301_dilations_0"), val = tensor([1, 1])]; + tensor obj_301_groups_0 = const()[name = tensor("obj_301_groups_0"), val = tensor(1)]; + tensor layers_21_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_21_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(818848000)))]; + tensor layers_21_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_21_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(820945216)))]; + tensor obj_301_cast_fp16 = conv(bias = layers_21_self_attn_o_proj_bias_to_fp16, dilations = obj_301_dilations_0, groups = obj_301_groups_0, pad = obj_301_pad_0, pad_type = obj_301_pad_type_0, strides = obj_301_strides_0, weight = layers_21_self_attn_o_proj_weight_to_fp16, x = input_211_cast_fp16)[name = tensor("obj_301_cast_fp16")]; + tensor inputs_129_cast_fp16 = add(x = inputs_127_cast_fp16, y = obj_301_cast_fp16)[name = tensor("inputs_129_cast_fp16")]; + tensor out_129_axes_0 = const()[name = tensor("out_129_axes_0"), val = tensor([1])]; + tensor var_4874_to_fp16 = const()[name = tensor("op_4874_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_129_cast_fp16 = layer_norm(axes = out_129_axes_0, epsilon = var_4874_to_fp16, x = inputs_129_cast_fp16)[name = tensor("out_129_cast_fp16")]; + tensor obj_303_gamma_0_to_fp16 = const()[name = tensor("obj_303_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(820947328)))]; + tensor obj_303_beta_0_to_fp16 = const()[name = tensor("obj_303_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(820949440)))]; + tensor obj_303_epsilon_0_to_fp16 = const()[name = tensor("obj_303_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_303_cast_fp16 = batch_norm(beta = obj_303_beta_0_to_fp16, epsilon = obj_303_epsilon_0_to_fp16, gamma = obj_303_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_129_cast_fp16)[name = tensor("obj_303_cast_fp16")]; + tensor query_87_pad_type_0 = const()[name = tensor("query_87_pad_type_0"), val = tensor("valid")]; + tensor query_87_strides_0 = const()[name = tensor("query_87_strides_0"), val = tensor([1, 1])]; + tensor query_87_pad_0 = const()[name = tensor("query_87_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_87_dilations_0 = const()[name = tensor("query_87_dilations_0"), val = tensor([1, 1])]; + tensor query_87_groups_0 = const()[name = tensor("query_87_groups_0"), val = tensor(1)]; + tensor layers_21_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_21_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(820951552)))]; + tensor layers_21_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_21_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(823048768)))]; + tensor query_87_cast_fp16 = conv(bias = layers_21_encoder_attn_q_proj_bias_to_fp16, dilations = query_87_dilations_0, groups = query_87_groups_0, pad = query_87_pad_0, pad_type = query_87_pad_type_0, strides = query_87_strides_0, weight = layers_21_encoder_attn_q_proj_weight_to_fp16, x = obj_303_cast_fp16)[name = tensor("query_87_cast_fp16")]; + tensor key_87_pad_type_0 = const()[name = tensor("key_87_pad_type_0"), val = tensor("valid")]; + tensor key_87_strides_0 = const()[name = tensor("key_87_strides_0"), val = tensor([1, 1])]; + tensor key_87_pad_0 = const()[name = tensor("key_87_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_87_dilations_0 = const()[name = tensor("key_87_dilations_0"), val = tensor([1, 1])]; + tensor key_87_groups_0 = const()[name = tensor("key_87_groups_0"), val = tensor(1)]; + tensor layers_21_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_21_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(823050880)))]; + tensor key_87_cast_fp16 = conv(dilations = key_87_dilations_0, groups = key_87_groups_0, pad = key_87_pad_0, pad_type = key_87_pad_type_0, strides = key_87_strides_0, weight = layers_21_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_87_cast_fp16")]; + tensor value_87_pad_type_0 = const()[name = tensor("value_87_pad_type_0"), val = tensor("valid")]; + tensor value_87_strides_0 = const()[name = tensor("value_87_strides_0"), val = tensor([1, 1])]; + tensor value_87_pad_0 = const()[name = tensor("value_87_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_87_dilations_0 = const()[name = tensor("value_87_dilations_0"), val = tensor([1, 1])]; + tensor value_87_groups_0 = const()[name = tensor("value_87_groups_0"), val = tensor(1)]; + tensor layers_21_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_21_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(825148096)))]; + tensor layers_21_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_21_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(827245312)))]; + tensor value_87_cast_fp16 = conv(bias = layers_21_encoder_attn_v_proj_bias_to_fp16, dilations = value_87_dilations_0, groups = value_87_groups_0, pad = value_87_pad_0, pad_type = value_87_pad_type_0, strides = value_87_strides_0, weight = layers_21_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_87_cast_fp16")]; + tensor var_4910 = const()[name = tensor("op_4910"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_87_cast_fp16 = reshape(shape = var_4910, x = query_87_cast_fp16)[name = tensor("mh_q_87_cast_fp16")]; + tensor var_4912_to_fp16 = const()[name = tensor("op_4912_to_fp16"), val = tensor(0x1p-3)]; + tensor var_4913_cast_fp16 = mul(x = mh_q_87_cast_fp16, y = var_4912_to_fp16)[name = tensor("op_4913_cast_fp16")]; + tensor var_4916 = const()[name = tensor("op_4916"), val = tensor([1, 16, 64, 1500])]; + tensor var_4917_cast_fp16 = reshape(shape = var_4916, x = key_87_cast_fp16)[name = tensor("op_4917_cast_fp16")]; + tensor mh_w_131_transpose_x_0 = const()[name = tensor("mh_w_131_transpose_x_0"), val = tensor(true)]; + tensor mh_w_131_transpose_y_0 = const()[name = tensor("mh_w_131_transpose_y_0"), val = tensor(false)]; + tensor mh_w_131_cast_fp16 = matmul(transpose_x = mh_w_131_transpose_x_0, transpose_y = mh_w_131_transpose_y_0, x = var_4913_cast_fp16, y = var_4917_cast_fp16)[name = tensor("mh_w_131_cast_fp16")]; + tensor obj_307_cast_fp16 = softmax(axis = var_4759, x = mh_w_131_cast_fp16)[name = tensor("obj_307_cast_fp16")]; + tensor var_4921 = const()[name = tensor("op_4921"), val = tensor([1, 16, 64, 1500])]; + tensor var_4922_cast_fp16 = reshape(shape = var_4921, x = value_87_cast_fp16)[name = tensor("op_4922_cast_fp16")]; + tensor attn_87_transpose_x_0 = const()[name = tensor("attn_87_transpose_x_0"), val = tensor(false)]; + tensor attn_87_transpose_y_0 = const()[name = tensor("attn_87_transpose_y_0"), val = tensor(true)]; + tensor attn_87_cast_fp16 = matmul(transpose_x = attn_87_transpose_x_0, transpose_y = attn_87_transpose_y_0, x = var_4922_cast_fp16, y = obj_307_cast_fp16)[name = tensor("attn_87_cast_fp16")]; + tensor var_4925 = const()[name = tensor("op_4925"), val = tensor([1, 1024, 1, 1])]; + tensor input_213_cast_fp16 = reshape(shape = var_4925, x = attn_87_cast_fp16)[name = tensor("input_213_cast_fp16")]; + tensor obj_305_pad_type_0 = const()[name = tensor("obj_305_pad_type_0"), val = tensor("valid")]; + tensor obj_305_strides_0 = const()[name = tensor("obj_305_strides_0"), val = tensor([1, 1])]; + tensor obj_305_pad_0 = const()[name = tensor("obj_305_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_305_dilations_0 = const()[name = tensor("obj_305_dilations_0"), val = tensor([1, 1])]; + tensor obj_305_groups_0 = const()[name = tensor("obj_305_groups_0"), val = tensor(1)]; + tensor layers_21_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_21_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(827247424)))]; + tensor layers_21_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_21_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(829344640)))]; + tensor obj_305_cast_fp16 = conv(bias = layers_21_encoder_attn_o_proj_bias_to_fp16, dilations = obj_305_dilations_0, groups = obj_305_groups_0, pad = obj_305_pad_0, pad_type = obj_305_pad_type_0, strides = obj_305_strides_0, weight = layers_21_encoder_attn_o_proj_weight_to_fp16, x = input_213_cast_fp16)[name = tensor("obj_305_cast_fp16")]; + tensor inputs_131_cast_fp16 = add(x = inputs_129_cast_fp16, y = obj_305_cast_fp16)[name = tensor("inputs_131_cast_fp16")]; + tensor out_131_axes_0 = const()[name = tensor("out_131_axes_0"), val = tensor([1])]; + tensor var_4943_to_fp16 = const()[name = tensor("op_4943_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_131_cast_fp16 = layer_norm(axes = out_131_axes_0, epsilon = var_4943_to_fp16, x = inputs_131_cast_fp16)[name = tensor("out_131_cast_fp16")]; + tensor input_215_gamma_0_to_fp16 = const()[name = tensor("input_215_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(829346752)))]; + tensor input_215_beta_0_to_fp16 = const()[name = tensor("input_215_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(829348864)))]; + tensor input_215_epsilon_0_to_fp16 = const()[name = tensor("input_215_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_215_cast_fp16 = batch_norm(beta = input_215_beta_0_to_fp16, epsilon = input_215_epsilon_0_to_fp16, gamma = input_215_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_131_cast_fp16)[name = tensor("input_215_cast_fp16")]; + tensor input_217_pad_type_0 = const()[name = tensor("input_217_pad_type_0"), val = tensor("valid")]; + tensor input_217_strides_0 = const()[name = tensor("input_217_strides_0"), val = tensor([1, 1])]; + tensor input_217_pad_0 = const()[name = tensor("input_217_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_217_dilations_0 = const()[name = tensor("input_217_dilations_0"), val = tensor([1, 1])]; + tensor input_217_groups_0 = const()[name = tensor("input_217_groups_0"), val = tensor(1)]; + tensor layers_21_fc1_weight_to_fp16 = const()[name = tensor("layers_21_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(829350976)))]; + tensor layers_21_fc1_bias_to_fp16 = const()[name = tensor("layers_21_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(837739648)))]; + tensor input_217_cast_fp16 = conv(bias = layers_21_fc1_bias_to_fp16, dilations = input_217_dilations_0, groups = input_217_groups_0, pad = input_217_pad_0, pad_type = input_217_pad_type_0, strides = input_217_strides_0, weight = layers_21_fc1_weight_to_fp16, x = input_215_cast_fp16)[name = tensor("input_217_cast_fp16")]; + tensor input_219_mode_0 = const()[name = tensor("input_219_mode_0"), val = tensor("EXACT")]; + tensor input_219_cast_fp16 = gelu(mode = input_219_mode_0, x = input_217_cast_fp16)[name = tensor("input_219_cast_fp16")]; + tensor hidden_states_45_pad_type_0 = const()[name = tensor("hidden_states_45_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_45_strides_0 = const()[name = tensor("hidden_states_45_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_45_pad_0 = const()[name = tensor("hidden_states_45_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_45_dilations_0 = const()[name = tensor("hidden_states_45_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_45_groups_0 = const()[name = tensor("hidden_states_45_groups_0"), val = tensor(1)]; + tensor layers_21_fc2_weight_to_fp16 = const()[name = tensor("layers_21_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(837747904)))]; + tensor layers_21_fc2_bias_to_fp16 = const()[name = tensor("layers_21_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(846136576)))]; + tensor hidden_states_45_cast_fp16 = conv(bias = layers_21_fc2_bias_to_fp16, dilations = hidden_states_45_dilations_0, groups = hidden_states_45_groups_0, pad = hidden_states_45_pad_0, pad_type = hidden_states_45_pad_type_0, strides = hidden_states_45_strides_0, weight = layers_21_fc2_weight_to_fp16, x = input_219_cast_fp16)[name = tensor("hidden_states_45_cast_fp16")]; + tensor inputs_133_cast_fp16 = add(x = inputs_131_cast_fp16, y = hidden_states_45_cast_fp16)[name = tensor("inputs_133_cast_fp16")]; + tensor var_4978 = const()[name = tensor("op_4978"), val = tensor(3)]; + tensor out_133_axes_0 = const()[name = tensor("out_133_axes_0"), val = tensor([1])]; + tensor var_5003_to_fp16 = const()[name = tensor("op_5003_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_133_cast_fp16 = layer_norm(axes = out_133_axes_0, epsilon = var_5003_to_fp16, x = inputs_133_cast_fp16)[name = tensor("out_133_cast_fp16")]; + tensor obj_309_gamma_0_to_fp16 = const()[name = tensor("obj_309_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(846138688)))]; + tensor obj_309_beta_0_to_fp16 = const()[name = tensor("obj_309_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(846140800)))]; + tensor obj_309_epsilon_0_to_fp16 = const()[name = tensor("obj_309_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_309_cast_fp16 = batch_norm(beta = obj_309_beta_0_to_fp16, epsilon = obj_309_epsilon_0_to_fp16, gamma = obj_309_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_133_cast_fp16)[name = tensor("obj_309_cast_fp16")]; + tensor query_89_pad_type_0 = const()[name = tensor("query_89_pad_type_0"), val = tensor("valid")]; + tensor query_89_strides_0 = const()[name = tensor("query_89_strides_0"), val = tensor([1, 1])]; + tensor query_89_pad_0 = const()[name = tensor("query_89_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_89_dilations_0 = const()[name = tensor("query_89_dilations_0"), val = tensor([1, 1])]; + tensor query_89_groups_0 = const()[name = tensor("query_89_groups_0"), val = tensor(1)]; + tensor layers_22_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_22_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(846142912)))]; + tensor layers_22_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_22_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(848240128)))]; + tensor query_89_cast_fp16 = conv(bias = layers_22_self_attn_q_proj_bias_to_fp16, dilations = query_89_dilations_0, groups = query_89_groups_0, pad = query_89_pad_0, pad_type = query_89_pad_type_0, strides = query_89_strides_0, weight = layers_22_self_attn_q_proj_weight_to_fp16, x = obj_309_cast_fp16)[name = tensor("query_89_cast_fp16")]; + tensor current_key_45_pad_type_0 = const()[name = tensor("current_key_45_pad_type_0"), val = tensor("valid")]; + tensor current_key_45_strides_0 = const()[name = tensor("current_key_45_strides_0"), val = tensor([1, 1])]; + tensor current_key_45_pad_0 = const()[name = tensor("current_key_45_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_45_dilations_0 = const()[name = tensor("current_key_45_dilations_0"), val = tensor([1, 1])]; + tensor current_key_45_groups_0 = const()[name = tensor("current_key_45_groups_0"), val = tensor(1)]; + tensor layers_22_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_22_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(848242240)))]; + tensor current_key_45_cast_fp16 = conv(dilations = current_key_45_dilations_0, groups = current_key_45_groups_0, pad = current_key_45_pad_0, pad_type = current_key_45_pad_type_0, strides = current_key_45_strides_0, weight = layers_22_self_attn_k_proj_weight_to_fp16, x = obj_309_cast_fp16)[name = tensor("current_key_45_cast_fp16")]; + tensor current_value_45_pad_type_0 = const()[name = tensor("current_value_45_pad_type_0"), val = tensor("valid")]; + tensor current_value_45_strides_0 = const()[name = tensor("current_value_45_strides_0"), val = tensor([1, 1])]; + tensor current_value_45_pad_0 = const()[name = tensor("current_value_45_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_45_dilations_0 = const()[name = tensor("current_value_45_dilations_0"), val = tensor([1, 1])]; + tensor current_value_45_groups_0 = const()[name = tensor("current_value_45_groups_0"), val = tensor(1)]; + tensor layers_22_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_22_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(850339456)))]; + tensor layers_22_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_22_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(852436672)))]; + tensor current_value_45_cast_fp16 = conv(bias = layers_22_self_attn_v_proj_bias_to_fp16, dilations = current_value_45_dilations_0, groups = current_value_45_groups_0, pad = current_value_45_pad_0, pad_type = current_value_45_pad_type_0, strides = current_value_45_strides_0, weight = layers_22_self_attn_v_proj_weight_to_fp16, x = obj_309_cast_fp16)[name = tensor("current_value_45_cast_fp16")]; + tensor var_5042_cast_fp16 = mul(x = var_87_cast_fp16_22, y = var_207_cast_fp16)[name = tensor("op_5042_cast_fp16")]; + tensor var_5043_cast_fp16 = mul(x = current_key_45_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_5043_cast_fp16")]; + tensor key_89_cast_fp16 = add(x = var_5042_cast_fp16, y = var_5043_cast_fp16)[name = tensor("key_89_cast_fp16")]; + tensor var_5046_cast_fp16 = mul(x = var_114_cast_fp16_22, y = var_207_cast_fp16)[name = tensor("op_5046_cast_fp16")]; + tensor var_5047_cast_fp16 = mul(x = current_value_45_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_5047_cast_fp16")]; + tensor value_89_cast_fp16 = add(x = var_5046_cast_fp16, y = var_5047_cast_fp16)[name = tensor("value_89_cast_fp16")]; + tensor var_5051 = const()[name = tensor("op_5051"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_89_cast_fp16 = reshape(shape = var_5051, x = query_89_cast_fp16)[name = tensor("mh_q_89_cast_fp16")]; + tensor var_5053_to_fp16 = const()[name = tensor("op_5053_to_fp16"), val = tensor(0x1p-3)]; + tensor var_5054_cast_fp16 = mul(x = mh_q_89_cast_fp16, y = var_5053_to_fp16)[name = tensor("op_5054_cast_fp16")]; + tensor var_5057 = const()[name = tensor("op_5057"), val = tensor([1, 16, 64, 448])]; + tensor var_5058_cast_fp16 = reshape(shape = var_5057, x = key_89_cast_fp16)[name = tensor("op_5058_cast_fp16")]; + tensor mh_w_133_transpose_x_0 = const()[name = tensor("mh_w_133_transpose_x_0"), val = tensor(true)]; + tensor mh_w_133_transpose_y_0 = const()[name = tensor("mh_w_133_transpose_y_0"), val = tensor(false)]; + tensor mh_w_133_cast_fp16 = matmul(transpose_x = mh_w_133_transpose_x_0, transpose_y = mh_w_133_transpose_y_0, x = var_5054_cast_fp16, y = var_5058_cast_fp16)[name = tensor("mh_w_133_cast_fp16")]; + tensor mh_w_135_cast_fp16 = add(x = mh_w_133_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_135_cast_fp16")]; + tensor var_5066_cast_fp16 = softmax(axis = var_4978, x = mh_w_135_cast_fp16)[name = tensor("op_5066_cast_fp16")]; + tensor var_5067 = const()[name = tensor("op_5067"), val = tensor([1, 16, 64, 448])]; + tensor var_5068_cast_fp16 = reshape(shape = var_5067, x = value_89_cast_fp16)[name = tensor("op_5068_cast_fp16")]; + tensor attn_89_transpose_x_0 = const()[name = tensor("attn_89_transpose_x_0"), val = tensor(false)]; + tensor attn_89_transpose_y_0 = const()[name = tensor("attn_89_transpose_y_0"), val = tensor(true)]; + tensor attn_89_cast_fp16 = matmul(transpose_x = attn_89_transpose_x_0, transpose_y = attn_89_transpose_y_0, x = var_5068_cast_fp16, y = var_5066_cast_fp16)[name = tensor("attn_89_cast_fp16")]; + tensor var_5071 = const()[name = tensor("op_5071"), val = tensor([1, 1024, 1, 1])]; + tensor input_221_cast_fp16 = reshape(shape = var_5071, x = attn_89_cast_fp16)[name = tensor("input_221_cast_fp16")]; + tensor obj_315_pad_type_0 = const()[name = tensor("obj_315_pad_type_0"), val = tensor("valid")]; + tensor obj_315_strides_0 = const()[name = tensor("obj_315_strides_0"), val = tensor([1, 1])]; + tensor obj_315_pad_0 = const()[name = tensor("obj_315_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_315_dilations_0 = const()[name = tensor("obj_315_dilations_0"), val = tensor([1, 1])]; + tensor obj_315_groups_0 = const()[name = tensor("obj_315_groups_0"), val = tensor(1)]; + tensor layers_22_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_22_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(852438784)))]; + tensor layers_22_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_22_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(854536000)))]; + tensor obj_315_cast_fp16 = conv(bias = layers_22_self_attn_o_proj_bias_to_fp16, dilations = obj_315_dilations_0, groups = obj_315_groups_0, pad = obj_315_pad_0, pad_type = obj_315_pad_type_0, strides = obj_315_strides_0, weight = layers_22_self_attn_o_proj_weight_to_fp16, x = input_221_cast_fp16)[name = tensor("obj_315_cast_fp16")]; + tensor inputs_135_cast_fp16 = add(x = inputs_133_cast_fp16, y = obj_315_cast_fp16)[name = tensor("inputs_135_cast_fp16")]; + tensor out_135_axes_0 = const()[name = tensor("out_135_axes_0"), val = tensor([1])]; + tensor var_5093_to_fp16 = const()[name = tensor("op_5093_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_135_cast_fp16 = layer_norm(axes = out_135_axes_0, epsilon = var_5093_to_fp16, x = inputs_135_cast_fp16)[name = tensor("out_135_cast_fp16")]; + tensor obj_317_gamma_0_to_fp16 = const()[name = tensor("obj_317_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(854538112)))]; + tensor obj_317_beta_0_to_fp16 = const()[name = tensor("obj_317_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(854540224)))]; + tensor obj_317_epsilon_0_to_fp16 = const()[name = tensor("obj_317_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_317_cast_fp16 = batch_norm(beta = obj_317_beta_0_to_fp16, epsilon = obj_317_epsilon_0_to_fp16, gamma = obj_317_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_135_cast_fp16)[name = tensor("obj_317_cast_fp16")]; + tensor query_91_pad_type_0 = const()[name = tensor("query_91_pad_type_0"), val = tensor("valid")]; + tensor query_91_strides_0 = const()[name = tensor("query_91_strides_0"), val = tensor([1, 1])]; + tensor query_91_pad_0 = const()[name = tensor("query_91_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_91_dilations_0 = const()[name = tensor("query_91_dilations_0"), val = tensor([1, 1])]; + tensor query_91_groups_0 = const()[name = tensor("query_91_groups_0"), val = tensor(1)]; + tensor layers_22_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_22_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(854542336)))]; + tensor layers_22_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_22_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(856639552)))]; + tensor query_91_cast_fp16 = conv(bias = layers_22_encoder_attn_q_proj_bias_to_fp16, dilations = query_91_dilations_0, groups = query_91_groups_0, pad = query_91_pad_0, pad_type = query_91_pad_type_0, strides = query_91_strides_0, weight = layers_22_encoder_attn_q_proj_weight_to_fp16, x = obj_317_cast_fp16)[name = tensor("query_91_cast_fp16")]; + tensor key_91_pad_type_0 = const()[name = tensor("key_91_pad_type_0"), val = tensor("valid")]; + tensor key_91_strides_0 = const()[name = tensor("key_91_strides_0"), val = tensor([1, 1])]; + tensor key_91_pad_0 = const()[name = tensor("key_91_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_91_dilations_0 = const()[name = tensor("key_91_dilations_0"), val = tensor([1, 1])]; + tensor key_91_groups_0 = const()[name = tensor("key_91_groups_0"), val = tensor(1)]; + tensor layers_22_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_22_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(856641664)))]; + tensor key_91_cast_fp16 = conv(dilations = key_91_dilations_0, groups = key_91_groups_0, pad = key_91_pad_0, pad_type = key_91_pad_type_0, strides = key_91_strides_0, weight = layers_22_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_91_cast_fp16")]; + tensor value_91_pad_type_0 = const()[name = tensor("value_91_pad_type_0"), val = tensor("valid")]; + tensor value_91_strides_0 = const()[name = tensor("value_91_strides_0"), val = tensor([1, 1])]; + tensor value_91_pad_0 = const()[name = tensor("value_91_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_91_dilations_0 = const()[name = tensor("value_91_dilations_0"), val = tensor([1, 1])]; + tensor value_91_groups_0 = const()[name = tensor("value_91_groups_0"), val = tensor(1)]; + tensor layers_22_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_22_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(858738880)))]; + tensor layers_22_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_22_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(860836096)))]; + tensor value_91_cast_fp16 = conv(bias = layers_22_encoder_attn_v_proj_bias_to_fp16, dilations = value_91_dilations_0, groups = value_91_groups_0, pad = value_91_pad_0, pad_type = value_91_pad_type_0, strides = value_91_strides_0, weight = layers_22_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_91_cast_fp16")]; + tensor var_5129 = const()[name = tensor("op_5129"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_91_cast_fp16 = reshape(shape = var_5129, x = query_91_cast_fp16)[name = tensor("mh_q_91_cast_fp16")]; + tensor var_5131_to_fp16 = const()[name = tensor("op_5131_to_fp16"), val = tensor(0x1p-3)]; + tensor var_5132_cast_fp16 = mul(x = mh_q_91_cast_fp16, y = var_5131_to_fp16)[name = tensor("op_5132_cast_fp16")]; + tensor var_5135 = const()[name = tensor("op_5135"), val = tensor([1, 16, 64, 1500])]; + tensor var_5136_cast_fp16 = reshape(shape = var_5135, x = key_91_cast_fp16)[name = tensor("op_5136_cast_fp16")]; + tensor mh_w_137_transpose_x_0 = const()[name = tensor("mh_w_137_transpose_x_0"), val = tensor(true)]; + tensor mh_w_137_transpose_y_0 = const()[name = tensor("mh_w_137_transpose_y_0"), val = tensor(false)]; + tensor mh_w_137_cast_fp16 = matmul(transpose_x = mh_w_137_transpose_x_0, transpose_y = mh_w_137_transpose_y_0, x = var_5132_cast_fp16, y = var_5136_cast_fp16)[name = tensor("mh_w_137_cast_fp16")]; + tensor obj_321_cast_fp16 = softmax(axis = var_4978, x = mh_w_137_cast_fp16)[name = tensor("obj_321_cast_fp16")]; + tensor var_5140 = const()[name = tensor("op_5140"), val = tensor([1, 16, 64, 1500])]; + tensor var_5141_cast_fp16 = reshape(shape = var_5140, x = value_91_cast_fp16)[name = tensor("op_5141_cast_fp16")]; + tensor attn_91_transpose_x_0 = const()[name = tensor("attn_91_transpose_x_0"), val = tensor(false)]; + tensor attn_91_transpose_y_0 = const()[name = tensor("attn_91_transpose_y_0"), val = tensor(true)]; + tensor attn_91_cast_fp16 = matmul(transpose_x = attn_91_transpose_x_0, transpose_y = attn_91_transpose_y_0, x = var_5141_cast_fp16, y = obj_321_cast_fp16)[name = tensor("attn_91_cast_fp16")]; + tensor var_5144 = const()[name = tensor("op_5144"), val = tensor([1, 1024, 1, 1])]; + tensor input_223_cast_fp16 = reshape(shape = var_5144, x = attn_91_cast_fp16)[name = tensor("input_223_cast_fp16")]; + tensor obj_319_pad_type_0 = const()[name = tensor("obj_319_pad_type_0"), val = tensor("valid")]; + tensor obj_319_strides_0 = const()[name = tensor("obj_319_strides_0"), val = tensor([1, 1])]; + tensor obj_319_pad_0 = const()[name = tensor("obj_319_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_319_dilations_0 = const()[name = tensor("obj_319_dilations_0"), val = tensor([1, 1])]; + tensor obj_319_groups_0 = const()[name = tensor("obj_319_groups_0"), val = tensor(1)]; + tensor layers_22_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_22_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(860838208)))]; + tensor layers_22_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_22_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(862935424)))]; + tensor obj_319_cast_fp16 = conv(bias = layers_22_encoder_attn_o_proj_bias_to_fp16, dilations = obj_319_dilations_0, groups = obj_319_groups_0, pad = obj_319_pad_0, pad_type = obj_319_pad_type_0, strides = obj_319_strides_0, weight = layers_22_encoder_attn_o_proj_weight_to_fp16, x = input_223_cast_fp16)[name = tensor("obj_319_cast_fp16")]; + tensor inputs_137_cast_fp16 = add(x = inputs_135_cast_fp16, y = obj_319_cast_fp16)[name = tensor("inputs_137_cast_fp16")]; + tensor out_137_axes_0 = const()[name = tensor("out_137_axes_0"), val = tensor([1])]; + tensor var_5162_to_fp16 = const()[name = tensor("op_5162_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_137_cast_fp16 = layer_norm(axes = out_137_axes_0, epsilon = var_5162_to_fp16, x = inputs_137_cast_fp16)[name = tensor("out_137_cast_fp16")]; + tensor input_225_gamma_0_to_fp16 = const()[name = tensor("input_225_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(862937536)))]; + tensor input_225_beta_0_to_fp16 = const()[name = tensor("input_225_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(862939648)))]; + tensor input_225_epsilon_0_to_fp16 = const()[name = tensor("input_225_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_225_cast_fp16 = batch_norm(beta = input_225_beta_0_to_fp16, epsilon = input_225_epsilon_0_to_fp16, gamma = input_225_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_137_cast_fp16)[name = tensor("input_225_cast_fp16")]; + tensor input_227_pad_type_0 = const()[name = tensor("input_227_pad_type_0"), val = tensor("valid")]; + tensor input_227_strides_0 = const()[name = tensor("input_227_strides_0"), val = tensor([1, 1])]; + tensor input_227_pad_0 = const()[name = tensor("input_227_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_227_dilations_0 = const()[name = tensor("input_227_dilations_0"), val = tensor([1, 1])]; + tensor input_227_groups_0 = const()[name = tensor("input_227_groups_0"), val = tensor(1)]; + tensor layers_22_fc1_weight_to_fp16 = const()[name = tensor("layers_22_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(862941760)))]; + tensor layers_22_fc1_bias_to_fp16 = const()[name = tensor("layers_22_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(871330432)))]; + tensor input_227_cast_fp16 = conv(bias = layers_22_fc1_bias_to_fp16, dilations = input_227_dilations_0, groups = input_227_groups_0, pad = input_227_pad_0, pad_type = input_227_pad_type_0, strides = input_227_strides_0, weight = layers_22_fc1_weight_to_fp16, x = input_225_cast_fp16)[name = tensor("input_227_cast_fp16")]; + tensor input_229_mode_0 = const()[name = tensor("input_229_mode_0"), val = tensor("EXACT")]; + tensor input_229_cast_fp16 = gelu(mode = input_229_mode_0, x = input_227_cast_fp16)[name = tensor("input_229_cast_fp16")]; + tensor hidden_states_47_pad_type_0 = const()[name = tensor("hidden_states_47_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_47_strides_0 = const()[name = tensor("hidden_states_47_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_47_pad_0 = const()[name = tensor("hidden_states_47_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_47_dilations_0 = const()[name = tensor("hidden_states_47_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_47_groups_0 = const()[name = tensor("hidden_states_47_groups_0"), val = tensor(1)]; + tensor layers_22_fc2_weight_to_fp16 = const()[name = tensor("layers_22_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(871338688)))]; + tensor layers_22_fc2_bias_to_fp16 = const()[name = tensor("layers_22_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(879727360)))]; + tensor hidden_states_47_cast_fp16 = conv(bias = layers_22_fc2_bias_to_fp16, dilations = hidden_states_47_dilations_0, groups = hidden_states_47_groups_0, pad = hidden_states_47_pad_0, pad_type = hidden_states_47_pad_type_0, strides = hidden_states_47_strides_0, weight = layers_22_fc2_weight_to_fp16, x = input_229_cast_fp16)[name = tensor("hidden_states_47_cast_fp16")]; + tensor inputs_139_cast_fp16 = add(x = inputs_137_cast_fp16, y = hidden_states_47_cast_fp16)[name = tensor("inputs_139_cast_fp16")]; + tensor var_5197 = const()[name = tensor("op_5197"), val = tensor(3)]; + tensor out_139_axes_0 = const()[name = tensor("out_139_axes_0"), val = tensor([1])]; + tensor var_5222_to_fp16 = const()[name = tensor("op_5222_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_139_cast_fp16 = layer_norm(axes = out_139_axes_0, epsilon = var_5222_to_fp16, x = inputs_139_cast_fp16)[name = tensor("out_139_cast_fp16")]; + tensor obj_323_gamma_0_to_fp16 = const()[name = tensor("obj_323_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(879729472)))]; + tensor obj_323_beta_0_to_fp16 = const()[name = tensor("obj_323_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(879731584)))]; + tensor obj_323_epsilon_0_to_fp16 = const()[name = tensor("obj_323_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_323_cast_fp16 = batch_norm(beta = obj_323_beta_0_to_fp16, epsilon = obj_323_epsilon_0_to_fp16, gamma = obj_323_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_139_cast_fp16)[name = tensor("obj_323_cast_fp16")]; + tensor query_93_pad_type_0 = const()[name = tensor("query_93_pad_type_0"), val = tensor("valid")]; + tensor query_93_strides_0 = const()[name = tensor("query_93_strides_0"), val = tensor([1, 1])]; + tensor query_93_pad_0 = const()[name = tensor("query_93_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_93_dilations_0 = const()[name = tensor("query_93_dilations_0"), val = tensor([1, 1])]; + tensor query_93_groups_0 = const()[name = tensor("query_93_groups_0"), val = tensor(1)]; + tensor layers_23_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_23_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(879733696)))]; + tensor layers_23_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_23_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(881830912)))]; + tensor query_93_cast_fp16 = conv(bias = layers_23_self_attn_q_proj_bias_to_fp16, dilations = query_93_dilations_0, groups = query_93_groups_0, pad = query_93_pad_0, pad_type = query_93_pad_type_0, strides = query_93_strides_0, weight = layers_23_self_attn_q_proj_weight_to_fp16, x = obj_323_cast_fp16)[name = tensor("query_93_cast_fp16")]; + tensor current_key_pad_type_0 = const()[name = tensor("current_key_pad_type_0"), val = tensor("valid")]; + tensor current_key_strides_0 = const()[name = tensor("current_key_strides_0"), val = tensor([1, 1])]; + tensor current_key_pad_0 = const()[name = tensor("current_key_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_key_dilations_0 = const()[name = tensor("current_key_dilations_0"), val = tensor([1, 1])]; + tensor current_key_groups_0 = const()[name = tensor("current_key_groups_0"), val = tensor(1)]; + tensor layers_23_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_23_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(881833024)))]; + tensor current_key_cast_fp16 = conv(dilations = current_key_dilations_0, groups = current_key_groups_0, pad = current_key_pad_0, pad_type = current_key_pad_type_0, strides = current_key_strides_0, weight = layers_23_self_attn_k_proj_weight_to_fp16, x = obj_323_cast_fp16)[name = tensor("current_key_cast_fp16")]; + tensor current_value_pad_type_0 = const()[name = tensor("current_value_pad_type_0"), val = tensor("valid")]; + tensor current_value_strides_0 = const()[name = tensor("current_value_strides_0"), val = tensor([1, 1])]; + tensor current_value_pad_0 = const()[name = tensor("current_value_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor current_value_dilations_0 = const()[name = tensor("current_value_dilations_0"), val = tensor([1, 1])]; + tensor current_value_groups_0 = const()[name = tensor("current_value_groups_0"), val = tensor(1)]; + tensor layers_23_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_23_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(883930240)))]; + tensor layers_23_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_23_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(886027456)))]; + tensor current_value_cast_fp16 = conv(bias = layers_23_self_attn_v_proj_bias_to_fp16, dilations = current_value_dilations_0, groups = current_value_groups_0, pad = current_value_pad_0, pad_type = current_value_pad_type_0, strides = current_value_strides_0, weight = layers_23_self_attn_v_proj_weight_to_fp16, x = obj_323_cast_fp16)[name = tensor("current_value_cast_fp16")]; + tensor var_5261_cast_fp16 = mul(x = var_87_cast_fp16_23, y = var_207_cast_fp16)[name = tensor("op_5261_cast_fp16")]; + tensor var_5262_cast_fp16 = mul(x = current_key_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_5262_cast_fp16")]; + tensor key_93_cast_fp16 = add(x = var_5261_cast_fp16, y = var_5262_cast_fp16)[name = tensor("key_93_cast_fp16")]; + tensor var_5265_cast_fp16 = mul(x = var_114_cast_fp16_23, y = var_207_cast_fp16)[name = tensor("op_5265_cast_fp16")]; + tensor var_5266_cast_fp16 = mul(x = current_value_cast_fp16, y = var_205_cast_fp16)[name = tensor("op_5266_cast_fp16")]; + tensor value_93_cast_fp16 = add(x = var_5265_cast_fp16, y = var_5266_cast_fp16)[name = tensor("value_93_cast_fp16")]; + tensor var_5270 = const()[name = tensor("op_5270"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_93_cast_fp16 = reshape(shape = var_5270, x = query_93_cast_fp16)[name = tensor("mh_q_93_cast_fp16")]; + tensor var_5272_to_fp16 = const()[name = tensor("op_5272_to_fp16"), val = tensor(0x1p-3)]; + tensor var_5273_cast_fp16 = mul(x = mh_q_93_cast_fp16, y = var_5272_to_fp16)[name = tensor("op_5273_cast_fp16")]; + tensor var_5276 = const()[name = tensor("op_5276"), val = tensor([1, 16, 64, 448])]; + tensor var_5277_cast_fp16 = reshape(shape = var_5276, x = key_93_cast_fp16)[name = tensor("op_5277_cast_fp16")]; + tensor mh_w_139_transpose_x_0 = const()[name = tensor("mh_w_139_transpose_x_0"), val = tensor(true)]; + tensor mh_w_139_transpose_y_0 = const()[name = tensor("mh_w_139_transpose_y_0"), val = tensor(false)]; + tensor mh_w_139_cast_fp16 = matmul(transpose_x = mh_w_139_transpose_x_0, transpose_y = mh_w_139_transpose_y_0, x = var_5273_cast_fp16, y = var_5277_cast_fp16)[name = tensor("mh_w_139_cast_fp16")]; + tensor mh_w_141_cast_fp16 = add(x = mh_w_139_cast_fp16, y = var_229_cast_fp16)[name = tensor("mh_w_141_cast_fp16")]; + tensor var_5285_cast_fp16 = softmax(axis = var_5197, x = mh_w_141_cast_fp16)[name = tensor("op_5285_cast_fp16")]; + tensor var_5286 = const()[name = tensor("op_5286"), val = tensor([1, 16, 64, 448])]; + tensor var_5287_cast_fp16 = reshape(shape = var_5286, x = value_93_cast_fp16)[name = tensor("op_5287_cast_fp16")]; + tensor attn_93_transpose_x_0 = const()[name = tensor("attn_93_transpose_x_0"), val = tensor(false)]; + tensor attn_93_transpose_y_0 = const()[name = tensor("attn_93_transpose_y_0"), val = tensor(true)]; + tensor attn_93_cast_fp16 = matmul(transpose_x = attn_93_transpose_x_0, transpose_y = attn_93_transpose_y_0, x = var_5287_cast_fp16, y = var_5285_cast_fp16)[name = tensor("attn_93_cast_fp16")]; + tensor var_5290 = const()[name = tensor("op_5290"), val = tensor([1, 1024, 1, 1])]; + tensor input_231_cast_fp16 = reshape(shape = var_5290, x = attn_93_cast_fp16)[name = tensor("input_231_cast_fp16")]; + tensor obj_329_pad_type_0 = const()[name = tensor("obj_329_pad_type_0"), val = tensor("valid")]; + tensor obj_329_strides_0 = const()[name = tensor("obj_329_strides_0"), val = tensor([1, 1])]; + tensor obj_329_pad_0 = const()[name = tensor("obj_329_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_329_dilations_0 = const()[name = tensor("obj_329_dilations_0"), val = tensor([1, 1])]; + tensor obj_329_groups_0 = const()[name = tensor("obj_329_groups_0"), val = tensor(1)]; + tensor layers_23_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_23_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(886029568)))]; + tensor layers_23_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_23_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(888126784)))]; + tensor obj_329_cast_fp16 = conv(bias = layers_23_self_attn_o_proj_bias_to_fp16, dilations = obj_329_dilations_0, groups = obj_329_groups_0, pad = obj_329_pad_0, pad_type = obj_329_pad_type_0, strides = obj_329_strides_0, weight = layers_23_self_attn_o_proj_weight_to_fp16, x = input_231_cast_fp16)[name = tensor("obj_329_cast_fp16")]; + tensor inputs_141_cast_fp16 = add(x = inputs_139_cast_fp16, y = obj_329_cast_fp16)[name = tensor("inputs_141_cast_fp16")]; + tensor out_141_axes_0 = const()[name = tensor("out_141_axes_0"), val = tensor([1])]; + tensor var_5312_to_fp16 = const()[name = tensor("op_5312_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_141_cast_fp16 = layer_norm(axes = out_141_axes_0, epsilon = var_5312_to_fp16, x = inputs_141_cast_fp16)[name = tensor("out_141_cast_fp16")]; + tensor obj_331_gamma_0_to_fp16 = const()[name = tensor("obj_331_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(888128896)))]; + tensor obj_331_beta_0_to_fp16 = const()[name = tensor("obj_331_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(888131008)))]; + tensor obj_331_epsilon_0_to_fp16 = const()[name = tensor("obj_331_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_331_cast_fp16 = batch_norm(beta = obj_331_beta_0_to_fp16, epsilon = obj_331_epsilon_0_to_fp16, gamma = obj_331_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_141_cast_fp16)[name = tensor("obj_331_cast_fp16")]; + tensor query_pad_type_0 = const()[name = tensor("query_pad_type_0"), val = tensor("valid")]; + tensor query_strides_0 = const()[name = tensor("query_strides_0"), val = tensor([1, 1])]; + tensor query_pad_0 = const()[name = tensor("query_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor query_dilations_0 = const()[name = tensor("query_dilations_0"), val = tensor([1, 1])]; + tensor query_groups_0 = const()[name = tensor("query_groups_0"), val = tensor(1)]; + tensor layers_23_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_23_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(888133120)))]; + tensor layers_23_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_23_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(890230336)))]; + tensor query_cast_fp16 = conv(bias = layers_23_encoder_attn_q_proj_bias_to_fp16, dilations = query_dilations_0, groups = query_groups_0, pad = query_pad_0, pad_type = query_pad_type_0, strides = query_strides_0, weight = layers_23_encoder_attn_q_proj_weight_to_fp16, x = obj_331_cast_fp16)[name = tensor("query_cast_fp16")]; + tensor key_pad_type_0 = const()[name = tensor("key_pad_type_0"), val = tensor("valid")]; + tensor key_strides_0 = const()[name = tensor("key_strides_0"), val = tensor([1, 1])]; + tensor key_pad_0 = const()[name = tensor("key_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor key_dilations_0 = const()[name = tensor("key_dilations_0"), val = tensor([1, 1])]; + tensor key_groups_0 = const()[name = tensor("key_groups_0"), val = tensor(1)]; + tensor layers_23_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_23_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(890232448)))]; + tensor key_cast_fp16 = conv(dilations = key_dilations_0, groups = key_groups_0, pad = key_pad_0, pad_type = key_pad_type_0, strides = key_strides_0, weight = layers_23_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_cast_fp16")]; + tensor value_pad_type_0 = const()[name = tensor("value_pad_type_0"), val = tensor("valid")]; + tensor value_strides_0 = const()[name = tensor("value_strides_0"), val = tensor([1, 1])]; + tensor value_pad_0 = const()[name = tensor("value_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor value_dilations_0 = const()[name = tensor("value_dilations_0"), val = tensor([1, 1])]; + tensor value_groups_0 = const()[name = tensor("value_groups_0"), val = tensor(1)]; + tensor layers_23_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_23_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(892329664)))]; + tensor layers_23_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_23_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(894426880)))]; + tensor value_cast_fp16 = conv(bias = layers_23_encoder_attn_v_proj_bias_to_fp16, dilations = value_dilations_0, groups = value_groups_0, pad = value_pad_0, pad_type = value_pad_type_0, strides = value_strides_0, weight = layers_23_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_cast_fp16")]; + tensor var_5348 = const()[name = tensor("op_5348"), val = tensor([1, 16, 64, 1])]; + tensor mh_q_cast_fp16 = reshape(shape = var_5348, x = query_cast_fp16)[name = tensor("mh_q_cast_fp16")]; + tensor var_5350_to_fp16 = const()[name = tensor("op_5350_to_fp16"), val = tensor(0x1p-3)]; + tensor var_5351_cast_fp16 = mul(x = mh_q_cast_fp16, y = var_5350_to_fp16)[name = tensor("op_5351_cast_fp16")]; + tensor var_5354 = const()[name = tensor("op_5354"), val = tensor([1, 16, 64, 1500])]; + tensor var_5355_cast_fp16 = reshape(shape = var_5354, x = key_cast_fp16)[name = tensor("op_5355_cast_fp16")]; + tensor mh_w_transpose_x_0 = const()[name = tensor("mh_w_transpose_x_0"), val = tensor(true)]; + tensor mh_w_transpose_y_0 = const()[name = tensor("mh_w_transpose_y_0"), val = tensor(false)]; + tensor mh_w_cast_fp16 = matmul(transpose_x = mh_w_transpose_x_0, transpose_y = mh_w_transpose_y_0, x = var_5351_cast_fp16, y = var_5355_cast_fp16)[name = tensor("mh_w_cast_fp16")]; + tensor obj_335_cast_fp16 = softmax(axis = var_5197, x = mh_w_cast_fp16)[name = tensor("obj_335_cast_fp16")]; + tensor var_5359 = const()[name = tensor("op_5359"), val = tensor([1, 16, 64, 1500])]; + tensor var_5360_cast_fp16 = reshape(shape = var_5359, x = value_cast_fp16)[name = tensor("op_5360_cast_fp16")]; + tensor attn_transpose_x_0 = const()[name = tensor("attn_transpose_x_0"), val = tensor(false)]; + tensor attn_transpose_y_0 = const()[name = tensor("attn_transpose_y_0"), val = tensor(true)]; + tensor attn_cast_fp16 = matmul(transpose_x = attn_transpose_x_0, transpose_y = attn_transpose_y_0, x = var_5360_cast_fp16, y = obj_335_cast_fp16)[name = tensor("attn_cast_fp16")]; + tensor var_5363 = const()[name = tensor("op_5363"), val = tensor([1, 1024, 1, 1])]; + tensor input_233_cast_fp16 = reshape(shape = var_5363, x = attn_cast_fp16)[name = tensor("input_233_cast_fp16")]; + tensor obj_333_pad_type_0 = const()[name = tensor("obj_333_pad_type_0"), val = tensor("valid")]; + tensor obj_333_strides_0 = const()[name = tensor("obj_333_strides_0"), val = tensor([1, 1])]; + tensor obj_333_pad_0 = const()[name = tensor("obj_333_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor obj_333_dilations_0 = const()[name = tensor("obj_333_dilations_0"), val = tensor([1, 1])]; + tensor obj_333_groups_0 = const()[name = tensor("obj_333_groups_0"), val = tensor(1)]; + tensor layers_23_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_23_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(894428992)))]; + tensor layers_23_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_23_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(896526208)))]; + tensor obj_333_cast_fp16 = conv(bias = layers_23_encoder_attn_o_proj_bias_to_fp16, dilations = obj_333_dilations_0, groups = obj_333_groups_0, pad = obj_333_pad_0, pad_type = obj_333_pad_type_0, strides = obj_333_strides_0, weight = layers_23_encoder_attn_o_proj_weight_to_fp16, x = input_233_cast_fp16)[name = tensor("obj_333_cast_fp16")]; + tensor inputs_143_cast_fp16 = add(x = inputs_141_cast_fp16, y = obj_333_cast_fp16)[name = tensor("inputs_143_cast_fp16")]; + tensor out_143_axes_0 = const()[name = tensor("out_143_axes_0"), val = tensor([1])]; + tensor var_5384_to_fp16 = const()[name = tensor("op_5384_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_143_cast_fp16 = layer_norm(axes = out_143_axes_0, epsilon = var_5384_to_fp16, x = inputs_143_cast_fp16)[name = tensor("out_143_cast_fp16")]; + tensor input_235_gamma_0_to_fp16 = const()[name = tensor("input_235_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(896528320)))]; + tensor input_235_beta_0_to_fp16 = const()[name = tensor("input_235_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(896530432)))]; + tensor input_235_epsilon_0_to_fp16 = const()[name = tensor("input_235_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_235_cast_fp16 = batch_norm(beta = input_235_beta_0_to_fp16, epsilon = input_235_epsilon_0_to_fp16, gamma = input_235_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_143_cast_fp16)[name = tensor("input_235_cast_fp16")]; + tensor input_237_pad_type_0 = const()[name = tensor("input_237_pad_type_0"), val = tensor("valid")]; + tensor input_237_strides_0 = const()[name = tensor("input_237_strides_0"), val = tensor([1, 1])]; + tensor input_237_pad_0 = const()[name = tensor("input_237_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_237_dilations_0 = const()[name = tensor("input_237_dilations_0"), val = tensor([1, 1])]; + tensor input_237_groups_0 = const()[name = tensor("input_237_groups_0"), val = tensor(1)]; + tensor layers_23_fc1_weight_to_fp16 = const()[name = tensor("layers_23_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(896532544)))]; + tensor layers_23_fc1_bias_to_fp16 = const()[name = tensor("layers_23_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(904921216)))]; + tensor input_237_cast_fp16 = conv(bias = layers_23_fc1_bias_to_fp16, dilations = input_237_dilations_0, groups = input_237_groups_0, pad = input_237_pad_0, pad_type = input_237_pad_type_0, strides = input_237_strides_0, weight = layers_23_fc1_weight_to_fp16, x = input_235_cast_fp16)[name = tensor("input_237_cast_fp16")]; + tensor input_mode_0 = const()[name = tensor("input_mode_0"), val = tensor("EXACT")]; + tensor input_cast_fp16 = gelu(mode = input_mode_0, x = input_237_cast_fp16)[name = tensor("input_cast_fp16")]; + tensor hidden_states_49_pad_type_0 = const()[name = tensor("hidden_states_49_pad_type_0"), val = tensor("valid")]; + tensor hidden_states_49_strides_0 = const()[name = tensor("hidden_states_49_strides_0"), val = tensor([1, 1])]; + tensor hidden_states_49_pad_0 = const()[name = tensor("hidden_states_49_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor hidden_states_49_dilations_0 = const()[name = tensor("hidden_states_49_dilations_0"), val = tensor([1, 1])]; + tensor hidden_states_49_groups_0 = const()[name = tensor("hidden_states_49_groups_0"), val = tensor(1)]; + tensor layers_23_fc2_weight_to_fp16 = const()[name = tensor("layers_23_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(904929472)))]; + tensor layers_23_fc2_bias_to_fp16 = const()[name = tensor("layers_23_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(913318144)))]; + tensor hidden_states_49_cast_fp16 = conv(bias = layers_23_fc2_bias_to_fp16, dilations = hidden_states_49_dilations_0, groups = hidden_states_49_groups_0, pad = hidden_states_49_pad_0, pad_type = hidden_states_49_pad_type_0, strides = hidden_states_49_strides_0, weight = layers_23_fc2_weight_to_fp16, x = input_cast_fp16)[name = tensor("hidden_states_49_cast_fp16")]; + tensor inputs_cast_fp16 = add(x = inputs_143_cast_fp16, y = hidden_states_49_cast_fp16)[name = tensor("inputs_cast_fp16")]; + tensor out_axes_0 = const()[name = tensor("out_axes_0"), val = tensor([1])]; + tensor var_5427_to_fp16 = const()[name = tensor("op_5427_to_fp16"), val = tensor(0x1.5p-17)]; + tensor out_cast_fp16 = layer_norm(axes = out_axes_0, epsilon = var_5427_to_fp16, x = inputs_cast_fp16)[name = tensor("out_cast_fp16")]; + tensor hidden_states_gamma_0_to_fp16 = const()[name = tensor("hidden_states_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(913320256)))]; + tensor hidden_states_beta_0_to_fp16 = const()[name = tensor("hidden_states_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(913322368)))]; + tensor hidden_states_epsilon_0_to_fp16 = const()[name = tensor("hidden_states_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor hidden_states_cast_fp16 = batch_norm(beta = hidden_states_beta_0_to_fp16, epsilon = hidden_states_epsilon_0_to_fp16, gamma = hidden_states_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_cast_fp16)[name = tensor("hidden_states_cast_fp16")]; + tensor var_5438_axes_0 = const()[name = tensor("op_5438_axes_0"), val = tensor([2])]; + tensor var_5438_cast_fp16 = squeeze(axes = var_5438_axes_0, x = hidden_states_cast_fp16)[name = tensor("op_5438_cast_fp16")]; + tensor var_5441_perm_0 = const()[name = tensor("op_5441_perm_0"), val = tensor([0, 2, 1])]; + tensor linear_0_bias_0_to_fp16 = const()[name = tensor("linear_0_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(913324480)))]; + tensor var_5441_cast_fp16 = transpose(perm = var_5441_perm_0, x = var_5438_cast_fp16)[name = tensor("transpose_0")]; + tensor logits = linear(bias = linear_0_bias_0_to_fp16, weight = embed_tokens_weight_to_fp16, x = var_5441_cast_fp16)[name = tensor("linear_0_cast_fp16")]; + tensor var_5445 = const()[name = tensor("op_5445"), val = tensor(1)]; + tensor obj_339_interleave_0 = const()[name = tensor("obj_339_interleave_0"), val = tensor(false)]; + tensor key_cache_updates = concat(axis = var_5445, interleave = obj_339_interleave_0, values = (current_key_1_cast_fp16, current_key_3_cast_fp16, current_key_5_cast_fp16, current_key_7_cast_fp16, current_key_9_cast_fp16, current_key_11_cast_fp16, current_key_13_cast_fp16, current_key_15_cast_fp16, current_key_17_cast_fp16, current_key_19_cast_fp16, current_key_21_cast_fp16, current_key_23_cast_fp16, current_key_25_cast_fp16, current_key_27_cast_fp16, current_key_29_cast_fp16, current_key_31_cast_fp16, current_key_33_cast_fp16, current_key_35_cast_fp16, current_key_37_cast_fp16, current_key_39_cast_fp16, current_key_41_cast_fp16, current_key_43_cast_fp16, current_key_45_cast_fp16, current_key_cast_fp16))[name = tensor("obj_339_cast_fp16")]; + tensor var_5448 = const()[name = tensor("op_5448"), val = tensor(1)]; + tensor obj_341_interleave_0 = const()[name = tensor("obj_341_interleave_0"), val = tensor(false)]; + tensor value_cache_updates = concat(axis = var_5448, interleave = obj_341_interleave_0, values = (current_value_1_cast_fp16, current_value_3_cast_fp16, current_value_5_cast_fp16, current_value_7_cast_fp16, current_value_9_cast_fp16, current_value_11_cast_fp16, current_value_13_cast_fp16, current_value_15_cast_fp16, current_value_17_cast_fp16, current_value_19_cast_fp16, current_value_21_cast_fp16, current_value_23_cast_fp16, current_value_25_cast_fp16, current_value_27_cast_fp16, current_value_29_cast_fp16, current_value_31_cast_fp16, current_value_33_cast_fp16, current_value_35_cast_fp16, current_value_37_cast_fp16, current_value_39_cast_fp16, current_value_41_cast_fp16, current_value_43_cast_fp16, current_value_45_cast_fp16, current_value_cast_fp16))[name = tensor("obj_341_cast_fp16")]; + tensor var_5459_begin_0 = const()[name = tensor("op_5459_begin_0"), val = tensor([0, 15, 0, 0])]; + tensor var_5459_end_0 = const()[name = tensor("op_5459_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_5459_end_mask_0 = const()[name = tensor("op_5459_end_mask_0"), val = tensor([true, true, true, true])]; + tensor var_5459_cast_fp16 = slice_by_index(begin = var_5459_begin_0, end = var_5459_end_0, end_mask = var_5459_end_mask_0, x = obj_195_cast_fp16)[name = tensor("op_5459_cast_fp16")]; + tensor var_5462_begin_0 = const()[name = tensor("op_5462_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5462_end_0 = const()[name = tensor("op_5462_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_5462_end_mask_0 = const()[name = tensor("op_5462_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_5462_squeeze_mask_0 = const()[name = tensor("op_5462_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_5462_cast_fp16 = slice_by_index(begin = var_5462_begin_0, end = var_5462_end_0, end_mask = var_5462_end_mask_0, squeeze_mask = var_5462_squeeze_mask_0, x = var_5459_cast_fp16)[name = tensor("op_5462_cast_fp16")]; + tensor var_5477_begin_0 = const()[name = tensor("op_5477_begin_0"), val = tensor([0, 4, 0, 0])]; + tensor var_5477_end_0 = const()[name = tensor("op_5477_end_0"), val = tensor([1, 5, 1, 1500])]; + tensor var_5477_end_mask_0 = const()[name = tensor("op_5477_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5477_cast_fp16 = slice_by_index(begin = var_5477_begin_0, end = var_5477_end_0, end_mask = var_5477_end_mask_0, x = obj_223_cast_fp16)[name = tensor("op_5477_cast_fp16")]; + tensor var_5480_begin_0 = const()[name = tensor("op_5480_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5480_end_0 = const()[name = tensor("op_5480_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_5480_end_mask_0 = const()[name = tensor("op_5480_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_5480_squeeze_mask_0 = const()[name = tensor("op_5480_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_5480_cast_fp16 = slice_by_index(begin = var_5480_begin_0, end = var_5480_end_0, end_mask = var_5480_end_mask_0, squeeze_mask = var_5480_squeeze_mask_0, x = var_5477_cast_fp16)[name = tensor("op_5480_cast_fp16")]; + tensor var_5495_begin_0 = const()[name = tensor("op_5495_begin_0"), val = tensor([0, 15, 0, 0])]; + tensor var_5495_end_0 = const()[name = tensor("op_5495_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_5495_end_mask_0 = const()[name = tensor("op_5495_end_mask_0"), val = tensor([true, true, true, true])]; + tensor var_5495_cast_fp16 = slice_by_index(begin = var_5495_begin_0, end = var_5495_end_0, end_mask = var_5495_end_mask_0, x = obj_223_cast_fp16)[name = tensor("op_5495_cast_fp16")]; + tensor var_5498_begin_0 = const()[name = tensor("op_5498_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5498_end_0 = const()[name = tensor("op_5498_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_5498_end_mask_0 = const()[name = tensor("op_5498_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_5498_squeeze_mask_0 = const()[name = tensor("op_5498_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_5498_cast_fp16 = slice_by_index(begin = var_5498_begin_0, end = var_5498_end_0, end_mask = var_5498_end_mask_0, squeeze_mask = var_5498_squeeze_mask_0, x = var_5495_cast_fp16)[name = tensor("op_5498_cast_fp16")]; + tensor var_5513_begin_0 = const()[name = tensor("op_5513_begin_0"), val = tensor([0, 1, 0, 0])]; + tensor var_5513_end_0 = const()[name = tensor("op_5513_end_0"), val = tensor([1, 2, 1, 1500])]; + tensor var_5513_end_mask_0 = const()[name = tensor("op_5513_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5513_cast_fp16 = slice_by_index(begin = var_5513_begin_0, end = var_5513_end_0, end_mask = var_5513_end_mask_0, x = obj_237_cast_fp16)[name = tensor("op_5513_cast_fp16")]; + tensor var_5516_begin_0 = const()[name = tensor("op_5516_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5516_end_0 = const()[name = tensor("op_5516_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_5516_end_mask_0 = const()[name = tensor("op_5516_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_5516_squeeze_mask_0 = const()[name = tensor("op_5516_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_5516_cast_fp16 = slice_by_index(begin = var_5516_begin_0, end = var_5516_end_0, end_mask = var_5516_end_mask_0, squeeze_mask = var_5516_squeeze_mask_0, x = var_5513_cast_fp16)[name = tensor("op_5516_cast_fp16")]; + tensor var_5531_begin_0 = const()[name = tensor("op_5531_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5531_end_0 = const()[name = tensor("op_5531_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_5531_end_mask_0 = const()[name = tensor("op_5531_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5531_cast_fp16 = slice_by_index(begin = var_5531_begin_0, end = var_5531_end_0, end_mask = var_5531_end_mask_0, x = obj_293_cast_fp16)[name = tensor("op_5531_cast_fp16")]; + tensor var_5534_begin_0 = const()[name = tensor("op_5534_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5534_end_0 = const()[name = tensor("op_5534_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_5534_end_mask_0 = const()[name = tensor("op_5534_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_5534_squeeze_mask_0 = const()[name = tensor("op_5534_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_5534_cast_fp16 = slice_by_index(begin = var_5534_begin_0, end = var_5534_end_0, end_mask = var_5534_end_mask_0, squeeze_mask = var_5534_squeeze_mask_0, x = var_5531_cast_fp16)[name = tensor("op_5534_cast_fp16")]; + tensor var_5549_begin_0 = const()[name = tensor("op_5549_begin_0"), val = tensor([0, 4, 0, 0])]; + tensor var_5549_end_0 = const()[name = tensor("op_5549_end_0"), val = tensor([1, 5, 1, 1500])]; + tensor var_5549_end_mask_0 = const()[name = tensor("op_5549_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5549_cast_fp16 = slice_by_index(begin = var_5549_begin_0, end = var_5549_end_0, end_mask = var_5549_end_mask_0, x = obj_335_cast_fp16)[name = tensor("op_5549_cast_fp16")]; + tensor var_5552_begin_0 = const()[name = tensor("op_5552_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5552_end_0 = const()[name = tensor("op_5552_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_5552_end_mask_0 = const()[name = tensor("op_5552_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_5552_squeeze_mask_0 = const()[name = tensor("op_5552_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_5552_cast_fp16 = slice_by_index(begin = var_5552_begin_0, end = var_5552_end_0, end_mask = var_5552_end_mask_0, squeeze_mask = var_5552_squeeze_mask_0, x = var_5549_cast_fp16)[name = tensor("op_5552_cast_fp16")]; + tensor var_5559 = const()[name = tensor("op_5559"), val = tensor(1)]; + tensor var_5560_interleave_0 = const()[name = tensor("op_5560_interleave_0"), val = tensor(false)]; + tensor var_5560_cast_fp16 = concat(axis = var_5559, interleave = var_5560_interleave_0, values = (var_5462_cast_fp16, var_5480_cast_fp16, var_5498_cast_fp16, var_5516_cast_fp16, var_5534_cast_fp16, var_5552_cast_fp16))[name = tensor("op_5560_cast_fp16")]; + tensor obj_axes_0 = const()[name = tensor("obj_axes_0"), val = tensor([1])]; + tensor obj_keep_dims_0 = const()[name = tensor("obj_keep_dims_0"), val = tensor(false)]; + tensor alignment_heads_weights = reduce_mean(axes = obj_axes_0, keep_dims = obj_keep_dims_0, x = var_5560_cast_fp16)[name = tensor("obj_cast_fp16")]; + } -> (logits, key_cache_updates, value_cache_updates, alignment_heads_weights); +} \ No newline at end of file diff --git a/openai_whisper-medium/TextDecoder.mlmodelc/weights/weight.bin b/openai_whisper-medium/TextDecoder.mlmodelc/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..1486869d1da66773552e9714729d96b56d6d7838 --- /dev/null +++ b/openai_whisper-medium/TextDecoder.mlmodelc/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:283878d285cb0e557eeb1c6a1524eb5fd33cae2c289a114bc9e72ca76c0bfc75 +size 913428274 diff --git a/openai_whisper-medium/config.json b/openai_whisper-medium/config.json new file mode 100644 index 0000000000000000000000000000000000000000..e6901659aef815672d5299b27e4b074e99540790 --- /dev/null +++ b/openai_whisper-medium/config.json @@ -0,0 +1 @@ +{"_name_or_path": "openai/whisper-medium", "activation_dropout": 0.0, "activation_function": "gelu", "architectures": ["WhisperForConditionalGeneration"], "attention_dropout": 0.0, "begin_suppress_tokens": [220, 50257], "bos_token_id": 50257, "d_model": 1024, "decoder_attention_heads": 16, "decoder_ffn_dim": 4096, "decoder_layerdrop": 0.0, "decoder_layers": 24, "decoder_start_token_id": 50258, "dropout": 0.0, "encoder_attention_heads": 16, "encoder_ffn_dim": 4096, "encoder_layerdrop": 0.0, "encoder_layers": 24, 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"MultiArray" + } + ], + "modelParameters" : [ + + ], + "specificationVersion" : 7, + "mlProgramOperationTypeHistogram" : { + "Concat" : 156, + "Ios16.rsqrt" : 25, + "Ios16.mul" : 626, + "SliceByIndex" : 1008, + "Ios16.sub" : 25, + "Transpose" : 12, + "Ios16.einsum" : 1152, + "Ios16.conv" : 74, + "Ios16.add" : 50, + "Ios16.reduceMean" : 50, + "Ios16.softmax" : 576, + "Ios16.gelu" : 14, + "Ios16.batchNorm" : 25 + }, + "computePrecision" : "Mixed (Float16, Int32)", + "isUpdatable" : "0", + "availability" : { + "macOS" : "13.0", + "tvOS" : "16.0", + "visionOS" : "1.0", + "watchOS" : "9.0", + "iOS" : "16.0", + "macCatalyst" : "16.0" + }, + "modelType" : { + "name" : "MLModelType_mlProgram" + }, + "userDefinedMetadata" : { + "com.github.apple.coremltools.source_dialect" : "TorchScript", + "com.github.apple.coremltools.source" : "torch==2.2.1", + "com.github.apple.coremltools.version" : "7.1" + }, + "inputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float16", + "formattedType" : "MultiArray (Float16 1 × 80 × 1 × 3000)", + "shortDescription" : "", + "shape" : "[1, 80, 1, 3000]", + "name" : "melspectrogram_features", + "type" : "MultiArray" + } + ], + "generatedClassName" : "AudioEncoder", + "method" : "predict" + } +] \ No newline at end of file diff --git a/openai_whisper-small/AudioEncoder.mlmodelc/model.mil b/openai_whisper-small/AudioEncoder.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..0dd59f0859f9a655599067124f0583a5263a0be5 --- /dev/null +++ b/openai_whisper-small/AudioEncoder.mlmodelc/model.mil @@ -0,0 +1,9382 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.2.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})] +{ + func main(tensor melspectrogram_features) { + tensor var_50 = const()[name = tensor("op_50"), val = tensor([1, 1])]; + tensor var_56 = const()[name = tensor("op_56"), val = tensor([1, 1])]; + tensor var_61 = const()[name = tensor("op_61"), val = tensor(1)]; + tensor var_66_pad_type_0 = const()[name = tensor("op_66_pad_type_0"), val = tensor("custom")]; + tensor var_66_pad_0 = const()[name = tensor("op_66_pad_0"), val = tensor([0, 0, 1, 1])]; + tensor var_41_to_fp16 = const()[name = tensor("op_41_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor var_47_to_fp16 = const()[name = tensor("op_47_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(368768)))]; + tensor var_66_cast_fp16 = conv(bias = var_47_to_fp16, dilations = var_56, groups = var_61, pad = var_66_pad_0, pad_type = var_66_pad_type_0, strides = var_50, weight = var_41_to_fp16, x = melspectrogram_features)[name = tensor("op_66_cast_fp16")]; + tensor hidden_states_1_mode_0 = const()[name = tensor("hidden_states_1_mode_0"), val = tensor("EXACT")]; + tensor hidden_states_1_cast_fp16 = gelu(mode = hidden_states_1_mode_0, x = var_66_cast_fp16)[name = tensor("hidden_states_1_cast_fp16")]; + tensor var_90 = const()[name = tensor("op_90"), val = tensor([2, 2])]; + tensor var_96 = const()[name = tensor("op_96"), val = tensor([1, 1])]; + tensor var_101 = const()[name = tensor("op_101"), val = tensor(1)]; + tensor var_106_pad_type_0 = const()[name = tensor("op_106_pad_type_0"), val = tensor("custom")]; + tensor var_106_pad_0 = const()[name = tensor("op_106_pad_0"), val = tensor([0, 0, 1, 1])]; + tensor var_81_to_fp16 = const()[name = tensor("op_81_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(370368)))]; + tensor var_87_to_fp16 = const()[name = tensor("op_87_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3909376)))]; + tensor var_106_cast_fp16 = conv(bias = var_87_to_fp16, dilations = var_96, groups = var_101, pad = var_106_pad_0, pad_type = var_106_pad_type_0, strides = var_90, weight = var_81_to_fp16, x = hidden_states_1_cast_fp16)[name = tensor("op_106_cast_fp16")]; + tensor hidden_states_3_mode_0 = const()[name = tensor("hidden_states_3_mode_0"), val = tensor("EXACT")]; + tensor hidden_states_3_cast_fp16 = gelu(mode = hidden_states_3_mode_0, x = var_106_cast_fp16)[name = tensor("hidden_states_3_cast_fp16")]; + tensor var_124_to_fp16 = const()[name = tensor("op_124_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3910976)))]; + tensor inputs_1_cast_fp16 = add(x = hidden_states_3_cast_fp16, y = var_124_to_fp16)[name = tensor("inputs_1_cast_fp16")]; + tensor var_134 = const()[name = tensor("op_134"), val = tensor(3)]; + tensor var_151 = const()[name = tensor("op_151"), val = tensor(1)]; + tensor var_152 = const()[name = tensor("op_152"), val = tensor(true)]; + tensor var_162 = const()[name = tensor("op_162"), val = tensor([1])]; + tensor channels_mean_1_cast_fp16 = reduce_mean(axes = var_162, keep_dims = var_152, x = inputs_1_cast_fp16)[name = tensor("channels_mean_1_cast_fp16")]; + tensor zero_mean_1_cast_fp16 = sub(x = inputs_1_cast_fp16, y = channels_mean_1_cast_fp16)[name = tensor("zero_mean_1_cast_fp16")]; + tensor zero_mean_sq_1_cast_fp16 = mul(x = zero_mean_1_cast_fp16, y = zero_mean_1_cast_fp16)[name = tensor("zero_mean_sq_1_cast_fp16")]; + tensor var_166 = const()[name = tensor("op_166"), val = tensor([1])]; + tensor var_167_cast_fp16 = reduce_mean(axes = var_166, keep_dims = var_152, x = zero_mean_sq_1_cast_fp16)[name = tensor("op_167_cast_fp16")]; + tensor var_168_to_fp16 = const()[name = tensor("op_168_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_169_cast_fp16 = add(x = var_167_cast_fp16, y = var_168_to_fp16)[name = tensor("op_169_cast_fp16")]; + tensor denom_1_epsilon_0_to_fp16 = const()[name = tensor("denom_1_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_1_cast_fp16 = rsqrt(epsilon = denom_1_epsilon_0_to_fp16, x = var_169_cast_fp16)[name = tensor("denom_1_cast_fp16")]; + tensor out_1_cast_fp16 = mul(x = zero_mean_1_cast_fp16, y = denom_1_cast_fp16)[name = tensor("out_1_cast_fp16")]; + tensor obj_1_mean_0_to_fp16 = const()[name = tensor("obj_1_mean_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6215040)))]; + tensor obj_1_variance_0_to_fp16 = const()[name = tensor("obj_1_variance_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6216640)))]; + tensor obj_1_gamma_0_to_fp16 = const()[name = tensor("obj_1_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6218240)))]; + tensor obj_1_beta_0_to_fp16 = const()[name = tensor("obj_1_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6219840)))]; + tensor obj_1_epsilon_0_to_fp16 = const()[name = tensor("obj_1_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_1_cast_fp16 = batch_norm(beta = obj_1_beta_0_to_fp16, epsilon = obj_1_epsilon_0_to_fp16, gamma = obj_1_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_1_cast_fp16)[name = tensor("obj_1_cast_fp16")]; + tensor var_184 = const()[name = tensor("op_184"), val = tensor([1, 1])]; + tensor var_186 = const()[name = tensor("op_186"), val = tensor([1, 1])]; + tensor query_1_pad_type_0 = const()[name = tensor("query_1_pad_type_0"), val = tensor("custom")]; + tensor query_1_pad_0 = const()[name = tensor("query_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6221440)))]; + tensor layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7401152)))]; + tensor query_1_cast_fp16 = conv(bias = layers_0_self_attn_q_proj_bias_to_fp16, dilations = var_186, groups = var_151, pad = query_1_pad_0, pad_type = query_1_pad_type_0, strides = var_184, weight = layers_0_self_attn_q_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("query_1_cast_fp16")]; + tensor var_190 = const()[name = tensor("op_190"), val = tensor([1, 1])]; + tensor var_192 = const()[name = tensor("op_192"), val = tensor([1, 1])]; + tensor key_1_pad_type_0 = const()[name = tensor("key_1_pad_type_0"), val = tensor("custom")]; + tensor key_1_pad_0 = const()[name = tensor("key_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7402752)))]; + tensor key_1_cast_fp16 = conv(dilations = var_192, groups = var_151, pad = key_1_pad_0, pad_type = key_1_pad_type_0, strides = var_190, weight = layers_0_self_attn_k_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("key_1_cast_fp16")]; + tensor var_197 = const()[name = tensor("op_197"), val = tensor([1, 1])]; + tensor var_199 = const()[name = tensor("op_199"), val = tensor([1, 1])]; + tensor value_1_pad_type_0 = const()[name = tensor("value_1_pad_type_0"), val = tensor("custom")]; + tensor value_1_pad_0 = const()[name = tensor("value_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8582464)))]; + tensor layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9762176)))]; + tensor value_1_cast_fp16 = conv(bias = layers_0_self_attn_v_proj_bias_to_fp16, dilations = var_199, groups = var_151, pad = value_1_pad_0, pad_type = value_1_pad_type_0, strides = var_197, weight = layers_0_self_attn_v_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("value_1_cast_fp16")]; + tensor var_206_begin_0 = const()[name = tensor("op_206_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_206_end_0 = const()[name = tensor("op_206_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_206_end_mask_0 = const()[name = tensor("op_206_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_206_cast_fp16 = slice_by_index(begin = var_206_begin_0, end = var_206_end_0, end_mask = var_206_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_206_cast_fp16")]; + tensor var_210_begin_0 = const()[name = tensor("op_210_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_210_end_0 = const()[name = tensor("op_210_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_210_end_mask_0 = const()[name = tensor("op_210_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_210_cast_fp16 = slice_by_index(begin = var_210_begin_0, end = var_210_end_0, end_mask = var_210_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_210_cast_fp16")]; + tensor var_214_begin_0 = const()[name = tensor("op_214_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_214_end_0 = const()[name = tensor("op_214_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_214_end_mask_0 = const()[name = tensor("op_214_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_214_cast_fp16 = slice_by_index(begin = var_214_begin_0, end = var_214_end_0, end_mask = var_214_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_214_cast_fp16")]; + tensor var_218_begin_0 = const()[name = tensor("op_218_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_218_end_0 = const()[name = tensor("op_218_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_218_end_mask_0 = const()[name = tensor("op_218_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_218_cast_fp16 = slice_by_index(begin = var_218_begin_0, end = var_218_end_0, end_mask = var_218_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_218_cast_fp16")]; + tensor var_222_begin_0 = const()[name = tensor("op_222_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_222_end_0 = const()[name = tensor("op_222_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_222_end_mask_0 = const()[name = tensor("op_222_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_222_cast_fp16 = slice_by_index(begin = var_222_begin_0, end = var_222_end_0, end_mask = var_222_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_222_cast_fp16")]; + tensor var_226_begin_0 = const()[name = tensor("op_226_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_226_end_0 = const()[name = tensor("op_226_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_226_end_mask_0 = const()[name = tensor("op_226_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_226_cast_fp16 = slice_by_index(begin = var_226_begin_0, end = var_226_end_0, end_mask = var_226_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_226_cast_fp16")]; + tensor var_230_begin_0 = const()[name = tensor("op_230_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_230_end_0 = const()[name = tensor("op_230_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_230_end_mask_0 = const()[name = tensor("op_230_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_230_cast_fp16 = slice_by_index(begin = var_230_begin_0, end = var_230_end_0, end_mask = var_230_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_230_cast_fp16")]; + tensor var_234_begin_0 = const()[name = tensor("op_234_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_234_end_0 = const()[name = tensor("op_234_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_234_end_mask_0 = const()[name = tensor("op_234_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_234_cast_fp16 = slice_by_index(begin = var_234_begin_0, end = var_234_end_0, end_mask = var_234_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_234_cast_fp16")]; + tensor var_238_begin_0 = const()[name = tensor("op_238_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_238_end_0 = const()[name = tensor("op_238_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_238_end_mask_0 = const()[name = tensor("op_238_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_238_cast_fp16 = slice_by_index(begin = var_238_begin_0, end = var_238_end_0, end_mask = var_238_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_238_cast_fp16")]; + tensor var_242_begin_0 = const()[name = tensor("op_242_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_242_end_0 = const()[name = tensor("op_242_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_242_end_mask_0 = const()[name = tensor("op_242_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_242_cast_fp16 = slice_by_index(begin = var_242_begin_0, end = var_242_end_0, end_mask = var_242_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_242_cast_fp16")]; + tensor var_246_begin_0 = const()[name = tensor("op_246_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_246_end_0 = const()[name = tensor("op_246_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_246_end_mask_0 = const()[name = tensor("op_246_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_246_cast_fp16 = slice_by_index(begin = var_246_begin_0, end = var_246_end_0, end_mask = var_246_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_246_cast_fp16")]; + tensor var_250_begin_0 = const()[name = tensor("op_250_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_250_end_0 = const()[name = tensor("op_250_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_250_end_mask_0 = const()[name = tensor("op_250_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_250_cast_fp16 = slice_by_index(begin = var_250_begin_0, end = var_250_end_0, end_mask = var_250_end_mask_0, x = query_1_cast_fp16)[name = tensor("op_250_cast_fp16")]; + tensor var_259_begin_0 = const()[name = tensor("op_259_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_259_end_0 = const()[name = tensor("op_259_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_259_end_mask_0 = const()[name = tensor("op_259_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_259_cast_fp16 = slice_by_index(begin = var_259_begin_0, end = var_259_end_0, end_mask = var_259_end_mask_0, x = var_206_cast_fp16)[name = tensor("op_259_cast_fp16")]; + tensor var_266_begin_0 = const()[name = tensor("op_266_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_266_end_0 = const()[name = tensor("op_266_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_266_end_mask_0 = const()[name = tensor("op_266_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_266_cast_fp16 = slice_by_index(begin = var_266_begin_0, end = var_266_end_0, end_mask = var_266_end_mask_0, x = var_206_cast_fp16)[name = tensor("op_266_cast_fp16")]; + tensor var_273_begin_0 = const()[name = tensor("op_273_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_273_end_0 = const()[name = tensor("op_273_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_273_end_mask_0 = const()[name = tensor("op_273_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_273_cast_fp16 = slice_by_index(begin = var_273_begin_0, end = var_273_end_0, end_mask = var_273_end_mask_0, x = var_206_cast_fp16)[name = tensor("op_273_cast_fp16")]; + tensor var_280_begin_0 = const()[name = tensor("op_280_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_280_end_0 = const()[name = tensor("op_280_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_280_end_mask_0 = const()[name = tensor("op_280_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_280_cast_fp16 = slice_by_index(begin = var_280_begin_0, end = var_280_end_0, end_mask = var_280_end_mask_0, x = var_206_cast_fp16)[name = tensor("op_280_cast_fp16")]; + tensor var_287_begin_0 = const()[name = tensor("op_287_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_287_end_0 = const()[name = tensor("op_287_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_287_end_mask_0 = const()[name = tensor("op_287_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_287_cast_fp16 = slice_by_index(begin = var_287_begin_0, end = var_287_end_0, end_mask = var_287_end_mask_0, x = var_210_cast_fp16)[name = tensor("op_287_cast_fp16")]; + tensor var_294_begin_0 = const()[name = tensor("op_294_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_294_end_0 = const()[name = tensor("op_294_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_294_end_mask_0 = const()[name = tensor("op_294_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_294_cast_fp16 = slice_by_index(begin = var_294_begin_0, end = var_294_end_0, end_mask = var_294_end_mask_0, x = var_210_cast_fp16)[name = tensor("op_294_cast_fp16")]; + tensor var_301_begin_0 = const()[name = tensor("op_301_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_301_end_0 = const()[name = tensor("op_301_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_301_end_mask_0 = const()[name = tensor("op_301_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_301_cast_fp16 = slice_by_index(begin = var_301_begin_0, end = var_301_end_0, end_mask = var_301_end_mask_0, x = var_210_cast_fp16)[name = tensor("op_301_cast_fp16")]; + tensor var_308_begin_0 = const()[name = tensor("op_308_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_308_end_0 = const()[name = tensor("op_308_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_308_end_mask_0 = const()[name = tensor("op_308_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_308_cast_fp16 = slice_by_index(begin = var_308_begin_0, end = var_308_end_0, end_mask = var_308_end_mask_0, x = var_210_cast_fp16)[name = tensor("op_308_cast_fp16")]; + tensor var_315_begin_0 = const()[name = tensor("op_315_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_315_end_0 = const()[name = tensor("op_315_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_315_end_mask_0 = const()[name = tensor("op_315_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_315_cast_fp16 = slice_by_index(begin = var_315_begin_0, end = var_315_end_0, end_mask = var_315_end_mask_0, x = var_214_cast_fp16)[name = tensor("op_315_cast_fp16")]; + tensor var_322_begin_0 = const()[name = tensor("op_322_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_322_end_0 = const()[name = tensor("op_322_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_322_end_mask_0 = const()[name = tensor("op_322_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_322_cast_fp16 = slice_by_index(begin = var_322_begin_0, end = var_322_end_0, end_mask = var_322_end_mask_0, x = var_214_cast_fp16)[name = tensor("op_322_cast_fp16")]; + tensor var_329_begin_0 = const()[name = tensor("op_329_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_329_end_0 = const()[name = tensor("op_329_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_329_end_mask_0 = const()[name = tensor("op_329_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_329_cast_fp16 = slice_by_index(begin = var_329_begin_0, end = var_329_end_0, end_mask = var_329_end_mask_0, x = var_214_cast_fp16)[name = tensor("op_329_cast_fp16")]; + tensor var_336_begin_0 = const()[name = tensor("op_336_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_336_end_0 = const()[name = tensor("op_336_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_336_end_mask_0 = const()[name = tensor("op_336_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_336_cast_fp16 = slice_by_index(begin = var_336_begin_0, end = var_336_end_0, end_mask = var_336_end_mask_0, x = var_214_cast_fp16)[name = tensor("op_336_cast_fp16")]; + tensor var_343_begin_0 = const()[name = tensor("op_343_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_343_end_0 = const()[name = tensor("op_343_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_343_end_mask_0 = const()[name = tensor("op_343_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_343_cast_fp16 = slice_by_index(begin = var_343_begin_0, end = var_343_end_0, end_mask = var_343_end_mask_0, x = var_218_cast_fp16)[name = tensor("op_343_cast_fp16")]; + tensor var_350_begin_0 = const()[name = tensor("op_350_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_350_end_0 = const()[name = tensor("op_350_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_350_end_mask_0 = const()[name = tensor("op_350_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_350_cast_fp16 = slice_by_index(begin = var_350_begin_0, end = var_350_end_0, end_mask = var_350_end_mask_0, x = var_218_cast_fp16)[name = tensor("op_350_cast_fp16")]; + tensor var_357_begin_0 = const()[name = tensor("op_357_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_357_end_0 = const()[name = tensor("op_357_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_357_end_mask_0 = const()[name = tensor("op_357_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_357_cast_fp16 = slice_by_index(begin = var_357_begin_0, end = var_357_end_0, end_mask = var_357_end_mask_0, x = var_218_cast_fp16)[name = tensor("op_357_cast_fp16")]; + tensor var_364_begin_0 = const()[name = tensor("op_364_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_364_end_0 = const()[name = tensor("op_364_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_364_end_mask_0 = const()[name = tensor("op_364_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_364_cast_fp16 = slice_by_index(begin = var_364_begin_0, end = var_364_end_0, end_mask = var_364_end_mask_0, x = var_218_cast_fp16)[name = tensor("op_364_cast_fp16")]; + tensor var_371_begin_0 = const()[name = tensor("op_371_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_371_end_0 = const()[name = tensor("op_371_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_371_end_mask_0 = const()[name = tensor("op_371_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_371_cast_fp16 = slice_by_index(begin = var_371_begin_0, end = var_371_end_0, end_mask = var_371_end_mask_0, x = var_222_cast_fp16)[name = tensor("op_371_cast_fp16")]; + tensor var_378_begin_0 = const()[name = tensor("op_378_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_378_end_0 = const()[name = tensor("op_378_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_378_end_mask_0 = const()[name = tensor("op_378_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_378_cast_fp16 = slice_by_index(begin = var_378_begin_0, end = var_378_end_0, end_mask = var_378_end_mask_0, x = var_222_cast_fp16)[name = tensor("op_378_cast_fp16")]; + tensor var_385_begin_0 = const()[name = tensor("op_385_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_385_end_0 = const()[name = tensor("op_385_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_385_end_mask_0 = const()[name = tensor("op_385_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_385_cast_fp16 = slice_by_index(begin = var_385_begin_0, end = var_385_end_0, end_mask = var_385_end_mask_0, x = var_222_cast_fp16)[name = tensor("op_385_cast_fp16")]; + tensor var_392_begin_0 = const()[name = tensor("op_392_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_392_end_0 = const()[name = tensor("op_392_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_392_end_mask_0 = const()[name = tensor("op_392_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_392_cast_fp16 = slice_by_index(begin = var_392_begin_0, end = var_392_end_0, end_mask = var_392_end_mask_0, x = var_222_cast_fp16)[name = tensor("op_392_cast_fp16")]; + tensor var_399_begin_0 = const()[name = tensor("op_399_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_399_end_0 = const()[name = tensor("op_399_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_399_end_mask_0 = const()[name = tensor("op_399_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_399_cast_fp16 = slice_by_index(begin = var_399_begin_0, end = var_399_end_0, end_mask = var_399_end_mask_0, x = var_226_cast_fp16)[name = tensor("op_399_cast_fp16")]; + tensor var_406_begin_0 = const()[name = tensor("op_406_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_406_end_0 = const()[name = tensor("op_406_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_406_end_mask_0 = const()[name = tensor("op_406_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_406_cast_fp16 = slice_by_index(begin = var_406_begin_0, end = var_406_end_0, end_mask = var_406_end_mask_0, x = var_226_cast_fp16)[name = tensor("op_406_cast_fp16")]; + tensor var_413_begin_0 = const()[name = tensor("op_413_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_413_end_0 = const()[name = tensor("op_413_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_413_end_mask_0 = const()[name = tensor("op_413_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_413_cast_fp16 = slice_by_index(begin = var_413_begin_0, end = var_413_end_0, end_mask = var_413_end_mask_0, x = var_226_cast_fp16)[name = tensor("op_413_cast_fp16")]; + tensor var_420_begin_0 = const()[name = tensor("op_420_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_420_end_0 = const()[name = tensor("op_420_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_420_end_mask_0 = const()[name = tensor("op_420_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_420_cast_fp16 = slice_by_index(begin = var_420_begin_0, end = var_420_end_0, end_mask = var_420_end_mask_0, x = var_226_cast_fp16)[name = tensor("op_420_cast_fp16")]; + tensor var_427_begin_0 = const()[name = tensor("op_427_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_427_end_0 = const()[name = tensor("op_427_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_427_end_mask_0 = const()[name = tensor("op_427_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_427_cast_fp16 = slice_by_index(begin = var_427_begin_0, end = var_427_end_0, end_mask = var_427_end_mask_0, x = var_230_cast_fp16)[name = tensor("op_427_cast_fp16")]; + tensor var_434_begin_0 = const()[name = tensor("op_434_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_434_end_0 = const()[name = tensor("op_434_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_434_end_mask_0 = const()[name = tensor("op_434_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_434_cast_fp16 = slice_by_index(begin = var_434_begin_0, end = var_434_end_0, end_mask = var_434_end_mask_0, x = var_230_cast_fp16)[name = tensor("op_434_cast_fp16")]; + tensor var_441_begin_0 = const()[name = tensor("op_441_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_441_end_0 = const()[name = tensor("op_441_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_441_end_mask_0 = const()[name = tensor("op_441_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_441_cast_fp16 = slice_by_index(begin = var_441_begin_0, end = var_441_end_0, end_mask = var_441_end_mask_0, x = var_230_cast_fp16)[name = tensor("op_441_cast_fp16")]; + tensor var_448_begin_0 = const()[name = tensor("op_448_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_448_end_0 = const()[name = tensor("op_448_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_448_end_mask_0 = const()[name = tensor("op_448_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_448_cast_fp16 = slice_by_index(begin = var_448_begin_0, end = var_448_end_0, end_mask = var_448_end_mask_0, x = var_230_cast_fp16)[name = tensor("op_448_cast_fp16")]; + tensor var_455_begin_0 = const()[name = tensor("op_455_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_455_end_0 = const()[name = tensor("op_455_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_455_end_mask_0 = const()[name = tensor("op_455_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_455_cast_fp16 = slice_by_index(begin = var_455_begin_0, end = var_455_end_0, end_mask = var_455_end_mask_0, x = var_234_cast_fp16)[name = tensor("op_455_cast_fp16")]; + tensor var_462_begin_0 = const()[name = tensor("op_462_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_462_end_0 = const()[name = tensor("op_462_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_462_end_mask_0 = const()[name = tensor("op_462_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_462_cast_fp16 = slice_by_index(begin = var_462_begin_0, end = var_462_end_0, end_mask = var_462_end_mask_0, x = var_234_cast_fp16)[name = tensor("op_462_cast_fp16")]; + tensor var_469_begin_0 = const()[name = tensor("op_469_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_469_end_0 = const()[name = tensor("op_469_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_469_end_mask_0 = const()[name = tensor("op_469_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_469_cast_fp16 = slice_by_index(begin = var_469_begin_0, end = var_469_end_0, end_mask = var_469_end_mask_0, x = var_234_cast_fp16)[name = tensor("op_469_cast_fp16")]; + tensor var_476_begin_0 = const()[name = tensor("op_476_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_476_end_0 = const()[name = tensor("op_476_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_476_end_mask_0 = const()[name = tensor("op_476_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_476_cast_fp16 = slice_by_index(begin = var_476_begin_0, end = var_476_end_0, end_mask = var_476_end_mask_0, x = var_234_cast_fp16)[name = tensor("op_476_cast_fp16")]; + tensor var_483_begin_0 = const()[name = tensor("op_483_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_483_end_0 = const()[name = tensor("op_483_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_483_end_mask_0 = const()[name = tensor("op_483_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_483_cast_fp16 = slice_by_index(begin = var_483_begin_0, end = var_483_end_0, end_mask = var_483_end_mask_0, x = var_238_cast_fp16)[name = tensor("op_483_cast_fp16")]; + tensor var_490_begin_0 = const()[name = tensor("op_490_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_490_end_0 = const()[name = tensor("op_490_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_490_end_mask_0 = const()[name = tensor("op_490_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_490_cast_fp16 = slice_by_index(begin = var_490_begin_0, end = var_490_end_0, end_mask = var_490_end_mask_0, x = var_238_cast_fp16)[name = tensor("op_490_cast_fp16")]; + tensor var_497_begin_0 = const()[name = tensor("op_497_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_497_end_0 = const()[name = tensor("op_497_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_497_end_mask_0 = const()[name = tensor("op_497_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_497_cast_fp16 = slice_by_index(begin = var_497_begin_0, end = var_497_end_0, end_mask = var_497_end_mask_0, x = var_238_cast_fp16)[name = tensor("op_497_cast_fp16")]; + tensor var_504_begin_0 = const()[name = tensor("op_504_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_504_end_0 = const()[name = tensor("op_504_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_504_end_mask_0 = const()[name = tensor("op_504_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_504_cast_fp16 = slice_by_index(begin = var_504_begin_0, end = var_504_end_0, end_mask = var_504_end_mask_0, x = var_238_cast_fp16)[name = tensor("op_504_cast_fp16")]; + tensor var_511_begin_0 = const()[name = tensor("op_511_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_511_end_0 = const()[name = tensor("op_511_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_511_end_mask_0 = const()[name = tensor("op_511_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_511_cast_fp16 = slice_by_index(begin = var_511_begin_0, end = var_511_end_0, end_mask = var_511_end_mask_0, x = var_242_cast_fp16)[name = tensor("op_511_cast_fp16")]; + tensor var_518_begin_0 = const()[name = tensor("op_518_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_518_end_0 = const()[name = tensor("op_518_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_518_end_mask_0 = const()[name = tensor("op_518_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_518_cast_fp16 = slice_by_index(begin = var_518_begin_0, end = var_518_end_0, end_mask = var_518_end_mask_0, x = var_242_cast_fp16)[name = tensor("op_518_cast_fp16")]; + tensor var_525_begin_0 = const()[name = tensor("op_525_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_525_end_0 = const()[name = tensor("op_525_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_525_end_mask_0 = const()[name = tensor("op_525_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_525_cast_fp16 = slice_by_index(begin = var_525_begin_0, end = var_525_end_0, end_mask = var_525_end_mask_0, x = var_242_cast_fp16)[name = tensor("op_525_cast_fp16")]; + tensor var_532_begin_0 = const()[name = tensor("op_532_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_532_end_0 = const()[name = tensor("op_532_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_532_end_mask_0 = const()[name = tensor("op_532_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_532_cast_fp16 = slice_by_index(begin = var_532_begin_0, end = var_532_end_0, end_mask = var_532_end_mask_0, x = var_242_cast_fp16)[name = tensor("op_532_cast_fp16")]; + tensor var_539_begin_0 = const()[name = tensor("op_539_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_539_end_0 = const()[name = tensor("op_539_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_539_end_mask_0 = const()[name = tensor("op_539_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_539_cast_fp16 = slice_by_index(begin = var_539_begin_0, end = var_539_end_0, end_mask = var_539_end_mask_0, x = var_246_cast_fp16)[name = tensor("op_539_cast_fp16")]; + tensor var_546_begin_0 = const()[name = tensor("op_546_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_546_end_0 = const()[name = tensor("op_546_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_546_end_mask_0 = const()[name = tensor("op_546_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_546_cast_fp16 = slice_by_index(begin = var_546_begin_0, end = var_546_end_0, end_mask = var_546_end_mask_0, x = var_246_cast_fp16)[name = tensor("op_546_cast_fp16")]; + tensor var_553_begin_0 = const()[name = tensor("op_553_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_553_end_0 = const()[name = tensor("op_553_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_553_end_mask_0 = const()[name = tensor("op_553_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_553_cast_fp16 = slice_by_index(begin = var_553_begin_0, end = var_553_end_0, end_mask = var_553_end_mask_0, x = var_246_cast_fp16)[name = tensor("op_553_cast_fp16")]; + tensor var_560_begin_0 = const()[name = tensor("op_560_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_560_end_0 = const()[name = tensor("op_560_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_560_end_mask_0 = const()[name = tensor("op_560_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_560_cast_fp16 = slice_by_index(begin = var_560_begin_0, end = var_560_end_0, end_mask = var_560_end_mask_0, x = var_246_cast_fp16)[name = tensor("op_560_cast_fp16")]; + tensor var_567_begin_0 = const()[name = tensor("op_567_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_567_end_0 = const()[name = tensor("op_567_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_567_end_mask_0 = const()[name = tensor("op_567_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_567_cast_fp16 = slice_by_index(begin = var_567_begin_0, end = var_567_end_0, end_mask = var_567_end_mask_0, x = var_250_cast_fp16)[name = tensor("op_567_cast_fp16")]; + tensor var_574_begin_0 = const()[name = tensor("op_574_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_574_end_0 = const()[name = tensor("op_574_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_574_end_mask_0 = const()[name = tensor("op_574_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_574_cast_fp16 = slice_by_index(begin = var_574_begin_0, end = var_574_end_0, end_mask = var_574_end_mask_0, x = var_250_cast_fp16)[name = tensor("op_574_cast_fp16")]; + tensor var_581_begin_0 = const()[name = tensor("op_581_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_581_end_0 = const()[name = tensor("op_581_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_581_end_mask_0 = const()[name = tensor("op_581_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_581_cast_fp16 = slice_by_index(begin = var_581_begin_0, end = var_581_end_0, end_mask = var_581_end_mask_0, x = var_250_cast_fp16)[name = tensor("op_581_cast_fp16")]; + tensor var_588_begin_0 = const()[name = tensor("op_588_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_588_end_0 = const()[name = tensor("op_588_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_588_end_mask_0 = const()[name = tensor("op_588_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_588_cast_fp16 = slice_by_index(begin = var_588_begin_0, end = var_588_end_0, end_mask = var_588_end_mask_0, x = var_250_cast_fp16)[name = tensor("op_588_cast_fp16")]; + tensor k_1_perm_0 = const()[name = tensor("k_1_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_593_begin_0 = const()[name = tensor("op_593_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_593_end_0 = const()[name = tensor("op_593_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_593_end_mask_0 = const()[name = tensor("op_593_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_11 = transpose(perm = k_1_perm_0, x = key_1_cast_fp16)[name = tensor("transpose_11")]; + tensor var_593_cast_fp16 = slice_by_index(begin = var_593_begin_0, end = var_593_end_0, end_mask = var_593_end_mask_0, x = transpose_11)[name = tensor("op_593_cast_fp16")]; + tensor var_597_begin_0 = const()[name = tensor("op_597_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_597_end_0 = const()[name = tensor("op_597_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_597_end_mask_0 = const()[name = tensor("op_597_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_597_cast_fp16 = slice_by_index(begin = var_597_begin_0, end = var_597_end_0, end_mask = var_597_end_mask_0, x = transpose_11)[name = tensor("op_597_cast_fp16")]; + tensor var_601_begin_0 = const()[name = tensor("op_601_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_601_end_0 = const()[name = tensor("op_601_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_601_end_mask_0 = const()[name = tensor("op_601_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_601_cast_fp16 = slice_by_index(begin = var_601_begin_0, end = var_601_end_0, end_mask = var_601_end_mask_0, x = transpose_11)[name = tensor("op_601_cast_fp16")]; + tensor var_605_begin_0 = const()[name = tensor("op_605_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_605_end_0 = const()[name = tensor("op_605_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_605_end_mask_0 = const()[name = tensor("op_605_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_605_cast_fp16 = slice_by_index(begin = var_605_begin_0, end = var_605_end_0, end_mask = var_605_end_mask_0, x = transpose_11)[name = tensor("op_605_cast_fp16")]; + tensor var_609_begin_0 = const()[name = tensor("op_609_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_609_end_0 = const()[name = tensor("op_609_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_609_end_mask_0 = const()[name = tensor("op_609_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_609_cast_fp16 = slice_by_index(begin = var_609_begin_0, end = var_609_end_0, end_mask = var_609_end_mask_0, x = transpose_11)[name = tensor("op_609_cast_fp16")]; + tensor var_613_begin_0 = const()[name = tensor("op_613_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_613_end_0 = const()[name = tensor("op_613_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_613_end_mask_0 = const()[name = tensor("op_613_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_613_cast_fp16 = slice_by_index(begin = var_613_begin_0, end = var_613_end_0, end_mask = var_613_end_mask_0, x = transpose_11)[name = tensor("op_613_cast_fp16")]; + tensor var_617_begin_0 = const()[name = tensor("op_617_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_617_end_0 = const()[name = tensor("op_617_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_617_end_mask_0 = const()[name = tensor("op_617_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_617_cast_fp16 = slice_by_index(begin = var_617_begin_0, end = var_617_end_0, end_mask = var_617_end_mask_0, x = transpose_11)[name = tensor("op_617_cast_fp16")]; + tensor var_621_begin_0 = const()[name = tensor("op_621_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_621_end_0 = const()[name = tensor("op_621_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_621_end_mask_0 = const()[name = tensor("op_621_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_621_cast_fp16 = slice_by_index(begin = var_621_begin_0, end = var_621_end_0, end_mask = var_621_end_mask_0, x = transpose_11)[name = tensor("op_621_cast_fp16")]; + tensor var_625_begin_0 = const()[name = tensor("op_625_begin_0"), val = tensor([0, 0, 0, 512])]; + tensor var_625_end_0 = const()[name = tensor("op_625_end_0"), val = tensor([1, 1500, 1, 576])]; + tensor var_625_end_mask_0 = const()[name = tensor("op_625_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_625_cast_fp16 = slice_by_index(begin = var_625_begin_0, end = var_625_end_0, end_mask = var_625_end_mask_0, x = transpose_11)[name = tensor("op_625_cast_fp16")]; + tensor var_629_begin_0 = const()[name = tensor("op_629_begin_0"), val = tensor([0, 0, 0, 576])]; + tensor var_629_end_0 = const()[name = tensor("op_629_end_0"), val = tensor([1, 1500, 1, 640])]; + tensor var_629_end_mask_0 = const()[name = tensor("op_629_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_629_cast_fp16 = slice_by_index(begin = var_629_begin_0, end = var_629_end_0, end_mask = var_629_end_mask_0, x = transpose_11)[name = tensor("op_629_cast_fp16")]; + tensor var_633_begin_0 = const()[name = tensor("op_633_begin_0"), val = tensor([0, 0, 0, 640])]; + tensor var_633_end_0 = const()[name = tensor("op_633_end_0"), val = tensor([1, 1500, 1, 704])]; + tensor var_633_end_mask_0 = const()[name = tensor("op_633_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_633_cast_fp16 = slice_by_index(begin = var_633_begin_0, end = var_633_end_0, end_mask = var_633_end_mask_0, x = transpose_11)[name = tensor("op_633_cast_fp16")]; + tensor var_637_begin_0 = const()[name = tensor("op_637_begin_0"), val = tensor([0, 0, 0, 704])]; + tensor var_637_end_0 = const()[name = tensor("op_637_end_0"), val = tensor([1, 1500, 1, 768])]; + tensor var_637_end_mask_0 = const()[name = tensor("op_637_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_637_cast_fp16 = slice_by_index(begin = var_637_begin_0, end = var_637_end_0, end_mask = var_637_end_mask_0, x = transpose_11)[name = tensor("op_637_cast_fp16")]; + tensor var_639_begin_0 = const()[name = tensor("op_639_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_639_end_0 = const()[name = tensor("op_639_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_639_end_mask_0 = const()[name = tensor("op_639_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_639_cast_fp16 = slice_by_index(begin = var_639_begin_0, end = var_639_end_0, end_mask = var_639_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_639_cast_fp16")]; + tensor var_643_begin_0 = const()[name = tensor("op_643_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_643_end_0 = const()[name = tensor("op_643_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_643_end_mask_0 = const()[name = tensor("op_643_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_643_cast_fp16 = slice_by_index(begin = var_643_begin_0, end = var_643_end_0, end_mask = var_643_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_643_cast_fp16")]; + tensor var_647_begin_0 = const()[name = tensor("op_647_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_647_end_0 = const()[name = tensor("op_647_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_647_end_mask_0 = const()[name = tensor("op_647_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_647_cast_fp16 = slice_by_index(begin = var_647_begin_0, end = var_647_end_0, end_mask = var_647_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_647_cast_fp16")]; + tensor var_651_begin_0 = const()[name = tensor("op_651_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_651_end_0 = const()[name = tensor("op_651_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_651_end_mask_0 = const()[name = tensor("op_651_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_651_cast_fp16 = slice_by_index(begin = var_651_begin_0, end = var_651_end_0, end_mask = var_651_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_651_cast_fp16")]; + tensor var_655_begin_0 = const()[name = tensor("op_655_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_655_end_0 = const()[name = tensor("op_655_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_655_end_mask_0 = const()[name = tensor("op_655_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_655_cast_fp16 = slice_by_index(begin = var_655_begin_0, end = var_655_end_0, end_mask = var_655_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_655_cast_fp16")]; + tensor var_659_begin_0 = const()[name = tensor("op_659_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_659_end_0 = const()[name = tensor("op_659_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_659_end_mask_0 = const()[name = tensor("op_659_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_659_cast_fp16 = slice_by_index(begin = var_659_begin_0, end = var_659_end_0, end_mask = var_659_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_659_cast_fp16")]; + tensor var_663_begin_0 = const()[name = tensor("op_663_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_663_end_0 = const()[name = tensor("op_663_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_663_end_mask_0 = const()[name = tensor("op_663_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_663_cast_fp16 = slice_by_index(begin = var_663_begin_0, end = var_663_end_0, end_mask = var_663_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_663_cast_fp16")]; + tensor var_667_begin_0 = const()[name = tensor("op_667_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_667_end_0 = const()[name = tensor("op_667_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_667_end_mask_0 = const()[name = tensor("op_667_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_667_cast_fp16 = slice_by_index(begin = var_667_begin_0, end = var_667_end_0, end_mask = var_667_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_667_cast_fp16")]; + tensor var_671_begin_0 = const()[name = tensor("op_671_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_671_end_0 = const()[name = tensor("op_671_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_671_end_mask_0 = const()[name = tensor("op_671_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_671_cast_fp16 = slice_by_index(begin = var_671_begin_0, end = var_671_end_0, end_mask = var_671_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_671_cast_fp16")]; + tensor var_675_begin_0 = const()[name = tensor("op_675_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_675_end_0 = const()[name = tensor("op_675_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_675_end_mask_0 = const()[name = tensor("op_675_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_675_cast_fp16 = slice_by_index(begin = var_675_begin_0, end = var_675_end_0, end_mask = var_675_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_675_cast_fp16")]; + tensor var_679_begin_0 = const()[name = tensor("op_679_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_679_end_0 = const()[name = tensor("op_679_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_679_end_mask_0 = const()[name = tensor("op_679_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_679_cast_fp16 = slice_by_index(begin = var_679_begin_0, end = var_679_end_0, end_mask = var_679_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_679_cast_fp16")]; + tensor var_683_begin_0 = const()[name = tensor("op_683_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_683_end_0 = const()[name = tensor("op_683_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_683_end_mask_0 = const()[name = tensor("op_683_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_683_cast_fp16 = slice_by_index(begin = var_683_begin_0, end = var_683_end_0, end_mask = var_683_end_mask_0, x = value_1_cast_fp16)[name = tensor("op_683_cast_fp16")]; + tensor var_687_equation_0 = const()[name = tensor("op_687_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_687_cast_fp16 = einsum(equation = var_687_equation_0, values = (var_593_cast_fp16, var_259_cast_fp16))[name = tensor("op_687_cast_fp16")]; + tensor var_688_to_fp16 = const()[name = tensor("op_688_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1_cast_fp16 = mul(x = var_687_cast_fp16, y = var_688_to_fp16)[name = tensor("aw_chunk_1_cast_fp16")]; + tensor var_691_equation_0 = const()[name = tensor("op_691_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_691_cast_fp16 = einsum(equation = var_691_equation_0, values = (var_593_cast_fp16, var_266_cast_fp16))[name = tensor("op_691_cast_fp16")]; + tensor var_692_to_fp16 = const()[name = tensor("op_692_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_3_cast_fp16 = mul(x = var_691_cast_fp16, y = var_692_to_fp16)[name = tensor("aw_chunk_3_cast_fp16")]; + tensor var_695_equation_0 = const()[name = tensor("op_695_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_695_cast_fp16 = einsum(equation = var_695_equation_0, values = (var_593_cast_fp16, var_273_cast_fp16))[name = tensor("op_695_cast_fp16")]; + tensor var_696_to_fp16 = const()[name = tensor("op_696_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_5_cast_fp16 = mul(x = var_695_cast_fp16, y = var_696_to_fp16)[name = tensor("aw_chunk_5_cast_fp16")]; + tensor var_699_equation_0 = const()[name = tensor("op_699_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_699_cast_fp16 = einsum(equation = var_699_equation_0, values = (var_593_cast_fp16, var_280_cast_fp16))[name = tensor("op_699_cast_fp16")]; + tensor var_700_to_fp16 = const()[name = tensor("op_700_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_7_cast_fp16 = mul(x = var_699_cast_fp16, y = var_700_to_fp16)[name = tensor("aw_chunk_7_cast_fp16")]; + tensor var_703_equation_0 = const()[name = tensor("op_703_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_703_cast_fp16 = einsum(equation = var_703_equation_0, values = (var_597_cast_fp16, var_287_cast_fp16))[name = tensor("op_703_cast_fp16")]; + tensor var_704_to_fp16 = const()[name = tensor("op_704_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_9_cast_fp16 = mul(x = var_703_cast_fp16, y = var_704_to_fp16)[name = tensor("aw_chunk_9_cast_fp16")]; + tensor var_707_equation_0 = const()[name = tensor("op_707_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_707_cast_fp16 = einsum(equation = var_707_equation_0, values = (var_597_cast_fp16, var_294_cast_fp16))[name = tensor("op_707_cast_fp16")]; + tensor var_708_to_fp16 = const()[name = tensor("op_708_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_11_cast_fp16 = mul(x = var_707_cast_fp16, y = var_708_to_fp16)[name = tensor("aw_chunk_11_cast_fp16")]; + tensor var_711_equation_0 = const()[name = tensor("op_711_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_711_cast_fp16 = einsum(equation = var_711_equation_0, values = (var_597_cast_fp16, var_301_cast_fp16))[name = tensor("op_711_cast_fp16")]; + tensor var_712_to_fp16 = const()[name = tensor("op_712_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_13_cast_fp16 = mul(x = var_711_cast_fp16, y = var_712_to_fp16)[name = tensor("aw_chunk_13_cast_fp16")]; + tensor var_715_equation_0 = const()[name = tensor("op_715_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_715_cast_fp16 = einsum(equation = var_715_equation_0, values = (var_597_cast_fp16, var_308_cast_fp16))[name = tensor("op_715_cast_fp16")]; + tensor var_716_to_fp16 = const()[name = tensor("op_716_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_15_cast_fp16 = mul(x = var_715_cast_fp16, y = var_716_to_fp16)[name = tensor("aw_chunk_15_cast_fp16")]; + tensor var_719_equation_0 = const()[name = tensor("op_719_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_719_cast_fp16 = einsum(equation = var_719_equation_0, values = (var_601_cast_fp16, var_315_cast_fp16))[name = tensor("op_719_cast_fp16")]; + tensor var_720_to_fp16 = const()[name = tensor("op_720_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_17_cast_fp16 = mul(x = var_719_cast_fp16, y = var_720_to_fp16)[name = tensor("aw_chunk_17_cast_fp16")]; + tensor var_723_equation_0 = const()[name = tensor("op_723_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_723_cast_fp16 = einsum(equation = var_723_equation_0, values = (var_601_cast_fp16, var_322_cast_fp16))[name = tensor("op_723_cast_fp16")]; + tensor var_724_to_fp16 = const()[name = tensor("op_724_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_19_cast_fp16 = mul(x = var_723_cast_fp16, y = var_724_to_fp16)[name = tensor("aw_chunk_19_cast_fp16")]; + tensor var_727_equation_0 = const()[name = tensor("op_727_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_727_cast_fp16 = einsum(equation = var_727_equation_0, values = (var_601_cast_fp16, var_329_cast_fp16))[name = tensor("op_727_cast_fp16")]; + tensor var_728_to_fp16 = const()[name = tensor("op_728_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_21_cast_fp16 = mul(x = var_727_cast_fp16, y = var_728_to_fp16)[name = tensor("aw_chunk_21_cast_fp16")]; + tensor var_731_equation_0 = const()[name = tensor("op_731_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_731_cast_fp16 = einsum(equation = var_731_equation_0, values = (var_601_cast_fp16, var_336_cast_fp16))[name = tensor("op_731_cast_fp16")]; + tensor var_732_to_fp16 = const()[name = tensor("op_732_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_23_cast_fp16 = mul(x = var_731_cast_fp16, y = var_732_to_fp16)[name = tensor("aw_chunk_23_cast_fp16")]; + tensor var_735_equation_0 = const()[name = tensor("op_735_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_735_cast_fp16 = einsum(equation = var_735_equation_0, values = (var_605_cast_fp16, var_343_cast_fp16))[name = tensor("op_735_cast_fp16")]; + tensor var_736_to_fp16 = const()[name = tensor("op_736_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_25_cast_fp16 = mul(x = var_735_cast_fp16, y = var_736_to_fp16)[name = tensor("aw_chunk_25_cast_fp16")]; + tensor var_739_equation_0 = const()[name = tensor("op_739_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_739_cast_fp16 = einsum(equation = var_739_equation_0, values = (var_605_cast_fp16, var_350_cast_fp16))[name = tensor("op_739_cast_fp16")]; + tensor var_740_to_fp16 = const()[name = tensor("op_740_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_27_cast_fp16 = mul(x = var_739_cast_fp16, y = var_740_to_fp16)[name = tensor("aw_chunk_27_cast_fp16")]; + tensor var_743_equation_0 = const()[name = tensor("op_743_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_743_cast_fp16 = einsum(equation = var_743_equation_0, values = (var_605_cast_fp16, var_357_cast_fp16))[name = tensor("op_743_cast_fp16")]; + tensor var_744_to_fp16 = const()[name = tensor("op_744_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_29_cast_fp16 = mul(x = var_743_cast_fp16, y = var_744_to_fp16)[name = tensor("aw_chunk_29_cast_fp16")]; + tensor var_747_equation_0 = const()[name = tensor("op_747_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_747_cast_fp16 = einsum(equation = var_747_equation_0, values = (var_605_cast_fp16, var_364_cast_fp16))[name = tensor("op_747_cast_fp16")]; + tensor var_748_to_fp16 = const()[name = tensor("op_748_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_31_cast_fp16 = mul(x = var_747_cast_fp16, y = var_748_to_fp16)[name = tensor("aw_chunk_31_cast_fp16")]; + tensor var_751_equation_0 = const()[name = tensor("op_751_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_751_cast_fp16 = einsum(equation = var_751_equation_0, values = (var_609_cast_fp16, var_371_cast_fp16))[name = tensor("op_751_cast_fp16")]; + tensor var_752_to_fp16 = const()[name = tensor("op_752_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_33_cast_fp16 = mul(x = var_751_cast_fp16, y = var_752_to_fp16)[name = tensor("aw_chunk_33_cast_fp16")]; + tensor var_755_equation_0 = const()[name = tensor("op_755_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_755_cast_fp16 = einsum(equation = var_755_equation_0, values = (var_609_cast_fp16, var_378_cast_fp16))[name = tensor("op_755_cast_fp16")]; + tensor var_756_to_fp16 = const()[name = tensor("op_756_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_35_cast_fp16 = mul(x = var_755_cast_fp16, y = var_756_to_fp16)[name = tensor("aw_chunk_35_cast_fp16")]; + tensor var_759_equation_0 = const()[name = tensor("op_759_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_759_cast_fp16 = einsum(equation = var_759_equation_0, values = (var_609_cast_fp16, var_385_cast_fp16))[name = tensor("op_759_cast_fp16")]; + tensor var_760_to_fp16 = const()[name = tensor("op_760_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_37_cast_fp16 = mul(x = var_759_cast_fp16, y = var_760_to_fp16)[name = tensor("aw_chunk_37_cast_fp16")]; + tensor var_763_equation_0 = const()[name = tensor("op_763_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_763_cast_fp16 = einsum(equation = var_763_equation_0, values = (var_609_cast_fp16, var_392_cast_fp16))[name = tensor("op_763_cast_fp16")]; + tensor var_764_to_fp16 = const()[name = tensor("op_764_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_39_cast_fp16 = mul(x = var_763_cast_fp16, y = var_764_to_fp16)[name = tensor("aw_chunk_39_cast_fp16")]; + tensor var_767_equation_0 = const()[name = tensor("op_767_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_767_cast_fp16 = einsum(equation = var_767_equation_0, values = (var_613_cast_fp16, var_399_cast_fp16))[name = tensor("op_767_cast_fp16")]; + tensor var_768_to_fp16 = const()[name = tensor("op_768_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_41_cast_fp16 = mul(x = var_767_cast_fp16, y = var_768_to_fp16)[name = tensor("aw_chunk_41_cast_fp16")]; + tensor var_771_equation_0 = const()[name = tensor("op_771_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_771_cast_fp16 = einsum(equation = var_771_equation_0, values = (var_613_cast_fp16, var_406_cast_fp16))[name = tensor("op_771_cast_fp16")]; + tensor var_772_to_fp16 = const()[name = tensor("op_772_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_43_cast_fp16 = mul(x = var_771_cast_fp16, y = var_772_to_fp16)[name = tensor("aw_chunk_43_cast_fp16")]; + tensor var_775_equation_0 = const()[name = tensor("op_775_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_775_cast_fp16 = einsum(equation = var_775_equation_0, values = (var_613_cast_fp16, var_413_cast_fp16))[name = tensor("op_775_cast_fp16")]; + tensor var_776_to_fp16 = const()[name = tensor("op_776_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_45_cast_fp16 = mul(x = var_775_cast_fp16, y = var_776_to_fp16)[name = tensor("aw_chunk_45_cast_fp16")]; + tensor var_779_equation_0 = const()[name = tensor("op_779_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_779_cast_fp16 = einsum(equation = var_779_equation_0, values = (var_613_cast_fp16, var_420_cast_fp16))[name = tensor("op_779_cast_fp16")]; + tensor var_780_to_fp16 = const()[name = tensor("op_780_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_47_cast_fp16 = mul(x = var_779_cast_fp16, y = var_780_to_fp16)[name = tensor("aw_chunk_47_cast_fp16")]; + tensor var_783_equation_0 = const()[name = tensor("op_783_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_783_cast_fp16 = einsum(equation = var_783_equation_0, values = (var_617_cast_fp16, var_427_cast_fp16))[name = tensor("op_783_cast_fp16")]; + tensor var_784_to_fp16 = const()[name = tensor("op_784_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_49_cast_fp16 = mul(x = var_783_cast_fp16, y = var_784_to_fp16)[name = tensor("aw_chunk_49_cast_fp16")]; + tensor var_787_equation_0 = const()[name = tensor("op_787_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_787_cast_fp16 = einsum(equation = var_787_equation_0, values = (var_617_cast_fp16, var_434_cast_fp16))[name = tensor("op_787_cast_fp16")]; + tensor var_788_to_fp16 = const()[name = tensor("op_788_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_51_cast_fp16 = mul(x = var_787_cast_fp16, y = var_788_to_fp16)[name = tensor("aw_chunk_51_cast_fp16")]; + tensor var_791_equation_0 = const()[name = tensor("op_791_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_791_cast_fp16 = einsum(equation = var_791_equation_0, values = (var_617_cast_fp16, var_441_cast_fp16))[name = tensor("op_791_cast_fp16")]; + tensor var_792_to_fp16 = const()[name = tensor("op_792_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_53_cast_fp16 = mul(x = var_791_cast_fp16, y = var_792_to_fp16)[name = tensor("aw_chunk_53_cast_fp16")]; + tensor var_795_equation_0 = const()[name = tensor("op_795_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_795_cast_fp16 = einsum(equation = var_795_equation_0, values = (var_617_cast_fp16, var_448_cast_fp16))[name = tensor("op_795_cast_fp16")]; + tensor var_796_to_fp16 = const()[name = tensor("op_796_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_55_cast_fp16 = mul(x = var_795_cast_fp16, y = var_796_to_fp16)[name = tensor("aw_chunk_55_cast_fp16")]; + tensor var_799_equation_0 = const()[name = tensor("op_799_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_799_cast_fp16 = einsum(equation = var_799_equation_0, values = (var_621_cast_fp16, var_455_cast_fp16))[name = tensor("op_799_cast_fp16")]; + tensor var_800_to_fp16 = const()[name = tensor("op_800_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_57_cast_fp16 = mul(x = var_799_cast_fp16, y = var_800_to_fp16)[name = tensor("aw_chunk_57_cast_fp16")]; + tensor var_803_equation_0 = const()[name = tensor("op_803_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_803_cast_fp16 = einsum(equation = var_803_equation_0, values = (var_621_cast_fp16, var_462_cast_fp16))[name = tensor("op_803_cast_fp16")]; + tensor var_804_to_fp16 = const()[name = tensor("op_804_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_59_cast_fp16 = mul(x = var_803_cast_fp16, y = var_804_to_fp16)[name = tensor("aw_chunk_59_cast_fp16")]; + tensor var_807_equation_0 = const()[name = tensor("op_807_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_807_cast_fp16 = einsum(equation = var_807_equation_0, values = (var_621_cast_fp16, var_469_cast_fp16))[name = tensor("op_807_cast_fp16")]; + tensor var_808_to_fp16 = const()[name = tensor("op_808_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_61_cast_fp16 = mul(x = var_807_cast_fp16, y = var_808_to_fp16)[name = tensor("aw_chunk_61_cast_fp16")]; + tensor var_811_equation_0 = const()[name = tensor("op_811_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_811_cast_fp16 = einsum(equation = var_811_equation_0, values = (var_621_cast_fp16, var_476_cast_fp16))[name = tensor("op_811_cast_fp16")]; + tensor var_812_to_fp16 = const()[name = tensor("op_812_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_63_cast_fp16 = mul(x = var_811_cast_fp16, y = var_812_to_fp16)[name = tensor("aw_chunk_63_cast_fp16")]; + tensor var_815_equation_0 = const()[name = tensor("op_815_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_815_cast_fp16 = einsum(equation = var_815_equation_0, values = (var_625_cast_fp16, var_483_cast_fp16))[name = tensor("op_815_cast_fp16")]; + tensor var_816_to_fp16 = const()[name = tensor("op_816_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_65_cast_fp16 = mul(x = var_815_cast_fp16, y = var_816_to_fp16)[name = tensor("aw_chunk_65_cast_fp16")]; + tensor var_819_equation_0 = const()[name = tensor("op_819_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_819_cast_fp16 = einsum(equation = var_819_equation_0, values = (var_625_cast_fp16, var_490_cast_fp16))[name = tensor("op_819_cast_fp16")]; + tensor var_820_to_fp16 = const()[name = tensor("op_820_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_67_cast_fp16 = mul(x = var_819_cast_fp16, y = var_820_to_fp16)[name = tensor("aw_chunk_67_cast_fp16")]; + tensor var_823_equation_0 = const()[name = tensor("op_823_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_823_cast_fp16 = einsum(equation = var_823_equation_0, values = (var_625_cast_fp16, var_497_cast_fp16))[name = tensor("op_823_cast_fp16")]; + tensor var_824_to_fp16 = const()[name = tensor("op_824_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_69_cast_fp16 = mul(x = var_823_cast_fp16, y = var_824_to_fp16)[name = tensor("aw_chunk_69_cast_fp16")]; + tensor var_827_equation_0 = const()[name = tensor("op_827_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_827_cast_fp16 = einsum(equation = var_827_equation_0, values = (var_625_cast_fp16, var_504_cast_fp16))[name = tensor("op_827_cast_fp16")]; + tensor var_828_to_fp16 = const()[name = tensor("op_828_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_71_cast_fp16 = mul(x = var_827_cast_fp16, y = var_828_to_fp16)[name = tensor("aw_chunk_71_cast_fp16")]; + tensor var_831_equation_0 = const()[name = tensor("op_831_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_831_cast_fp16 = einsum(equation = var_831_equation_0, values = (var_629_cast_fp16, var_511_cast_fp16))[name = tensor("op_831_cast_fp16")]; + tensor var_832_to_fp16 = const()[name = tensor("op_832_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_73_cast_fp16 = mul(x = var_831_cast_fp16, y = var_832_to_fp16)[name = tensor("aw_chunk_73_cast_fp16")]; + tensor var_835_equation_0 = const()[name = tensor("op_835_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_835_cast_fp16 = einsum(equation = var_835_equation_0, values = (var_629_cast_fp16, var_518_cast_fp16))[name = tensor("op_835_cast_fp16")]; + tensor var_836_to_fp16 = const()[name = tensor("op_836_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_75_cast_fp16 = mul(x = var_835_cast_fp16, y = var_836_to_fp16)[name = tensor("aw_chunk_75_cast_fp16")]; + tensor var_839_equation_0 = const()[name = tensor("op_839_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_839_cast_fp16 = einsum(equation = var_839_equation_0, values = (var_629_cast_fp16, var_525_cast_fp16))[name = tensor("op_839_cast_fp16")]; + tensor var_840_to_fp16 = const()[name = tensor("op_840_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_77_cast_fp16 = mul(x = var_839_cast_fp16, y = var_840_to_fp16)[name = tensor("aw_chunk_77_cast_fp16")]; + tensor var_843_equation_0 = const()[name = tensor("op_843_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_843_cast_fp16 = einsum(equation = var_843_equation_0, values = (var_629_cast_fp16, var_532_cast_fp16))[name = tensor("op_843_cast_fp16")]; + tensor var_844_to_fp16 = const()[name = tensor("op_844_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_79_cast_fp16 = mul(x = var_843_cast_fp16, y = var_844_to_fp16)[name = tensor("aw_chunk_79_cast_fp16")]; + tensor var_847_equation_0 = const()[name = tensor("op_847_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_847_cast_fp16 = einsum(equation = var_847_equation_0, values = (var_633_cast_fp16, var_539_cast_fp16))[name = tensor("op_847_cast_fp16")]; + tensor var_848_to_fp16 = const()[name = tensor("op_848_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_81_cast_fp16 = mul(x = var_847_cast_fp16, y = var_848_to_fp16)[name = tensor("aw_chunk_81_cast_fp16")]; + tensor var_851_equation_0 = const()[name = tensor("op_851_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_851_cast_fp16 = einsum(equation = var_851_equation_0, values = (var_633_cast_fp16, var_546_cast_fp16))[name = tensor("op_851_cast_fp16")]; + tensor var_852_to_fp16 = const()[name = tensor("op_852_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_83_cast_fp16 = mul(x = var_851_cast_fp16, y = var_852_to_fp16)[name = tensor("aw_chunk_83_cast_fp16")]; + tensor var_855_equation_0 = const()[name = tensor("op_855_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_855_cast_fp16 = einsum(equation = var_855_equation_0, values = (var_633_cast_fp16, var_553_cast_fp16))[name = tensor("op_855_cast_fp16")]; + tensor var_856_to_fp16 = const()[name = tensor("op_856_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_85_cast_fp16 = mul(x = var_855_cast_fp16, y = var_856_to_fp16)[name = tensor("aw_chunk_85_cast_fp16")]; + tensor var_859_equation_0 = const()[name = tensor("op_859_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_859_cast_fp16 = einsum(equation = var_859_equation_0, values = (var_633_cast_fp16, var_560_cast_fp16))[name = tensor("op_859_cast_fp16")]; + tensor var_860_to_fp16 = const()[name = tensor("op_860_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_87_cast_fp16 = mul(x = var_859_cast_fp16, y = var_860_to_fp16)[name = tensor("aw_chunk_87_cast_fp16")]; + tensor var_863_equation_0 = const()[name = tensor("op_863_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_863_cast_fp16 = einsum(equation = var_863_equation_0, values = (var_637_cast_fp16, var_567_cast_fp16))[name = tensor("op_863_cast_fp16")]; + tensor var_864_to_fp16 = const()[name = tensor("op_864_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_89_cast_fp16 = mul(x = var_863_cast_fp16, y = var_864_to_fp16)[name = tensor("aw_chunk_89_cast_fp16")]; + tensor var_867_equation_0 = const()[name = tensor("op_867_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_867_cast_fp16 = einsum(equation = var_867_equation_0, values = (var_637_cast_fp16, var_574_cast_fp16))[name = tensor("op_867_cast_fp16")]; + tensor var_868_to_fp16 = const()[name = tensor("op_868_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_91_cast_fp16 = mul(x = var_867_cast_fp16, y = var_868_to_fp16)[name = tensor("aw_chunk_91_cast_fp16")]; + tensor var_871_equation_0 = const()[name = tensor("op_871_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_871_cast_fp16 = einsum(equation = var_871_equation_0, values = (var_637_cast_fp16, var_581_cast_fp16))[name = tensor("op_871_cast_fp16")]; + tensor var_872_to_fp16 = const()[name = tensor("op_872_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_93_cast_fp16 = mul(x = var_871_cast_fp16, y = var_872_to_fp16)[name = tensor("aw_chunk_93_cast_fp16")]; + tensor var_875_equation_0 = const()[name = tensor("op_875_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_875_cast_fp16 = einsum(equation = var_875_equation_0, values = (var_637_cast_fp16, var_588_cast_fp16))[name = tensor("op_875_cast_fp16")]; + tensor var_876_to_fp16 = const()[name = tensor("op_876_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_95_cast_fp16 = mul(x = var_875_cast_fp16, y = var_876_to_fp16)[name = tensor("aw_chunk_95_cast_fp16")]; + tensor var_878_cast_fp16 = softmax(axis = var_151, x = aw_chunk_1_cast_fp16)[name = tensor("op_878_cast_fp16")]; + tensor var_879_cast_fp16 = softmax(axis = var_151, x = aw_chunk_3_cast_fp16)[name = tensor("op_879_cast_fp16")]; + tensor var_880_cast_fp16 = softmax(axis = var_151, x = aw_chunk_5_cast_fp16)[name = tensor("op_880_cast_fp16")]; + tensor var_881_cast_fp16 = softmax(axis = var_151, x = aw_chunk_7_cast_fp16)[name = tensor("op_881_cast_fp16")]; + tensor var_882_cast_fp16 = softmax(axis = var_151, x = aw_chunk_9_cast_fp16)[name = tensor("op_882_cast_fp16")]; + tensor var_883_cast_fp16 = softmax(axis = var_151, x = aw_chunk_11_cast_fp16)[name = tensor("op_883_cast_fp16")]; + tensor var_884_cast_fp16 = softmax(axis = var_151, x = aw_chunk_13_cast_fp16)[name = tensor("op_884_cast_fp16")]; + tensor var_885_cast_fp16 = softmax(axis = var_151, x = aw_chunk_15_cast_fp16)[name = tensor("op_885_cast_fp16")]; + tensor var_886_cast_fp16 = softmax(axis = var_151, x = aw_chunk_17_cast_fp16)[name = tensor("op_886_cast_fp16")]; + tensor var_887_cast_fp16 = softmax(axis = var_151, x = aw_chunk_19_cast_fp16)[name = tensor("op_887_cast_fp16")]; + tensor var_888_cast_fp16 = softmax(axis = var_151, x = aw_chunk_21_cast_fp16)[name = tensor("op_888_cast_fp16")]; + tensor var_889_cast_fp16 = softmax(axis = var_151, x = aw_chunk_23_cast_fp16)[name = tensor("op_889_cast_fp16")]; + tensor var_890_cast_fp16 = softmax(axis = var_151, x = aw_chunk_25_cast_fp16)[name = tensor("op_890_cast_fp16")]; + tensor var_891_cast_fp16 = softmax(axis = var_151, x = aw_chunk_27_cast_fp16)[name = tensor("op_891_cast_fp16")]; + tensor var_892_cast_fp16 = softmax(axis = var_151, x = aw_chunk_29_cast_fp16)[name = tensor("op_892_cast_fp16")]; + tensor var_893_cast_fp16 = softmax(axis = var_151, x = aw_chunk_31_cast_fp16)[name = tensor("op_893_cast_fp16")]; + tensor var_894_cast_fp16 = softmax(axis = var_151, x = aw_chunk_33_cast_fp16)[name = tensor("op_894_cast_fp16")]; + tensor var_895_cast_fp16 = softmax(axis = var_151, x = aw_chunk_35_cast_fp16)[name = tensor("op_895_cast_fp16")]; + tensor var_896_cast_fp16 = softmax(axis = var_151, x = aw_chunk_37_cast_fp16)[name = tensor("op_896_cast_fp16")]; + tensor var_897_cast_fp16 = softmax(axis = var_151, x = aw_chunk_39_cast_fp16)[name = tensor("op_897_cast_fp16")]; + tensor var_898_cast_fp16 = softmax(axis = var_151, x = aw_chunk_41_cast_fp16)[name = tensor("op_898_cast_fp16")]; + tensor var_899_cast_fp16 = softmax(axis = var_151, x = aw_chunk_43_cast_fp16)[name = tensor("op_899_cast_fp16")]; + tensor var_900_cast_fp16 = softmax(axis = var_151, x = aw_chunk_45_cast_fp16)[name = tensor("op_900_cast_fp16")]; + tensor var_901_cast_fp16 = softmax(axis = var_151, x = aw_chunk_47_cast_fp16)[name = tensor("op_901_cast_fp16")]; + tensor var_902_cast_fp16 = softmax(axis = var_151, x = aw_chunk_49_cast_fp16)[name = tensor("op_902_cast_fp16")]; + tensor var_903_cast_fp16 = softmax(axis = var_151, x = aw_chunk_51_cast_fp16)[name = tensor("op_903_cast_fp16")]; + tensor var_904_cast_fp16 = softmax(axis = var_151, x = aw_chunk_53_cast_fp16)[name = tensor("op_904_cast_fp16")]; + tensor var_905_cast_fp16 = softmax(axis = var_151, x = aw_chunk_55_cast_fp16)[name = tensor("op_905_cast_fp16")]; + tensor var_906_cast_fp16 = softmax(axis = var_151, x = aw_chunk_57_cast_fp16)[name = tensor("op_906_cast_fp16")]; + tensor var_907_cast_fp16 = softmax(axis = var_151, x = aw_chunk_59_cast_fp16)[name = tensor("op_907_cast_fp16")]; + tensor var_908_cast_fp16 = softmax(axis = var_151, x = aw_chunk_61_cast_fp16)[name = tensor("op_908_cast_fp16")]; + tensor var_909_cast_fp16 = softmax(axis = var_151, x = aw_chunk_63_cast_fp16)[name = tensor("op_909_cast_fp16")]; + tensor var_910_cast_fp16 = softmax(axis = var_151, x = aw_chunk_65_cast_fp16)[name = tensor("op_910_cast_fp16")]; + tensor var_911_cast_fp16 = softmax(axis = var_151, x = aw_chunk_67_cast_fp16)[name = tensor("op_911_cast_fp16")]; + tensor var_912_cast_fp16 = softmax(axis = var_151, x = aw_chunk_69_cast_fp16)[name = tensor("op_912_cast_fp16")]; + tensor var_913_cast_fp16 = softmax(axis = var_151, x = aw_chunk_71_cast_fp16)[name = tensor("op_913_cast_fp16")]; + tensor var_914_cast_fp16 = softmax(axis = var_151, x = aw_chunk_73_cast_fp16)[name = tensor("op_914_cast_fp16")]; + tensor var_915_cast_fp16 = softmax(axis = var_151, x = aw_chunk_75_cast_fp16)[name = tensor("op_915_cast_fp16")]; + tensor var_916_cast_fp16 = softmax(axis = var_151, x = aw_chunk_77_cast_fp16)[name = tensor("op_916_cast_fp16")]; + tensor var_917_cast_fp16 = softmax(axis = var_151, x = aw_chunk_79_cast_fp16)[name = tensor("op_917_cast_fp16")]; + tensor var_918_cast_fp16 = softmax(axis = var_151, x = aw_chunk_81_cast_fp16)[name = tensor("op_918_cast_fp16")]; + tensor var_919_cast_fp16 = softmax(axis = var_151, x = aw_chunk_83_cast_fp16)[name = tensor("op_919_cast_fp16")]; + tensor var_920_cast_fp16 = softmax(axis = var_151, x = aw_chunk_85_cast_fp16)[name = tensor("op_920_cast_fp16")]; + tensor var_921_cast_fp16 = softmax(axis = var_151, x = aw_chunk_87_cast_fp16)[name = tensor("op_921_cast_fp16")]; + tensor var_922_cast_fp16 = softmax(axis = var_151, x = aw_chunk_89_cast_fp16)[name = tensor("op_922_cast_fp16")]; + tensor var_923_cast_fp16 = softmax(axis = var_151, x = aw_chunk_91_cast_fp16)[name = tensor("op_923_cast_fp16")]; + tensor var_924_cast_fp16 = softmax(axis = var_151, x = aw_chunk_93_cast_fp16)[name = tensor("op_924_cast_fp16")]; + tensor var_925_cast_fp16 = softmax(axis = var_151, x = aw_chunk_95_cast_fp16)[name = tensor("op_925_cast_fp16")]; + tensor var_927_equation_0 = const()[name = tensor("op_927_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_927_cast_fp16 = einsum(equation = var_927_equation_0, values = (var_639_cast_fp16, var_878_cast_fp16))[name = tensor("op_927_cast_fp16")]; + tensor var_929_equation_0 = const()[name = tensor("op_929_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_929_cast_fp16 = einsum(equation = var_929_equation_0, values = (var_639_cast_fp16, var_879_cast_fp16))[name = tensor("op_929_cast_fp16")]; + tensor var_931_equation_0 = const()[name = tensor("op_931_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_931_cast_fp16 = einsum(equation = var_931_equation_0, values = (var_639_cast_fp16, var_880_cast_fp16))[name = tensor("op_931_cast_fp16")]; + tensor var_933_equation_0 = const()[name = tensor("op_933_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_933_cast_fp16 = einsum(equation = var_933_equation_0, values = (var_639_cast_fp16, var_881_cast_fp16))[name = tensor("op_933_cast_fp16")]; + tensor var_935_equation_0 = const()[name = tensor("op_935_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_935_cast_fp16 = einsum(equation = var_935_equation_0, values = (var_643_cast_fp16, var_882_cast_fp16))[name = tensor("op_935_cast_fp16")]; + tensor var_937_equation_0 = const()[name = tensor("op_937_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_937_cast_fp16 = einsum(equation = var_937_equation_0, values = (var_643_cast_fp16, var_883_cast_fp16))[name = tensor("op_937_cast_fp16")]; + tensor var_939_equation_0 = const()[name = tensor("op_939_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_939_cast_fp16 = einsum(equation = var_939_equation_0, values = (var_643_cast_fp16, var_884_cast_fp16))[name = tensor("op_939_cast_fp16")]; + tensor var_941_equation_0 = const()[name = tensor("op_941_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_941_cast_fp16 = einsum(equation = var_941_equation_0, values = (var_643_cast_fp16, var_885_cast_fp16))[name = tensor("op_941_cast_fp16")]; + tensor var_943_equation_0 = const()[name = tensor("op_943_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_943_cast_fp16 = einsum(equation = var_943_equation_0, values = (var_647_cast_fp16, var_886_cast_fp16))[name = tensor("op_943_cast_fp16")]; + tensor var_945_equation_0 = const()[name = tensor("op_945_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_945_cast_fp16 = einsum(equation = var_945_equation_0, values = (var_647_cast_fp16, var_887_cast_fp16))[name = tensor("op_945_cast_fp16")]; + tensor var_947_equation_0 = const()[name = tensor("op_947_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_947_cast_fp16 = einsum(equation = var_947_equation_0, values = (var_647_cast_fp16, var_888_cast_fp16))[name = tensor("op_947_cast_fp16")]; + tensor var_949_equation_0 = const()[name = tensor("op_949_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_949_cast_fp16 = einsum(equation = var_949_equation_0, values = (var_647_cast_fp16, var_889_cast_fp16))[name = tensor("op_949_cast_fp16")]; + tensor var_951_equation_0 = const()[name = tensor("op_951_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_951_cast_fp16 = einsum(equation = var_951_equation_0, values = (var_651_cast_fp16, var_890_cast_fp16))[name = tensor("op_951_cast_fp16")]; + tensor var_953_equation_0 = const()[name = tensor("op_953_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_953_cast_fp16 = einsum(equation = var_953_equation_0, values = (var_651_cast_fp16, var_891_cast_fp16))[name = tensor("op_953_cast_fp16")]; + tensor var_955_equation_0 = const()[name = tensor("op_955_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_955_cast_fp16 = einsum(equation = var_955_equation_0, values = (var_651_cast_fp16, var_892_cast_fp16))[name = tensor("op_955_cast_fp16")]; + tensor var_957_equation_0 = const()[name = tensor("op_957_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_957_cast_fp16 = einsum(equation = var_957_equation_0, values = (var_651_cast_fp16, var_893_cast_fp16))[name = tensor("op_957_cast_fp16")]; + tensor var_959_equation_0 = const()[name = tensor("op_959_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_959_cast_fp16 = einsum(equation = var_959_equation_0, values = (var_655_cast_fp16, var_894_cast_fp16))[name = tensor("op_959_cast_fp16")]; + tensor var_961_equation_0 = const()[name = tensor("op_961_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_961_cast_fp16 = einsum(equation = var_961_equation_0, values = (var_655_cast_fp16, var_895_cast_fp16))[name = tensor("op_961_cast_fp16")]; + tensor var_963_equation_0 = const()[name = tensor("op_963_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_963_cast_fp16 = einsum(equation = var_963_equation_0, values = (var_655_cast_fp16, var_896_cast_fp16))[name = tensor("op_963_cast_fp16")]; + tensor var_965_equation_0 = const()[name = tensor("op_965_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_965_cast_fp16 = einsum(equation = var_965_equation_0, values = (var_655_cast_fp16, var_897_cast_fp16))[name = tensor("op_965_cast_fp16")]; + tensor var_967_equation_0 = const()[name = tensor("op_967_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_967_cast_fp16 = einsum(equation = var_967_equation_0, values = (var_659_cast_fp16, var_898_cast_fp16))[name = tensor("op_967_cast_fp16")]; + tensor var_969_equation_0 = const()[name = tensor("op_969_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_969_cast_fp16 = einsum(equation = var_969_equation_0, values = (var_659_cast_fp16, var_899_cast_fp16))[name = tensor("op_969_cast_fp16")]; + tensor var_971_equation_0 = const()[name = tensor("op_971_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_971_cast_fp16 = einsum(equation = var_971_equation_0, values = (var_659_cast_fp16, var_900_cast_fp16))[name = tensor("op_971_cast_fp16")]; + tensor var_973_equation_0 = const()[name = tensor("op_973_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_973_cast_fp16 = einsum(equation = var_973_equation_0, values = (var_659_cast_fp16, var_901_cast_fp16))[name = tensor("op_973_cast_fp16")]; + tensor var_975_equation_0 = const()[name = tensor("op_975_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_975_cast_fp16 = einsum(equation = var_975_equation_0, values = (var_663_cast_fp16, var_902_cast_fp16))[name = tensor("op_975_cast_fp16")]; + tensor var_977_equation_0 = const()[name = tensor("op_977_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_977_cast_fp16 = einsum(equation = var_977_equation_0, values = (var_663_cast_fp16, var_903_cast_fp16))[name = tensor("op_977_cast_fp16")]; + tensor var_979_equation_0 = const()[name = tensor("op_979_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_979_cast_fp16 = einsum(equation = var_979_equation_0, values = (var_663_cast_fp16, var_904_cast_fp16))[name = tensor("op_979_cast_fp16")]; + tensor var_981_equation_0 = const()[name = tensor("op_981_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_981_cast_fp16 = einsum(equation = var_981_equation_0, values = (var_663_cast_fp16, var_905_cast_fp16))[name = tensor("op_981_cast_fp16")]; + tensor var_983_equation_0 = const()[name = tensor("op_983_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_983_cast_fp16 = einsum(equation = var_983_equation_0, values = (var_667_cast_fp16, var_906_cast_fp16))[name = tensor("op_983_cast_fp16")]; + tensor var_985_equation_0 = const()[name = tensor("op_985_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_985_cast_fp16 = einsum(equation = var_985_equation_0, values = (var_667_cast_fp16, var_907_cast_fp16))[name = tensor("op_985_cast_fp16")]; + tensor var_987_equation_0 = const()[name = tensor("op_987_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_987_cast_fp16 = einsum(equation = var_987_equation_0, values = (var_667_cast_fp16, var_908_cast_fp16))[name = tensor("op_987_cast_fp16")]; + tensor var_989_equation_0 = const()[name = tensor("op_989_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_989_cast_fp16 = einsum(equation = var_989_equation_0, values = (var_667_cast_fp16, var_909_cast_fp16))[name = tensor("op_989_cast_fp16")]; + tensor var_991_equation_0 = const()[name = tensor("op_991_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_991_cast_fp16 = einsum(equation = var_991_equation_0, values = (var_671_cast_fp16, var_910_cast_fp16))[name = tensor("op_991_cast_fp16")]; + tensor var_993_equation_0 = const()[name = tensor("op_993_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_993_cast_fp16 = einsum(equation = var_993_equation_0, values = (var_671_cast_fp16, var_911_cast_fp16))[name = tensor("op_993_cast_fp16")]; + tensor var_995_equation_0 = const()[name = tensor("op_995_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_995_cast_fp16 = einsum(equation = var_995_equation_0, values = (var_671_cast_fp16, var_912_cast_fp16))[name = tensor("op_995_cast_fp16")]; + tensor var_997_equation_0 = const()[name = tensor("op_997_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_997_cast_fp16 = einsum(equation = var_997_equation_0, values = (var_671_cast_fp16, var_913_cast_fp16))[name = tensor("op_997_cast_fp16")]; + tensor var_999_equation_0 = const()[name = tensor("op_999_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_999_cast_fp16 = einsum(equation = var_999_equation_0, values = (var_675_cast_fp16, var_914_cast_fp16))[name = tensor("op_999_cast_fp16")]; + tensor var_1001_equation_0 = const()[name = tensor("op_1001_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1001_cast_fp16 = einsum(equation = var_1001_equation_0, values = (var_675_cast_fp16, var_915_cast_fp16))[name = tensor("op_1001_cast_fp16")]; + tensor var_1003_equation_0 = const()[name = tensor("op_1003_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1003_cast_fp16 = einsum(equation = var_1003_equation_0, values = (var_675_cast_fp16, var_916_cast_fp16))[name = tensor("op_1003_cast_fp16")]; + tensor var_1005_equation_0 = const()[name = tensor("op_1005_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1005_cast_fp16 = einsum(equation = var_1005_equation_0, values = (var_675_cast_fp16, var_917_cast_fp16))[name = tensor("op_1005_cast_fp16")]; + tensor var_1007_equation_0 = const()[name = tensor("op_1007_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1007_cast_fp16 = einsum(equation = var_1007_equation_0, values = (var_679_cast_fp16, var_918_cast_fp16))[name = tensor("op_1007_cast_fp16")]; + tensor var_1009_equation_0 = const()[name = tensor("op_1009_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1009_cast_fp16 = einsum(equation = var_1009_equation_0, values = (var_679_cast_fp16, var_919_cast_fp16))[name = tensor("op_1009_cast_fp16")]; + tensor var_1011_equation_0 = const()[name = tensor("op_1011_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1011_cast_fp16 = einsum(equation = var_1011_equation_0, values = (var_679_cast_fp16, var_920_cast_fp16))[name = tensor("op_1011_cast_fp16")]; + tensor var_1013_equation_0 = const()[name = tensor("op_1013_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1013_cast_fp16 = einsum(equation = var_1013_equation_0, values = (var_679_cast_fp16, var_921_cast_fp16))[name = tensor("op_1013_cast_fp16")]; + tensor var_1015_equation_0 = const()[name = tensor("op_1015_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1015_cast_fp16 = einsum(equation = var_1015_equation_0, values = (var_683_cast_fp16, var_922_cast_fp16))[name = tensor("op_1015_cast_fp16")]; + tensor var_1017_equation_0 = const()[name = tensor("op_1017_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1017_cast_fp16 = einsum(equation = var_1017_equation_0, values = (var_683_cast_fp16, var_923_cast_fp16))[name = tensor("op_1017_cast_fp16")]; + tensor var_1019_equation_0 = const()[name = tensor("op_1019_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1019_cast_fp16 = einsum(equation = var_1019_equation_0, values = (var_683_cast_fp16, var_924_cast_fp16))[name = tensor("op_1019_cast_fp16")]; + tensor var_1021_equation_0 = const()[name = tensor("op_1021_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1021_cast_fp16 = einsum(equation = var_1021_equation_0, values = (var_683_cast_fp16, var_925_cast_fp16))[name = tensor("op_1021_cast_fp16")]; + tensor var_1023_interleave_0 = const()[name = tensor("op_1023_interleave_0"), val = tensor(false)]; + tensor var_1023_cast_fp16 = concat(axis = var_134, interleave = var_1023_interleave_0, values = (var_927_cast_fp16, var_929_cast_fp16, var_931_cast_fp16, var_933_cast_fp16))[name = tensor("op_1023_cast_fp16")]; + tensor var_1025_interleave_0 = const()[name = tensor("op_1025_interleave_0"), val = tensor(false)]; + tensor var_1025_cast_fp16 = concat(axis = var_134, interleave = var_1025_interleave_0, values = (var_935_cast_fp16, var_937_cast_fp16, var_939_cast_fp16, var_941_cast_fp16))[name = tensor("op_1025_cast_fp16")]; + tensor var_1027_interleave_0 = const()[name = tensor("op_1027_interleave_0"), val = tensor(false)]; + tensor var_1027_cast_fp16 = concat(axis = var_134, interleave = var_1027_interleave_0, values = (var_943_cast_fp16, var_945_cast_fp16, var_947_cast_fp16, var_949_cast_fp16))[name = tensor("op_1027_cast_fp16")]; + tensor var_1029_interleave_0 = const()[name = tensor("op_1029_interleave_0"), val = tensor(false)]; + tensor var_1029_cast_fp16 = concat(axis = var_134, interleave = var_1029_interleave_0, values = (var_951_cast_fp16, var_953_cast_fp16, var_955_cast_fp16, var_957_cast_fp16))[name = tensor("op_1029_cast_fp16")]; + tensor var_1031_interleave_0 = const()[name = tensor("op_1031_interleave_0"), val = tensor(false)]; + tensor var_1031_cast_fp16 = concat(axis = var_134, interleave = var_1031_interleave_0, values = (var_959_cast_fp16, var_961_cast_fp16, var_963_cast_fp16, var_965_cast_fp16))[name = tensor("op_1031_cast_fp16")]; + tensor var_1033_interleave_0 = const()[name = tensor("op_1033_interleave_0"), val = tensor(false)]; + tensor var_1033_cast_fp16 = concat(axis = var_134, interleave = var_1033_interleave_0, values = (var_967_cast_fp16, var_969_cast_fp16, var_971_cast_fp16, var_973_cast_fp16))[name = tensor("op_1033_cast_fp16")]; + tensor var_1035_interleave_0 = const()[name = tensor("op_1035_interleave_0"), val = tensor(false)]; + tensor var_1035_cast_fp16 = concat(axis = var_134, interleave = var_1035_interleave_0, values = (var_975_cast_fp16, var_977_cast_fp16, var_979_cast_fp16, var_981_cast_fp16))[name = tensor("op_1035_cast_fp16")]; + tensor var_1037_interleave_0 = const()[name = tensor("op_1037_interleave_0"), val = tensor(false)]; + tensor var_1037_cast_fp16 = concat(axis = var_134, interleave = var_1037_interleave_0, values = (var_983_cast_fp16, var_985_cast_fp16, var_987_cast_fp16, var_989_cast_fp16))[name = tensor("op_1037_cast_fp16")]; + tensor var_1039_interleave_0 = const()[name = tensor("op_1039_interleave_0"), val = tensor(false)]; + tensor var_1039_cast_fp16 = concat(axis = var_134, interleave = var_1039_interleave_0, values = (var_991_cast_fp16, var_993_cast_fp16, var_995_cast_fp16, var_997_cast_fp16))[name = tensor("op_1039_cast_fp16")]; + tensor var_1041_interleave_0 = const()[name = tensor("op_1041_interleave_0"), val = tensor(false)]; + tensor var_1041_cast_fp16 = concat(axis = var_134, interleave = var_1041_interleave_0, values = (var_999_cast_fp16, var_1001_cast_fp16, var_1003_cast_fp16, var_1005_cast_fp16))[name = tensor("op_1041_cast_fp16")]; + tensor var_1043_interleave_0 = const()[name = tensor("op_1043_interleave_0"), val = tensor(false)]; + tensor var_1043_cast_fp16 = concat(axis = var_134, interleave = var_1043_interleave_0, values = (var_1007_cast_fp16, var_1009_cast_fp16, var_1011_cast_fp16, var_1013_cast_fp16))[name = tensor("op_1043_cast_fp16")]; + tensor var_1045_interleave_0 = const()[name = tensor("op_1045_interleave_0"), val = tensor(false)]; + tensor var_1045_cast_fp16 = concat(axis = var_134, interleave = var_1045_interleave_0, values = (var_1015_cast_fp16, var_1017_cast_fp16, var_1019_cast_fp16, var_1021_cast_fp16))[name = tensor("op_1045_cast_fp16")]; + tensor input_1_interleave_0 = const()[name = tensor("input_1_interleave_0"), val = tensor(false)]; + tensor input_1_cast_fp16 = concat(axis = var_151, interleave = input_1_interleave_0, values = (var_1023_cast_fp16, var_1025_cast_fp16, var_1027_cast_fp16, var_1029_cast_fp16, var_1031_cast_fp16, var_1033_cast_fp16, var_1035_cast_fp16, var_1037_cast_fp16, var_1039_cast_fp16, var_1041_cast_fp16, var_1043_cast_fp16, var_1045_cast_fp16))[name = tensor("input_1_cast_fp16")]; + tensor var_1050 = const()[name = tensor("op_1050"), val = tensor([1, 1])]; + tensor var_1052 = const()[name = tensor("op_1052"), val = tensor([1, 1])]; + tensor obj_3_pad_type_0 = const()[name = tensor("obj_3_pad_type_0"), val = tensor("custom")]; + tensor obj_3_pad_0 = const()[name = tensor("obj_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9763776)))]; + tensor layers_0_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10943488)))]; + tensor obj_3_cast_fp16 = conv(bias = layers_0_self_attn_o_proj_bias_to_fp16, dilations = var_1052, groups = var_151, pad = obj_3_pad_0, pad_type = obj_3_pad_type_0, strides = var_1050, weight = layers_0_self_attn_o_proj_weight_to_fp16, x = input_1_cast_fp16)[name = tensor("obj_3_cast_fp16")]; + tensor inputs_3_cast_fp16 = add(x = inputs_1_cast_fp16, y = obj_3_cast_fp16)[name = tensor("inputs_3_cast_fp16")]; + tensor var_1058 = const()[name = tensor("op_1058"), val = tensor([1])]; + tensor channels_mean_3_cast_fp16 = reduce_mean(axes = var_1058, keep_dims = var_152, x = inputs_3_cast_fp16)[name = tensor("channels_mean_3_cast_fp16")]; + tensor zero_mean_3_cast_fp16 = sub(x = inputs_3_cast_fp16, y = channels_mean_3_cast_fp16)[name = tensor("zero_mean_3_cast_fp16")]; + tensor zero_mean_sq_3_cast_fp16 = mul(x = zero_mean_3_cast_fp16, y = zero_mean_3_cast_fp16)[name = tensor("zero_mean_sq_3_cast_fp16")]; + tensor var_1062 = const()[name = tensor("op_1062"), val = tensor([1])]; + tensor var_1063_cast_fp16 = reduce_mean(axes = var_1062, keep_dims = var_152, x = zero_mean_sq_3_cast_fp16)[name = tensor("op_1063_cast_fp16")]; + tensor var_1064_to_fp16 = const()[name = tensor("op_1064_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1065_cast_fp16 = add(x = var_1063_cast_fp16, y = var_1064_to_fp16)[name = tensor("op_1065_cast_fp16")]; + tensor denom_3_epsilon_0_to_fp16 = const()[name = tensor("denom_3_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_3_cast_fp16 = rsqrt(epsilon = denom_3_epsilon_0_to_fp16, x = var_1065_cast_fp16)[name = tensor("denom_3_cast_fp16")]; + tensor out_3_cast_fp16 = mul(x = zero_mean_3_cast_fp16, y = denom_3_cast_fp16)[name = tensor("out_3_cast_fp16")]; + tensor input_3_gamma_0_to_fp16 = const()[name = tensor("input_3_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10945088)))]; + tensor input_3_beta_0_to_fp16 = const()[name = tensor("input_3_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10946688)))]; + tensor input_3_epsilon_0_to_fp16 = const()[name = tensor("input_3_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_3_cast_fp16 = batch_norm(beta = input_3_beta_0_to_fp16, epsilon = input_3_epsilon_0_to_fp16, gamma = input_3_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_3_cast_fp16)[name = tensor("input_3_cast_fp16")]; + tensor var_1076 = const()[name = tensor("op_1076"), val = tensor([1, 1])]; + tensor var_1078 = const()[name = tensor("op_1078"), val = tensor([1, 1])]; + tensor input_5_pad_type_0 = const()[name = tensor("input_5_pad_type_0"), val = tensor("custom")]; + tensor input_5_pad_0 = const()[name = tensor("input_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_fc1_weight_to_fp16 = const()[name = tensor("layers_0_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10948288)))]; + tensor layers_0_fc1_bias_to_fp16 = const()[name = tensor("layers_0_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15666944)))]; + tensor input_5_cast_fp16 = conv(bias = layers_0_fc1_bias_to_fp16, dilations = var_1078, groups = var_151, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = var_1076, weight = layers_0_fc1_weight_to_fp16, x = input_3_cast_fp16)[name = tensor("input_5_cast_fp16")]; + tensor input_7_mode_0 = const()[name = tensor("input_7_mode_0"), val = tensor("EXACT")]; + tensor input_7_cast_fp16 = gelu(mode = input_7_mode_0, x = input_5_cast_fp16)[name = tensor("input_7_cast_fp16")]; + tensor var_1084 = const()[name = tensor("op_1084"), val = tensor([1, 1])]; + tensor var_1086 = const()[name = tensor("op_1086"), val = tensor([1, 1])]; + tensor hidden_states_5_pad_type_0 = const()[name = tensor("hidden_states_5_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_5_pad_0 = const()[name = tensor("hidden_states_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_fc2_weight_to_fp16 = const()[name = tensor("layers_0_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15673152)))]; + tensor layers_0_fc2_bias_to_fp16 = const()[name = tensor("layers_0_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20391808)))]; + tensor hidden_states_5_cast_fp16 = conv(bias = layers_0_fc2_bias_to_fp16, dilations = var_1086, groups = var_151, pad = hidden_states_5_pad_0, pad_type = hidden_states_5_pad_type_0, strides = var_1084, weight = layers_0_fc2_weight_to_fp16, x = input_7_cast_fp16)[name = tensor("hidden_states_5_cast_fp16")]; + tensor inputs_5_cast_fp16 = add(x = inputs_3_cast_fp16, y = hidden_states_5_cast_fp16)[name = tensor("inputs_5_cast_fp16")]; + tensor var_1093 = const()[name = tensor("op_1093"), val = tensor(3)]; + tensor var_1110 = const()[name = tensor("op_1110"), val = tensor(1)]; + tensor var_1111 = const()[name = tensor("op_1111"), val = tensor(true)]; + tensor var_1121 = const()[name = tensor("op_1121"), val = tensor([1])]; + tensor channels_mean_5_cast_fp16 = reduce_mean(axes = var_1121, keep_dims = var_1111, x = inputs_5_cast_fp16)[name = tensor("channels_mean_5_cast_fp16")]; + tensor zero_mean_5_cast_fp16 = sub(x = inputs_5_cast_fp16, y = channels_mean_5_cast_fp16)[name = tensor("zero_mean_5_cast_fp16")]; + tensor zero_mean_sq_5_cast_fp16 = mul(x = zero_mean_5_cast_fp16, y = zero_mean_5_cast_fp16)[name = tensor("zero_mean_sq_5_cast_fp16")]; + tensor var_1125 = const()[name = tensor("op_1125"), val = tensor([1])]; + tensor var_1126_cast_fp16 = reduce_mean(axes = var_1125, keep_dims = var_1111, x = zero_mean_sq_5_cast_fp16)[name = tensor("op_1126_cast_fp16")]; + tensor var_1127_to_fp16 = const()[name = tensor("op_1127_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1128_cast_fp16 = add(x = var_1126_cast_fp16, y = var_1127_to_fp16)[name = tensor("op_1128_cast_fp16")]; + tensor denom_5_epsilon_0_to_fp16 = const()[name = tensor("denom_5_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_5_cast_fp16 = rsqrt(epsilon = denom_5_epsilon_0_to_fp16, x = var_1128_cast_fp16)[name = tensor("denom_5_cast_fp16")]; + tensor out_5_cast_fp16 = mul(x = zero_mean_5_cast_fp16, y = denom_5_cast_fp16)[name = tensor("out_5_cast_fp16")]; + tensor obj_5_gamma_0_to_fp16 = const()[name = tensor("obj_5_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20393408)))]; + tensor obj_5_beta_0_to_fp16 = const()[name = tensor("obj_5_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20395008)))]; + tensor obj_5_epsilon_0_to_fp16 = const()[name = tensor("obj_5_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_5_cast_fp16 = batch_norm(beta = obj_5_beta_0_to_fp16, epsilon = obj_5_epsilon_0_to_fp16, gamma = obj_5_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_5_cast_fp16)[name = tensor("obj_5_cast_fp16")]; + tensor var_1143 = const()[name = tensor("op_1143"), val = tensor([1, 1])]; + tensor var_1145 = const()[name = tensor("op_1145"), val = tensor([1, 1])]; + tensor query_3_pad_type_0 = const()[name = tensor("query_3_pad_type_0"), val = tensor("custom")]; + tensor query_3_pad_0 = const()[name = tensor("query_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20396608)))]; + tensor layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21576320)))]; + tensor query_3_cast_fp16 = conv(bias = layers_1_self_attn_q_proj_bias_to_fp16, dilations = var_1145, groups = var_1110, pad = query_3_pad_0, pad_type = query_3_pad_type_0, strides = var_1143, weight = layers_1_self_attn_q_proj_weight_to_fp16, x = obj_5_cast_fp16)[name = tensor("query_3_cast_fp16")]; + tensor var_1149 = const()[name = tensor("op_1149"), val = tensor([1, 1])]; + tensor var_1151 = const()[name = tensor("op_1151"), val = tensor([1, 1])]; + tensor key_3_pad_type_0 = const()[name = tensor("key_3_pad_type_0"), val = tensor("custom")]; + tensor key_3_pad_0 = const()[name = tensor("key_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21577920)))]; + tensor key_3_cast_fp16 = conv(dilations = var_1151, groups = var_1110, pad = key_3_pad_0, pad_type = key_3_pad_type_0, strides = var_1149, weight = layers_1_self_attn_k_proj_weight_to_fp16, x = obj_5_cast_fp16)[name = tensor("key_3_cast_fp16")]; + tensor var_1156 = const()[name = tensor("op_1156"), val = tensor([1, 1])]; + tensor var_1158 = const()[name = tensor("op_1158"), val = tensor([1, 1])]; + tensor value_3_pad_type_0 = const()[name = tensor("value_3_pad_type_0"), val = tensor("custom")]; + tensor value_3_pad_0 = const()[name = tensor("value_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22757632)))]; + tensor layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23937344)))]; + tensor value_3_cast_fp16 = conv(bias = layers_1_self_attn_v_proj_bias_to_fp16, dilations = var_1158, groups = var_1110, pad = value_3_pad_0, pad_type = value_3_pad_type_0, strides = var_1156, weight = layers_1_self_attn_v_proj_weight_to_fp16, x = obj_5_cast_fp16)[name = tensor("value_3_cast_fp16")]; + tensor var_1165_begin_0 = const()[name = tensor("op_1165_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1165_end_0 = const()[name = tensor("op_1165_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1165_end_mask_0 = const()[name = tensor("op_1165_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1165_cast_fp16 = slice_by_index(begin = var_1165_begin_0, end = var_1165_end_0, end_mask = var_1165_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_1165_cast_fp16")]; + tensor var_1169_begin_0 = const()[name = tensor("op_1169_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_1169_end_0 = const()[name = tensor("op_1169_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_1169_end_mask_0 = const()[name = tensor("op_1169_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1169_cast_fp16 = slice_by_index(begin = var_1169_begin_0, end = var_1169_end_0, end_mask = var_1169_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_1169_cast_fp16")]; + tensor var_1173_begin_0 = const()[name = tensor("op_1173_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_1173_end_0 = const()[name = tensor("op_1173_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_1173_end_mask_0 = const()[name = tensor("op_1173_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1173_cast_fp16 = slice_by_index(begin = var_1173_begin_0, end = var_1173_end_0, end_mask = var_1173_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_1173_cast_fp16")]; + tensor var_1177_begin_0 = const()[name = tensor("op_1177_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_1177_end_0 = const()[name = tensor("op_1177_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_1177_end_mask_0 = const()[name = tensor("op_1177_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1177_cast_fp16 = slice_by_index(begin = var_1177_begin_0, end = var_1177_end_0, end_mask = var_1177_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_1177_cast_fp16")]; + tensor var_1181_begin_0 = const()[name = tensor("op_1181_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_1181_end_0 = const()[name = tensor("op_1181_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_1181_end_mask_0 = const()[name = tensor("op_1181_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1181_cast_fp16 = slice_by_index(begin = var_1181_begin_0, end = var_1181_end_0, end_mask = var_1181_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_1181_cast_fp16")]; + tensor var_1185_begin_0 = const()[name = tensor("op_1185_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_1185_end_0 = const()[name = tensor("op_1185_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_1185_end_mask_0 = const()[name = tensor("op_1185_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1185_cast_fp16 = slice_by_index(begin = var_1185_begin_0, end = var_1185_end_0, end_mask = var_1185_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_1185_cast_fp16")]; + tensor var_1189_begin_0 = const()[name = tensor("op_1189_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_1189_end_0 = const()[name = tensor("op_1189_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_1189_end_mask_0 = const()[name = tensor("op_1189_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1189_cast_fp16 = slice_by_index(begin = var_1189_begin_0, end = var_1189_end_0, end_mask = var_1189_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_1189_cast_fp16")]; + tensor var_1193_begin_0 = const()[name = tensor("op_1193_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_1193_end_0 = const()[name = tensor("op_1193_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_1193_end_mask_0 = const()[name = tensor("op_1193_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1193_cast_fp16 = slice_by_index(begin = var_1193_begin_0, end = var_1193_end_0, end_mask = var_1193_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_1193_cast_fp16")]; + tensor var_1197_begin_0 = const()[name = tensor("op_1197_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_1197_end_0 = const()[name = tensor("op_1197_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_1197_end_mask_0 = const()[name = tensor("op_1197_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1197_cast_fp16 = slice_by_index(begin = var_1197_begin_0, end = var_1197_end_0, end_mask = var_1197_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_1197_cast_fp16")]; + tensor var_1201_begin_0 = const()[name = tensor("op_1201_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_1201_end_0 = const()[name = tensor("op_1201_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_1201_end_mask_0 = const()[name = tensor("op_1201_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1201_cast_fp16 = slice_by_index(begin = var_1201_begin_0, end = var_1201_end_0, end_mask = var_1201_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_1201_cast_fp16")]; + tensor var_1205_begin_0 = const()[name = tensor("op_1205_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_1205_end_0 = const()[name = tensor("op_1205_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_1205_end_mask_0 = const()[name = tensor("op_1205_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1205_cast_fp16 = slice_by_index(begin = var_1205_begin_0, end = var_1205_end_0, end_mask = var_1205_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_1205_cast_fp16")]; + tensor var_1209_begin_0 = const()[name = tensor("op_1209_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_1209_end_0 = const()[name = tensor("op_1209_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_1209_end_mask_0 = const()[name = tensor("op_1209_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1209_cast_fp16 = slice_by_index(begin = var_1209_begin_0, end = var_1209_end_0, end_mask = var_1209_end_mask_0, x = query_3_cast_fp16)[name = tensor("op_1209_cast_fp16")]; + tensor var_1218_begin_0 = const()[name = tensor("op_1218_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1218_end_0 = const()[name = tensor("op_1218_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1218_end_mask_0 = const()[name = tensor("op_1218_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1218_cast_fp16 = slice_by_index(begin = var_1218_begin_0, end = var_1218_end_0, end_mask = var_1218_end_mask_0, x = var_1165_cast_fp16)[name = tensor("op_1218_cast_fp16")]; + tensor var_1225_begin_0 = const()[name = tensor("op_1225_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1225_end_0 = const()[name = tensor("op_1225_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1225_end_mask_0 = const()[name = tensor("op_1225_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1225_cast_fp16 = slice_by_index(begin = var_1225_begin_0, end = var_1225_end_0, end_mask = var_1225_end_mask_0, x = var_1165_cast_fp16)[name = tensor("op_1225_cast_fp16")]; + tensor var_1232_begin_0 = const()[name = tensor("op_1232_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1232_end_0 = const()[name = tensor("op_1232_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1232_end_mask_0 = const()[name = tensor("op_1232_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1232_cast_fp16 = slice_by_index(begin = var_1232_begin_0, end = var_1232_end_0, end_mask = var_1232_end_mask_0, x = var_1165_cast_fp16)[name = tensor("op_1232_cast_fp16")]; + tensor var_1239_begin_0 = const()[name = tensor("op_1239_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1239_end_0 = const()[name = tensor("op_1239_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1239_end_mask_0 = const()[name = tensor("op_1239_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1239_cast_fp16 = slice_by_index(begin = var_1239_begin_0, end = var_1239_end_0, end_mask = var_1239_end_mask_0, x = var_1165_cast_fp16)[name = tensor("op_1239_cast_fp16")]; + tensor var_1246_begin_0 = const()[name = tensor("op_1246_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1246_end_0 = const()[name = tensor("op_1246_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1246_end_mask_0 = const()[name = tensor("op_1246_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1246_cast_fp16 = slice_by_index(begin = var_1246_begin_0, end = var_1246_end_0, end_mask = var_1246_end_mask_0, x = var_1169_cast_fp16)[name = tensor("op_1246_cast_fp16")]; + tensor var_1253_begin_0 = const()[name = tensor("op_1253_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1253_end_0 = const()[name = tensor("op_1253_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1253_end_mask_0 = const()[name = tensor("op_1253_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1253_cast_fp16 = slice_by_index(begin = var_1253_begin_0, end = var_1253_end_0, end_mask = var_1253_end_mask_0, x = var_1169_cast_fp16)[name = tensor("op_1253_cast_fp16")]; + tensor var_1260_begin_0 = const()[name = tensor("op_1260_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1260_end_0 = const()[name = tensor("op_1260_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1260_end_mask_0 = const()[name = tensor("op_1260_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1260_cast_fp16 = slice_by_index(begin = var_1260_begin_0, end = var_1260_end_0, end_mask = var_1260_end_mask_0, x = var_1169_cast_fp16)[name = tensor("op_1260_cast_fp16")]; + tensor var_1267_begin_0 = const()[name = tensor("op_1267_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1267_end_0 = const()[name = tensor("op_1267_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1267_end_mask_0 = const()[name = tensor("op_1267_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1267_cast_fp16 = slice_by_index(begin = var_1267_begin_0, end = var_1267_end_0, end_mask = var_1267_end_mask_0, x = var_1169_cast_fp16)[name = tensor("op_1267_cast_fp16")]; + tensor var_1274_begin_0 = const()[name = tensor("op_1274_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1274_end_0 = const()[name = tensor("op_1274_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1274_end_mask_0 = const()[name = tensor("op_1274_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1274_cast_fp16 = slice_by_index(begin = var_1274_begin_0, end = var_1274_end_0, end_mask = var_1274_end_mask_0, x = var_1173_cast_fp16)[name = tensor("op_1274_cast_fp16")]; + tensor var_1281_begin_0 = const()[name = tensor("op_1281_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1281_end_0 = const()[name = tensor("op_1281_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1281_end_mask_0 = const()[name = tensor("op_1281_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1281_cast_fp16 = slice_by_index(begin = var_1281_begin_0, end = var_1281_end_0, end_mask = var_1281_end_mask_0, x = var_1173_cast_fp16)[name = tensor("op_1281_cast_fp16")]; + tensor var_1288_begin_0 = const()[name = tensor("op_1288_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1288_end_0 = const()[name = tensor("op_1288_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1288_end_mask_0 = const()[name = tensor("op_1288_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1288_cast_fp16 = slice_by_index(begin = var_1288_begin_0, end = var_1288_end_0, end_mask = var_1288_end_mask_0, x = var_1173_cast_fp16)[name = tensor("op_1288_cast_fp16")]; + tensor var_1295_begin_0 = const()[name = tensor("op_1295_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1295_end_0 = const()[name = tensor("op_1295_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1295_end_mask_0 = const()[name = tensor("op_1295_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1295_cast_fp16 = slice_by_index(begin = var_1295_begin_0, end = var_1295_end_0, end_mask = var_1295_end_mask_0, x = var_1173_cast_fp16)[name = tensor("op_1295_cast_fp16")]; + tensor var_1302_begin_0 = const()[name = tensor("op_1302_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1302_end_0 = const()[name = tensor("op_1302_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1302_end_mask_0 = const()[name = tensor("op_1302_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1302_cast_fp16 = slice_by_index(begin = var_1302_begin_0, end = var_1302_end_0, end_mask = var_1302_end_mask_0, x = var_1177_cast_fp16)[name = tensor("op_1302_cast_fp16")]; + tensor var_1309_begin_0 = const()[name = tensor("op_1309_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1309_end_0 = const()[name = tensor("op_1309_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1309_end_mask_0 = const()[name = tensor("op_1309_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1309_cast_fp16 = slice_by_index(begin = var_1309_begin_0, end = var_1309_end_0, end_mask = var_1309_end_mask_0, x = var_1177_cast_fp16)[name = tensor("op_1309_cast_fp16")]; + tensor var_1316_begin_0 = const()[name = tensor("op_1316_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1316_end_0 = const()[name = tensor("op_1316_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1316_end_mask_0 = const()[name = tensor("op_1316_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1316_cast_fp16 = slice_by_index(begin = var_1316_begin_0, end = var_1316_end_0, end_mask = var_1316_end_mask_0, x = var_1177_cast_fp16)[name = tensor("op_1316_cast_fp16")]; + tensor var_1323_begin_0 = const()[name = tensor("op_1323_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1323_end_0 = const()[name = tensor("op_1323_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1323_end_mask_0 = const()[name = tensor("op_1323_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1323_cast_fp16 = slice_by_index(begin = var_1323_begin_0, end = var_1323_end_0, end_mask = var_1323_end_mask_0, x = var_1177_cast_fp16)[name = tensor("op_1323_cast_fp16")]; + tensor var_1330_begin_0 = const()[name = tensor("op_1330_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1330_end_0 = const()[name = tensor("op_1330_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1330_end_mask_0 = const()[name = tensor("op_1330_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1330_cast_fp16 = slice_by_index(begin = var_1330_begin_0, end = var_1330_end_0, end_mask = var_1330_end_mask_0, x = var_1181_cast_fp16)[name = tensor("op_1330_cast_fp16")]; + tensor var_1337_begin_0 = const()[name = tensor("op_1337_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1337_end_0 = const()[name = tensor("op_1337_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1337_end_mask_0 = const()[name = tensor("op_1337_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1337_cast_fp16 = slice_by_index(begin = var_1337_begin_0, end = var_1337_end_0, end_mask = var_1337_end_mask_0, x = var_1181_cast_fp16)[name = tensor("op_1337_cast_fp16")]; + tensor var_1344_begin_0 = const()[name = tensor("op_1344_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1344_end_0 = const()[name = tensor("op_1344_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1344_end_mask_0 = const()[name = tensor("op_1344_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1344_cast_fp16 = slice_by_index(begin = var_1344_begin_0, end = var_1344_end_0, end_mask = var_1344_end_mask_0, x = var_1181_cast_fp16)[name = tensor("op_1344_cast_fp16")]; + tensor var_1351_begin_0 = const()[name = tensor("op_1351_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1351_end_0 = const()[name = tensor("op_1351_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1351_end_mask_0 = const()[name = tensor("op_1351_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1351_cast_fp16 = slice_by_index(begin = var_1351_begin_0, end = var_1351_end_0, end_mask = var_1351_end_mask_0, x = var_1181_cast_fp16)[name = tensor("op_1351_cast_fp16")]; + tensor var_1358_begin_0 = const()[name = tensor("op_1358_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1358_end_0 = const()[name = tensor("op_1358_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1358_end_mask_0 = const()[name = tensor("op_1358_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1358_cast_fp16 = slice_by_index(begin = var_1358_begin_0, end = var_1358_end_0, end_mask = var_1358_end_mask_0, x = var_1185_cast_fp16)[name = tensor("op_1358_cast_fp16")]; + tensor var_1365_begin_0 = const()[name = tensor("op_1365_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1365_end_0 = const()[name = tensor("op_1365_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1365_end_mask_0 = const()[name = tensor("op_1365_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1365_cast_fp16 = slice_by_index(begin = var_1365_begin_0, end = var_1365_end_0, end_mask = var_1365_end_mask_0, x = var_1185_cast_fp16)[name = tensor("op_1365_cast_fp16")]; + tensor var_1372_begin_0 = const()[name = tensor("op_1372_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1372_end_0 = const()[name = tensor("op_1372_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1372_end_mask_0 = const()[name = tensor("op_1372_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1372_cast_fp16 = slice_by_index(begin = var_1372_begin_0, end = var_1372_end_0, end_mask = var_1372_end_mask_0, x = var_1185_cast_fp16)[name = tensor("op_1372_cast_fp16")]; + tensor var_1379_begin_0 = const()[name = tensor("op_1379_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1379_end_0 = const()[name = tensor("op_1379_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1379_end_mask_0 = const()[name = tensor("op_1379_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1379_cast_fp16 = slice_by_index(begin = var_1379_begin_0, end = var_1379_end_0, end_mask = var_1379_end_mask_0, x = var_1185_cast_fp16)[name = tensor("op_1379_cast_fp16")]; + tensor var_1386_begin_0 = const()[name = tensor("op_1386_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1386_end_0 = const()[name = tensor("op_1386_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1386_end_mask_0 = const()[name = tensor("op_1386_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1386_cast_fp16 = slice_by_index(begin = var_1386_begin_0, end = var_1386_end_0, end_mask = var_1386_end_mask_0, x = var_1189_cast_fp16)[name = tensor("op_1386_cast_fp16")]; + tensor var_1393_begin_0 = const()[name = tensor("op_1393_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1393_end_0 = const()[name = tensor("op_1393_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1393_end_mask_0 = const()[name = tensor("op_1393_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1393_cast_fp16 = slice_by_index(begin = var_1393_begin_0, end = var_1393_end_0, end_mask = var_1393_end_mask_0, x = var_1189_cast_fp16)[name = tensor("op_1393_cast_fp16")]; + tensor var_1400_begin_0 = const()[name = tensor("op_1400_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1400_end_0 = const()[name = tensor("op_1400_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1400_end_mask_0 = const()[name = tensor("op_1400_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1400_cast_fp16 = slice_by_index(begin = var_1400_begin_0, end = var_1400_end_0, end_mask = var_1400_end_mask_0, x = var_1189_cast_fp16)[name = tensor("op_1400_cast_fp16")]; + tensor var_1407_begin_0 = const()[name = tensor("op_1407_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1407_end_0 = const()[name = tensor("op_1407_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1407_end_mask_0 = const()[name = tensor("op_1407_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1407_cast_fp16 = slice_by_index(begin = var_1407_begin_0, end = var_1407_end_0, end_mask = var_1407_end_mask_0, x = var_1189_cast_fp16)[name = tensor("op_1407_cast_fp16")]; + tensor var_1414_begin_0 = const()[name = tensor("op_1414_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1414_end_0 = const()[name = tensor("op_1414_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1414_end_mask_0 = const()[name = tensor("op_1414_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1414_cast_fp16 = slice_by_index(begin = var_1414_begin_0, end = var_1414_end_0, end_mask = var_1414_end_mask_0, x = var_1193_cast_fp16)[name = tensor("op_1414_cast_fp16")]; + tensor var_1421_begin_0 = const()[name = tensor("op_1421_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1421_end_0 = const()[name = tensor("op_1421_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1421_end_mask_0 = const()[name = tensor("op_1421_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1421_cast_fp16 = slice_by_index(begin = var_1421_begin_0, end = var_1421_end_0, end_mask = var_1421_end_mask_0, x = var_1193_cast_fp16)[name = tensor("op_1421_cast_fp16")]; + tensor var_1428_begin_0 = const()[name = tensor("op_1428_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1428_end_0 = const()[name = tensor("op_1428_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1428_end_mask_0 = const()[name = tensor("op_1428_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1428_cast_fp16 = slice_by_index(begin = var_1428_begin_0, end = var_1428_end_0, end_mask = var_1428_end_mask_0, x = var_1193_cast_fp16)[name = tensor("op_1428_cast_fp16")]; + tensor var_1435_begin_0 = const()[name = tensor("op_1435_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1435_end_0 = const()[name = tensor("op_1435_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1435_end_mask_0 = const()[name = tensor("op_1435_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1435_cast_fp16 = slice_by_index(begin = var_1435_begin_0, end = var_1435_end_0, end_mask = var_1435_end_mask_0, x = var_1193_cast_fp16)[name = tensor("op_1435_cast_fp16")]; + tensor var_1442_begin_0 = const()[name = tensor("op_1442_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1442_end_0 = const()[name = tensor("op_1442_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1442_end_mask_0 = const()[name = tensor("op_1442_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1442_cast_fp16 = slice_by_index(begin = var_1442_begin_0, end = var_1442_end_0, end_mask = var_1442_end_mask_0, x = var_1197_cast_fp16)[name = tensor("op_1442_cast_fp16")]; + tensor var_1449_begin_0 = const()[name = tensor("op_1449_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1449_end_0 = const()[name = tensor("op_1449_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1449_end_mask_0 = const()[name = tensor("op_1449_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1449_cast_fp16 = slice_by_index(begin = var_1449_begin_0, end = var_1449_end_0, end_mask = var_1449_end_mask_0, x = var_1197_cast_fp16)[name = tensor("op_1449_cast_fp16")]; + tensor var_1456_begin_0 = const()[name = tensor("op_1456_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1456_end_0 = const()[name = tensor("op_1456_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1456_end_mask_0 = const()[name = tensor("op_1456_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1456_cast_fp16 = slice_by_index(begin = var_1456_begin_0, end = var_1456_end_0, end_mask = var_1456_end_mask_0, x = var_1197_cast_fp16)[name = tensor("op_1456_cast_fp16")]; + tensor var_1463_begin_0 = const()[name = tensor("op_1463_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1463_end_0 = const()[name = tensor("op_1463_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1463_end_mask_0 = const()[name = tensor("op_1463_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1463_cast_fp16 = slice_by_index(begin = var_1463_begin_0, end = var_1463_end_0, end_mask = var_1463_end_mask_0, x = var_1197_cast_fp16)[name = tensor("op_1463_cast_fp16")]; + tensor var_1470_begin_0 = const()[name = tensor("op_1470_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1470_end_0 = const()[name = tensor("op_1470_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1470_end_mask_0 = const()[name = tensor("op_1470_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1470_cast_fp16 = slice_by_index(begin = var_1470_begin_0, end = var_1470_end_0, end_mask = var_1470_end_mask_0, x = var_1201_cast_fp16)[name = tensor("op_1470_cast_fp16")]; + tensor var_1477_begin_0 = const()[name = tensor("op_1477_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1477_end_0 = const()[name = tensor("op_1477_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1477_end_mask_0 = const()[name = tensor("op_1477_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1477_cast_fp16 = slice_by_index(begin = var_1477_begin_0, end = var_1477_end_0, end_mask = var_1477_end_mask_0, x = var_1201_cast_fp16)[name = tensor("op_1477_cast_fp16")]; + tensor var_1484_begin_0 = const()[name = tensor("op_1484_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1484_end_0 = const()[name = tensor("op_1484_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1484_end_mask_0 = const()[name = tensor("op_1484_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1484_cast_fp16 = slice_by_index(begin = var_1484_begin_0, end = var_1484_end_0, end_mask = var_1484_end_mask_0, x = var_1201_cast_fp16)[name = tensor("op_1484_cast_fp16")]; + tensor var_1491_begin_0 = const()[name = tensor("op_1491_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1491_end_0 = const()[name = tensor("op_1491_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1491_end_mask_0 = const()[name = tensor("op_1491_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1491_cast_fp16 = slice_by_index(begin = var_1491_begin_0, end = var_1491_end_0, end_mask = var_1491_end_mask_0, x = var_1201_cast_fp16)[name = tensor("op_1491_cast_fp16")]; + tensor var_1498_begin_0 = const()[name = tensor("op_1498_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1498_end_0 = const()[name = tensor("op_1498_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1498_end_mask_0 = const()[name = tensor("op_1498_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1498_cast_fp16 = slice_by_index(begin = var_1498_begin_0, end = var_1498_end_0, end_mask = var_1498_end_mask_0, x = var_1205_cast_fp16)[name = tensor("op_1498_cast_fp16")]; + tensor var_1505_begin_0 = const()[name = tensor("op_1505_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1505_end_0 = const()[name = tensor("op_1505_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1505_end_mask_0 = const()[name = tensor("op_1505_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1505_cast_fp16 = slice_by_index(begin = var_1505_begin_0, end = var_1505_end_0, end_mask = var_1505_end_mask_0, x = var_1205_cast_fp16)[name = tensor("op_1505_cast_fp16")]; + tensor var_1512_begin_0 = const()[name = tensor("op_1512_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1512_end_0 = const()[name = tensor("op_1512_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1512_end_mask_0 = const()[name = tensor("op_1512_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1512_cast_fp16 = slice_by_index(begin = var_1512_begin_0, end = var_1512_end_0, end_mask = var_1512_end_mask_0, x = var_1205_cast_fp16)[name = tensor("op_1512_cast_fp16")]; + tensor var_1519_begin_0 = const()[name = tensor("op_1519_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1519_end_0 = const()[name = tensor("op_1519_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1519_end_mask_0 = const()[name = tensor("op_1519_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1519_cast_fp16 = slice_by_index(begin = var_1519_begin_0, end = var_1519_end_0, end_mask = var_1519_end_mask_0, x = var_1205_cast_fp16)[name = tensor("op_1519_cast_fp16")]; + tensor var_1526_begin_0 = const()[name = tensor("op_1526_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1526_end_0 = const()[name = tensor("op_1526_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_1526_end_mask_0 = const()[name = tensor("op_1526_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1526_cast_fp16 = slice_by_index(begin = var_1526_begin_0, end = var_1526_end_0, end_mask = var_1526_end_mask_0, x = var_1209_cast_fp16)[name = tensor("op_1526_cast_fp16")]; + tensor var_1533_begin_0 = const()[name = tensor("op_1533_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_1533_end_0 = const()[name = tensor("op_1533_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_1533_end_mask_0 = const()[name = tensor("op_1533_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1533_cast_fp16 = slice_by_index(begin = var_1533_begin_0, end = var_1533_end_0, end_mask = var_1533_end_mask_0, x = var_1209_cast_fp16)[name = tensor("op_1533_cast_fp16")]; + tensor var_1540_begin_0 = const()[name = tensor("op_1540_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_1540_end_0 = const()[name = tensor("op_1540_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_1540_end_mask_0 = const()[name = tensor("op_1540_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1540_cast_fp16 = slice_by_index(begin = var_1540_begin_0, end = var_1540_end_0, end_mask = var_1540_end_mask_0, x = var_1209_cast_fp16)[name = tensor("op_1540_cast_fp16")]; + tensor var_1547_begin_0 = const()[name = tensor("op_1547_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_1547_end_0 = const()[name = tensor("op_1547_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1547_end_mask_0 = const()[name = tensor("op_1547_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1547_cast_fp16 = slice_by_index(begin = var_1547_begin_0, end = var_1547_end_0, end_mask = var_1547_end_mask_0, x = var_1209_cast_fp16)[name = tensor("op_1547_cast_fp16")]; + tensor k_3_perm_0 = const()[name = tensor("k_3_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_1552_begin_0 = const()[name = tensor("op_1552_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1552_end_0 = const()[name = tensor("op_1552_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_1552_end_mask_0 = const()[name = tensor("op_1552_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_10 = transpose(perm = k_3_perm_0, x = key_3_cast_fp16)[name = tensor("transpose_10")]; + tensor var_1552_cast_fp16 = slice_by_index(begin = var_1552_begin_0, end = var_1552_end_0, end_mask = var_1552_end_mask_0, x = transpose_10)[name = tensor("op_1552_cast_fp16")]; + tensor var_1556_begin_0 = const()[name = tensor("op_1556_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_1556_end_0 = const()[name = tensor("op_1556_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_1556_end_mask_0 = const()[name = tensor("op_1556_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1556_cast_fp16 = slice_by_index(begin = var_1556_begin_0, end = var_1556_end_0, end_mask = var_1556_end_mask_0, x = transpose_10)[name = tensor("op_1556_cast_fp16")]; + tensor var_1560_begin_0 = const()[name = tensor("op_1560_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_1560_end_0 = const()[name = tensor("op_1560_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_1560_end_mask_0 = const()[name = tensor("op_1560_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1560_cast_fp16 = slice_by_index(begin = var_1560_begin_0, end = var_1560_end_0, end_mask = var_1560_end_mask_0, x = transpose_10)[name = tensor("op_1560_cast_fp16")]; + tensor var_1564_begin_0 = const()[name = tensor("op_1564_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_1564_end_0 = const()[name = tensor("op_1564_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_1564_end_mask_0 = const()[name = tensor("op_1564_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1564_cast_fp16 = slice_by_index(begin = var_1564_begin_0, end = var_1564_end_0, end_mask = var_1564_end_mask_0, x = transpose_10)[name = tensor("op_1564_cast_fp16")]; + tensor var_1568_begin_0 = const()[name = tensor("op_1568_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_1568_end_0 = const()[name = tensor("op_1568_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_1568_end_mask_0 = const()[name = tensor("op_1568_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1568_cast_fp16 = slice_by_index(begin = var_1568_begin_0, end = var_1568_end_0, end_mask = var_1568_end_mask_0, x = transpose_10)[name = tensor("op_1568_cast_fp16")]; + tensor var_1572_begin_0 = const()[name = tensor("op_1572_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_1572_end_0 = const()[name = tensor("op_1572_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_1572_end_mask_0 = const()[name = tensor("op_1572_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1572_cast_fp16 = slice_by_index(begin = var_1572_begin_0, end = var_1572_end_0, end_mask = var_1572_end_mask_0, x = transpose_10)[name = tensor("op_1572_cast_fp16")]; + tensor var_1576_begin_0 = const()[name = tensor("op_1576_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_1576_end_0 = const()[name = tensor("op_1576_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_1576_end_mask_0 = const()[name = tensor("op_1576_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1576_cast_fp16 = slice_by_index(begin = var_1576_begin_0, end = var_1576_end_0, end_mask = var_1576_end_mask_0, x = transpose_10)[name = tensor("op_1576_cast_fp16")]; + tensor var_1580_begin_0 = const()[name = tensor("op_1580_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_1580_end_0 = const()[name = tensor("op_1580_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_1580_end_mask_0 = const()[name = tensor("op_1580_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1580_cast_fp16 = slice_by_index(begin = var_1580_begin_0, end = var_1580_end_0, end_mask = var_1580_end_mask_0, x = transpose_10)[name = tensor("op_1580_cast_fp16")]; + tensor var_1584_begin_0 = const()[name = tensor("op_1584_begin_0"), val = tensor([0, 0, 0, 512])]; + tensor var_1584_end_0 = const()[name = tensor("op_1584_end_0"), val = tensor([1, 1500, 1, 576])]; + tensor var_1584_end_mask_0 = const()[name = tensor("op_1584_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1584_cast_fp16 = slice_by_index(begin = var_1584_begin_0, end = var_1584_end_0, end_mask = var_1584_end_mask_0, x = transpose_10)[name = tensor("op_1584_cast_fp16")]; + tensor var_1588_begin_0 = const()[name = tensor("op_1588_begin_0"), val = tensor([0, 0, 0, 576])]; + tensor var_1588_end_0 = const()[name = tensor("op_1588_end_0"), val = tensor([1, 1500, 1, 640])]; + tensor var_1588_end_mask_0 = const()[name = tensor("op_1588_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1588_cast_fp16 = slice_by_index(begin = var_1588_begin_0, end = var_1588_end_0, end_mask = var_1588_end_mask_0, x = transpose_10)[name = tensor("op_1588_cast_fp16")]; + tensor var_1592_begin_0 = const()[name = tensor("op_1592_begin_0"), val = tensor([0, 0, 0, 640])]; + tensor var_1592_end_0 = const()[name = tensor("op_1592_end_0"), val = tensor([1, 1500, 1, 704])]; + tensor var_1592_end_mask_0 = const()[name = tensor("op_1592_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1592_cast_fp16 = slice_by_index(begin = var_1592_begin_0, end = var_1592_end_0, end_mask = var_1592_end_mask_0, x = transpose_10)[name = tensor("op_1592_cast_fp16")]; + tensor var_1596_begin_0 = const()[name = tensor("op_1596_begin_0"), val = tensor([0, 0, 0, 704])]; + tensor var_1596_end_0 = const()[name = tensor("op_1596_end_0"), val = tensor([1, 1500, 1, 768])]; + tensor var_1596_end_mask_0 = const()[name = tensor("op_1596_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_1596_cast_fp16 = slice_by_index(begin = var_1596_begin_0, end = var_1596_end_0, end_mask = var_1596_end_mask_0, x = transpose_10)[name = tensor("op_1596_cast_fp16")]; + tensor var_1598_begin_0 = const()[name = tensor("op_1598_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_1598_end_0 = const()[name = tensor("op_1598_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_1598_end_mask_0 = const()[name = tensor("op_1598_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1598_cast_fp16 = slice_by_index(begin = var_1598_begin_0, end = var_1598_end_0, end_mask = var_1598_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1598_cast_fp16")]; + tensor var_1602_begin_0 = const()[name = tensor("op_1602_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_1602_end_0 = const()[name = tensor("op_1602_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_1602_end_mask_0 = const()[name = tensor("op_1602_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1602_cast_fp16 = slice_by_index(begin = var_1602_begin_0, end = var_1602_end_0, end_mask = var_1602_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1602_cast_fp16")]; + tensor var_1606_begin_0 = const()[name = tensor("op_1606_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_1606_end_0 = const()[name = tensor("op_1606_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_1606_end_mask_0 = const()[name = tensor("op_1606_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1606_cast_fp16 = slice_by_index(begin = var_1606_begin_0, end = var_1606_end_0, end_mask = var_1606_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1606_cast_fp16")]; + tensor var_1610_begin_0 = const()[name = tensor("op_1610_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_1610_end_0 = const()[name = tensor("op_1610_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_1610_end_mask_0 = const()[name = tensor("op_1610_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1610_cast_fp16 = slice_by_index(begin = var_1610_begin_0, end = var_1610_end_0, end_mask = var_1610_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1610_cast_fp16")]; + tensor var_1614_begin_0 = const()[name = tensor("op_1614_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_1614_end_0 = const()[name = tensor("op_1614_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_1614_end_mask_0 = const()[name = tensor("op_1614_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1614_cast_fp16 = slice_by_index(begin = var_1614_begin_0, end = var_1614_end_0, end_mask = var_1614_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1614_cast_fp16")]; + tensor var_1618_begin_0 = const()[name = tensor("op_1618_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_1618_end_0 = const()[name = tensor("op_1618_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_1618_end_mask_0 = const()[name = tensor("op_1618_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1618_cast_fp16 = slice_by_index(begin = var_1618_begin_0, end = var_1618_end_0, end_mask = var_1618_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1618_cast_fp16")]; + tensor var_1622_begin_0 = const()[name = tensor("op_1622_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_1622_end_0 = const()[name = tensor("op_1622_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_1622_end_mask_0 = const()[name = tensor("op_1622_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1622_cast_fp16 = slice_by_index(begin = var_1622_begin_0, end = var_1622_end_0, end_mask = var_1622_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1622_cast_fp16")]; + tensor var_1626_begin_0 = const()[name = tensor("op_1626_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_1626_end_0 = const()[name = tensor("op_1626_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_1626_end_mask_0 = const()[name = tensor("op_1626_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1626_cast_fp16 = slice_by_index(begin = var_1626_begin_0, end = var_1626_end_0, end_mask = var_1626_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1626_cast_fp16")]; + tensor var_1630_begin_0 = const()[name = tensor("op_1630_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_1630_end_0 = const()[name = tensor("op_1630_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_1630_end_mask_0 = const()[name = tensor("op_1630_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1630_cast_fp16 = slice_by_index(begin = var_1630_begin_0, end = var_1630_end_0, end_mask = var_1630_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1630_cast_fp16")]; + tensor var_1634_begin_0 = const()[name = tensor("op_1634_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_1634_end_0 = const()[name = tensor("op_1634_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_1634_end_mask_0 = const()[name = tensor("op_1634_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1634_cast_fp16 = slice_by_index(begin = var_1634_begin_0, end = var_1634_end_0, end_mask = var_1634_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1634_cast_fp16")]; + tensor var_1638_begin_0 = const()[name = tensor("op_1638_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_1638_end_0 = const()[name = tensor("op_1638_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_1638_end_mask_0 = const()[name = tensor("op_1638_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1638_cast_fp16 = slice_by_index(begin = var_1638_begin_0, end = var_1638_end_0, end_mask = var_1638_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1638_cast_fp16")]; + tensor var_1642_begin_0 = const()[name = tensor("op_1642_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_1642_end_0 = const()[name = tensor("op_1642_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_1642_end_mask_0 = const()[name = tensor("op_1642_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_1642_cast_fp16 = slice_by_index(begin = var_1642_begin_0, end = var_1642_end_0, end_mask = var_1642_end_mask_0, x = value_3_cast_fp16)[name = tensor("op_1642_cast_fp16")]; + tensor var_1646_equation_0 = const()[name = tensor("op_1646_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1646_cast_fp16 = einsum(equation = var_1646_equation_0, values = (var_1552_cast_fp16, var_1218_cast_fp16))[name = tensor("op_1646_cast_fp16")]; + tensor var_1647_to_fp16 = const()[name = tensor("op_1647_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_97_cast_fp16 = mul(x = var_1646_cast_fp16, y = var_1647_to_fp16)[name = tensor("aw_chunk_97_cast_fp16")]; + tensor var_1650_equation_0 = const()[name = tensor("op_1650_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1650_cast_fp16 = einsum(equation = var_1650_equation_0, values = (var_1552_cast_fp16, var_1225_cast_fp16))[name = tensor("op_1650_cast_fp16")]; + tensor var_1651_to_fp16 = const()[name = tensor("op_1651_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_99_cast_fp16 = mul(x = var_1650_cast_fp16, y = var_1651_to_fp16)[name = tensor("aw_chunk_99_cast_fp16")]; + tensor var_1654_equation_0 = const()[name = tensor("op_1654_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1654_cast_fp16 = einsum(equation = var_1654_equation_0, values = (var_1552_cast_fp16, var_1232_cast_fp16))[name = tensor("op_1654_cast_fp16")]; + tensor var_1655_to_fp16 = const()[name = tensor("op_1655_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_101_cast_fp16 = mul(x = var_1654_cast_fp16, y = var_1655_to_fp16)[name = tensor("aw_chunk_101_cast_fp16")]; + tensor var_1658_equation_0 = const()[name = tensor("op_1658_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1658_cast_fp16 = einsum(equation = var_1658_equation_0, values = (var_1552_cast_fp16, var_1239_cast_fp16))[name = tensor("op_1658_cast_fp16")]; + tensor var_1659_to_fp16 = const()[name = tensor("op_1659_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_103_cast_fp16 = mul(x = var_1658_cast_fp16, y = var_1659_to_fp16)[name = tensor("aw_chunk_103_cast_fp16")]; + tensor var_1662_equation_0 = const()[name = tensor("op_1662_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1662_cast_fp16 = einsum(equation = var_1662_equation_0, values = (var_1556_cast_fp16, var_1246_cast_fp16))[name = tensor("op_1662_cast_fp16")]; + tensor var_1663_to_fp16 = const()[name = tensor("op_1663_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_105_cast_fp16 = mul(x = var_1662_cast_fp16, y = var_1663_to_fp16)[name = tensor("aw_chunk_105_cast_fp16")]; + tensor var_1666_equation_0 = const()[name = tensor("op_1666_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1666_cast_fp16 = einsum(equation = var_1666_equation_0, values = (var_1556_cast_fp16, var_1253_cast_fp16))[name = tensor("op_1666_cast_fp16")]; + tensor var_1667_to_fp16 = const()[name = tensor("op_1667_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_107_cast_fp16 = mul(x = var_1666_cast_fp16, y = var_1667_to_fp16)[name = tensor("aw_chunk_107_cast_fp16")]; + tensor var_1670_equation_0 = const()[name = tensor("op_1670_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1670_cast_fp16 = einsum(equation = var_1670_equation_0, values = (var_1556_cast_fp16, var_1260_cast_fp16))[name = tensor("op_1670_cast_fp16")]; + tensor var_1671_to_fp16 = const()[name = tensor("op_1671_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_109_cast_fp16 = mul(x = var_1670_cast_fp16, y = var_1671_to_fp16)[name = tensor("aw_chunk_109_cast_fp16")]; + tensor var_1674_equation_0 = const()[name = tensor("op_1674_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1674_cast_fp16 = einsum(equation = var_1674_equation_0, values = (var_1556_cast_fp16, var_1267_cast_fp16))[name = tensor("op_1674_cast_fp16")]; + tensor var_1675_to_fp16 = const()[name = tensor("op_1675_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_111_cast_fp16 = mul(x = var_1674_cast_fp16, y = var_1675_to_fp16)[name = tensor("aw_chunk_111_cast_fp16")]; + tensor var_1678_equation_0 = const()[name = tensor("op_1678_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1678_cast_fp16 = einsum(equation = var_1678_equation_0, values = (var_1560_cast_fp16, var_1274_cast_fp16))[name = tensor("op_1678_cast_fp16")]; + tensor var_1679_to_fp16 = const()[name = tensor("op_1679_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_113_cast_fp16 = mul(x = var_1678_cast_fp16, y = var_1679_to_fp16)[name = tensor("aw_chunk_113_cast_fp16")]; + tensor var_1682_equation_0 = const()[name = tensor("op_1682_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1682_cast_fp16 = einsum(equation = var_1682_equation_0, values = (var_1560_cast_fp16, var_1281_cast_fp16))[name = tensor("op_1682_cast_fp16")]; + tensor var_1683_to_fp16 = const()[name = tensor("op_1683_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_115_cast_fp16 = mul(x = var_1682_cast_fp16, y = var_1683_to_fp16)[name = tensor("aw_chunk_115_cast_fp16")]; + tensor var_1686_equation_0 = const()[name = tensor("op_1686_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1686_cast_fp16 = einsum(equation = var_1686_equation_0, values = (var_1560_cast_fp16, var_1288_cast_fp16))[name = tensor("op_1686_cast_fp16")]; + tensor var_1687_to_fp16 = const()[name = tensor("op_1687_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_117_cast_fp16 = mul(x = var_1686_cast_fp16, y = var_1687_to_fp16)[name = tensor("aw_chunk_117_cast_fp16")]; + tensor var_1690_equation_0 = const()[name = tensor("op_1690_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1690_cast_fp16 = einsum(equation = var_1690_equation_0, values = (var_1560_cast_fp16, var_1295_cast_fp16))[name = tensor("op_1690_cast_fp16")]; + tensor var_1691_to_fp16 = const()[name = tensor("op_1691_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_119_cast_fp16 = mul(x = var_1690_cast_fp16, y = var_1691_to_fp16)[name = tensor("aw_chunk_119_cast_fp16")]; + tensor var_1694_equation_0 = const()[name = tensor("op_1694_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1694_cast_fp16 = einsum(equation = var_1694_equation_0, values = (var_1564_cast_fp16, var_1302_cast_fp16))[name = tensor("op_1694_cast_fp16")]; + tensor var_1695_to_fp16 = const()[name = tensor("op_1695_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_121_cast_fp16 = mul(x = var_1694_cast_fp16, y = var_1695_to_fp16)[name = tensor("aw_chunk_121_cast_fp16")]; + tensor var_1698_equation_0 = const()[name = tensor("op_1698_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1698_cast_fp16 = einsum(equation = var_1698_equation_0, values = (var_1564_cast_fp16, var_1309_cast_fp16))[name = tensor("op_1698_cast_fp16")]; + tensor var_1699_to_fp16 = const()[name = tensor("op_1699_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_123_cast_fp16 = mul(x = var_1698_cast_fp16, y = var_1699_to_fp16)[name = tensor("aw_chunk_123_cast_fp16")]; + tensor var_1702_equation_0 = const()[name = tensor("op_1702_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1702_cast_fp16 = einsum(equation = var_1702_equation_0, values = (var_1564_cast_fp16, var_1316_cast_fp16))[name = tensor("op_1702_cast_fp16")]; + tensor var_1703_to_fp16 = const()[name = tensor("op_1703_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_125_cast_fp16 = mul(x = var_1702_cast_fp16, y = var_1703_to_fp16)[name = tensor("aw_chunk_125_cast_fp16")]; + tensor var_1706_equation_0 = const()[name = tensor("op_1706_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1706_cast_fp16 = einsum(equation = var_1706_equation_0, values = (var_1564_cast_fp16, var_1323_cast_fp16))[name = tensor("op_1706_cast_fp16")]; + tensor var_1707_to_fp16 = const()[name = tensor("op_1707_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_127_cast_fp16 = mul(x = var_1706_cast_fp16, y = var_1707_to_fp16)[name = tensor("aw_chunk_127_cast_fp16")]; + tensor var_1710_equation_0 = const()[name = tensor("op_1710_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1710_cast_fp16 = einsum(equation = var_1710_equation_0, values = (var_1568_cast_fp16, var_1330_cast_fp16))[name = tensor("op_1710_cast_fp16")]; + tensor var_1711_to_fp16 = const()[name = tensor("op_1711_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_129_cast_fp16 = mul(x = var_1710_cast_fp16, y = var_1711_to_fp16)[name = tensor("aw_chunk_129_cast_fp16")]; + tensor var_1714_equation_0 = const()[name = tensor("op_1714_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1714_cast_fp16 = einsum(equation = var_1714_equation_0, values = (var_1568_cast_fp16, var_1337_cast_fp16))[name = tensor("op_1714_cast_fp16")]; + tensor var_1715_to_fp16 = const()[name = tensor("op_1715_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_131_cast_fp16 = mul(x = var_1714_cast_fp16, y = var_1715_to_fp16)[name = tensor("aw_chunk_131_cast_fp16")]; + tensor var_1718_equation_0 = const()[name = tensor("op_1718_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1718_cast_fp16 = einsum(equation = var_1718_equation_0, values = (var_1568_cast_fp16, var_1344_cast_fp16))[name = tensor("op_1718_cast_fp16")]; + tensor var_1719_to_fp16 = const()[name = tensor("op_1719_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_133_cast_fp16 = mul(x = var_1718_cast_fp16, y = var_1719_to_fp16)[name = tensor("aw_chunk_133_cast_fp16")]; + tensor var_1722_equation_0 = const()[name = tensor("op_1722_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1722_cast_fp16 = einsum(equation = var_1722_equation_0, values = (var_1568_cast_fp16, var_1351_cast_fp16))[name = tensor("op_1722_cast_fp16")]; + tensor var_1723_to_fp16 = const()[name = tensor("op_1723_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_135_cast_fp16 = mul(x = var_1722_cast_fp16, y = var_1723_to_fp16)[name = tensor("aw_chunk_135_cast_fp16")]; + tensor var_1726_equation_0 = const()[name = tensor("op_1726_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1726_cast_fp16 = einsum(equation = var_1726_equation_0, values = (var_1572_cast_fp16, var_1358_cast_fp16))[name = tensor("op_1726_cast_fp16")]; + tensor var_1727_to_fp16 = const()[name = tensor("op_1727_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_137_cast_fp16 = mul(x = var_1726_cast_fp16, y = var_1727_to_fp16)[name = tensor("aw_chunk_137_cast_fp16")]; + tensor var_1730_equation_0 = const()[name = tensor("op_1730_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1730_cast_fp16 = einsum(equation = var_1730_equation_0, values = (var_1572_cast_fp16, var_1365_cast_fp16))[name = tensor("op_1730_cast_fp16")]; + tensor var_1731_to_fp16 = const()[name = tensor("op_1731_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_139_cast_fp16 = mul(x = var_1730_cast_fp16, y = var_1731_to_fp16)[name = tensor("aw_chunk_139_cast_fp16")]; + tensor var_1734_equation_0 = const()[name = tensor("op_1734_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1734_cast_fp16 = einsum(equation = var_1734_equation_0, values = (var_1572_cast_fp16, var_1372_cast_fp16))[name = tensor("op_1734_cast_fp16")]; + tensor var_1735_to_fp16 = const()[name = tensor("op_1735_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_141_cast_fp16 = mul(x = var_1734_cast_fp16, y = var_1735_to_fp16)[name = tensor("aw_chunk_141_cast_fp16")]; + tensor var_1738_equation_0 = const()[name = tensor("op_1738_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1738_cast_fp16 = einsum(equation = var_1738_equation_0, values = (var_1572_cast_fp16, var_1379_cast_fp16))[name = tensor("op_1738_cast_fp16")]; + tensor var_1739_to_fp16 = const()[name = tensor("op_1739_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_143_cast_fp16 = mul(x = var_1738_cast_fp16, y = var_1739_to_fp16)[name = tensor("aw_chunk_143_cast_fp16")]; + tensor var_1742_equation_0 = const()[name = tensor("op_1742_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1742_cast_fp16 = einsum(equation = var_1742_equation_0, values = (var_1576_cast_fp16, var_1386_cast_fp16))[name = tensor("op_1742_cast_fp16")]; + tensor var_1743_to_fp16 = const()[name = tensor("op_1743_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_145_cast_fp16 = mul(x = var_1742_cast_fp16, y = var_1743_to_fp16)[name = tensor("aw_chunk_145_cast_fp16")]; + tensor var_1746_equation_0 = const()[name = tensor("op_1746_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1746_cast_fp16 = einsum(equation = var_1746_equation_0, values = (var_1576_cast_fp16, var_1393_cast_fp16))[name = tensor("op_1746_cast_fp16")]; + tensor var_1747_to_fp16 = const()[name = tensor("op_1747_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_147_cast_fp16 = mul(x = var_1746_cast_fp16, y = var_1747_to_fp16)[name = tensor("aw_chunk_147_cast_fp16")]; + tensor var_1750_equation_0 = const()[name = tensor("op_1750_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1750_cast_fp16 = einsum(equation = var_1750_equation_0, values = (var_1576_cast_fp16, var_1400_cast_fp16))[name = tensor("op_1750_cast_fp16")]; + tensor var_1751_to_fp16 = const()[name = tensor("op_1751_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_149_cast_fp16 = mul(x = var_1750_cast_fp16, y = var_1751_to_fp16)[name = tensor("aw_chunk_149_cast_fp16")]; + tensor var_1754_equation_0 = const()[name = tensor("op_1754_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1754_cast_fp16 = einsum(equation = var_1754_equation_0, values = (var_1576_cast_fp16, var_1407_cast_fp16))[name = tensor("op_1754_cast_fp16")]; + tensor var_1755_to_fp16 = const()[name = tensor("op_1755_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_151_cast_fp16 = mul(x = var_1754_cast_fp16, y = var_1755_to_fp16)[name = tensor("aw_chunk_151_cast_fp16")]; + tensor var_1758_equation_0 = const()[name = tensor("op_1758_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1758_cast_fp16 = einsum(equation = var_1758_equation_0, values = (var_1580_cast_fp16, var_1414_cast_fp16))[name = tensor("op_1758_cast_fp16")]; + tensor var_1759_to_fp16 = const()[name = tensor("op_1759_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_153_cast_fp16 = mul(x = var_1758_cast_fp16, y = var_1759_to_fp16)[name = tensor("aw_chunk_153_cast_fp16")]; + tensor var_1762_equation_0 = const()[name = tensor("op_1762_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1762_cast_fp16 = einsum(equation = var_1762_equation_0, values = (var_1580_cast_fp16, var_1421_cast_fp16))[name = tensor("op_1762_cast_fp16")]; + tensor var_1763_to_fp16 = const()[name = tensor("op_1763_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_155_cast_fp16 = mul(x = var_1762_cast_fp16, y = var_1763_to_fp16)[name = tensor("aw_chunk_155_cast_fp16")]; + tensor var_1766_equation_0 = const()[name = tensor("op_1766_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1766_cast_fp16 = einsum(equation = var_1766_equation_0, values = (var_1580_cast_fp16, var_1428_cast_fp16))[name = tensor("op_1766_cast_fp16")]; + tensor var_1767_to_fp16 = const()[name = tensor("op_1767_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_157_cast_fp16 = mul(x = var_1766_cast_fp16, y = var_1767_to_fp16)[name = tensor("aw_chunk_157_cast_fp16")]; + tensor var_1770_equation_0 = const()[name = tensor("op_1770_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1770_cast_fp16 = einsum(equation = var_1770_equation_0, values = (var_1580_cast_fp16, var_1435_cast_fp16))[name = tensor("op_1770_cast_fp16")]; + tensor var_1771_to_fp16 = const()[name = tensor("op_1771_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_159_cast_fp16 = mul(x = var_1770_cast_fp16, y = var_1771_to_fp16)[name = tensor("aw_chunk_159_cast_fp16")]; + tensor var_1774_equation_0 = const()[name = tensor("op_1774_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1774_cast_fp16 = einsum(equation = var_1774_equation_0, values = (var_1584_cast_fp16, var_1442_cast_fp16))[name = tensor("op_1774_cast_fp16")]; + tensor var_1775_to_fp16 = const()[name = tensor("op_1775_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_161_cast_fp16 = mul(x = var_1774_cast_fp16, y = var_1775_to_fp16)[name = tensor("aw_chunk_161_cast_fp16")]; + tensor var_1778_equation_0 = const()[name = tensor("op_1778_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1778_cast_fp16 = einsum(equation = var_1778_equation_0, values = (var_1584_cast_fp16, var_1449_cast_fp16))[name = tensor("op_1778_cast_fp16")]; + tensor var_1779_to_fp16 = const()[name = tensor("op_1779_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_163_cast_fp16 = mul(x = var_1778_cast_fp16, y = var_1779_to_fp16)[name = tensor("aw_chunk_163_cast_fp16")]; + tensor var_1782_equation_0 = const()[name = tensor("op_1782_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1782_cast_fp16 = einsum(equation = var_1782_equation_0, values = (var_1584_cast_fp16, var_1456_cast_fp16))[name = tensor("op_1782_cast_fp16")]; + tensor var_1783_to_fp16 = const()[name = tensor("op_1783_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_165_cast_fp16 = mul(x = var_1782_cast_fp16, y = var_1783_to_fp16)[name = tensor("aw_chunk_165_cast_fp16")]; + tensor var_1786_equation_0 = const()[name = tensor("op_1786_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1786_cast_fp16 = einsum(equation = var_1786_equation_0, values = (var_1584_cast_fp16, var_1463_cast_fp16))[name = tensor("op_1786_cast_fp16")]; + tensor var_1787_to_fp16 = const()[name = tensor("op_1787_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_167_cast_fp16 = mul(x = var_1786_cast_fp16, y = var_1787_to_fp16)[name = tensor("aw_chunk_167_cast_fp16")]; + tensor var_1790_equation_0 = const()[name = tensor("op_1790_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1790_cast_fp16 = einsum(equation = var_1790_equation_0, values = (var_1588_cast_fp16, var_1470_cast_fp16))[name = tensor("op_1790_cast_fp16")]; + tensor var_1791_to_fp16 = const()[name = tensor("op_1791_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_169_cast_fp16 = mul(x = var_1790_cast_fp16, y = var_1791_to_fp16)[name = tensor("aw_chunk_169_cast_fp16")]; + tensor var_1794_equation_0 = const()[name = tensor("op_1794_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1794_cast_fp16 = einsum(equation = var_1794_equation_0, values = (var_1588_cast_fp16, var_1477_cast_fp16))[name = tensor("op_1794_cast_fp16")]; + tensor var_1795_to_fp16 = const()[name = tensor("op_1795_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_171_cast_fp16 = mul(x = var_1794_cast_fp16, y = var_1795_to_fp16)[name = tensor("aw_chunk_171_cast_fp16")]; + tensor var_1798_equation_0 = const()[name = tensor("op_1798_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1798_cast_fp16 = einsum(equation = var_1798_equation_0, values = (var_1588_cast_fp16, var_1484_cast_fp16))[name = tensor("op_1798_cast_fp16")]; + tensor var_1799_to_fp16 = const()[name = tensor("op_1799_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_173_cast_fp16 = mul(x = var_1798_cast_fp16, y = var_1799_to_fp16)[name = tensor("aw_chunk_173_cast_fp16")]; + tensor var_1802_equation_0 = const()[name = tensor("op_1802_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1802_cast_fp16 = einsum(equation = var_1802_equation_0, values = (var_1588_cast_fp16, var_1491_cast_fp16))[name = tensor("op_1802_cast_fp16")]; + tensor var_1803_to_fp16 = const()[name = tensor("op_1803_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_175_cast_fp16 = mul(x = var_1802_cast_fp16, y = var_1803_to_fp16)[name = tensor("aw_chunk_175_cast_fp16")]; + tensor var_1806_equation_0 = const()[name = tensor("op_1806_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1806_cast_fp16 = einsum(equation = var_1806_equation_0, values = (var_1592_cast_fp16, var_1498_cast_fp16))[name = tensor("op_1806_cast_fp16")]; + tensor var_1807_to_fp16 = const()[name = tensor("op_1807_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_177_cast_fp16 = mul(x = var_1806_cast_fp16, y = var_1807_to_fp16)[name = tensor("aw_chunk_177_cast_fp16")]; + tensor var_1810_equation_0 = const()[name = tensor("op_1810_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1810_cast_fp16 = einsum(equation = var_1810_equation_0, values = (var_1592_cast_fp16, var_1505_cast_fp16))[name = tensor("op_1810_cast_fp16")]; + tensor var_1811_to_fp16 = const()[name = tensor("op_1811_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_179_cast_fp16 = mul(x = var_1810_cast_fp16, y = var_1811_to_fp16)[name = tensor("aw_chunk_179_cast_fp16")]; + tensor var_1814_equation_0 = const()[name = tensor("op_1814_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1814_cast_fp16 = einsum(equation = var_1814_equation_0, values = (var_1592_cast_fp16, var_1512_cast_fp16))[name = tensor("op_1814_cast_fp16")]; + tensor var_1815_to_fp16 = const()[name = tensor("op_1815_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_181_cast_fp16 = mul(x = var_1814_cast_fp16, y = var_1815_to_fp16)[name = tensor("aw_chunk_181_cast_fp16")]; + tensor var_1818_equation_0 = const()[name = tensor("op_1818_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1818_cast_fp16 = einsum(equation = var_1818_equation_0, values = (var_1592_cast_fp16, var_1519_cast_fp16))[name = tensor("op_1818_cast_fp16")]; + tensor var_1819_to_fp16 = const()[name = tensor("op_1819_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_183_cast_fp16 = mul(x = var_1818_cast_fp16, y = var_1819_to_fp16)[name = tensor("aw_chunk_183_cast_fp16")]; + tensor var_1822_equation_0 = const()[name = tensor("op_1822_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1822_cast_fp16 = einsum(equation = var_1822_equation_0, values = (var_1596_cast_fp16, var_1526_cast_fp16))[name = tensor("op_1822_cast_fp16")]; + tensor var_1823_to_fp16 = const()[name = tensor("op_1823_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_185_cast_fp16 = mul(x = var_1822_cast_fp16, y = var_1823_to_fp16)[name = tensor("aw_chunk_185_cast_fp16")]; + tensor var_1826_equation_0 = const()[name = tensor("op_1826_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1826_cast_fp16 = einsum(equation = var_1826_equation_0, values = (var_1596_cast_fp16, var_1533_cast_fp16))[name = tensor("op_1826_cast_fp16")]; + tensor var_1827_to_fp16 = const()[name = tensor("op_1827_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_187_cast_fp16 = mul(x = var_1826_cast_fp16, y = var_1827_to_fp16)[name = tensor("aw_chunk_187_cast_fp16")]; + tensor var_1830_equation_0 = const()[name = tensor("op_1830_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1830_cast_fp16 = einsum(equation = var_1830_equation_0, values = (var_1596_cast_fp16, var_1540_cast_fp16))[name = tensor("op_1830_cast_fp16")]; + tensor var_1831_to_fp16 = const()[name = tensor("op_1831_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_189_cast_fp16 = mul(x = var_1830_cast_fp16, y = var_1831_to_fp16)[name = tensor("aw_chunk_189_cast_fp16")]; + tensor var_1834_equation_0 = const()[name = tensor("op_1834_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_1834_cast_fp16 = einsum(equation = var_1834_equation_0, values = (var_1596_cast_fp16, var_1547_cast_fp16))[name = tensor("op_1834_cast_fp16")]; + tensor var_1835_to_fp16 = const()[name = tensor("op_1835_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_191_cast_fp16 = mul(x = var_1834_cast_fp16, y = var_1835_to_fp16)[name = tensor("aw_chunk_191_cast_fp16")]; + tensor var_1837_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_97_cast_fp16)[name = tensor("op_1837_cast_fp16")]; + tensor var_1838_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_99_cast_fp16)[name = tensor("op_1838_cast_fp16")]; + tensor var_1839_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_101_cast_fp16)[name = tensor("op_1839_cast_fp16")]; + tensor var_1840_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_103_cast_fp16)[name = tensor("op_1840_cast_fp16")]; + tensor var_1841_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_105_cast_fp16)[name = tensor("op_1841_cast_fp16")]; + tensor var_1842_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_107_cast_fp16)[name = tensor("op_1842_cast_fp16")]; + tensor var_1843_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_109_cast_fp16)[name = tensor("op_1843_cast_fp16")]; + tensor var_1844_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_111_cast_fp16)[name = tensor("op_1844_cast_fp16")]; + tensor var_1845_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_113_cast_fp16)[name = tensor("op_1845_cast_fp16")]; + tensor var_1846_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_115_cast_fp16)[name = tensor("op_1846_cast_fp16")]; + tensor var_1847_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_117_cast_fp16)[name = tensor("op_1847_cast_fp16")]; + tensor var_1848_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_119_cast_fp16)[name = tensor("op_1848_cast_fp16")]; + tensor var_1849_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_121_cast_fp16)[name = tensor("op_1849_cast_fp16")]; + tensor var_1850_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_123_cast_fp16)[name = tensor("op_1850_cast_fp16")]; + tensor var_1851_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_125_cast_fp16)[name = tensor("op_1851_cast_fp16")]; + tensor var_1852_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_127_cast_fp16)[name = tensor("op_1852_cast_fp16")]; + tensor var_1853_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_129_cast_fp16)[name = tensor("op_1853_cast_fp16")]; + tensor var_1854_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_131_cast_fp16)[name = tensor("op_1854_cast_fp16")]; + tensor var_1855_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_133_cast_fp16)[name = tensor("op_1855_cast_fp16")]; + tensor var_1856_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_135_cast_fp16)[name = tensor("op_1856_cast_fp16")]; + tensor var_1857_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_137_cast_fp16)[name = tensor("op_1857_cast_fp16")]; + tensor var_1858_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_139_cast_fp16)[name = tensor("op_1858_cast_fp16")]; + tensor var_1859_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_141_cast_fp16)[name = tensor("op_1859_cast_fp16")]; + tensor var_1860_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_143_cast_fp16)[name = tensor("op_1860_cast_fp16")]; + tensor var_1861_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_145_cast_fp16)[name = tensor("op_1861_cast_fp16")]; + tensor var_1862_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_147_cast_fp16)[name = tensor("op_1862_cast_fp16")]; + tensor var_1863_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_149_cast_fp16)[name = tensor("op_1863_cast_fp16")]; + tensor var_1864_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_151_cast_fp16)[name = tensor("op_1864_cast_fp16")]; + tensor var_1865_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_153_cast_fp16)[name = tensor("op_1865_cast_fp16")]; + tensor var_1866_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_155_cast_fp16)[name = tensor("op_1866_cast_fp16")]; + tensor var_1867_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_157_cast_fp16)[name = tensor("op_1867_cast_fp16")]; + tensor var_1868_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_159_cast_fp16)[name = tensor("op_1868_cast_fp16")]; + tensor var_1869_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_161_cast_fp16)[name = tensor("op_1869_cast_fp16")]; + tensor var_1870_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_163_cast_fp16)[name = tensor("op_1870_cast_fp16")]; + tensor var_1871_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_165_cast_fp16)[name = tensor("op_1871_cast_fp16")]; + tensor var_1872_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_167_cast_fp16)[name = tensor("op_1872_cast_fp16")]; + tensor var_1873_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_169_cast_fp16)[name = tensor("op_1873_cast_fp16")]; + tensor var_1874_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_171_cast_fp16)[name = tensor("op_1874_cast_fp16")]; + tensor var_1875_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_173_cast_fp16)[name = tensor("op_1875_cast_fp16")]; + tensor var_1876_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_175_cast_fp16)[name = tensor("op_1876_cast_fp16")]; + tensor var_1877_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_177_cast_fp16)[name = tensor("op_1877_cast_fp16")]; + tensor var_1878_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_179_cast_fp16)[name = tensor("op_1878_cast_fp16")]; + tensor var_1879_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_181_cast_fp16)[name = tensor("op_1879_cast_fp16")]; + tensor var_1880_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_183_cast_fp16)[name = tensor("op_1880_cast_fp16")]; + tensor var_1881_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_185_cast_fp16)[name = tensor("op_1881_cast_fp16")]; + tensor var_1882_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_187_cast_fp16)[name = tensor("op_1882_cast_fp16")]; + tensor var_1883_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_189_cast_fp16)[name = tensor("op_1883_cast_fp16")]; + tensor var_1884_cast_fp16 = softmax(axis = var_1110, x = aw_chunk_191_cast_fp16)[name = tensor("op_1884_cast_fp16")]; + tensor var_1886_equation_0 = const()[name = tensor("op_1886_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1886_cast_fp16 = einsum(equation = var_1886_equation_0, values = (var_1598_cast_fp16, var_1837_cast_fp16))[name = tensor("op_1886_cast_fp16")]; + tensor var_1888_equation_0 = const()[name = tensor("op_1888_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1888_cast_fp16 = einsum(equation = var_1888_equation_0, values = (var_1598_cast_fp16, var_1838_cast_fp16))[name = tensor("op_1888_cast_fp16")]; + tensor var_1890_equation_0 = const()[name = tensor("op_1890_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1890_cast_fp16 = einsum(equation = var_1890_equation_0, values = (var_1598_cast_fp16, var_1839_cast_fp16))[name = tensor("op_1890_cast_fp16")]; + tensor var_1892_equation_0 = const()[name = tensor("op_1892_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1892_cast_fp16 = einsum(equation = var_1892_equation_0, values = (var_1598_cast_fp16, var_1840_cast_fp16))[name = tensor("op_1892_cast_fp16")]; + tensor var_1894_equation_0 = const()[name = tensor("op_1894_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1894_cast_fp16 = einsum(equation = var_1894_equation_0, values = (var_1602_cast_fp16, var_1841_cast_fp16))[name = tensor("op_1894_cast_fp16")]; + tensor var_1896_equation_0 = const()[name = tensor("op_1896_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1896_cast_fp16 = einsum(equation = var_1896_equation_0, values = (var_1602_cast_fp16, var_1842_cast_fp16))[name = tensor("op_1896_cast_fp16")]; + tensor var_1898_equation_0 = const()[name = tensor("op_1898_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1898_cast_fp16 = einsum(equation = var_1898_equation_0, values = (var_1602_cast_fp16, var_1843_cast_fp16))[name = tensor("op_1898_cast_fp16")]; + tensor var_1900_equation_0 = const()[name = tensor("op_1900_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1900_cast_fp16 = einsum(equation = var_1900_equation_0, values = (var_1602_cast_fp16, var_1844_cast_fp16))[name = tensor("op_1900_cast_fp16")]; + tensor var_1902_equation_0 = const()[name = tensor("op_1902_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1902_cast_fp16 = einsum(equation = var_1902_equation_0, values = (var_1606_cast_fp16, var_1845_cast_fp16))[name = tensor("op_1902_cast_fp16")]; + tensor var_1904_equation_0 = const()[name = tensor("op_1904_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1904_cast_fp16 = einsum(equation = var_1904_equation_0, values = (var_1606_cast_fp16, var_1846_cast_fp16))[name = tensor("op_1904_cast_fp16")]; + tensor var_1906_equation_0 = const()[name = tensor("op_1906_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1906_cast_fp16 = einsum(equation = var_1906_equation_0, values = (var_1606_cast_fp16, var_1847_cast_fp16))[name = tensor("op_1906_cast_fp16")]; + tensor var_1908_equation_0 = const()[name = tensor("op_1908_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1908_cast_fp16 = einsum(equation = var_1908_equation_0, values = (var_1606_cast_fp16, var_1848_cast_fp16))[name = tensor("op_1908_cast_fp16")]; + tensor var_1910_equation_0 = const()[name = tensor("op_1910_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1910_cast_fp16 = einsum(equation = var_1910_equation_0, values = (var_1610_cast_fp16, var_1849_cast_fp16))[name = tensor("op_1910_cast_fp16")]; + tensor var_1912_equation_0 = const()[name = tensor("op_1912_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1912_cast_fp16 = einsum(equation = var_1912_equation_0, values = (var_1610_cast_fp16, var_1850_cast_fp16))[name = tensor("op_1912_cast_fp16")]; + tensor var_1914_equation_0 = const()[name = tensor("op_1914_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1914_cast_fp16 = einsum(equation = var_1914_equation_0, values = (var_1610_cast_fp16, var_1851_cast_fp16))[name = tensor("op_1914_cast_fp16")]; + tensor var_1916_equation_0 = const()[name = tensor("op_1916_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1916_cast_fp16 = einsum(equation = var_1916_equation_0, values = (var_1610_cast_fp16, var_1852_cast_fp16))[name = tensor("op_1916_cast_fp16")]; + tensor var_1918_equation_0 = const()[name = tensor("op_1918_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1918_cast_fp16 = einsum(equation = var_1918_equation_0, values = (var_1614_cast_fp16, var_1853_cast_fp16))[name = tensor("op_1918_cast_fp16")]; + tensor var_1920_equation_0 = const()[name = tensor("op_1920_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1920_cast_fp16 = einsum(equation = var_1920_equation_0, values = (var_1614_cast_fp16, var_1854_cast_fp16))[name = tensor("op_1920_cast_fp16")]; + tensor var_1922_equation_0 = const()[name = tensor("op_1922_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1922_cast_fp16 = einsum(equation = var_1922_equation_0, values = (var_1614_cast_fp16, var_1855_cast_fp16))[name = tensor("op_1922_cast_fp16")]; + tensor var_1924_equation_0 = const()[name = tensor("op_1924_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1924_cast_fp16 = einsum(equation = var_1924_equation_0, values = (var_1614_cast_fp16, var_1856_cast_fp16))[name = tensor("op_1924_cast_fp16")]; + tensor var_1926_equation_0 = const()[name = tensor("op_1926_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1926_cast_fp16 = einsum(equation = var_1926_equation_0, values = (var_1618_cast_fp16, var_1857_cast_fp16))[name = tensor("op_1926_cast_fp16")]; + tensor var_1928_equation_0 = const()[name = tensor("op_1928_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1928_cast_fp16 = einsum(equation = var_1928_equation_0, values = (var_1618_cast_fp16, var_1858_cast_fp16))[name = tensor("op_1928_cast_fp16")]; + tensor var_1930_equation_0 = const()[name = tensor("op_1930_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1930_cast_fp16 = einsum(equation = var_1930_equation_0, values = (var_1618_cast_fp16, var_1859_cast_fp16))[name = tensor("op_1930_cast_fp16")]; + tensor var_1932_equation_0 = const()[name = tensor("op_1932_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1932_cast_fp16 = einsum(equation = var_1932_equation_0, values = (var_1618_cast_fp16, var_1860_cast_fp16))[name = tensor("op_1932_cast_fp16")]; + tensor var_1934_equation_0 = const()[name = tensor("op_1934_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1934_cast_fp16 = einsum(equation = var_1934_equation_0, values = (var_1622_cast_fp16, var_1861_cast_fp16))[name = tensor("op_1934_cast_fp16")]; + tensor var_1936_equation_0 = const()[name = tensor("op_1936_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1936_cast_fp16 = einsum(equation = var_1936_equation_0, values = (var_1622_cast_fp16, var_1862_cast_fp16))[name = tensor("op_1936_cast_fp16")]; + tensor var_1938_equation_0 = const()[name = tensor("op_1938_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1938_cast_fp16 = einsum(equation = var_1938_equation_0, values = (var_1622_cast_fp16, var_1863_cast_fp16))[name = tensor("op_1938_cast_fp16")]; + tensor var_1940_equation_0 = const()[name = tensor("op_1940_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1940_cast_fp16 = einsum(equation = var_1940_equation_0, values = (var_1622_cast_fp16, var_1864_cast_fp16))[name = tensor("op_1940_cast_fp16")]; + tensor var_1942_equation_0 = const()[name = tensor("op_1942_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1942_cast_fp16 = einsum(equation = var_1942_equation_0, values = (var_1626_cast_fp16, var_1865_cast_fp16))[name = tensor("op_1942_cast_fp16")]; + tensor var_1944_equation_0 = const()[name = tensor("op_1944_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1944_cast_fp16 = einsum(equation = var_1944_equation_0, values = (var_1626_cast_fp16, var_1866_cast_fp16))[name = tensor("op_1944_cast_fp16")]; + tensor var_1946_equation_0 = const()[name = tensor("op_1946_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1946_cast_fp16 = einsum(equation = var_1946_equation_0, values = (var_1626_cast_fp16, var_1867_cast_fp16))[name = tensor("op_1946_cast_fp16")]; + tensor var_1948_equation_0 = const()[name = tensor("op_1948_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1948_cast_fp16 = einsum(equation = var_1948_equation_0, values = (var_1626_cast_fp16, var_1868_cast_fp16))[name = tensor("op_1948_cast_fp16")]; + tensor var_1950_equation_0 = const()[name = tensor("op_1950_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1950_cast_fp16 = einsum(equation = var_1950_equation_0, values = (var_1630_cast_fp16, var_1869_cast_fp16))[name = tensor("op_1950_cast_fp16")]; + tensor var_1952_equation_0 = const()[name = tensor("op_1952_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1952_cast_fp16 = einsum(equation = var_1952_equation_0, values = (var_1630_cast_fp16, var_1870_cast_fp16))[name = tensor("op_1952_cast_fp16")]; + tensor var_1954_equation_0 = const()[name = tensor("op_1954_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1954_cast_fp16 = einsum(equation = var_1954_equation_0, values = (var_1630_cast_fp16, var_1871_cast_fp16))[name = tensor("op_1954_cast_fp16")]; + tensor var_1956_equation_0 = const()[name = tensor("op_1956_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1956_cast_fp16 = einsum(equation = var_1956_equation_0, values = (var_1630_cast_fp16, var_1872_cast_fp16))[name = tensor("op_1956_cast_fp16")]; + tensor var_1958_equation_0 = const()[name = tensor("op_1958_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1958_cast_fp16 = einsum(equation = var_1958_equation_0, values = (var_1634_cast_fp16, var_1873_cast_fp16))[name = tensor("op_1958_cast_fp16")]; + tensor var_1960_equation_0 = const()[name = tensor("op_1960_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1960_cast_fp16 = einsum(equation = var_1960_equation_0, values = (var_1634_cast_fp16, var_1874_cast_fp16))[name = tensor("op_1960_cast_fp16")]; + tensor var_1962_equation_0 = const()[name = tensor("op_1962_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1962_cast_fp16 = einsum(equation = var_1962_equation_0, values = (var_1634_cast_fp16, var_1875_cast_fp16))[name = tensor("op_1962_cast_fp16")]; + tensor var_1964_equation_0 = const()[name = tensor("op_1964_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1964_cast_fp16 = einsum(equation = var_1964_equation_0, values = (var_1634_cast_fp16, var_1876_cast_fp16))[name = tensor("op_1964_cast_fp16")]; + tensor var_1966_equation_0 = const()[name = tensor("op_1966_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1966_cast_fp16 = einsum(equation = var_1966_equation_0, values = (var_1638_cast_fp16, var_1877_cast_fp16))[name = tensor("op_1966_cast_fp16")]; + tensor var_1968_equation_0 = const()[name = tensor("op_1968_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1968_cast_fp16 = einsum(equation = var_1968_equation_0, values = (var_1638_cast_fp16, var_1878_cast_fp16))[name = tensor("op_1968_cast_fp16")]; + tensor var_1970_equation_0 = const()[name = tensor("op_1970_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1970_cast_fp16 = einsum(equation = var_1970_equation_0, values = (var_1638_cast_fp16, var_1879_cast_fp16))[name = tensor("op_1970_cast_fp16")]; + tensor var_1972_equation_0 = const()[name = tensor("op_1972_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1972_cast_fp16 = einsum(equation = var_1972_equation_0, values = (var_1638_cast_fp16, var_1880_cast_fp16))[name = tensor("op_1972_cast_fp16")]; + tensor var_1974_equation_0 = const()[name = tensor("op_1974_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1974_cast_fp16 = einsum(equation = var_1974_equation_0, values = (var_1642_cast_fp16, var_1881_cast_fp16))[name = tensor("op_1974_cast_fp16")]; + tensor var_1976_equation_0 = const()[name = tensor("op_1976_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1976_cast_fp16 = einsum(equation = var_1976_equation_0, values = (var_1642_cast_fp16, var_1882_cast_fp16))[name = tensor("op_1976_cast_fp16")]; + tensor var_1978_equation_0 = const()[name = tensor("op_1978_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1978_cast_fp16 = einsum(equation = var_1978_equation_0, values = (var_1642_cast_fp16, var_1883_cast_fp16))[name = tensor("op_1978_cast_fp16")]; + tensor var_1980_equation_0 = const()[name = tensor("op_1980_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_1980_cast_fp16 = einsum(equation = var_1980_equation_0, values = (var_1642_cast_fp16, var_1884_cast_fp16))[name = tensor("op_1980_cast_fp16")]; + tensor var_1982_interleave_0 = const()[name = tensor("op_1982_interleave_0"), val = tensor(false)]; + tensor var_1982_cast_fp16 = concat(axis = var_1093, interleave = var_1982_interleave_0, values = (var_1886_cast_fp16, var_1888_cast_fp16, var_1890_cast_fp16, var_1892_cast_fp16))[name = tensor("op_1982_cast_fp16")]; + tensor var_1984_interleave_0 = const()[name = tensor("op_1984_interleave_0"), val = tensor(false)]; + tensor var_1984_cast_fp16 = concat(axis = var_1093, interleave = var_1984_interleave_0, values = (var_1894_cast_fp16, var_1896_cast_fp16, var_1898_cast_fp16, var_1900_cast_fp16))[name = tensor("op_1984_cast_fp16")]; + tensor var_1986_interleave_0 = const()[name = tensor("op_1986_interleave_0"), val = tensor(false)]; + tensor var_1986_cast_fp16 = concat(axis = var_1093, interleave = var_1986_interleave_0, values = (var_1902_cast_fp16, var_1904_cast_fp16, var_1906_cast_fp16, var_1908_cast_fp16))[name = tensor("op_1986_cast_fp16")]; + tensor var_1988_interleave_0 = const()[name = tensor("op_1988_interleave_0"), val = tensor(false)]; + tensor var_1988_cast_fp16 = concat(axis = var_1093, interleave = var_1988_interleave_0, values = (var_1910_cast_fp16, var_1912_cast_fp16, var_1914_cast_fp16, var_1916_cast_fp16))[name = tensor("op_1988_cast_fp16")]; + tensor var_1990_interleave_0 = const()[name = tensor("op_1990_interleave_0"), val = tensor(false)]; + tensor var_1990_cast_fp16 = concat(axis = var_1093, interleave = var_1990_interleave_0, values = (var_1918_cast_fp16, var_1920_cast_fp16, var_1922_cast_fp16, var_1924_cast_fp16))[name = tensor("op_1990_cast_fp16")]; + tensor var_1992_interleave_0 = const()[name = tensor("op_1992_interleave_0"), val = tensor(false)]; + tensor var_1992_cast_fp16 = concat(axis = var_1093, interleave = var_1992_interleave_0, values = (var_1926_cast_fp16, var_1928_cast_fp16, var_1930_cast_fp16, var_1932_cast_fp16))[name = tensor("op_1992_cast_fp16")]; + tensor var_1994_interleave_0 = const()[name = tensor("op_1994_interleave_0"), val = tensor(false)]; + tensor var_1994_cast_fp16 = concat(axis = var_1093, interleave = var_1994_interleave_0, values = (var_1934_cast_fp16, var_1936_cast_fp16, var_1938_cast_fp16, var_1940_cast_fp16))[name = tensor("op_1994_cast_fp16")]; + tensor var_1996_interleave_0 = const()[name = tensor("op_1996_interleave_0"), val = tensor(false)]; + tensor var_1996_cast_fp16 = concat(axis = var_1093, interleave = var_1996_interleave_0, values = (var_1942_cast_fp16, var_1944_cast_fp16, var_1946_cast_fp16, var_1948_cast_fp16))[name = tensor("op_1996_cast_fp16")]; + tensor var_1998_interleave_0 = const()[name = tensor("op_1998_interleave_0"), val = tensor(false)]; + tensor var_1998_cast_fp16 = concat(axis = var_1093, interleave = var_1998_interleave_0, values = (var_1950_cast_fp16, var_1952_cast_fp16, var_1954_cast_fp16, var_1956_cast_fp16))[name = tensor("op_1998_cast_fp16")]; + tensor var_2000_interleave_0 = const()[name = tensor("op_2000_interleave_0"), val = tensor(false)]; + tensor var_2000_cast_fp16 = concat(axis = var_1093, interleave = var_2000_interleave_0, values = (var_1958_cast_fp16, var_1960_cast_fp16, var_1962_cast_fp16, var_1964_cast_fp16))[name = tensor("op_2000_cast_fp16")]; + tensor var_2002_interleave_0 = const()[name = tensor("op_2002_interleave_0"), val = tensor(false)]; + tensor var_2002_cast_fp16 = concat(axis = var_1093, interleave = var_2002_interleave_0, values = (var_1966_cast_fp16, var_1968_cast_fp16, var_1970_cast_fp16, var_1972_cast_fp16))[name = tensor("op_2002_cast_fp16")]; + tensor var_2004_interleave_0 = const()[name = tensor("op_2004_interleave_0"), val = tensor(false)]; + tensor var_2004_cast_fp16 = concat(axis = var_1093, interleave = var_2004_interleave_0, values = (var_1974_cast_fp16, var_1976_cast_fp16, var_1978_cast_fp16, var_1980_cast_fp16))[name = tensor("op_2004_cast_fp16")]; + tensor input_9_interleave_0 = const()[name = tensor("input_9_interleave_0"), val = tensor(false)]; + tensor input_9_cast_fp16 = concat(axis = var_1110, interleave = input_9_interleave_0, values = (var_1982_cast_fp16, var_1984_cast_fp16, var_1986_cast_fp16, var_1988_cast_fp16, var_1990_cast_fp16, var_1992_cast_fp16, var_1994_cast_fp16, var_1996_cast_fp16, var_1998_cast_fp16, var_2000_cast_fp16, var_2002_cast_fp16, var_2004_cast_fp16))[name = tensor("input_9_cast_fp16")]; + tensor var_2009 = const()[name = tensor("op_2009"), val = tensor([1, 1])]; + tensor var_2011 = const()[name = tensor("op_2011"), val = tensor([1, 1])]; + tensor obj_7_pad_type_0 = const()[name = tensor("obj_7_pad_type_0"), val = tensor("custom")]; + tensor obj_7_pad_0 = const()[name = tensor("obj_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23938944)))]; + tensor layers_1_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25118656)))]; + tensor obj_7_cast_fp16 = conv(bias = layers_1_self_attn_o_proj_bias_to_fp16, dilations = var_2011, groups = var_1110, pad = obj_7_pad_0, pad_type = obj_7_pad_type_0, strides = var_2009, weight = layers_1_self_attn_o_proj_weight_to_fp16, x = input_9_cast_fp16)[name = tensor("obj_7_cast_fp16")]; + tensor inputs_7_cast_fp16 = add(x = inputs_5_cast_fp16, y = obj_7_cast_fp16)[name = tensor("inputs_7_cast_fp16")]; + tensor var_2017 = const()[name = tensor("op_2017"), val = tensor([1])]; + tensor channels_mean_7_cast_fp16 = reduce_mean(axes = var_2017, keep_dims = var_1111, x = inputs_7_cast_fp16)[name = tensor("channels_mean_7_cast_fp16")]; + tensor zero_mean_7_cast_fp16 = sub(x = inputs_7_cast_fp16, y = channels_mean_7_cast_fp16)[name = tensor("zero_mean_7_cast_fp16")]; + tensor zero_mean_sq_7_cast_fp16 = mul(x = zero_mean_7_cast_fp16, y = zero_mean_7_cast_fp16)[name = tensor("zero_mean_sq_7_cast_fp16")]; + tensor var_2021 = const()[name = tensor("op_2021"), val = tensor([1])]; + tensor var_2022_cast_fp16 = reduce_mean(axes = var_2021, keep_dims = var_1111, x = zero_mean_sq_7_cast_fp16)[name = tensor("op_2022_cast_fp16")]; + tensor var_2023_to_fp16 = const()[name = tensor("op_2023_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2024_cast_fp16 = add(x = var_2022_cast_fp16, y = var_2023_to_fp16)[name = tensor("op_2024_cast_fp16")]; + tensor denom_7_epsilon_0_to_fp16 = const()[name = tensor("denom_7_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_7_cast_fp16 = rsqrt(epsilon = denom_7_epsilon_0_to_fp16, x = var_2024_cast_fp16)[name = tensor("denom_7_cast_fp16")]; + tensor out_7_cast_fp16 = mul(x = zero_mean_7_cast_fp16, y = denom_7_cast_fp16)[name = tensor("out_7_cast_fp16")]; + tensor input_11_gamma_0_to_fp16 = const()[name = tensor("input_11_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25120256)))]; + tensor input_11_beta_0_to_fp16 = const()[name = tensor("input_11_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25121856)))]; + tensor input_11_epsilon_0_to_fp16 = const()[name = tensor("input_11_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_11_cast_fp16 = batch_norm(beta = input_11_beta_0_to_fp16, epsilon = input_11_epsilon_0_to_fp16, gamma = input_11_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_7_cast_fp16)[name = tensor("input_11_cast_fp16")]; + tensor var_2035 = const()[name = tensor("op_2035"), val = tensor([1, 1])]; + tensor var_2037 = const()[name = tensor("op_2037"), val = tensor([1, 1])]; + tensor input_13_pad_type_0 = const()[name = tensor("input_13_pad_type_0"), val = tensor("custom")]; + tensor input_13_pad_0 = const()[name = tensor("input_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_fc1_weight_to_fp16 = const()[name = tensor("layers_1_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25123456)))]; + tensor layers_1_fc1_bias_to_fp16 = const()[name = tensor("layers_1_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29842112)))]; + tensor input_13_cast_fp16 = conv(bias = layers_1_fc1_bias_to_fp16, dilations = var_2037, groups = var_1110, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = var_2035, weight = layers_1_fc1_weight_to_fp16, x = input_11_cast_fp16)[name = tensor("input_13_cast_fp16")]; + tensor input_15_mode_0 = const()[name = tensor("input_15_mode_0"), val = tensor("EXACT")]; + tensor input_15_cast_fp16 = gelu(mode = input_15_mode_0, x = input_13_cast_fp16)[name = tensor("input_15_cast_fp16")]; + tensor var_2043 = const()[name = tensor("op_2043"), val = tensor([1, 1])]; + tensor var_2045 = const()[name = tensor("op_2045"), val = tensor([1, 1])]; + tensor hidden_states_7_pad_type_0 = const()[name = tensor("hidden_states_7_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_7_pad_0 = const()[name = tensor("hidden_states_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_fc2_weight_to_fp16 = const()[name = tensor("layers_1_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29848320)))]; + tensor layers_1_fc2_bias_to_fp16 = const()[name = tensor("layers_1_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(34566976)))]; + tensor hidden_states_7_cast_fp16 = conv(bias = layers_1_fc2_bias_to_fp16, dilations = var_2045, groups = var_1110, pad = hidden_states_7_pad_0, pad_type = hidden_states_7_pad_type_0, strides = var_2043, weight = layers_1_fc2_weight_to_fp16, x = input_15_cast_fp16)[name = tensor("hidden_states_7_cast_fp16")]; + tensor inputs_9_cast_fp16 = add(x = inputs_7_cast_fp16, y = hidden_states_7_cast_fp16)[name = tensor("inputs_9_cast_fp16")]; + tensor var_2052 = const()[name = tensor("op_2052"), val = tensor(3)]; + tensor var_2069 = const()[name = tensor("op_2069"), val = tensor(1)]; + tensor var_2070 = const()[name = tensor("op_2070"), val = tensor(true)]; + tensor var_2080 = const()[name = tensor("op_2080"), val = tensor([1])]; + tensor channels_mean_9_cast_fp16 = reduce_mean(axes = var_2080, keep_dims = var_2070, x = inputs_9_cast_fp16)[name = tensor("channels_mean_9_cast_fp16")]; + tensor zero_mean_9_cast_fp16 = sub(x = inputs_9_cast_fp16, y = channels_mean_9_cast_fp16)[name = tensor("zero_mean_9_cast_fp16")]; + tensor zero_mean_sq_9_cast_fp16 = mul(x = zero_mean_9_cast_fp16, y = zero_mean_9_cast_fp16)[name = tensor("zero_mean_sq_9_cast_fp16")]; + tensor var_2084 = const()[name = tensor("op_2084"), val = tensor([1])]; + tensor var_2085_cast_fp16 = reduce_mean(axes = var_2084, keep_dims = var_2070, x = zero_mean_sq_9_cast_fp16)[name = tensor("op_2085_cast_fp16")]; + tensor var_2086_to_fp16 = const()[name = tensor("op_2086_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2087_cast_fp16 = add(x = var_2085_cast_fp16, y = var_2086_to_fp16)[name = tensor("op_2087_cast_fp16")]; + tensor denom_9_epsilon_0_to_fp16 = const()[name = tensor("denom_9_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_9_cast_fp16 = rsqrt(epsilon = denom_9_epsilon_0_to_fp16, x = var_2087_cast_fp16)[name = tensor("denom_9_cast_fp16")]; + tensor out_9_cast_fp16 = mul(x = zero_mean_9_cast_fp16, y = denom_9_cast_fp16)[name = tensor("out_9_cast_fp16")]; + tensor obj_9_gamma_0_to_fp16 = const()[name = tensor("obj_9_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(34568576)))]; + tensor obj_9_beta_0_to_fp16 = const()[name = tensor("obj_9_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(34570176)))]; + tensor obj_9_epsilon_0_to_fp16 = const()[name = tensor("obj_9_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_9_cast_fp16 = batch_norm(beta = obj_9_beta_0_to_fp16, epsilon = obj_9_epsilon_0_to_fp16, gamma = obj_9_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_9_cast_fp16)[name = tensor("obj_9_cast_fp16")]; + tensor var_2102 = const()[name = tensor("op_2102"), val = tensor([1, 1])]; + tensor var_2104 = const()[name = tensor("op_2104"), val = tensor([1, 1])]; + tensor query_5_pad_type_0 = const()[name = tensor("query_5_pad_type_0"), val = tensor("custom")]; + tensor query_5_pad_0 = const()[name = tensor("query_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(34571776)))]; + tensor layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35751488)))]; + tensor query_5_cast_fp16 = conv(bias = layers_2_self_attn_q_proj_bias_to_fp16, dilations = var_2104, groups = var_2069, pad = query_5_pad_0, pad_type = query_5_pad_type_0, strides = var_2102, weight = layers_2_self_attn_q_proj_weight_to_fp16, x = obj_9_cast_fp16)[name = tensor("query_5_cast_fp16")]; + tensor var_2108 = const()[name = tensor("op_2108"), val = tensor([1, 1])]; + tensor var_2110 = const()[name = tensor("op_2110"), val = tensor([1, 1])]; + tensor key_5_pad_type_0 = const()[name = tensor("key_5_pad_type_0"), val = tensor("custom")]; + tensor key_5_pad_0 = const()[name = tensor("key_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35753088)))]; + tensor key_5_cast_fp16 = conv(dilations = var_2110, groups = var_2069, pad = key_5_pad_0, pad_type = key_5_pad_type_0, strides = var_2108, weight = layers_2_self_attn_k_proj_weight_to_fp16, x = obj_9_cast_fp16)[name = tensor("key_5_cast_fp16")]; + tensor var_2115 = const()[name = tensor("op_2115"), val = tensor([1, 1])]; + tensor var_2117 = const()[name = tensor("op_2117"), val = tensor([1, 1])]; + tensor value_5_pad_type_0 = const()[name = tensor("value_5_pad_type_0"), val = tensor("custom")]; + tensor value_5_pad_0 = const()[name = tensor("value_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36932800)))]; + tensor layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38112512)))]; + tensor value_5_cast_fp16 = conv(bias = layers_2_self_attn_v_proj_bias_to_fp16, dilations = var_2117, groups = var_2069, pad = value_5_pad_0, pad_type = value_5_pad_type_0, strides = var_2115, weight = layers_2_self_attn_v_proj_weight_to_fp16, x = obj_9_cast_fp16)[name = tensor("value_5_cast_fp16")]; + tensor var_2124_begin_0 = const()[name = tensor("op_2124_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2124_end_0 = const()[name = tensor("op_2124_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2124_end_mask_0 = const()[name = tensor("op_2124_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2124_cast_fp16 = slice_by_index(begin = var_2124_begin_0, end = var_2124_end_0, end_mask = var_2124_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_2124_cast_fp16")]; + tensor var_2128_begin_0 = const()[name = tensor("op_2128_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_2128_end_0 = const()[name = tensor("op_2128_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_2128_end_mask_0 = const()[name = tensor("op_2128_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2128_cast_fp16 = slice_by_index(begin = var_2128_begin_0, end = var_2128_end_0, end_mask = var_2128_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_2128_cast_fp16")]; + tensor var_2132_begin_0 = const()[name = tensor("op_2132_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_2132_end_0 = const()[name = tensor("op_2132_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_2132_end_mask_0 = const()[name = tensor("op_2132_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2132_cast_fp16 = slice_by_index(begin = var_2132_begin_0, end = var_2132_end_0, end_mask = var_2132_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_2132_cast_fp16")]; + tensor var_2136_begin_0 = const()[name = tensor("op_2136_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_2136_end_0 = const()[name = tensor("op_2136_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_2136_end_mask_0 = const()[name = tensor("op_2136_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2136_cast_fp16 = slice_by_index(begin = var_2136_begin_0, end = var_2136_end_0, end_mask = var_2136_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_2136_cast_fp16")]; + tensor var_2140_begin_0 = const()[name = tensor("op_2140_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_2140_end_0 = const()[name = tensor("op_2140_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_2140_end_mask_0 = const()[name = tensor("op_2140_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2140_cast_fp16 = slice_by_index(begin = var_2140_begin_0, end = var_2140_end_0, end_mask = var_2140_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_2140_cast_fp16")]; + tensor var_2144_begin_0 = const()[name = tensor("op_2144_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_2144_end_0 = const()[name = tensor("op_2144_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_2144_end_mask_0 = const()[name = tensor("op_2144_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2144_cast_fp16 = slice_by_index(begin = var_2144_begin_0, end = var_2144_end_0, end_mask = var_2144_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_2144_cast_fp16")]; + tensor var_2148_begin_0 = const()[name = tensor("op_2148_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_2148_end_0 = const()[name = tensor("op_2148_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_2148_end_mask_0 = const()[name = tensor("op_2148_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2148_cast_fp16 = slice_by_index(begin = var_2148_begin_0, end = var_2148_end_0, end_mask = var_2148_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_2148_cast_fp16")]; + tensor var_2152_begin_0 = const()[name = tensor("op_2152_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_2152_end_0 = const()[name = tensor("op_2152_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_2152_end_mask_0 = const()[name = tensor("op_2152_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2152_cast_fp16 = slice_by_index(begin = var_2152_begin_0, end = var_2152_end_0, end_mask = var_2152_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_2152_cast_fp16")]; + tensor var_2156_begin_0 = const()[name = tensor("op_2156_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_2156_end_0 = const()[name = tensor("op_2156_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_2156_end_mask_0 = const()[name = tensor("op_2156_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2156_cast_fp16 = slice_by_index(begin = var_2156_begin_0, end = var_2156_end_0, end_mask = var_2156_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_2156_cast_fp16")]; + tensor var_2160_begin_0 = const()[name = tensor("op_2160_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_2160_end_0 = const()[name = tensor("op_2160_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_2160_end_mask_0 = const()[name = tensor("op_2160_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2160_cast_fp16 = slice_by_index(begin = var_2160_begin_0, end = var_2160_end_0, end_mask = var_2160_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_2160_cast_fp16")]; + tensor var_2164_begin_0 = const()[name = tensor("op_2164_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_2164_end_0 = const()[name = tensor("op_2164_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_2164_end_mask_0 = const()[name = tensor("op_2164_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2164_cast_fp16 = slice_by_index(begin = var_2164_begin_0, end = var_2164_end_0, end_mask = var_2164_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_2164_cast_fp16")]; + tensor var_2168_begin_0 = const()[name = tensor("op_2168_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_2168_end_0 = const()[name = tensor("op_2168_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_2168_end_mask_0 = const()[name = tensor("op_2168_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2168_cast_fp16 = slice_by_index(begin = var_2168_begin_0, end = var_2168_end_0, end_mask = var_2168_end_mask_0, x = query_5_cast_fp16)[name = tensor("op_2168_cast_fp16")]; + tensor var_2177_begin_0 = const()[name = tensor("op_2177_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2177_end_0 = const()[name = tensor("op_2177_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2177_end_mask_0 = const()[name = tensor("op_2177_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2177_cast_fp16 = slice_by_index(begin = var_2177_begin_0, end = var_2177_end_0, end_mask = var_2177_end_mask_0, x = var_2124_cast_fp16)[name = tensor("op_2177_cast_fp16")]; + tensor var_2184_begin_0 = const()[name = tensor("op_2184_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2184_end_0 = const()[name = tensor("op_2184_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2184_end_mask_0 = const()[name = tensor("op_2184_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2184_cast_fp16 = slice_by_index(begin = var_2184_begin_0, end = var_2184_end_0, end_mask = var_2184_end_mask_0, x = var_2124_cast_fp16)[name = tensor("op_2184_cast_fp16")]; + tensor var_2191_begin_0 = const()[name = tensor("op_2191_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2191_end_0 = const()[name = tensor("op_2191_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2191_end_mask_0 = const()[name = tensor("op_2191_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2191_cast_fp16 = slice_by_index(begin = var_2191_begin_0, end = var_2191_end_0, end_mask = var_2191_end_mask_0, x = var_2124_cast_fp16)[name = tensor("op_2191_cast_fp16")]; + tensor var_2198_begin_0 = const()[name = tensor("op_2198_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2198_end_0 = const()[name = tensor("op_2198_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2198_end_mask_0 = const()[name = tensor("op_2198_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2198_cast_fp16 = slice_by_index(begin = var_2198_begin_0, end = var_2198_end_0, end_mask = var_2198_end_mask_0, x = var_2124_cast_fp16)[name = tensor("op_2198_cast_fp16")]; + tensor var_2205_begin_0 = const()[name = tensor("op_2205_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2205_end_0 = const()[name = tensor("op_2205_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2205_end_mask_0 = const()[name = tensor("op_2205_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2205_cast_fp16 = slice_by_index(begin = var_2205_begin_0, end = var_2205_end_0, end_mask = var_2205_end_mask_0, x = var_2128_cast_fp16)[name = tensor("op_2205_cast_fp16")]; + tensor var_2212_begin_0 = const()[name = tensor("op_2212_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2212_end_0 = const()[name = tensor("op_2212_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2212_end_mask_0 = const()[name = tensor("op_2212_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2212_cast_fp16 = slice_by_index(begin = var_2212_begin_0, end = var_2212_end_0, end_mask = var_2212_end_mask_0, x = var_2128_cast_fp16)[name = tensor("op_2212_cast_fp16")]; + tensor var_2219_begin_0 = const()[name = tensor("op_2219_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2219_end_0 = const()[name = tensor("op_2219_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2219_end_mask_0 = const()[name = tensor("op_2219_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2219_cast_fp16 = slice_by_index(begin = var_2219_begin_0, end = var_2219_end_0, end_mask = var_2219_end_mask_0, x = var_2128_cast_fp16)[name = tensor("op_2219_cast_fp16")]; + tensor var_2226_begin_0 = const()[name = tensor("op_2226_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2226_end_0 = const()[name = tensor("op_2226_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2226_end_mask_0 = const()[name = tensor("op_2226_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2226_cast_fp16 = slice_by_index(begin = var_2226_begin_0, end = var_2226_end_0, end_mask = var_2226_end_mask_0, x = var_2128_cast_fp16)[name = tensor("op_2226_cast_fp16")]; + tensor var_2233_begin_0 = const()[name = tensor("op_2233_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2233_end_0 = const()[name = tensor("op_2233_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2233_end_mask_0 = const()[name = tensor("op_2233_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2233_cast_fp16 = slice_by_index(begin = var_2233_begin_0, end = var_2233_end_0, end_mask = var_2233_end_mask_0, x = var_2132_cast_fp16)[name = tensor("op_2233_cast_fp16")]; + tensor var_2240_begin_0 = const()[name = tensor("op_2240_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2240_end_0 = const()[name = tensor("op_2240_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2240_end_mask_0 = const()[name = tensor("op_2240_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2240_cast_fp16 = slice_by_index(begin = var_2240_begin_0, end = var_2240_end_0, end_mask = var_2240_end_mask_0, x = var_2132_cast_fp16)[name = tensor("op_2240_cast_fp16")]; + tensor var_2247_begin_0 = const()[name = tensor("op_2247_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2247_end_0 = const()[name = tensor("op_2247_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2247_end_mask_0 = const()[name = tensor("op_2247_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2247_cast_fp16 = slice_by_index(begin = var_2247_begin_0, end = var_2247_end_0, end_mask = var_2247_end_mask_0, x = var_2132_cast_fp16)[name = tensor("op_2247_cast_fp16")]; + tensor var_2254_begin_0 = const()[name = tensor("op_2254_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2254_end_0 = const()[name = tensor("op_2254_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2254_end_mask_0 = const()[name = tensor("op_2254_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2254_cast_fp16 = slice_by_index(begin = var_2254_begin_0, end = var_2254_end_0, end_mask = var_2254_end_mask_0, x = var_2132_cast_fp16)[name = tensor("op_2254_cast_fp16")]; + tensor var_2261_begin_0 = const()[name = tensor("op_2261_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2261_end_0 = const()[name = tensor("op_2261_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2261_end_mask_0 = const()[name = tensor("op_2261_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2261_cast_fp16 = slice_by_index(begin = var_2261_begin_0, end = var_2261_end_0, end_mask = var_2261_end_mask_0, x = var_2136_cast_fp16)[name = tensor("op_2261_cast_fp16")]; + tensor var_2268_begin_0 = const()[name = tensor("op_2268_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2268_end_0 = const()[name = tensor("op_2268_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2268_end_mask_0 = const()[name = tensor("op_2268_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2268_cast_fp16 = slice_by_index(begin = var_2268_begin_0, end = var_2268_end_0, end_mask = var_2268_end_mask_0, x = var_2136_cast_fp16)[name = tensor("op_2268_cast_fp16")]; + tensor var_2275_begin_0 = const()[name = tensor("op_2275_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2275_end_0 = const()[name = tensor("op_2275_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2275_end_mask_0 = const()[name = tensor("op_2275_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2275_cast_fp16 = slice_by_index(begin = var_2275_begin_0, end = var_2275_end_0, end_mask = var_2275_end_mask_0, x = var_2136_cast_fp16)[name = tensor("op_2275_cast_fp16")]; + tensor var_2282_begin_0 = const()[name = tensor("op_2282_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2282_end_0 = const()[name = tensor("op_2282_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2282_end_mask_0 = const()[name = tensor("op_2282_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2282_cast_fp16 = slice_by_index(begin = var_2282_begin_0, end = var_2282_end_0, end_mask = var_2282_end_mask_0, x = var_2136_cast_fp16)[name = tensor("op_2282_cast_fp16")]; + tensor var_2289_begin_0 = const()[name = tensor("op_2289_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2289_end_0 = const()[name = tensor("op_2289_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2289_end_mask_0 = const()[name = tensor("op_2289_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2289_cast_fp16 = slice_by_index(begin = var_2289_begin_0, end = var_2289_end_0, end_mask = var_2289_end_mask_0, x = var_2140_cast_fp16)[name = tensor("op_2289_cast_fp16")]; + tensor var_2296_begin_0 = const()[name = tensor("op_2296_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2296_end_0 = const()[name = tensor("op_2296_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2296_end_mask_0 = const()[name = tensor("op_2296_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2296_cast_fp16 = slice_by_index(begin = var_2296_begin_0, end = var_2296_end_0, end_mask = var_2296_end_mask_0, x = var_2140_cast_fp16)[name = tensor("op_2296_cast_fp16")]; + tensor var_2303_begin_0 = const()[name = tensor("op_2303_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2303_end_0 = const()[name = tensor("op_2303_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2303_end_mask_0 = const()[name = tensor("op_2303_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2303_cast_fp16 = slice_by_index(begin = var_2303_begin_0, end = var_2303_end_0, end_mask = var_2303_end_mask_0, x = var_2140_cast_fp16)[name = tensor("op_2303_cast_fp16")]; + tensor var_2310_begin_0 = const()[name = tensor("op_2310_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2310_end_0 = const()[name = tensor("op_2310_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2310_end_mask_0 = const()[name = tensor("op_2310_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2310_cast_fp16 = slice_by_index(begin = var_2310_begin_0, end = var_2310_end_0, end_mask = var_2310_end_mask_0, x = var_2140_cast_fp16)[name = tensor("op_2310_cast_fp16")]; + tensor var_2317_begin_0 = const()[name = tensor("op_2317_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2317_end_0 = const()[name = tensor("op_2317_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2317_end_mask_0 = const()[name = tensor("op_2317_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2317_cast_fp16 = slice_by_index(begin = var_2317_begin_0, end = var_2317_end_0, end_mask = var_2317_end_mask_0, x = var_2144_cast_fp16)[name = tensor("op_2317_cast_fp16")]; + tensor var_2324_begin_0 = const()[name = tensor("op_2324_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2324_end_0 = const()[name = tensor("op_2324_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2324_end_mask_0 = const()[name = tensor("op_2324_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2324_cast_fp16 = slice_by_index(begin = var_2324_begin_0, end = var_2324_end_0, end_mask = var_2324_end_mask_0, x = var_2144_cast_fp16)[name = tensor("op_2324_cast_fp16")]; + tensor var_2331_begin_0 = const()[name = tensor("op_2331_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2331_end_0 = const()[name = tensor("op_2331_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2331_end_mask_0 = const()[name = tensor("op_2331_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2331_cast_fp16 = slice_by_index(begin = var_2331_begin_0, end = var_2331_end_0, end_mask = var_2331_end_mask_0, x = var_2144_cast_fp16)[name = tensor("op_2331_cast_fp16")]; + tensor var_2338_begin_0 = const()[name = tensor("op_2338_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2338_end_0 = const()[name = tensor("op_2338_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2338_end_mask_0 = const()[name = tensor("op_2338_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2338_cast_fp16 = slice_by_index(begin = var_2338_begin_0, end = var_2338_end_0, end_mask = var_2338_end_mask_0, x = var_2144_cast_fp16)[name = tensor("op_2338_cast_fp16")]; + tensor var_2345_begin_0 = const()[name = tensor("op_2345_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2345_end_0 = const()[name = tensor("op_2345_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2345_end_mask_0 = const()[name = tensor("op_2345_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2345_cast_fp16 = slice_by_index(begin = var_2345_begin_0, end = var_2345_end_0, end_mask = var_2345_end_mask_0, x = var_2148_cast_fp16)[name = tensor("op_2345_cast_fp16")]; + tensor var_2352_begin_0 = const()[name = tensor("op_2352_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2352_end_0 = const()[name = tensor("op_2352_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2352_end_mask_0 = const()[name = tensor("op_2352_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2352_cast_fp16 = slice_by_index(begin = var_2352_begin_0, end = var_2352_end_0, end_mask = var_2352_end_mask_0, x = var_2148_cast_fp16)[name = tensor("op_2352_cast_fp16")]; + tensor var_2359_begin_0 = const()[name = tensor("op_2359_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2359_end_0 = const()[name = tensor("op_2359_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2359_end_mask_0 = const()[name = tensor("op_2359_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2359_cast_fp16 = slice_by_index(begin = var_2359_begin_0, end = var_2359_end_0, end_mask = var_2359_end_mask_0, x = var_2148_cast_fp16)[name = tensor("op_2359_cast_fp16")]; + tensor var_2366_begin_0 = const()[name = tensor("op_2366_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2366_end_0 = const()[name = tensor("op_2366_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2366_end_mask_0 = const()[name = tensor("op_2366_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2366_cast_fp16 = slice_by_index(begin = var_2366_begin_0, end = var_2366_end_0, end_mask = var_2366_end_mask_0, x = var_2148_cast_fp16)[name = tensor("op_2366_cast_fp16")]; + tensor var_2373_begin_0 = const()[name = tensor("op_2373_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2373_end_0 = const()[name = tensor("op_2373_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2373_end_mask_0 = const()[name = tensor("op_2373_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2373_cast_fp16 = slice_by_index(begin = var_2373_begin_0, end = var_2373_end_0, end_mask = var_2373_end_mask_0, x = var_2152_cast_fp16)[name = tensor("op_2373_cast_fp16")]; + tensor var_2380_begin_0 = const()[name = tensor("op_2380_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2380_end_0 = const()[name = tensor("op_2380_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2380_end_mask_0 = const()[name = tensor("op_2380_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2380_cast_fp16 = slice_by_index(begin = var_2380_begin_0, end = var_2380_end_0, end_mask = var_2380_end_mask_0, x = var_2152_cast_fp16)[name = tensor("op_2380_cast_fp16")]; + tensor var_2387_begin_0 = const()[name = tensor("op_2387_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2387_end_0 = const()[name = tensor("op_2387_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2387_end_mask_0 = const()[name = tensor("op_2387_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2387_cast_fp16 = slice_by_index(begin = var_2387_begin_0, end = var_2387_end_0, end_mask = var_2387_end_mask_0, x = var_2152_cast_fp16)[name = tensor("op_2387_cast_fp16")]; + tensor var_2394_begin_0 = const()[name = tensor("op_2394_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2394_end_0 = const()[name = tensor("op_2394_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2394_end_mask_0 = const()[name = tensor("op_2394_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2394_cast_fp16 = slice_by_index(begin = var_2394_begin_0, end = var_2394_end_0, end_mask = var_2394_end_mask_0, x = var_2152_cast_fp16)[name = tensor("op_2394_cast_fp16")]; + tensor var_2401_begin_0 = const()[name = tensor("op_2401_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2401_end_0 = const()[name = tensor("op_2401_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2401_end_mask_0 = const()[name = tensor("op_2401_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2401_cast_fp16 = slice_by_index(begin = var_2401_begin_0, end = var_2401_end_0, end_mask = var_2401_end_mask_0, x = var_2156_cast_fp16)[name = tensor("op_2401_cast_fp16")]; + tensor var_2408_begin_0 = const()[name = tensor("op_2408_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2408_end_0 = const()[name = tensor("op_2408_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2408_end_mask_0 = const()[name = tensor("op_2408_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2408_cast_fp16 = slice_by_index(begin = var_2408_begin_0, end = var_2408_end_0, end_mask = var_2408_end_mask_0, x = var_2156_cast_fp16)[name = tensor("op_2408_cast_fp16")]; + tensor var_2415_begin_0 = const()[name = tensor("op_2415_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2415_end_0 = const()[name = tensor("op_2415_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2415_end_mask_0 = const()[name = tensor("op_2415_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2415_cast_fp16 = slice_by_index(begin = var_2415_begin_0, end = var_2415_end_0, end_mask = var_2415_end_mask_0, x = var_2156_cast_fp16)[name = tensor("op_2415_cast_fp16")]; + tensor var_2422_begin_0 = const()[name = tensor("op_2422_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2422_end_0 = const()[name = tensor("op_2422_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2422_end_mask_0 = const()[name = tensor("op_2422_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2422_cast_fp16 = slice_by_index(begin = var_2422_begin_0, end = var_2422_end_0, end_mask = var_2422_end_mask_0, x = var_2156_cast_fp16)[name = tensor("op_2422_cast_fp16")]; + tensor var_2429_begin_0 = const()[name = tensor("op_2429_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2429_end_0 = const()[name = tensor("op_2429_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2429_end_mask_0 = const()[name = tensor("op_2429_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2429_cast_fp16 = slice_by_index(begin = var_2429_begin_0, end = var_2429_end_0, end_mask = var_2429_end_mask_0, x = var_2160_cast_fp16)[name = tensor("op_2429_cast_fp16")]; + tensor var_2436_begin_0 = const()[name = tensor("op_2436_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2436_end_0 = const()[name = tensor("op_2436_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2436_end_mask_0 = const()[name = tensor("op_2436_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2436_cast_fp16 = slice_by_index(begin = var_2436_begin_0, end = var_2436_end_0, end_mask = var_2436_end_mask_0, x = var_2160_cast_fp16)[name = tensor("op_2436_cast_fp16")]; + tensor var_2443_begin_0 = const()[name = tensor("op_2443_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2443_end_0 = const()[name = tensor("op_2443_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2443_end_mask_0 = const()[name = tensor("op_2443_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2443_cast_fp16 = slice_by_index(begin = var_2443_begin_0, end = var_2443_end_0, end_mask = var_2443_end_mask_0, x = var_2160_cast_fp16)[name = tensor("op_2443_cast_fp16")]; + tensor var_2450_begin_0 = const()[name = tensor("op_2450_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2450_end_0 = const()[name = tensor("op_2450_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2450_end_mask_0 = const()[name = tensor("op_2450_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2450_cast_fp16 = slice_by_index(begin = var_2450_begin_0, end = var_2450_end_0, end_mask = var_2450_end_mask_0, x = var_2160_cast_fp16)[name = tensor("op_2450_cast_fp16")]; + tensor var_2457_begin_0 = const()[name = tensor("op_2457_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2457_end_0 = const()[name = tensor("op_2457_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2457_end_mask_0 = const()[name = tensor("op_2457_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2457_cast_fp16 = slice_by_index(begin = var_2457_begin_0, end = var_2457_end_0, end_mask = var_2457_end_mask_0, x = var_2164_cast_fp16)[name = tensor("op_2457_cast_fp16")]; + tensor var_2464_begin_0 = const()[name = tensor("op_2464_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2464_end_0 = const()[name = tensor("op_2464_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2464_end_mask_0 = const()[name = tensor("op_2464_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2464_cast_fp16 = slice_by_index(begin = var_2464_begin_0, end = var_2464_end_0, end_mask = var_2464_end_mask_0, x = var_2164_cast_fp16)[name = tensor("op_2464_cast_fp16")]; + tensor var_2471_begin_0 = const()[name = tensor("op_2471_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2471_end_0 = const()[name = tensor("op_2471_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2471_end_mask_0 = const()[name = tensor("op_2471_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2471_cast_fp16 = slice_by_index(begin = var_2471_begin_0, end = var_2471_end_0, end_mask = var_2471_end_mask_0, x = var_2164_cast_fp16)[name = tensor("op_2471_cast_fp16")]; + tensor var_2478_begin_0 = const()[name = tensor("op_2478_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2478_end_0 = const()[name = tensor("op_2478_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2478_end_mask_0 = const()[name = tensor("op_2478_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2478_cast_fp16 = slice_by_index(begin = var_2478_begin_0, end = var_2478_end_0, end_mask = var_2478_end_mask_0, x = var_2164_cast_fp16)[name = tensor("op_2478_cast_fp16")]; + tensor var_2485_begin_0 = const()[name = tensor("op_2485_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2485_end_0 = const()[name = tensor("op_2485_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_2485_end_mask_0 = const()[name = tensor("op_2485_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2485_cast_fp16 = slice_by_index(begin = var_2485_begin_0, end = var_2485_end_0, end_mask = var_2485_end_mask_0, x = var_2168_cast_fp16)[name = tensor("op_2485_cast_fp16")]; + tensor var_2492_begin_0 = const()[name = tensor("op_2492_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_2492_end_0 = const()[name = tensor("op_2492_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_2492_end_mask_0 = const()[name = tensor("op_2492_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2492_cast_fp16 = slice_by_index(begin = var_2492_begin_0, end = var_2492_end_0, end_mask = var_2492_end_mask_0, x = var_2168_cast_fp16)[name = tensor("op_2492_cast_fp16")]; + tensor var_2499_begin_0 = const()[name = tensor("op_2499_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_2499_end_0 = const()[name = tensor("op_2499_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_2499_end_mask_0 = const()[name = tensor("op_2499_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2499_cast_fp16 = slice_by_index(begin = var_2499_begin_0, end = var_2499_end_0, end_mask = var_2499_end_mask_0, x = var_2168_cast_fp16)[name = tensor("op_2499_cast_fp16")]; + tensor var_2506_begin_0 = const()[name = tensor("op_2506_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_2506_end_0 = const()[name = tensor("op_2506_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2506_end_mask_0 = const()[name = tensor("op_2506_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2506_cast_fp16 = slice_by_index(begin = var_2506_begin_0, end = var_2506_end_0, end_mask = var_2506_end_mask_0, x = var_2168_cast_fp16)[name = tensor("op_2506_cast_fp16")]; + tensor k_5_perm_0 = const()[name = tensor("k_5_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_2511_begin_0 = const()[name = tensor("op_2511_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2511_end_0 = const()[name = tensor("op_2511_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_2511_end_mask_0 = const()[name = tensor("op_2511_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_9 = transpose(perm = k_5_perm_0, x = key_5_cast_fp16)[name = tensor("transpose_9")]; + tensor var_2511_cast_fp16 = slice_by_index(begin = var_2511_begin_0, end = var_2511_end_0, end_mask = var_2511_end_mask_0, x = transpose_9)[name = tensor("op_2511_cast_fp16")]; + tensor var_2515_begin_0 = const()[name = tensor("op_2515_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_2515_end_0 = const()[name = tensor("op_2515_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_2515_end_mask_0 = const()[name = tensor("op_2515_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2515_cast_fp16 = slice_by_index(begin = var_2515_begin_0, end = var_2515_end_0, end_mask = var_2515_end_mask_0, x = transpose_9)[name = tensor("op_2515_cast_fp16")]; + tensor var_2519_begin_0 = const()[name = tensor("op_2519_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_2519_end_0 = const()[name = tensor("op_2519_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_2519_end_mask_0 = const()[name = tensor("op_2519_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2519_cast_fp16 = slice_by_index(begin = var_2519_begin_0, end = var_2519_end_0, end_mask = var_2519_end_mask_0, x = transpose_9)[name = tensor("op_2519_cast_fp16")]; + tensor var_2523_begin_0 = const()[name = tensor("op_2523_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_2523_end_0 = const()[name = tensor("op_2523_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_2523_end_mask_0 = const()[name = tensor("op_2523_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2523_cast_fp16 = slice_by_index(begin = var_2523_begin_0, end = var_2523_end_0, end_mask = var_2523_end_mask_0, x = transpose_9)[name = tensor("op_2523_cast_fp16")]; + tensor var_2527_begin_0 = const()[name = tensor("op_2527_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_2527_end_0 = const()[name = tensor("op_2527_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_2527_end_mask_0 = const()[name = tensor("op_2527_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2527_cast_fp16 = slice_by_index(begin = var_2527_begin_0, end = var_2527_end_0, end_mask = var_2527_end_mask_0, x = transpose_9)[name = tensor("op_2527_cast_fp16")]; + tensor var_2531_begin_0 = const()[name = tensor("op_2531_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_2531_end_0 = const()[name = tensor("op_2531_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_2531_end_mask_0 = const()[name = tensor("op_2531_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2531_cast_fp16 = slice_by_index(begin = var_2531_begin_0, end = var_2531_end_0, end_mask = var_2531_end_mask_0, x = transpose_9)[name = tensor("op_2531_cast_fp16")]; + tensor var_2535_begin_0 = const()[name = tensor("op_2535_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_2535_end_0 = const()[name = tensor("op_2535_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_2535_end_mask_0 = const()[name = tensor("op_2535_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2535_cast_fp16 = slice_by_index(begin = var_2535_begin_0, end = var_2535_end_0, end_mask = var_2535_end_mask_0, x = transpose_9)[name = tensor("op_2535_cast_fp16")]; + tensor var_2539_begin_0 = const()[name = tensor("op_2539_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_2539_end_0 = const()[name = tensor("op_2539_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_2539_end_mask_0 = const()[name = tensor("op_2539_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2539_cast_fp16 = slice_by_index(begin = var_2539_begin_0, end = var_2539_end_0, end_mask = var_2539_end_mask_0, x = transpose_9)[name = tensor("op_2539_cast_fp16")]; + tensor var_2543_begin_0 = const()[name = tensor("op_2543_begin_0"), val = tensor([0, 0, 0, 512])]; + tensor var_2543_end_0 = const()[name = tensor("op_2543_end_0"), val = tensor([1, 1500, 1, 576])]; + tensor var_2543_end_mask_0 = const()[name = tensor("op_2543_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2543_cast_fp16 = slice_by_index(begin = var_2543_begin_0, end = var_2543_end_0, end_mask = var_2543_end_mask_0, x = transpose_9)[name = tensor("op_2543_cast_fp16")]; + tensor var_2547_begin_0 = const()[name = tensor("op_2547_begin_0"), val = tensor([0, 0, 0, 576])]; + tensor var_2547_end_0 = const()[name = tensor("op_2547_end_0"), val = tensor([1, 1500, 1, 640])]; + tensor var_2547_end_mask_0 = const()[name = tensor("op_2547_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2547_cast_fp16 = slice_by_index(begin = var_2547_begin_0, end = var_2547_end_0, end_mask = var_2547_end_mask_0, x = transpose_9)[name = tensor("op_2547_cast_fp16")]; + tensor var_2551_begin_0 = const()[name = tensor("op_2551_begin_0"), val = tensor([0, 0, 0, 640])]; + tensor var_2551_end_0 = const()[name = tensor("op_2551_end_0"), val = tensor([1, 1500, 1, 704])]; + tensor var_2551_end_mask_0 = const()[name = tensor("op_2551_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2551_cast_fp16 = slice_by_index(begin = var_2551_begin_0, end = var_2551_end_0, end_mask = var_2551_end_mask_0, x = transpose_9)[name = tensor("op_2551_cast_fp16")]; + tensor var_2555_begin_0 = const()[name = tensor("op_2555_begin_0"), val = tensor([0, 0, 0, 704])]; + tensor var_2555_end_0 = const()[name = tensor("op_2555_end_0"), val = tensor([1, 1500, 1, 768])]; + tensor var_2555_end_mask_0 = const()[name = tensor("op_2555_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_2555_cast_fp16 = slice_by_index(begin = var_2555_begin_0, end = var_2555_end_0, end_mask = var_2555_end_mask_0, x = transpose_9)[name = tensor("op_2555_cast_fp16")]; + tensor var_2557_begin_0 = const()[name = tensor("op_2557_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2557_end_0 = const()[name = tensor("op_2557_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_2557_end_mask_0 = const()[name = tensor("op_2557_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2557_cast_fp16 = slice_by_index(begin = var_2557_begin_0, end = var_2557_end_0, end_mask = var_2557_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_2557_cast_fp16")]; + tensor var_2561_begin_0 = const()[name = tensor("op_2561_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_2561_end_0 = const()[name = tensor("op_2561_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_2561_end_mask_0 = const()[name = tensor("op_2561_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2561_cast_fp16 = slice_by_index(begin = var_2561_begin_0, end = var_2561_end_0, end_mask = var_2561_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_2561_cast_fp16")]; + tensor var_2565_begin_0 = const()[name = tensor("op_2565_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_2565_end_0 = const()[name = tensor("op_2565_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_2565_end_mask_0 = const()[name = tensor("op_2565_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2565_cast_fp16 = slice_by_index(begin = var_2565_begin_0, end = var_2565_end_0, end_mask = var_2565_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_2565_cast_fp16")]; + tensor var_2569_begin_0 = const()[name = tensor("op_2569_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_2569_end_0 = const()[name = tensor("op_2569_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_2569_end_mask_0 = const()[name = tensor("op_2569_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2569_cast_fp16 = slice_by_index(begin = var_2569_begin_0, end = var_2569_end_0, end_mask = var_2569_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_2569_cast_fp16")]; + tensor var_2573_begin_0 = const()[name = tensor("op_2573_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_2573_end_0 = const()[name = tensor("op_2573_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_2573_end_mask_0 = const()[name = tensor("op_2573_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2573_cast_fp16 = slice_by_index(begin = var_2573_begin_0, end = var_2573_end_0, end_mask = var_2573_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_2573_cast_fp16")]; + tensor var_2577_begin_0 = const()[name = tensor("op_2577_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_2577_end_0 = const()[name = tensor("op_2577_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_2577_end_mask_0 = const()[name = tensor("op_2577_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2577_cast_fp16 = slice_by_index(begin = var_2577_begin_0, end = var_2577_end_0, end_mask = var_2577_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_2577_cast_fp16")]; + tensor var_2581_begin_0 = const()[name = tensor("op_2581_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_2581_end_0 = const()[name = tensor("op_2581_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_2581_end_mask_0 = const()[name = tensor("op_2581_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2581_cast_fp16 = slice_by_index(begin = var_2581_begin_0, end = var_2581_end_0, end_mask = var_2581_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_2581_cast_fp16")]; + tensor var_2585_begin_0 = const()[name = tensor("op_2585_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_2585_end_0 = const()[name = tensor("op_2585_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_2585_end_mask_0 = const()[name = tensor("op_2585_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2585_cast_fp16 = slice_by_index(begin = var_2585_begin_0, end = var_2585_end_0, end_mask = var_2585_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_2585_cast_fp16")]; + tensor var_2589_begin_0 = const()[name = tensor("op_2589_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_2589_end_0 = const()[name = tensor("op_2589_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_2589_end_mask_0 = const()[name = tensor("op_2589_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2589_cast_fp16 = slice_by_index(begin = var_2589_begin_0, end = var_2589_end_0, end_mask = var_2589_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_2589_cast_fp16")]; + tensor var_2593_begin_0 = const()[name = tensor("op_2593_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_2593_end_0 = const()[name = tensor("op_2593_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_2593_end_mask_0 = const()[name = tensor("op_2593_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2593_cast_fp16 = slice_by_index(begin = var_2593_begin_0, end = var_2593_end_0, end_mask = var_2593_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_2593_cast_fp16")]; + tensor var_2597_begin_0 = const()[name = tensor("op_2597_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_2597_end_0 = const()[name = tensor("op_2597_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_2597_end_mask_0 = const()[name = tensor("op_2597_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2597_cast_fp16 = slice_by_index(begin = var_2597_begin_0, end = var_2597_end_0, end_mask = var_2597_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_2597_cast_fp16")]; + tensor var_2601_begin_0 = const()[name = tensor("op_2601_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_2601_end_0 = const()[name = tensor("op_2601_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_2601_end_mask_0 = const()[name = tensor("op_2601_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2601_cast_fp16 = slice_by_index(begin = var_2601_begin_0, end = var_2601_end_0, end_mask = var_2601_end_mask_0, x = value_5_cast_fp16)[name = tensor("op_2601_cast_fp16")]; + tensor var_2605_equation_0 = const()[name = tensor("op_2605_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2605_cast_fp16 = einsum(equation = var_2605_equation_0, values = (var_2511_cast_fp16, var_2177_cast_fp16))[name = tensor("op_2605_cast_fp16")]; + tensor var_2606_to_fp16 = const()[name = tensor("op_2606_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_193_cast_fp16 = mul(x = var_2605_cast_fp16, y = var_2606_to_fp16)[name = tensor("aw_chunk_193_cast_fp16")]; + tensor var_2609_equation_0 = const()[name = tensor("op_2609_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2609_cast_fp16 = einsum(equation = var_2609_equation_0, values = (var_2511_cast_fp16, var_2184_cast_fp16))[name = tensor("op_2609_cast_fp16")]; + tensor var_2610_to_fp16 = const()[name = tensor("op_2610_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_195_cast_fp16 = mul(x = var_2609_cast_fp16, y = var_2610_to_fp16)[name = tensor("aw_chunk_195_cast_fp16")]; + tensor var_2613_equation_0 = const()[name = tensor("op_2613_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2613_cast_fp16 = einsum(equation = var_2613_equation_0, values = (var_2511_cast_fp16, var_2191_cast_fp16))[name = tensor("op_2613_cast_fp16")]; + tensor var_2614_to_fp16 = const()[name = tensor("op_2614_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_197_cast_fp16 = mul(x = var_2613_cast_fp16, y = var_2614_to_fp16)[name = tensor("aw_chunk_197_cast_fp16")]; + tensor var_2617_equation_0 = const()[name = tensor("op_2617_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2617_cast_fp16 = einsum(equation = var_2617_equation_0, values = (var_2511_cast_fp16, var_2198_cast_fp16))[name = tensor("op_2617_cast_fp16")]; + tensor var_2618_to_fp16 = const()[name = tensor("op_2618_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_199_cast_fp16 = mul(x = var_2617_cast_fp16, y = var_2618_to_fp16)[name = tensor("aw_chunk_199_cast_fp16")]; + tensor var_2621_equation_0 = const()[name = tensor("op_2621_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2621_cast_fp16 = einsum(equation = var_2621_equation_0, values = (var_2515_cast_fp16, var_2205_cast_fp16))[name = tensor("op_2621_cast_fp16")]; + tensor var_2622_to_fp16 = const()[name = tensor("op_2622_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_201_cast_fp16 = mul(x = var_2621_cast_fp16, y = var_2622_to_fp16)[name = tensor("aw_chunk_201_cast_fp16")]; + tensor var_2625_equation_0 = const()[name = tensor("op_2625_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2625_cast_fp16 = einsum(equation = var_2625_equation_0, values = (var_2515_cast_fp16, var_2212_cast_fp16))[name = tensor("op_2625_cast_fp16")]; + tensor var_2626_to_fp16 = const()[name = tensor("op_2626_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_203_cast_fp16 = mul(x = var_2625_cast_fp16, y = var_2626_to_fp16)[name = tensor("aw_chunk_203_cast_fp16")]; + tensor var_2629_equation_0 = const()[name = tensor("op_2629_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2629_cast_fp16 = einsum(equation = var_2629_equation_0, values = (var_2515_cast_fp16, var_2219_cast_fp16))[name = tensor("op_2629_cast_fp16")]; + tensor var_2630_to_fp16 = const()[name = tensor("op_2630_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_205_cast_fp16 = mul(x = var_2629_cast_fp16, y = var_2630_to_fp16)[name = tensor("aw_chunk_205_cast_fp16")]; + tensor var_2633_equation_0 = const()[name = tensor("op_2633_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2633_cast_fp16 = einsum(equation = var_2633_equation_0, values = (var_2515_cast_fp16, var_2226_cast_fp16))[name = tensor("op_2633_cast_fp16")]; + tensor var_2634_to_fp16 = const()[name = tensor("op_2634_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_207_cast_fp16 = mul(x = var_2633_cast_fp16, y = var_2634_to_fp16)[name = tensor("aw_chunk_207_cast_fp16")]; + tensor var_2637_equation_0 = const()[name = tensor("op_2637_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2637_cast_fp16 = einsum(equation = var_2637_equation_0, values = (var_2519_cast_fp16, var_2233_cast_fp16))[name = tensor("op_2637_cast_fp16")]; + tensor var_2638_to_fp16 = const()[name = tensor("op_2638_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_209_cast_fp16 = mul(x = var_2637_cast_fp16, y = var_2638_to_fp16)[name = tensor("aw_chunk_209_cast_fp16")]; + tensor var_2641_equation_0 = const()[name = tensor("op_2641_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2641_cast_fp16 = einsum(equation = var_2641_equation_0, values = (var_2519_cast_fp16, var_2240_cast_fp16))[name = tensor("op_2641_cast_fp16")]; + tensor var_2642_to_fp16 = const()[name = tensor("op_2642_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_211_cast_fp16 = mul(x = var_2641_cast_fp16, y = var_2642_to_fp16)[name = tensor("aw_chunk_211_cast_fp16")]; + tensor var_2645_equation_0 = const()[name = tensor("op_2645_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2645_cast_fp16 = einsum(equation = var_2645_equation_0, values = (var_2519_cast_fp16, var_2247_cast_fp16))[name = tensor("op_2645_cast_fp16")]; + tensor var_2646_to_fp16 = const()[name = tensor("op_2646_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_213_cast_fp16 = mul(x = var_2645_cast_fp16, y = var_2646_to_fp16)[name = tensor("aw_chunk_213_cast_fp16")]; + tensor var_2649_equation_0 = const()[name = tensor("op_2649_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2649_cast_fp16 = einsum(equation = var_2649_equation_0, values = (var_2519_cast_fp16, var_2254_cast_fp16))[name = tensor("op_2649_cast_fp16")]; + tensor var_2650_to_fp16 = const()[name = tensor("op_2650_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_215_cast_fp16 = mul(x = var_2649_cast_fp16, y = var_2650_to_fp16)[name = tensor("aw_chunk_215_cast_fp16")]; + tensor var_2653_equation_0 = const()[name = tensor("op_2653_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2653_cast_fp16 = einsum(equation = var_2653_equation_0, values = (var_2523_cast_fp16, var_2261_cast_fp16))[name = tensor("op_2653_cast_fp16")]; + tensor var_2654_to_fp16 = const()[name = tensor("op_2654_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_217_cast_fp16 = mul(x = var_2653_cast_fp16, y = var_2654_to_fp16)[name = tensor("aw_chunk_217_cast_fp16")]; + tensor var_2657_equation_0 = const()[name = tensor("op_2657_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2657_cast_fp16 = einsum(equation = var_2657_equation_0, values = (var_2523_cast_fp16, var_2268_cast_fp16))[name = tensor("op_2657_cast_fp16")]; + tensor var_2658_to_fp16 = const()[name = tensor("op_2658_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_219_cast_fp16 = mul(x = var_2657_cast_fp16, y = var_2658_to_fp16)[name = tensor("aw_chunk_219_cast_fp16")]; + tensor var_2661_equation_0 = const()[name = tensor("op_2661_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2661_cast_fp16 = einsum(equation = var_2661_equation_0, values = (var_2523_cast_fp16, var_2275_cast_fp16))[name = tensor("op_2661_cast_fp16")]; + tensor var_2662_to_fp16 = const()[name = tensor("op_2662_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_221_cast_fp16 = mul(x = var_2661_cast_fp16, y = var_2662_to_fp16)[name = tensor("aw_chunk_221_cast_fp16")]; + tensor var_2665_equation_0 = const()[name = tensor("op_2665_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2665_cast_fp16 = einsum(equation = var_2665_equation_0, values = (var_2523_cast_fp16, var_2282_cast_fp16))[name = tensor("op_2665_cast_fp16")]; + tensor var_2666_to_fp16 = const()[name = tensor("op_2666_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_223_cast_fp16 = mul(x = var_2665_cast_fp16, y = var_2666_to_fp16)[name = tensor("aw_chunk_223_cast_fp16")]; + tensor var_2669_equation_0 = const()[name = tensor("op_2669_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2669_cast_fp16 = einsum(equation = var_2669_equation_0, values = (var_2527_cast_fp16, var_2289_cast_fp16))[name = tensor("op_2669_cast_fp16")]; + tensor var_2670_to_fp16 = const()[name = tensor("op_2670_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_225_cast_fp16 = mul(x = var_2669_cast_fp16, y = var_2670_to_fp16)[name = tensor("aw_chunk_225_cast_fp16")]; + tensor var_2673_equation_0 = const()[name = tensor("op_2673_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2673_cast_fp16 = einsum(equation = var_2673_equation_0, values = (var_2527_cast_fp16, var_2296_cast_fp16))[name = tensor("op_2673_cast_fp16")]; + tensor var_2674_to_fp16 = const()[name = tensor("op_2674_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_227_cast_fp16 = mul(x = var_2673_cast_fp16, y = var_2674_to_fp16)[name = tensor("aw_chunk_227_cast_fp16")]; + tensor var_2677_equation_0 = const()[name = tensor("op_2677_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2677_cast_fp16 = einsum(equation = var_2677_equation_0, values = (var_2527_cast_fp16, var_2303_cast_fp16))[name = tensor("op_2677_cast_fp16")]; + tensor var_2678_to_fp16 = const()[name = tensor("op_2678_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_229_cast_fp16 = mul(x = var_2677_cast_fp16, y = var_2678_to_fp16)[name = tensor("aw_chunk_229_cast_fp16")]; + tensor var_2681_equation_0 = const()[name = tensor("op_2681_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2681_cast_fp16 = einsum(equation = var_2681_equation_0, values = (var_2527_cast_fp16, var_2310_cast_fp16))[name = tensor("op_2681_cast_fp16")]; + tensor var_2682_to_fp16 = const()[name = tensor("op_2682_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_231_cast_fp16 = mul(x = var_2681_cast_fp16, y = var_2682_to_fp16)[name = tensor("aw_chunk_231_cast_fp16")]; + tensor var_2685_equation_0 = const()[name = tensor("op_2685_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2685_cast_fp16 = einsum(equation = var_2685_equation_0, values = (var_2531_cast_fp16, var_2317_cast_fp16))[name = tensor("op_2685_cast_fp16")]; + tensor var_2686_to_fp16 = const()[name = tensor("op_2686_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_233_cast_fp16 = mul(x = var_2685_cast_fp16, y = var_2686_to_fp16)[name = tensor("aw_chunk_233_cast_fp16")]; + tensor var_2689_equation_0 = const()[name = tensor("op_2689_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2689_cast_fp16 = einsum(equation = var_2689_equation_0, values = (var_2531_cast_fp16, var_2324_cast_fp16))[name = tensor("op_2689_cast_fp16")]; + tensor var_2690_to_fp16 = const()[name = tensor("op_2690_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_235_cast_fp16 = mul(x = var_2689_cast_fp16, y = var_2690_to_fp16)[name = tensor("aw_chunk_235_cast_fp16")]; + tensor var_2693_equation_0 = const()[name = tensor("op_2693_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2693_cast_fp16 = einsum(equation = var_2693_equation_0, values = (var_2531_cast_fp16, var_2331_cast_fp16))[name = tensor("op_2693_cast_fp16")]; + tensor var_2694_to_fp16 = const()[name = tensor("op_2694_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_237_cast_fp16 = mul(x = var_2693_cast_fp16, y = var_2694_to_fp16)[name = tensor("aw_chunk_237_cast_fp16")]; + tensor var_2697_equation_0 = const()[name = tensor("op_2697_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2697_cast_fp16 = einsum(equation = var_2697_equation_0, values = (var_2531_cast_fp16, var_2338_cast_fp16))[name = tensor("op_2697_cast_fp16")]; + tensor var_2698_to_fp16 = const()[name = tensor("op_2698_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_239_cast_fp16 = mul(x = var_2697_cast_fp16, y = var_2698_to_fp16)[name = tensor("aw_chunk_239_cast_fp16")]; + tensor var_2701_equation_0 = const()[name = tensor("op_2701_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2701_cast_fp16 = einsum(equation = var_2701_equation_0, values = (var_2535_cast_fp16, var_2345_cast_fp16))[name = tensor("op_2701_cast_fp16")]; + tensor var_2702_to_fp16 = const()[name = tensor("op_2702_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_241_cast_fp16 = mul(x = var_2701_cast_fp16, y = var_2702_to_fp16)[name = tensor("aw_chunk_241_cast_fp16")]; + tensor var_2705_equation_0 = const()[name = tensor("op_2705_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2705_cast_fp16 = einsum(equation = var_2705_equation_0, values = (var_2535_cast_fp16, var_2352_cast_fp16))[name = tensor("op_2705_cast_fp16")]; + tensor var_2706_to_fp16 = const()[name = tensor("op_2706_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_243_cast_fp16 = mul(x = var_2705_cast_fp16, y = var_2706_to_fp16)[name = tensor("aw_chunk_243_cast_fp16")]; + tensor var_2709_equation_0 = const()[name = tensor("op_2709_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2709_cast_fp16 = einsum(equation = var_2709_equation_0, values = (var_2535_cast_fp16, var_2359_cast_fp16))[name = tensor("op_2709_cast_fp16")]; + tensor var_2710_to_fp16 = const()[name = tensor("op_2710_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_245_cast_fp16 = mul(x = var_2709_cast_fp16, y = var_2710_to_fp16)[name = tensor("aw_chunk_245_cast_fp16")]; + tensor var_2713_equation_0 = const()[name = tensor("op_2713_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2713_cast_fp16 = einsum(equation = var_2713_equation_0, values = (var_2535_cast_fp16, var_2366_cast_fp16))[name = tensor("op_2713_cast_fp16")]; + tensor var_2714_to_fp16 = const()[name = tensor("op_2714_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_247_cast_fp16 = mul(x = var_2713_cast_fp16, y = var_2714_to_fp16)[name = tensor("aw_chunk_247_cast_fp16")]; + tensor var_2717_equation_0 = const()[name = tensor("op_2717_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2717_cast_fp16 = einsum(equation = var_2717_equation_0, values = (var_2539_cast_fp16, var_2373_cast_fp16))[name = tensor("op_2717_cast_fp16")]; + tensor var_2718_to_fp16 = const()[name = tensor("op_2718_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_249_cast_fp16 = mul(x = var_2717_cast_fp16, y = var_2718_to_fp16)[name = tensor("aw_chunk_249_cast_fp16")]; + tensor var_2721_equation_0 = const()[name = tensor("op_2721_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2721_cast_fp16 = einsum(equation = var_2721_equation_0, values = (var_2539_cast_fp16, var_2380_cast_fp16))[name = tensor("op_2721_cast_fp16")]; + tensor var_2722_to_fp16 = const()[name = tensor("op_2722_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_251_cast_fp16 = mul(x = var_2721_cast_fp16, y = var_2722_to_fp16)[name = tensor("aw_chunk_251_cast_fp16")]; + tensor var_2725_equation_0 = const()[name = tensor("op_2725_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2725_cast_fp16 = einsum(equation = var_2725_equation_0, values = (var_2539_cast_fp16, var_2387_cast_fp16))[name = tensor("op_2725_cast_fp16")]; + tensor var_2726_to_fp16 = const()[name = tensor("op_2726_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_253_cast_fp16 = mul(x = var_2725_cast_fp16, y = var_2726_to_fp16)[name = tensor("aw_chunk_253_cast_fp16")]; + tensor var_2729_equation_0 = const()[name = tensor("op_2729_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2729_cast_fp16 = einsum(equation = var_2729_equation_0, values = (var_2539_cast_fp16, var_2394_cast_fp16))[name = tensor("op_2729_cast_fp16")]; + tensor var_2730_to_fp16 = const()[name = tensor("op_2730_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_255_cast_fp16 = mul(x = var_2729_cast_fp16, y = var_2730_to_fp16)[name = tensor("aw_chunk_255_cast_fp16")]; + tensor var_2733_equation_0 = const()[name = tensor("op_2733_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2733_cast_fp16 = einsum(equation = var_2733_equation_0, values = (var_2543_cast_fp16, var_2401_cast_fp16))[name = tensor("op_2733_cast_fp16")]; + tensor var_2734_to_fp16 = const()[name = tensor("op_2734_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_257_cast_fp16 = mul(x = var_2733_cast_fp16, y = var_2734_to_fp16)[name = tensor("aw_chunk_257_cast_fp16")]; + tensor var_2737_equation_0 = const()[name = tensor("op_2737_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2737_cast_fp16 = einsum(equation = var_2737_equation_0, values = (var_2543_cast_fp16, var_2408_cast_fp16))[name = tensor("op_2737_cast_fp16")]; + tensor var_2738_to_fp16 = const()[name = tensor("op_2738_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_259_cast_fp16 = mul(x = var_2737_cast_fp16, y = var_2738_to_fp16)[name = tensor("aw_chunk_259_cast_fp16")]; + tensor var_2741_equation_0 = const()[name = tensor("op_2741_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2741_cast_fp16 = einsum(equation = var_2741_equation_0, values = (var_2543_cast_fp16, var_2415_cast_fp16))[name = tensor("op_2741_cast_fp16")]; + tensor var_2742_to_fp16 = const()[name = tensor("op_2742_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_261_cast_fp16 = mul(x = var_2741_cast_fp16, y = var_2742_to_fp16)[name = tensor("aw_chunk_261_cast_fp16")]; + tensor var_2745_equation_0 = const()[name = tensor("op_2745_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2745_cast_fp16 = einsum(equation = var_2745_equation_0, values = (var_2543_cast_fp16, var_2422_cast_fp16))[name = tensor("op_2745_cast_fp16")]; + tensor var_2746_to_fp16 = const()[name = tensor("op_2746_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_263_cast_fp16 = mul(x = var_2745_cast_fp16, y = var_2746_to_fp16)[name = tensor("aw_chunk_263_cast_fp16")]; + tensor var_2749_equation_0 = const()[name = tensor("op_2749_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2749_cast_fp16 = einsum(equation = var_2749_equation_0, values = (var_2547_cast_fp16, var_2429_cast_fp16))[name = tensor("op_2749_cast_fp16")]; + tensor var_2750_to_fp16 = const()[name = tensor("op_2750_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_265_cast_fp16 = mul(x = var_2749_cast_fp16, y = var_2750_to_fp16)[name = tensor("aw_chunk_265_cast_fp16")]; + tensor var_2753_equation_0 = const()[name = tensor("op_2753_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2753_cast_fp16 = einsum(equation = var_2753_equation_0, values = (var_2547_cast_fp16, var_2436_cast_fp16))[name = tensor("op_2753_cast_fp16")]; + tensor var_2754_to_fp16 = const()[name = tensor("op_2754_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_267_cast_fp16 = mul(x = var_2753_cast_fp16, y = var_2754_to_fp16)[name = tensor("aw_chunk_267_cast_fp16")]; + tensor var_2757_equation_0 = const()[name = tensor("op_2757_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2757_cast_fp16 = einsum(equation = var_2757_equation_0, values = (var_2547_cast_fp16, var_2443_cast_fp16))[name = tensor("op_2757_cast_fp16")]; + tensor var_2758_to_fp16 = const()[name = tensor("op_2758_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_269_cast_fp16 = mul(x = var_2757_cast_fp16, y = var_2758_to_fp16)[name = tensor("aw_chunk_269_cast_fp16")]; + tensor var_2761_equation_0 = const()[name = tensor("op_2761_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2761_cast_fp16 = einsum(equation = var_2761_equation_0, values = (var_2547_cast_fp16, var_2450_cast_fp16))[name = tensor("op_2761_cast_fp16")]; + tensor var_2762_to_fp16 = const()[name = tensor("op_2762_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_271_cast_fp16 = mul(x = var_2761_cast_fp16, y = var_2762_to_fp16)[name = tensor("aw_chunk_271_cast_fp16")]; + tensor var_2765_equation_0 = const()[name = tensor("op_2765_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2765_cast_fp16 = einsum(equation = var_2765_equation_0, values = (var_2551_cast_fp16, var_2457_cast_fp16))[name = tensor("op_2765_cast_fp16")]; + tensor var_2766_to_fp16 = const()[name = tensor("op_2766_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_273_cast_fp16 = mul(x = var_2765_cast_fp16, y = var_2766_to_fp16)[name = tensor("aw_chunk_273_cast_fp16")]; + tensor var_2769_equation_0 = const()[name = tensor("op_2769_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2769_cast_fp16 = einsum(equation = var_2769_equation_0, values = (var_2551_cast_fp16, var_2464_cast_fp16))[name = tensor("op_2769_cast_fp16")]; + tensor var_2770_to_fp16 = const()[name = tensor("op_2770_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_275_cast_fp16 = mul(x = var_2769_cast_fp16, y = var_2770_to_fp16)[name = tensor("aw_chunk_275_cast_fp16")]; + tensor var_2773_equation_0 = const()[name = tensor("op_2773_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2773_cast_fp16 = einsum(equation = var_2773_equation_0, values = (var_2551_cast_fp16, var_2471_cast_fp16))[name = tensor("op_2773_cast_fp16")]; + tensor var_2774_to_fp16 = const()[name = tensor("op_2774_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_277_cast_fp16 = mul(x = var_2773_cast_fp16, y = var_2774_to_fp16)[name = tensor("aw_chunk_277_cast_fp16")]; + tensor var_2777_equation_0 = const()[name = tensor("op_2777_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2777_cast_fp16 = einsum(equation = var_2777_equation_0, values = (var_2551_cast_fp16, var_2478_cast_fp16))[name = tensor("op_2777_cast_fp16")]; + tensor var_2778_to_fp16 = const()[name = tensor("op_2778_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_279_cast_fp16 = mul(x = var_2777_cast_fp16, y = var_2778_to_fp16)[name = tensor("aw_chunk_279_cast_fp16")]; + tensor var_2781_equation_0 = const()[name = tensor("op_2781_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2781_cast_fp16 = einsum(equation = var_2781_equation_0, values = (var_2555_cast_fp16, var_2485_cast_fp16))[name = tensor("op_2781_cast_fp16")]; + tensor var_2782_to_fp16 = const()[name = tensor("op_2782_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_281_cast_fp16 = mul(x = var_2781_cast_fp16, y = var_2782_to_fp16)[name = tensor("aw_chunk_281_cast_fp16")]; + tensor var_2785_equation_0 = const()[name = tensor("op_2785_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2785_cast_fp16 = einsum(equation = var_2785_equation_0, values = (var_2555_cast_fp16, var_2492_cast_fp16))[name = tensor("op_2785_cast_fp16")]; + tensor var_2786_to_fp16 = const()[name = tensor("op_2786_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_283_cast_fp16 = mul(x = var_2785_cast_fp16, y = var_2786_to_fp16)[name = tensor("aw_chunk_283_cast_fp16")]; + tensor var_2789_equation_0 = const()[name = tensor("op_2789_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2789_cast_fp16 = einsum(equation = var_2789_equation_0, values = (var_2555_cast_fp16, var_2499_cast_fp16))[name = tensor("op_2789_cast_fp16")]; + tensor var_2790_to_fp16 = const()[name = tensor("op_2790_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_285_cast_fp16 = mul(x = var_2789_cast_fp16, y = var_2790_to_fp16)[name = tensor("aw_chunk_285_cast_fp16")]; + tensor var_2793_equation_0 = const()[name = tensor("op_2793_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_2793_cast_fp16 = einsum(equation = var_2793_equation_0, values = (var_2555_cast_fp16, var_2506_cast_fp16))[name = tensor("op_2793_cast_fp16")]; + tensor var_2794_to_fp16 = const()[name = tensor("op_2794_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_287_cast_fp16 = mul(x = var_2793_cast_fp16, y = var_2794_to_fp16)[name = tensor("aw_chunk_287_cast_fp16")]; + tensor var_2796_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_193_cast_fp16)[name = tensor("op_2796_cast_fp16")]; + tensor var_2797_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_195_cast_fp16)[name = tensor("op_2797_cast_fp16")]; + tensor var_2798_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_197_cast_fp16)[name = tensor("op_2798_cast_fp16")]; + tensor var_2799_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_199_cast_fp16)[name = tensor("op_2799_cast_fp16")]; + tensor var_2800_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_201_cast_fp16)[name = tensor("op_2800_cast_fp16")]; + tensor var_2801_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_203_cast_fp16)[name = tensor("op_2801_cast_fp16")]; + tensor var_2802_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_205_cast_fp16)[name = tensor("op_2802_cast_fp16")]; + tensor var_2803_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_207_cast_fp16)[name = tensor("op_2803_cast_fp16")]; + tensor var_2804_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_209_cast_fp16)[name = tensor("op_2804_cast_fp16")]; + tensor var_2805_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_211_cast_fp16)[name = tensor("op_2805_cast_fp16")]; + tensor var_2806_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_213_cast_fp16)[name = tensor("op_2806_cast_fp16")]; + tensor var_2807_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_215_cast_fp16)[name = tensor("op_2807_cast_fp16")]; + tensor var_2808_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_217_cast_fp16)[name = tensor("op_2808_cast_fp16")]; + tensor var_2809_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_219_cast_fp16)[name = tensor("op_2809_cast_fp16")]; + tensor var_2810_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_221_cast_fp16)[name = tensor("op_2810_cast_fp16")]; + tensor var_2811_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_223_cast_fp16)[name = tensor("op_2811_cast_fp16")]; + tensor var_2812_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_225_cast_fp16)[name = tensor("op_2812_cast_fp16")]; + tensor var_2813_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_227_cast_fp16)[name = tensor("op_2813_cast_fp16")]; + tensor var_2814_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_229_cast_fp16)[name = tensor("op_2814_cast_fp16")]; + tensor var_2815_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_231_cast_fp16)[name = tensor("op_2815_cast_fp16")]; + tensor var_2816_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_233_cast_fp16)[name = tensor("op_2816_cast_fp16")]; + tensor var_2817_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_235_cast_fp16)[name = tensor("op_2817_cast_fp16")]; + tensor var_2818_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_237_cast_fp16)[name = tensor("op_2818_cast_fp16")]; + tensor var_2819_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_239_cast_fp16)[name = tensor("op_2819_cast_fp16")]; + tensor var_2820_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_241_cast_fp16)[name = tensor("op_2820_cast_fp16")]; + tensor var_2821_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_243_cast_fp16)[name = tensor("op_2821_cast_fp16")]; + tensor var_2822_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_245_cast_fp16)[name = tensor("op_2822_cast_fp16")]; + tensor var_2823_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_247_cast_fp16)[name = tensor("op_2823_cast_fp16")]; + tensor var_2824_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_249_cast_fp16)[name = tensor("op_2824_cast_fp16")]; + tensor var_2825_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_251_cast_fp16)[name = tensor("op_2825_cast_fp16")]; + tensor var_2826_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_253_cast_fp16)[name = tensor("op_2826_cast_fp16")]; + tensor var_2827_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_255_cast_fp16)[name = tensor("op_2827_cast_fp16")]; + tensor var_2828_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_257_cast_fp16)[name = tensor("op_2828_cast_fp16")]; + tensor var_2829_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_259_cast_fp16)[name = tensor("op_2829_cast_fp16")]; + tensor var_2830_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_261_cast_fp16)[name = tensor("op_2830_cast_fp16")]; + tensor var_2831_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_263_cast_fp16)[name = tensor("op_2831_cast_fp16")]; + tensor var_2832_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_265_cast_fp16)[name = tensor("op_2832_cast_fp16")]; + tensor var_2833_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_267_cast_fp16)[name = tensor("op_2833_cast_fp16")]; + tensor var_2834_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_269_cast_fp16)[name = tensor("op_2834_cast_fp16")]; + tensor var_2835_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_271_cast_fp16)[name = tensor("op_2835_cast_fp16")]; + tensor var_2836_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_273_cast_fp16)[name = tensor("op_2836_cast_fp16")]; + tensor var_2837_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_275_cast_fp16)[name = tensor("op_2837_cast_fp16")]; + tensor var_2838_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_277_cast_fp16)[name = tensor("op_2838_cast_fp16")]; + tensor var_2839_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_279_cast_fp16)[name = tensor("op_2839_cast_fp16")]; + tensor var_2840_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_281_cast_fp16)[name = tensor("op_2840_cast_fp16")]; + tensor var_2841_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_283_cast_fp16)[name = tensor("op_2841_cast_fp16")]; + tensor var_2842_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_285_cast_fp16)[name = tensor("op_2842_cast_fp16")]; + tensor var_2843_cast_fp16 = softmax(axis = var_2069, x = aw_chunk_287_cast_fp16)[name = tensor("op_2843_cast_fp16")]; + tensor var_2845_equation_0 = const()[name = tensor("op_2845_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2845_cast_fp16 = einsum(equation = var_2845_equation_0, values = (var_2557_cast_fp16, var_2796_cast_fp16))[name = tensor("op_2845_cast_fp16")]; + tensor var_2847_equation_0 = const()[name = tensor("op_2847_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2847_cast_fp16 = einsum(equation = var_2847_equation_0, values = (var_2557_cast_fp16, var_2797_cast_fp16))[name = tensor("op_2847_cast_fp16")]; + tensor var_2849_equation_0 = const()[name = tensor("op_2849_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2849_cast_fp16 = einsum(equation = var_2849_equation_0, values = (var_2557_cast_fp16, var_2798_cast_fp16))[name = tensor("op_2849_cast_fp16")]; + tensor var_2851_equation_0 = const()[name = tensor("op_2851_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2851_cast_fp16 = einsum(equation = var_2851_equation_0, values = (var_2557_cast_fp16, var_2799_cast_fp16))[name = tensor("op_2851_cast_fp16")]; + tensor var_2853_equation_0 = const()[name = tensor("op_2853_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2853_cast_fp16 = einsum(equation = var_2853_equation_0, values = (var_2561_cast_fp16, var_2800_cast_fp16))[name = tensor("op_2853_cast_fp16")]; + tensor var_2855_equation_0 = const()[name = tensor("op_2855_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2855_cast_fp16 = einsum(equation = var_2855_equation_0, values = (var_2561_cast_fp16, var_2801_cast_fp16))[name = tensor("op_2855_cast_fp16")]; + tensor var_2857_equation_0 = const()[name = tensor("op_2857_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2857_cast_fp16 = einsum(equation = var_2857_equation_0, values = (var_2561_cast_fp16, var_2802_cast_fp16))[name = tensor("op_2857_cast_fp16")]; + tensor var_2859_equation_0 = const()[name = tensor("op_2859_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2859_cast_fp16 = einsum(equation = var_2859_equation_0, values = (var_2561_cast_fp16, var_2803_cast_fp16))[name = tensor("op_2859_cast_fp16")]; + tensor var_2861_equation_0 = const()[name = tensor("op_2861_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2861_cast_fp16 = einsum(equation = var_2861_equation_0, values = (var_2565_cast_fp16, var_2804_cast_fp16))[name = tensor("op_2861_cast_fp16")]; + tensor var_2863_equation_0 = const()[name = tensor("op_2863_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2863_cast_fp16 = einsum(equation = var_2863_equation_0, values = (var_2565_cast_fp16, var_2805_cast_fp16))[name = tensor("op_2863_cast_fp16")]; + tensor var_2865_equation_0 = const()[name = tensor("op_2865_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2865_cast_fp16 = einsum(equation = var_2865_equation_0, values = (var_2565_cast_fp16, var_2806_cast_fp16))[name = tensor("op_2865_cast_fp16")]; + tensor var_2867_equation_0 = const()[name = tensor("op_2867_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2867_cast_fp16 = einsum(equation = var_2867_equation_0, values = (var_2565_cast_fp16, var_2807_cast_fp16))[name = tensor("op_2867_cast_fp16")]; + tensor var_2869_equation_0 = const()[name = tensor("op_2869_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2869_cast_fp16 = einsum(equation = var_2869_equation_0, values = (var_2569_cast_fp16, var_2808_cast_fp16))[name = tensor("op_2869_cast_fp16")]; + tensor var_2871_equation_0 = const()[name = tensor("op_2871_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2871_cast_fp16 = einsum(equation = var_2871_equation_0, values = (var_2569_cast_fp16, var_2809_cast_fp16))[name = tensor("op_2871_cast_fp16")]; + tensor var_2873_equation_0 = const()[name = tensor("op_2873_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2873_cast_fp16 = einsum(equation = var_2873_equation_0, values = (var_2569_cast_fp16, var_2810_cast_fp16))[name = tensor("op_2873_cast_fp16")]; + tensor var_2875_equation_0 = const()[name = tensor("op_2875_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2875_cast_fp16 = einsum(equation = var_2875_equation_0, values = (var_2569_cast_fp16, var_2811_cast_fp16))[name = tensor("op_2875_cast_fp16")]; + tensor var_2877_equation_0 = const()[name = tensor("op_2877_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2877_cast_fp16 = einsum(equation = var_2877_equation_0, values = (var_2573_cast_fp16, var_2812_cast_fp16))[name = tensor("op_2877_cast_fp16")]; + tensor var_2879_equation_0 = const()[name = tensor("op_2879_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2879_cast_fp16 = einsum(equation = var_2879_equation_0, values = (var_2573_cast_fp16, var_2813_cast_fp16))[name = tensor("op_2879_cast_fp16")]; + tensor var_2881_equation_0 = const()[name = tensor("op_2881_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2881_cast_fp16 = einsum(equation = var_2881_equation_0, values = (var_2573_cast_fp16, var_2814_cast_fp16))[name = tensor("op_2881_cast_fp16")]; + tensor var_2883_equation_0 = const()[name = tensor("op_2883_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2883_cast_fp16 = einsum(equation = var_2883_equation_0, values = (var_2573_cast_fp16, var_2815_cast_fp16))[name = tensor("op_2883_cast_fp16")]; + tensor var_2885_equation_0 = const()[name = tensor("op_2885_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2885_cast_fp16 = einsum(equation = var_2885_equation_0, values = (var_2577_cast_fp16, var_2816_cast_fp16))[name = tensor("op_2885_cast_fp16")]; + tensor var_2887_equation_0 = const()[name = tensor("op_2887_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2887_cast_fp16 = einsum(equation = var_2887_equation_0, values = (var_2577_cast_fp16, var_2817_cast_fp16))[name = tensor("op_2887_cast_fp16")]; + tensor var_2889_equation_0 = const()[name = tensor("op_2889_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2889_cast_fp16 = einsum(equation = var_2889_equation_0, values = (var_2577_cast_fp16, var_2818_cast_fp16))[name = tensor("op_2889_cast_fp16")]; + tensor var_2891_equation_0 = const()[name = tensor("op_2891_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2891_cast_fp16 = einsum(equation = var_2891_equation_0, values = (var_2577_cast_fp16, var_2819_cast_fp16))[name = tensor("op_2891_cast_fp16")]; + tensor var_2893_equation_0 = const()[name = tensor("op_2893_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2893_cast_fp16 = einsum(equation = var_2893_equation_0, values = (var_2581_cast_fp16, var_2820_cast_fp16))[name = tensor("op_2893_cast_fp16")]; + tensor var_2895_equation_0 = const()[name = tensor("op_2895_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2895_cast_fp16 = einsum(equation = var_2895_equation_0, values = (var_2581_cast_fp16, var_2821_cast_fp16))[name = tensor("op_2895_cast_fp16")]; + tensor var_2897_equation_0 = const()[name = tensor("op_2897_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2897_cast_fp16 = einsum(equation = var_2897_equation_0, values = (var_2581_cast_fp16, var_2822_cast_fp16))[name = tensor("op_2897_cast_fp16")]; + tensor var_2899_equation_0 = const()[name = tensor("op_2899_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2899_cast_fp16 = einsum(equation = var_2899_equation_0, values = (var_2581_cast_fp16, var_2823_cast_fp16))[name = tensor("op_2899_cast_fp16")]; + tensor var_2901_equation_0 = const()[name = tensor("op_2901_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2901_cast_fp16 = einsum(equation = var_2901_equation_0, values = (var_2585_cast_fp16, var_2824_cast_fp16))[name = tensor("op_2901_cast_fp16")]; + tensor var_2903_equation_0 = const()[name = tensor("op_2903_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2903_cast_fp16 = einsum(equation = var_2903_equation_0, values = (var_2585_cast_fp16, var_2825_cast_fp16))[name = tensor("op_2903_cast_fp16")]; + tensor var_2905_equation_0 = const()[name = tensor("op_2905_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2905_cast_fp16 = einsum(equation = var_2905_equation_0, values = (var_2585_cast_fp16, var_2826_cast_fp16))[name = tensor("op_2905_cast_fp16")]; + tensor var_2907_equation_0 = const()[name = tensor("op_2907_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2907_cast_fp16 = einsum(equation = var_2907_equation_0, values = (var_2585_cast_fp16, var_2827_cast_fp16))[name = tensor("op_2907_cast_fp16")]; + tensor var_2909_equation_0 = const()[name = tensor("op_2909_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2909_cast_fp16 = einsum(equation = var_2909_equation_0, values = (var_2589_cast_fp16, var_2828_cast_fp16))[name = tensor("op_2909_cast_fp16")]; + tensor var_2911_equation_0 = const()[name = tensor("op_2911_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2911_cast_fp16 = einsum(equation = var_2911_equation_0, values = (var_2589_cast_fp16, var_2829_cast_fp16))[name = tensor("op_2911_cast_fp16")]; + tensor var_2913_equation_0 = const()[name = tensor("op_2913_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2913_cast_fp16 = einsum(equation = var_2913_equation_0, values = (var_2589_cast_fp16, var_2830_cast_fp16))[name = tensor("op_2913_cast_fp16")]; + tensor var_2915_equation_0 = const()[name = tensor("op_2915_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2915_cast_fp16 = einsum(equation = var_2915_equation_0, values = (var_2589_cast_fp16, var_2831_cast_fp16))[name = tensor("op_2915_cast_fp16")]; + tensor var_2917_equation_0 = const()[name = tensor("op_2917_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2917_cast_fp16 = einsum(equation = var_2917_equation_0, values = (var_2593_cast_fp16, var_2832_cast_fp16))[name = tensor("op_2917_cast_fp16")]; + tensor var_2919_equation_0 = const()[name = tensor("op_2919_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2919_cast_fp16 = einsum(equation = var_2919_equation_0, values = (var_2593_cast_fp16, var_2833_cast_fp16))[name = tensor("op_2919_cast_fp16")]; + tensor var_2921_equation_0 = const()[name = tensor("op_2921_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2921_cast_fp16 = einsum(equation = var_2921_equation_0, values = (var_2593_cast_fp16, var_2834_cast_fp16))[name = tensor("op_2921_cast_fp16")]; + tensor var_2923_equation_0 = const()[name = tensor("op_2923_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2923_cast_fp16 = einsum(equation = var_2923_equation_0, values = (var_2593_cast_fp16, var_2835_cast_fp16))[name = tensor("op_2923_cast_fp16")]; + tensor var_2925_equation_0 = const()[name = tensor("op_2925_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2925_cast_fp16 = einsum(equation = var_2925_equation_0, values = (var_2597_cast_fp16, var_2836_cast_fp16))[name = tensor("op_2925_cast_fp16")]; + tensor var_2927_equation_0 = const()[name = tensor("op_2927_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2927_cast_fp16 = einsum(equation = var_2927_equation_0, values = (var_2597_cast_fp16, var_2837_cast_fp16))[name = tensor("op_2927_cast_fp16")]; + tensor var_2929_equation_0 = const()[name = tensor("op_2929_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2929_cast_fp16 = einsum(equation = var_2929_equation_0, values = (var_2597_cast_fp16, var_2838_cast_fp16))[name = tensor("op_2929_cast_fp16")]; + tensor var_2931_equation_0 = const()[name = tensor("op_2931_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2931_cast_fp16 = einsum(equation = var_2931_equation_0, values = (var_2597_cast_fp16, var_2839_cast_fp16))[name = tensor("op_2931_cast_fp16")]; + tensor var_2933_equation_0 = const()[name = tensor("op_2933_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2933_cast_fp16 = einsum(equation = var_2933_equation_0, values = (var_2601_cast_fp16, var_2840_cast_fp16))[name = tensor("op_2933_cast_fp16")]; + tensor var_2935_equation_0 = const()[name = tensor("op_2935_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2935_cast_fp16 = einsum(equation = var_2935_equation_0, values = (var_2601_cast_fp16, var_2841_cast_fp16))[name = tensor("op_2935_cast_fp16")]; + tensor var_2937_equation_0 = const()[name = tensor("op_2937_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2937_cast_fp16 = einsum(equation = var_2937_equation_0, values = (var_2601_cast_fp16, var_2842_cast_fp16))[name = tensor("op_2937_cast_fp16")]; + tensor var_2939_equation_0 = const()[name = tensor("op_2939_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_2939_cast_fp16 = einsum(equation = var_2939_equation_0, values = (var_2601_cast_fp16, var_2843_cast_fp16))[name = tensor("op_2939_cast_fp16")]; + tensor var_2941_interleave_0 = const()[name = tensor("op_2941_interleave_0"), val = tensor(false)]; + tensor var_2941_cast_fp16 = concat(axis = var_2052, interleave = var_2941_interleave_0, values = (var_2845_cast_fp16, var_2847_cast_fp16, var_2849_cast_fp16, var_2851_cast_fp16))[name = tensor("op_2941_cast_fp16")]; + tensor var_2943_interleave_0 = const()[name = tensor("op_2943_interleave_0"), val = tensor(false)]; + tensor var_2943_cast_fp16 = concat(axis = var_2052, interleave = var_2943_interleave_0, values = (var_2853_cast_fp16, var_2855_cast_fp16, var_2857_cast_fp16, var_2859_cast_fp16))[name = tensor("op_2943_cast_fp16")]; + tensor var_2945_interleave_0 = const()[name = tensor("op_2945_interleave_0"), val = tensor(false)]; + tensor var_2945_cast_fp16 = concat(axis = var_2052, interleave = var_2945_interleave_0, values = (var_2861_cast_fp16, var_2863_cast_fp16, var_2865_cast_fp16, var_2867_cast_fp16))[name = tensor("op_2945_cast_fp16")]; + tensor var_2947_interleave_0 = const()[name = tensor("op_2947_interleave_0"), val = tensor(false)]; + tensor var_2947_cast_fp16 = concat(axis = var_2052, interleave = var_2947_interleave_0, values = (var_2869_cast_fp16, var_2871_cast_fp16, var_2873_cast_fp16, var_2875_cast_fp16))[name = tensor("op_2947_cast_fp16")]; + tensor var_2949_interleave_0 = const()[name = tensor("op_2949_interleave_0"), val = tensor(false)]; + tensor var_2949_cast_fp16 = concat(axis = var_2052, interleave = var_2949_interleave_0, values = (var_2877_cast_fp16, var_2879_cast_fp16, var_2881_cast_fp16, var_2883_cast_fp16))[name = tensor("op_2949_cast_fp16")]; + tensor var_2951_interleave_0 = const()[name = tensor("op_2951_interleave_0"), val = tensor(false)]; + tensor var_2951_cast_fp16 = concat(axis = var_2052, interleave = var_2951_interleave_0, values = (var_2885_cast_fp16, var_2887_cast_fp16, var_2889_cast_fp16, var_2891_cast_fp16))[name = tensor("op_2951_cast_fp16")]; + tensor var_2953_interleave_0 = const()[name = tensor("op_2953_interleave_0"), val = tensor(false)]; + tensor var_2953_cast_fp16 = concat(axis = var_2052, interleave = var_2953_interleave_0, values = (var_2893_cast_fp16, var_2895_cast_fp16, var_2897_cast_fp16, var_2899_cast_fp16))[name = tensor("op_2953_cast_fp16")]; + tensor var_2955_interleave_0 = const()[name = tensor("op_2955_interleave_0"), val = tensor(false)]; + tensor var_2955_cast_fp16 = concat(axis = var_2052, interleave = var_2955_interleave_0, values = (var_2901_cast_fp16, var_2903_cast_fp16, var_2905_cast_fp16, var_2907_cast_fp16))[name = tensor("op_2955_cast_fp16")]; + tensor var_2957_interleave_0 = const()[name = tensor("op_2957_interleave_0"), val = tensor(false)]; + tensor var_2957_cast_fp16 = concat(axis = var_2052, interleave = var_2957_interleave_0, values = (var_2909_cast_fp16, var_2911_cast_fp16, var_2913_cast_fp16, var_2915_cast_fp16))[name = tensor("op_2957_cast_fp16")]; + tensor var_2959_interleave_0 = const()[name = tensor("op_2959_interleave_0"), val = tensor(false)]; + tensor var_2959_cast_fp16 = concat(axis = var_2052, interleave = var_2959_interleave_0, values = (var_2917_cast_fp16, var_2919_cast_fp16, var_2921_cast_fp16, var_2923_cast_fp16))[name = tensor("op_2959_cast_fp16")]; + tensor var_2961_interleave_0 = const()[name = tensor("op_2961_interleave_0"), val = tensor(false)]; + tensor var_2961_cast_fp16 = concat(axis = var_2052, interleave = var_2961_interleave_0, values = (var_2925_cast_fp16, var_2927_cast_fp16, var_2929_cast_fp16, var_2931_cast_fp16))[name = tensor("op_2961_cast_fp16")]; + tensor var_2963_interleave_0 = const()[name = tensor("op_2963_interleave_0"), val = tensor(false)]; + tensor var_2963_cast_fp16 = concat(axis = var_2052, interleave = var_2963_interleave_0, values = (var_2933_cast_fp16, var_2935_cast_fp16, var_2937_cast_fp16, var_2939_cast_fp16))[name = tensor("op_2963_cast_fp16")]; + tensor input_17_interleave_0 = const()[name = tensor("input_17_interleave_0"), val = tensor(false)]; + tensor input_17_cast_fp16 = concat(axis = var_2069, interleave = input_17_interleave_0, values = (var_2941_cast_fp16, var_2943_cast_fp16, var_2945_cast_fp16, var_2947_cast_fp16, var_2949_cast_fp16, var_2951_cast_fp16, var_2953_cast_fp16, var_2955_cast_fp16, var_2957_cast_fp16, var_2959_cast_fp16, var_2961_cast_fp16, var_2963_cast_fp16))[name = tensor("input_17_cast_fp16")]; + tensor var_2968 = const()[name = tensor("op_2968"), val = tensor([1, 1])]; + tensor var_2970 = const()[name = tensor("op_2970"), val = tensor([1, 1])]; + tensor obj_11_pad_type_0 = const()[name = tensor("obj_11_pad_type_0"), val = tensor("custom")]; + tensor obj_11_pad_0 = const()[name = tensor("obj_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38114112)))]; + tensor layers_2_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39293824)))]; + tensor obj_11_cast_fp16 = conv(bias = layers_2_self_attn_o_proj_bias_to_fp16, dilations = var_2970, groups = var_2069, pad = obj_11_pad_0, pad_type = obj_11_pad_type_0, strides = var_2968, weight = layers_2_self_attn_o_proj_weight_to_fp16, x = input_17_cast_fp16)[name = tensor("obj_11_cast_fp16")]; + tensor inputs_11_cast_fp16 = add(x = inputs_9_cast_fp16, y = obj_11_cast_fp16)[name = tensor("inputs_11_cast_fp16")]; + tensor var_2976 = const()[name = tensor("op_2976"), val = tensor([1])]; + tensor channels_mean_11_cast_fp16 = reduce_mean(axes = var_2976, keep_dims = var_2070, x = inputs_11_cast_fp16)[name = tensor("channels_mean_11_cast_fp16")]; + tensor zero_mean_11_cast_fp16 = sub(x = inputs_11_cast_fp16, y = channels_mean_11_cast_fp16)[name = tensor("zero_mean_11_cast_fp16")]; + tensor zero_mean_sq_11_cast_fp16 = mul(x = zero_mean_11_cast_fp16, y = zero_mean_11_cast_fp16)[name = tensor("zero_mean_sq_11_cast_fp16")]; + tensor var_2980 = const()[name = tensor("op_2980"), val = tensor([1])]; + tensor var_2981_cast_fp16 = reduce_mean(axes = var_2980, keep_dims = var_2070, x = zero_mean_sq_11_cast_fp16)[name = tensor("op_2981_cast_fp16")]; + tensor var_2982_to_fp16 = const()[name = tensor("op_2982_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2983_cast_fp16 = add(x = var_2981_cast_fp16, y = var_2982_to_fp16)[name = tensor("op_2983_cast_fp16")]; + tensor denom_11_epsilon_0_to_fp16 = const()[name = tensor("denom_11_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_11_cast_fp16 = rsqrt(epsilon = denom_11_epsilon_0_to_fp16, x = var_2983_cast_fp16)[name = tensor("denom_11_cast_fp16")]; + tensor out_11_cast_fp16 = mul(x = zero_mean_11_cast_fp16, y = denom_11_cast_fp16)[name = tensor("out_11_cast_fp16")]; + tensor input_19_gamma_0_to_fp16 = const()[name = tensor("input_19_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39295424)))]; + tensor input_19_beta_0_to_fp16 = const()[name = tensor("input_19_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39297024)))]; + tensor input_19_epsilon_0_to_fp16 = const()[name = tensor("input_19_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_19_cast_fp16 = batch_norm(beta = input_19_beta_0_to_fp16, epsilon = input_19_epsilon_0_to_fp16, gamma = input_19_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_11_cast_fp16)[name = tensor("input_19_cast_fp16")]; + tensor var_2994 = const()[name = tensor("op_2994"), val = tensor([1, 1])]; + tensor var_2996 = const()[name = tensor("op_2996"), val = tensor([1, 1])]; + tensor input_21_pad_type_0 = const()[name = tensor("input_21_pad_type_0"), val = tensor("custom")]; + tensor input_21_pad_0 = const()[name = tensor("input_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_fc1_weight_to_fp16 = const()[name = tensor("layers_2_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39298624)))]; + tensor layers_2_fc1_bias_to_fp16 = const()[name = tensor("layers_2_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44017280)))]; + tensor input_21_cast_fp16 = conv(bias = layers_2_fc1_bias_to_fp16, dilations = var_2996, groups = var_2069, pad = input_21_pad_0, pad_type = input_21_pad_type_0, strides = var_2994, weight = layers_2_fc1_weight_to_fp16, x = input_19_cast_fp16)[name = tensor("input_21_cast_fp16")]; + tensor input_23_mode_0 = const()[name = tensor("input_23_mode_0"), val = tensor("EXACT")]; + tensor input_23_cast_fp16 = gelu(mode = input_23_mode_0, x = input_21_cast_fp16)[name = tensor("input_23_cast_fp16")]; + tensor var_3002 = const()[name = tensor("op_3002"), val = tensor([1, 1])]; + tensor var_3004 = const()[name = tensor("op_3004"), val = tensor([1, 1])]; + tensor hidden_states_9_pad_type_0 = const()[name = tensor("hidden_states_9_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_9_pad_0 = const()[name = tensor("hidden_states_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_fc2_weight_to_fp16 = const()[name = tensor("layers_2_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44023488)))]; + tensor layers_2_fc2_bias_to_fp16 = const()[name = tensor("layers_2_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48742144)))]; + tensor hidden_states_9_cast_fp16 = conv(bias = layers_2_fc2_bias_to_fp16, dilations = var_3004, groups = var_2069, pad = hidden_states_9_pad_0, pad_type = hidden_states_9_pad_type_0, strides = var_3002, weight = layers_2_fc2_weight_to_fp16, x = input_23_cast_fp16)[name = tensor("hidden_states_9_cast_fp16")]; + tensor inputs_13_cast_fp16 = add(x = inputs_11_cast_fp16, y = hidden_states_9_cast_fp16)[name = tensor("inputs_13_cast_fp16")]; + tensor var_3011 = const()[name = tensor("op_3011"), val = tensor(3)]; + tensor var_3028 = const()[name = tensor("op_3028"), val = tensor(1)]; + tensor var_3029 = const()[name = tensor("op_3029"), val = tensor(true)]; + tensor var_3039 = const()[name = tensor("op_3039"), val = tensor([1])]; + tensor channels_mean_13_cast_fp16 = reduce_mean(axes = var_3039, keep_dims = var_3029, x = inputs_13_cast_fp16)[name = tensor("channels_mean_13_cast_fp16")]; + tensor zero_mean_13_cast_fp16 = sub(x = inputs_13_cast_fp16, y = channels_mean_13_cast_fp16)[name = tensor("zero_mean_13_cast_fp16")]; + tensor zero_mean_sq_13_cast_fp16 = mul(x = zero_mean_13_cast_fp16, y = zero_mean_13_cast_fp16)[name = tensor("zero_mean_sq_13_cast_fp16")]; + tensor var_3043 = const()[name = tensor("op_3043"), val = tensor([1])]; + tensor var_3044_cast_fp16 = reduce_mean(axes = var_3043, keep_dims = var_3029, x = zero_mean_sq_13_cast_fp16)[name = tensor("op_3044_cast_fp16")]; + tensor var_3045_to_fp16 = const()[name = tensor("op_3045_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_3046_cast_fp16 = add(x = var_3044_cast_fp16, y = var_3045_to_fp16)[name = tensor("op_3046_cast_fp16")]; + tensor denom_13_epsilon_0_to_fp16 = const()[name = tensor("denom_13_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_13_cast_fp16 = rsqrt(epsilon = denom_13_epsilon_0_to_fp16, x = var_3046_cast_fp16)[name = tensor("denom_13_cast_fp16")]; + tensor out_13_cast_fp16 = mul(x = zero_mean_13_cast_fp16, y = denom_13_cast_fp16)[name = tensor("out_13_cast_fp16")]; + tensor obj_13_gamma_0_to_fp16 = const()[name = tensor("obj_13_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48743744)))]; + tensor obj_13_beta_0_to_fp16 = const()[name = tensor("obj_13_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48745344)))]; + tensor obj_13_epsilon_0_to_fp16 = const()[name = tensor("obj_13_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_13_cast_fp16 = batch_norm(beta = obj_13_beta_0_to_fp16, epsilon = obj_13_epsilon_0_to_fp16, gamma = obj_13_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_13_cast_fp16)[name = tensor("obj_13_cast_fp16")]; + tensor var_3061 = const()[name = tensor("op_3061"), val = tensor([1, 1])]; + tensor var_3063 = const()[name = tensor("op_3063"), val = tensor([1, 1])]; + tensor query_7_pad_type_0 = const()[name = tensor("query_7_pad_type_0"), val = tensor("custom")]; + tensor query_7_pad_0 = const()[name = tensor("query_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48746944)))]; + tensor layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49926656)))]; + tensor query_7_cast_fp16 = conv(bias = layers_3_self_attn_q_proj_bias_to_fp16, dilations = var_3063, groups = var_3028, pad = query_7_pad_0, pad_type = query_7_pad_type_0, strides = var_3061, weight = layers_3_self_attn_q_proj_weight_to_fp16, x = obj_13_cast_fp16)[name = tensor("query_7_cast_fp16")]; + tensor var_3067 = const()[name = tensor("op_3067"), val = tensor([1, 1])]; + tensor var_3069 = const()[name = tensor("op_3069"), val = tensor([1, 1])]; + tensor key_7_pad_type_0 = const()[name = tensor("key_7_pad_type_0"), val = tensor("custom")]; + tensor key_7_pad_0 = const()[name = tensor("key_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49928256)))]; + tensor key_7_cast_fp16 = conv(dilations = var_3069, groups = var_3028, pad = key_7_pad_0, pad_type = key_7_pad_type_0, strides = var_3067, weight = layers_3_self_attn_k_proj_weight_to_fp16, x = obj_13_cast_fp16)[name = tensor("key_7_cast_fp16")]; + tensor var_3074 = const()[name = tensor("op_3074"), val = tensor([1, 1])]; + tensor var_3076 = const()[name = tensor("op_3076"), val = tensor([1, 1])]; + tensor value_7_pad_type_0 = const()[name = tensor("value_7_pad_type_0"), val = tensor("custom")]; + tensor value_7_pad_0 = const()[name = tensor("value_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51107968)))]; + tensor layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52287680)))]; + tensor value_7_cast_fp16 = conv(bias = layers_3_self_attn_v_proj_bias_to_fp16, dilations = var_3076, groups = var_3028, pad = value_7_pad_0, pad_type = value_7_pad_type_0, strides = var_3074, weight = layers_3_self_attn_v_proj_weight_to_fp16, x = obj_13_cast_fp16)[name = tensor("value_7_cast_fp16")]; + tensor var_3083_begin_0 = const()[name = tensor("op_3083_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3083_end_0 = const()[name = tensor("op_3083_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3083_end_mask_0 = const()[name = tensor("op_3083_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3083_cast_fp16 = slice_by_index(begin = var_3083_begin_0, end = var_3083_end_0, end_mask = var_3083_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_3083_cast_fp16")]; + tensor var_3087_begin_0 = const()[name = tensor("op_3087_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_3087_end_0 = const()[name = tensor("op_3087_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_3087_end_mask_0 = const()[name = tensor("op_3087_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3087_cast_fp16 = slice_by_index(begin = var_3087_begin_0, end = var_3087_end_0, end_mask = var_3087_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_3087_cast_fp16")]; + tensor var_3091_begin_0 = const()[name = tensor("op_3091_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_3091_end_0 = const()[name = tensor("op_3091_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_3091_end_mask_0 = const()[name = tensor("op_3091_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3091_cast_fp16 = slice_by_index(begin = var_3091_begin_0, end = var_3091_end_0, end_mask = var_3091_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_3091_cast_fp16")]; + tensor var_3095_begin_0 = const()[name = tensor("op_3095_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_3095_end_0 = const()[name = tensor("op_3095_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_3095_end_mask_0 = const()[name = tensor("op_3095_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3095_cast_fp16 = slice_by_index(begin = var_3095_begin_0, end = var_3095_end_0, end_mask = var_3095_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_3095_cast_fp16")]; + tensor var_3099_begin_0 = const()[name = tensor("op_3099_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_3099_end_0 = const()[name = tensor("op_3099_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_3099_end_mask_0 = const()[name = tensor("op_3099_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3099_cast_fp16 = slice_by_index(begin = var_3099_begin_0, end = var_3099_end_0, end_mask = var_3099_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_3099_cast_fp16")]; + tensor var_3103_begin_0 = const()[name = tensor("op_3103_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_3103_end_0 = const()[name = tensor("op_3103_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_3103_end_mask_0 = const()[name = tensor("op_3103_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3103_cast_fp16 = slice_by_index(begin = var_3103_begin_0, end = var_3103_end_0, end_mask = var_3103_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_3103_cast_fp16")]; + tensor var_3107_begin_0 = const()[name = tensor("op_3107_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_3107_end_0 = const()[name = tensor("op_3107_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_3107_end_mask_0 = const()[name = tensor("op_3107_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3107_cast_fp16 = slice_by_index(begin = var_3107_begin_0, end = var_3107_end_0, end_mask = var_3107_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_3107_cast_fp16")]; + tensor var_3111_begin_0 = const()[name = tensor("op_3111_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_3111_end_0 = const()[name = tensor("op_3111_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_3111_end_mask_0 = const()[name = tensor("op_3111_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3111_cast_fp16 = slice_by_index(begin = var_3111_begin_0, end = var_3111_end_0, end_mask = var_3111_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_3111_cast_fp16")]; + tensor var_3115_begin_0 = const()[name = tensor("op_3115_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_3115_end_0 = const()[name = tensor("op_3115_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_3115_end_mask_0 = const()[name = tensor("op_3115_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3115_cast_fp16 = slice_by_index(begin = var_3115_begin_0, end = var_3115_end_0, end_mask = var_3115_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_3115_cast_fp16")]; + tensor var_3119_begin_0 = const()[name = tensor("op_3119_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_3119_end_0 = const()[name = tensor("op_3119_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_3119_end_mask_0 = const()[name = tensor("op_3119_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3119_cast_fp16 = slice_by_index(begin = var_3119_begin_0, end = var_3119_end_0, end_mask = var_3119_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_3119_cast_fp16")]; + tensor var_3123_begin_0 = const()[name = tensor("op_3123_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_3123_end_0 = const()[name = tensor("op_3123_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_3123_end_mask_0 = const()[name = tensor("op_3123_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3123_cast_fp16 = slice_by_index(begin = var_3123_begin_0, end = var_3123_end_0, end_mask = var_3123_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_3123_cast_fp16")]; + tensor var_3127_begin_0 = const()[name = tensor("op_3127_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_3127_end_0 = const()[name = tensor("op_3127_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_3127_end_mask_0 = const()[name = tensor("op_3127_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3127_cast_fp16 = slice_by_index(begin = var_3127_begin_0, end = var_3127_end_0, end_mask = var_3127_end_mask_0, x = query_7_cast_fp16)[name = tensor("op_3127_cast_fp16")]; + tensor var_3136_begin_0 = const()[name = tensor("op_3136_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3136_end_0 = const()[name = tensor("op_3136_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3136_end_mask_0 = const()[name = tensor("op_3136_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3136_cast_fp16 = slice_by_index(begin = var_3136_begin_0, end = var_3136_end_0, end_mask = var_3136_end_mask_0, x = var_3083_cast_fp16)[name = tensor("op_3136_cast_fp16")]; + tensor var_3143_begin_0 = const()[name = tensor("op_3143_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3143_end_0 = const()[name = tensor("op_3143_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3143_end_mask_0 = const()[name = tensor("op_3143_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3143_cast_fp16 = slice_by_index(begin = var_3143_begin_0, end = var_3143_end_0, end_mask = var_3143_end_mask_0, x = var_3083_cast_fp16)[name = tensor("op_3143_cast_fp16")]; + tensor var_3150_begin_0 = const()[name = tensor("op_3150_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3150_end_0 = const()[name = tensor("op_3150_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3150_end_mask_0 = const()[name = tensor("op_3150_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3150_cast_fp16 = slice_by_index(begin = var_3150_begin_0, end = var_3150_end_0, end_mask = var_3150_end_mask_0, x = var_3083_cast_fp16)[name = tensor("op_3150_cast_fp16")]; + tensor var_3157_begin_0 = const()[name = tensor("op_3157_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3157_end_0 = const()[name = tensor("op_3157_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3157_end_mask_0 = const()[name = tensor("op_3157_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3157_cast_fp16 = slice_by_index(begin = var_3157_begin_0, end = var_3157_end_0, end_mask = var_3157_end_mask_0, x = var_3083_cast_fp16)[name = tensor("op_3157_cast_fp16")]; + tensor var_3164_begin_0 = const()[name = tensor("op_3164_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3164_end_0 = const()[name = tensor("op_3164_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3164_end_mask_0 = const()[name = tensor("op_3164_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3164_cast_fp16 = slice_by_index(begin = var_3164_begin_0, end = var_3164_end_0, end_mask = var_3164_end_mask_0, x = var_3087_cast_fp16)[name = tensor("op_3164_cast_fp16")]; + tensor var_3171_begin_0 = const()[name = tensor("op_3171_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3171_end_0 = const()[name = tensor("op_3171_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3171_end_mask_0 = const()[name = tensor("op_3171_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3171_cast_fp16 = slice_by_index(begin = var_3171_begin_0, end = var_3171_end_0, end_mask = var_3171_end_mask_0, x = var_3087_cast_fp16)[name = tensor("op_3171_cast_fp16")]; + tensor var_3178_begin_0 = const()[name = tensor("op_3178_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3178_end_0 = const()[name = tensor("op_3178_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3178_end_mask_0 = const()[name = tensor("op_3178_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3178_cast_fp16 = slice_by_index(begin = var_3178_begin_0, end = var_3178_end_0, end_mask = var_3178_end_mask_0, x = var_3087_cast_fp16)[name = tensor("op_3178_cast_fp16")]; + tensor var_3185_begin_0 = const()[name = tensor("op_3185_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3185_end_0 = const()[name = tensor("op_3185_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3185_end_mask_0 = const()[name = tensor("op_3185_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3185_cast_fp16 = slice_by_index(begin = var_3185_begin_0, end = var_3185_end_0, end_mask = var_3185_end_mask_0, x = var_3087_cast_fp16)[name = tensor("op_3185_cast_fp16")]; + tensor var_3192_begin_0 = const()[name = tensor("op_3192_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3192_end_0 = const()[name = tensor("op_3192_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3192_end_mask_0 = const()[name = tensor("op_3192_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3192_cast_fp16 = slice_by_index(begin = var_3192_begin_0, end = var_3192_end_0, end_mask = var_3192_end_mask_0, x = var_3091_cast_fp16)[name = tensor("op_3192_cast_fp16")]; + tensor var_3199_begin_0 = const()[name = tensor("op_3199_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3199_end_0 = const()[name = tensor("op_3199_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3199_end_mask_0 = const()[name = tensor("op_3199_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3199_cast_fp16 = slice_by_index(begin = var_3199_begin_0, end = var_3199_end_0, end_mask = var_3199_end_mask_0, x = var_3091_cast_fp16)[name = tensor("op_3199_cast_fp16")]; + tensor var_3206_begin_0 = const()[name = tensor("op_3206_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3206_end_0 = const()[name = tensor("op_3206_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3206_end_mask_0 = const()[name = tensor("op_3206_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3206_cast_fp16 = slice_by_index(begin = var_3206_begin_0, end = var_3206_end_0, end_mask = var_3206_end_mask_0, x = var_3091_cast_fp16)[name = tensor("op_3206_cast_fp16")]; + tensor var_3213_begin_0 = const()[name = tensor("op_3213_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3213_end_0 = const()[name = tensor("op_3213_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3213_end_mask_0 = const()[name = tensor("op_3213_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3213_cast_fp16 = slice_by_index(begin = var_3213_begin_0, end = var_3213_end_0, end_mask = var_3213_end_mask_0, x = var_3091_cast_fp16)[name = tensor("op_3213_cast_fp16")]; + tensor var_3220_begin_0 = const()[name = tensor("op_3220_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3220_end_0 = const()[name = tensor("op_3220_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3220_end_mask_0 = const()[name = tensor("op_3220_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3220_cast_fp16 = slice_by_index(begin = var_3220_begin_0, end = var_3220_end_0, end_mask = var_3220_end_mask_0, x = var_3095_cast_fp16)[name = tensor("op_3220_cast_fp16")]; + tensor var_3227_begin_0 = const()[name = tensor("op_3227_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3227_end_0 = const()[name = tensor("op_3227_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3227_end_mask_0 = const()[name = tensor("op_3227_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3227_cast_fp16 = slice_by_index(begin = var_3227_begin_0, end = var_3227_end_0, end_mask = var_3227_end_mask_0, x = var_3095_cast_fp16)[name = tensor("op_3227_cast_fp16")]; + tensor var_3234_begin_0 = const()[name = tensor("op_3234_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3234_end_0 = const()[name = tensor("op_3234_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3234_end_mask_0 = const()[name = tensor("op_3234_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3234_cast_fp16 = slice_by_index(begin = var_3234_begin_0, end = var_3234_end_0, end_mask = var_3234_end_mask_0, x = var_3095_cast_fp16)[name = tensor("op_3234_cast_fp16")]; + tensor var_3241_begin_0 = const()[name = tensor("op_3241_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3241_end_0 = const()[name = tensor("op_3241_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3241_end_mask_0 = const()[name = tensor("op_3241_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3241_cast_fp16 = slice_by_index(begin = var_3241_begin_0, end = var_3241_end_0, end_mask = var_3241_end_mask_0, x = var_3095_cast_fp16)[name = tensor("op_3241_cast_fp16")]; + tensor var_3248_begin_0 = const()[name = tensor("op_3248_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3248_end_0 = const()[name = tensor("op_3248_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3248_end_mask_0 = const()[name = tensor("op_3248_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3248_cast_fp16 = slice_by_index(begin = var_3248_begin_0, end = var_3248_end_0, end_mask = var_3248_end_mask_0, x = var_3099_cast_fp16)[name = tensor("op_3248_cast_fp16")]; + tensor var_3255_begin_0 = const()[name = tensor("op_3255_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3255_end_0 = const()[name = tensor("op_3255_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3255_end_mask_0 = const()[name = tensor("op_3255_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3255_cast_fp16 = slice_by_index(begin = var_3255_begin_0, end = var_3255_end_0, end_mask = var_3255_end_mask_0, x = var_3099_cast_fp16)[name = tensor("op_3255_cast_fp16")]; + tensor var_3262_begin_0 = const()[name = tensor("op_3262_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3262_end_0 = const()[name = tensor("op_3262_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3262_end_mask_0 = const()[name = tensor("op_3262_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3262_cast_fp16 = slice_by_index(begin = var_3262_begin_0, end = var_3262_end_0, end_mask = var_3262_end_mask_0, x = var_3099_cast_fp16)[name = tensor("op_3262_cast_fp16")]; + tensor var_3269_begin_0 = const()[name = tensor("op_3269_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3269_end_0 = const()[name = tensor("op_3269_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3269_end_mask_0 = const()[name = tensor("op_3269_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3269_cast_fp16 = slice_by_index(begin = var_3269_begin_0, end = var_3269_end_0, end_mask = var_3269_end_mask_0, x = var_3099_cast_fp16)[name = tensor("op_3269_cast_fp16")]; + tensor var_3276_begin_0 = const()[name = tensor("op_3276_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3276_end_0 = const()[name = tensor("op_3276_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3276_end_mask_0 = const()[name = tensor("op_3276_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3276_cast_fp16 = slice_by_index(begin = var_3276_begin_0, end = var_3276_end_0, end_mask = var_3276_end_mask_0, x = var_3103_cast_fp16)[name = tensor("op_3276_cast_fp16")]; + tensor var_3283_begin_0 = const()[name = tensor("op_3283_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3283_end_0 = const()[name = tensor("op_3283_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3283_end_mask_0 = const()[name = tensor("op_3283_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3283_cast_fp16 = slice_by_index(begin = var_3283_begin_0, end = var_3283_end_0, end_mask = var_3283_end_mask_0, x = var_3103_cast_fp16)[name = tensor("op_3283_cast_fp16")]; + tensor var_3290_begin_0 = const()[name = tensor("op_3290_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3290_end_0 = const()[name = tensor("op_3290_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3290_end_mask_0 = const()[name = tensor("op_3290_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3290_cast_fp16 = slice_by_index(begin = var_3290_begin_0, end = var_3290_end_0, end_mask = var_3290_end_mask_0, x = var_3103_cast_fp16)[name = tensor("op_3290_cast_fp16")]; + tensor var_3297_begin_0 = const()[name = tensor("op_3297_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3297_end_0 = const()[name = tensor("op_3297_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3297_end_mask_0 = const()[name = tensor("op_3297_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3297_cast_fp16 = slice_by_index(begin = var_3297_begin_0, end = var_3297_end_0, end_mask = var_3297_end_mask_0, x = var_3103_cast_fp16)[name = tensor("op_3297_cast_fp16")]; + tensor var_3304_begin_0 = const()[name = tensor("op_3304_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3304_end_0 = const()[name = tensor("op_3304_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3304_end_mask_0 = const()[name = tensor("op_3304_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3304_cast_fp16 = slice_by_index(begin = var_3304_begin_0, end = var_3304_end_0, end_mask = var_3304_end_mask_0, x = var_3107_cast_fp16)[name = tensor("op_3304_cast_fp16")]; + tensor var_3311_begin_0 = const()[name = tensor("op_3311_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3311_end_0 = const()[name = tensor("op_3311_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3311_end_mask_0 = const()[name = tensor("op_3311_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3311_cast_fp16 = slice_by_index(begin = var_3311_begin_0, end = var_3311_end_0, end_mask = var_3311_end_mask_0, x = var_3107_cast_fp16)[name = tensor("op_3311_cast_fp16")]; + tensor var_3318_begin_0 = const()[name = tensor("op_3318_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3318_end_0 = const()[name = tensor("op_3318_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3318_end_mask_0 = const()[name = tensor("op_3318_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3318_cast_fp16 = slice_by_index(begin = var_3318_begin_0, end = var_3318_end_0, end_mask = var_3318_end_mask_0, x = var_3107_cast_fp16)[name = tensor("op_3318_cast_fp16")]; + tensor var_3325_begin_0 = const()[name = tensor("op_3325_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3325_end_0 = const()[name = tensor("op_3325_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3325_end_mask_0 = const()[name = tensor("op_3325_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3325_cast_fp16 = slice_by_index(begin = var_3325_begin_0, end = var_3325_end_0, end_mask = var_3325_end_mask_0, x = var_3107_cast_fp16)[name = tensor("op_3325_cast_fp16")]; + tensor var_3332_begin_0 = const()[name = tensor("op_3332_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3332_end_0 = const()[name = tensor("op_3332_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3332_end_mask_0 = const()[name = tensor("op_3332_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3332_cast_fp16 = slice_by_index(begin = var_3332_begin_0, end = var_3332_end_0, end_mask = var_3332_end_mask_0, x = var_3111_cast_fp16)[name = tensor("op_3332_cast_fp16")]; + tensor var_3339_begin_0 = const()[name = tensor("op_3339_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3339_end_0 = const()[name = tensor("op_3339_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3339_end_mask_0 = const()[name = tensor("op_3339_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3339_cast_fp16 = slice_by_index(begin = var_3339_begin_0, end = var_3339_end_0, end_mask = var_3339_end_mask_0, x = var_3111_cast_fp16)[name = tensor("op_3339_cast_fp16")]; + tensor var_3346_begin_0 = const()[name = tensor("op_3346_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3346_end_0 = const()[name = tensor("op_3346_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3346_end_mask_0 = const()[name = tensor("op_3346_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3346_cast_fp16 = slice_by_index(begin = var_3346_begin_0, end = var_3346_end_0, end_mask = var_3346_end_mask_0, x = var_3111_cast_fp16)[name = tensor("op_3346_cast_fp16")]; + tensor var_3353_begin_0 = const()[name = tensor("op_3353_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3353_end_0 = const()[name = tensor("op_3353_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3353_end_mask_0 = const()[name = tensor("op_3353_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3353_cast_fp16 = slice_by_index(begin = var_3353_begin_0, end = var_3353_end_0, end_mask = var_3353_end_mask_0, x = var_3111_cast_fp16)[name = tensor("op_3353_cast_fp16")]; + tensor var_3360_begin_0 = const()[name = tensor("op_3360_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3360_end_0 = const()[name = tensor("op_3360_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3360_end_mask_0 = const()[name = tensor("op_3360_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3360_cast_fp16 = slice_by_index(begin = var_3360_begin_0, end = var_3360_end_0, end_mask = var_3360_end_mask_0, x = var_3115_cast_fp16)[name = tensor("op_3360_cast_fp16")]; + tensor var_3367_begin_0 = const()[name = tensor("op_3367_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3367_end_0 = const()[name = tensor("op_3367_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3367_end_mask_0 = const()[name = tensor("op_3367_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3367_cast_fp16 = slice_by_index(begin = var_3367_begin_0, end = var_3367_end_0, end_mask = var_3367_end_mask_0, x = var_3115_cast_fp16)[name = tensor("op_3367_cast_fp16")]; + tensor var_3374_begin_0 = const()[name = tensor("op_3374_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3374_end_0 = const()[name = tensor("op_3374_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3374_end_mask_0 = const()[name = tensor("op_3374_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3374_cast_fp16 = slice_by_index(begin = var_3374_begin_0, end = var_3374_end_0, end_mask = var_3374_end_mask_0, x = var_3115_cast_fp16)[name = tensor("op_3374_cast_fp16")]; + tensor var_3381_begin_0 = const()[name = tensor("op_3381_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3381_end_0 = const()[name = tensor("op_3381_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3381_end_mask_0 = const()[name = tensor("op_3381_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3381_cast_fp16 = slice_by_index(begin = var_3381_begin_0, end = var_3381_end_0, end_mask = var_3381_end_mask_0, x = var_3115_cast_fp16)[name = tensor("op_3381_cast_fp16")]; + tensor var_3388_begin_0 = const()[name = tensor("op_3388_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3388_end_0 = const()[name = tensor("op_3388_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3388_end_mask_0 = const()[name = tensor("op_3388_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3388_cast_fp16 = slice_by_index(begin = var_3388_begin_0, end = var_3388_end_0, end_mask = var_3388_end_mask_0, x = var_3119_cast_fp16)[name = tensor("op_3388_cast_fp16")]; + tensor var_3395_begin_0 = const()[name = tensor("op_3395_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3395_end_0 = const()[name = tensor("op_3395_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3395_end_mask_0 = const()[name = tensor("op_3395_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3395_cast_fp16 = slice_by_index(begin = var_3395_begin_0, end = var_3395_end_0, end_mask = var_3395_end_mask_0, x = var_3119_cast_fp16)[name = tensor("op_3395_cast_fp16")]; + tensor var_3402_begin_0 = const()[name = tensor("op_3402_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3402_end_0 = const()[name = tensor("op_3402_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3402_end_mask_0 = const()[name = tensor("op_3402_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3402_cast_fp16 = slice_by_index(begin = var_3402_begin_0, end = var_3402_end_0, end_mask = var_3402_end_mask_0, x = var_3119_cast_fp16)[name = tensor("op_3402_cast_fp16")]; + tensor var_3409_begin_0 = const()[name = tensor("op_3409_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3409_end_0 = const()[name = tensor("op_3409_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3409_end_mask_0 = const()[name = tensor("op_3409_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3409_cast_fp16 = slice_by_index(begin = var_3409_begin_0, end = var_3409_end_0, end_mask = var_3409_end_mask_0, x = var_3119_cast_fp16)[name = tensor("op_3409_cast_fp16")]; + tensor var_3416_begin_0 = const()[name = tensor("op_3416_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3416_end_0 = const()[name = tensor("op_3416_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3416_end_mask_0 = const()[name = tensor("op_3416_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3416_cast_fp16 = slice_by_index(begin = var_3416_begin_0, end = var_3416_end_0, end_mask = var_3416_end_mask_0, x = var_3123_cast_fp16)[name = tensor("op_3416_cast_fp16")]; + tensor var_3423_begin_0 = const()[name = tensor("op_3423_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3423_end_0 = const()[name = tensor("op_3423_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3423_end_mask_0 = const()[name = tensor("op_3423_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3423_cast_fp16 = slice_by_index(begin = var_3423_begin_0, end = var_3423_end_0, end_mask = var_3423_end_mask_0, x = var_3123_cast_fp16)[name = tensor("op_3423_cast_fp16")]; + tensor var_3430_begin_0 = const()[name = tensor("op_3430_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3430_end_0 = const()[name = tensor("op_3430_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3430_end_mask_0 = const()[name = tensor("op_3430_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3430_cast_fp16 = slice_by_index(begin = var_3430_begin_0, end = var_3430_end_0, end_mask = var_3430_end_mask_0, x = var_3123_cast_fp16)[name = tensor("op_3430_cast_fp16")]; + tensor var_3437_begin_0 = const()[name = tensor("op_3437_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3437_end_0 = const()[name = tensor("op_3437_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3437_end_mask_0 = const()[name = tensor("op_3437_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3437_cast_fp16 = slice_by_index(begin = var_3437_begin_0, end = var_3437_end_0, end_mask = var_3437_end_mask_0, x = var_3123_cast_fp16)[name = tensor("op_3437_cast_fp16")]; + tensor var_3444_begin_0 = const()[name = tensor("op_3444_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3444_end_0 = const()[name = tensor("op_3444_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_3444_end_mask_0 = const()[name = tensor("op_3444_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3444_cast_fp16 = slice_by_index(begin = var_3444_begin_0, end = var_3444_end_0, end_mask = var_3444_end_mask_0, x = var_3127_cast_fp16)[name = tensor("op_3444_cast_fp16")]; + tensor var_3451_begin_0 = const()[name = tensor("op_3451_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_3451_end_0 = const()[name = tensor("op_3451_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_3451_end_mask_0 = const()[name = tensor("op_3451_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3451_cast_fp16 = slice_by_index(begin = var_3451_begin_0, end = var_3451_end_0, end_mask = var_3451_end_mask_0, x = var_3127_cast_fp16)[name = tensor("op_3451_cast_fp16")]; + tensor var_3458_begin_0 = const()[name = tensor("op_3458_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_3458_end_0 = const()[name = tensor("op_3458_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_3458_end_mask_0 = const()[name = tensor("op_3458_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3458_cast_fp16 = slice_by_index(begin = var_3458_begin_0, end = var_3458_end_0, end_mask = var_3458_end_mask_0, x = var_3127_cast_fp16)[name = tensor("op_3458_cast_fp16")]; + tensor var_3465_begin_0 = const()[name = tensor("op_3465_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_3465_end_0 = const()[name = tensor("op_3465_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3465_end_mask_0 = const()[name = tensor("op_3465_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3465_cast_fp16 = slice_by_index(begin = var_3465_begin_0, end = var_3465_end_0, end_mask = var_3465_end_mask_0, x = var_3127_cast_fp16)[name = tensor("op_3465_cast_fp16")]; + tensor k_7_perm_0 = const()[name = tensor("k_7_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_3470_begin_0 = const()[name = tensor("op_3470_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3470_end_0 = const()[name = tensor("op_3470_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_3470_end_mask_0 = const()[name = tensor("op_3470_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_8 = transpose(perm = k_7_perm_0, x = key_7_cast_fp16)[name = tensor("transpose_8")]; + tensor var_3470_cast_fp16 = slice_by_index(begin = var_3470_begin_0, end = var_3470_end_0, end_mask = var_3470_end_mask_0, x = transpose_8)[name = tensor("op_3470_cast_fp16")]; + tensor var_3474_begin_0 = const()[name = tensor("op_3474_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_3474_end_0 = const()[name = tensor("op_3474_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_3474_end_mask_0 = const()[name = tensor("op_3474_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3474_cast_fp16 = slice_by_index(begin = var_3474_begin_0, end = var_3474_end_0, end_mask = var_3474_end_mask_0, x = transpose_8)[name = tensor("op_3474_cast_fp16")]; + tensor var_3478_begin_0 = const()[name = tensor("op_3478_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_3478_end_0 = const()[name = tensor("op_3478_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_3478_end_mask_0 = const()[name = tensor("op_3478_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3478_cast_fp16 = slice_by_index(begin = var_3478_begin_0, end = var_3478_end_0, end_mask = var_3478_end_mask_0, x = transpose_8)[name = tensor("op_3478_cast_fp16")]; + tensor var_3482_begin_0 = const()[name = tensor("op_3482_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_3482_end_0 = const()[name = tensor("op_3482_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_3482_end_mask_0 = const()[name = tensor("op_3482_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3482_cast_fp16 = slice_by_index(begin = var_3482_begin_0, end = var_3482_end_0, end_mask = var_3482_end_mask_0, x = transpose_8)[name = tensor("op_3482_cast_fp16")]; + tensor var_3486_begin_0 = const()[name = tensor("op_3486_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_3486_end_0 = const()[name = tensor("op_3486_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_3486_end_mask_0 = const()[name = tensor("op_3486_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3486_cast_fp16 = slice_by_index(begin = var_3486_begin_0, end = var_3486_end_0, end_mask = var_3486_end_mask_0, x = transpose_8)[name = tensor("op_3486_cast_fp16")]; + tensor var_3490_begin_0 = const()[name = tensor("op_3490_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_3490_end_0 = const()[name = tensor("op_3490_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_3490_end_mask_0 = const()[name = tensor("op_3490_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3490_cast_fp16 = slice_by_index(begin = var_3490_begin_0, end = var_3490_end_0, end_mask = var_3490_end_mask_0, x = transpose_8)[name = tensor("op_3490_cast_fp16")]; + tensor var_3494_begin_0 = const()[name = tensor("op_3494_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_3494_end_0 = const()[name = tensor("op_3494_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_3494_end_mask_0 = const()[name = tensor("op_3494_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3494_cast_fp16 = slice_by_index(begin = var_3494_begin_0, end = var_3494_end_0, end_mask = var_3494_end_mask_0, x = transpose_8)[name = tensor("op_3494_cast_fp16")]; + tensor var_3498_begin_0 = const()[name = tensor("op_3498_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_3498_end_0 = const()[name = tensor("op_3498_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_3498_end_mask_0 = const()[name = tensor("op_3498_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3498_cast_fp16 = slice_by_index(begin = var_3498_begin_0, end = var_3498_end_0, end_mask = var_3498_end_mask_0, x = transpose_8)[name = tensor("op_3498_cast_fp16")]; + tensor var_3502_begin_0 = const()[name = tensor("op_3502_begin_0"), val = tensor([0, 0, 0, 512])]; + tensor var_3502_end_0 = const()[name = tensor("op_3502_end_0"), val = tensor([1, 1500, 1, 576])]; + tensor var_3502_end_mask_0 = const()[name = tensor("op_3502_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3502_cast_fp16 = slice_by_index(begin = var_3502_begin_0, end = var_3502_end_0, end_mask = var_3502_end_mask_0, x = transpose_8)[name = tensor("op_3502_cast_fp16")]; + tensor var_3506_begin_0 = const()[name = tensor("op_3506_begin_0"), val = tensor([0, 0, 0, 576])]; + tensor var_3506_end_0 = const()[name = tensor("op_3506_end_0"), val = tensor([1, 1500, 1, 640])]; + tensor var_3506_end_mask_0 = const()[name = tensor("op_3506_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3506_cast_fp16 = slice_by_index(begin = var_3506_begin_0, end = var_3506_end_0, end_mask = var_3506_end_mask_0, x = transpose_8)[name = tensor("op_3506_cast_fp16")]; + tensor var_3510_begin_0 = const()[name = tensor("op_3510_begin_0"), val = tensor([0, 0, 0, 640])]; + tensor var_3510_end_0 = const()[name = tensor("op_3510_end_0"), val = tensor([1, 1500, 1, 704])]; + tensor var_3510_end_mask_0 = const()[name = tensor("op_3510_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3510_cast_fp16 = slice_by_index(begin = var_3510_begin_0, end = var_3510_end_0, end_mask = var_3510_end_mask_0, x = transpose_8)[name = tensor("op_3510_cast_fp16")]; + tensor var_3514_begin_0 = const()[name = tensor("op_3514_begin_0"), val = tensor([0, 0, 0, 704])]; + tensor var_3514_end_0 = const()[name = tensor("op_3514_end_0"), val = tensor([1, 1500, 1, 768])]; + tensor var_3514_end_mask_0 = const()[name = tensor("op_3514_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_3514_cast_fp16 = slice_by_index(begin = var_3514_begin_0, end = var_3514_end_0, end_mask = var_3514_end_mask_0, x = transpose_8)[name = tensor("op_3514_cast_fp16")]; + tensor var_3516_begin_0 = const()[name = tensor("op_3516_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_3516_end_0 = const()[name = tensor("op_3516_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_3516_end_mask_0 = const()[name = tensor("op_3516_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3516_cast_fp16 = slice_by_index(begin = var_3516_begin_0, end = var_3516_end_0, end_mask = var_3516_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_3516_cast_fp16")]; + tensor var_3520_begin_0 = const()[name = tensor("op_3520_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_3520_end_0 = const()[name = tensor("op_3520_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_3520_end_mask_0 = const()[name = tensor("op_3520_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3520_cast_fp16 = slice_by_index(begin = var_3520_begin_0, end = var_3520_end_0, end_mask = var_3520_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_3520_cast_fp16")]; + tensor var_3524_begin_0 = const()[name = tensor("op_3524_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_3524_end_0 = const()[name = tensor("op_3524_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_3524_end_mask_0 = const()[name = tensor("op_3524_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3524_cast_fp16 = slice_by_index(begin = var_3524_begin_0, end = var_3524_end_0, end_mask = var_3524_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_3524_cast_fp16")]; + tensor var_3528_begin_0 = const()[name = tensor("op_3528_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_3528_end_0 = const()[name = tensor("op_3528_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_3528_end_mask_0 = const()[name = tensor("op_3528_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3528_cast_fp16 = slice_by_index(begin = var_3528_begin_0, end = var_3528_end_0, end_mask = var_3528_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_3528_cast_fp16")]; + tensor var_3532_begin_0 = const()[name = tensor("op_3532_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_3532_end_0 = const()[name = tensor("op_3532_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_3532_end_mask_0 = const()[name = tensor("op_3532_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3532_cast_fp16 = slice_by_index(begin = var_3532_begin_0, end = var_3532_end_0, end_mask = var_3532_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_3532_cast_fp16")]; + tensor var_3536_begin_0 = const()[name = tensor("op_3536_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_3536_end_0 = const()[name = tensor("op_3536_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_3536_end_mask_0 = const()[name = tensor("op_3536_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3536_cast_fp16 = slice_by_index(begin = var_3536_begin_0, end = var_3536_end_0, end_mask = var_3536_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_3536_cast_fp16")]; + tensor var_3540_begin_0 = const()[name = tensor("op_3540_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_3540_end_0 = const()[name = tensor("op_3540_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_3540_end_mask_0 = const()[name = tensor("op_3540_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3540_cast_fp16 = slice_by_index(begin = var_3540_begin_0, end = var_3540_end_0, end_mask = var_3540_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_3540_cast_fp16")]; + tensor var_3544_begin_0 = const()[name = tensor("op_3544_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_3544_end_0 = const()[name = tensor("op_3544_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_3544_end_mask_0 = const()[name = tensor("op_3544_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3544_cast_fp16 = slice_by_index(begin = var_3544_begin_0, end = var_3544_end_0, end_mask = var_3544_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_3544_cast_fp16")]; + tensor var_3548_begin_0 = const()[name = tensor("op_3548_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_3548_end_0 = const()[name = tensor("op_3548_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_3548_end_mask_0 = const()[name = tensor("op_3548_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3548_cast_fp16 = slice_by_index(begin = var_3548_begin_0, end = var_3548_end_0, end_mask = var_3548_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_3548_cast_fp16")]; + tensor var_3552_begin_0 = const()[name = tensor("op_3552_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_3552_end_0 = const()[name = tensor("op_3552_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_3552_end_mask_0 = const()[name = tensor("op_3552_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3552_cast_fp16 = slice_by_index(begin = var_3552_begin_0, end = var_3552_end_0, end_mask = var_3552_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_3552_cast_fp16")]; + tensor var_3556_begin_0 = const()[name = tensor("op_3556_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_3556_end_0 = const()[name = tensor("op_3556_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_3556_end_mask_0 = const()[name = tensor("op_3556_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3556_cast_fp16 = slice_by_index(begin = var_3556_begin_0, end = var_3556_end_0, end_mask = var_3556_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_3556_cast_fp16")]; + tensor var_3560_begin_0 = const()[name = tensor("op_3560_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_3560_end_0 = const()[name = tensor("op_3560_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_3560_end_mask_0 = const()[name = tensor("op_3560_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_3560_cast_fp16 = slice_by_index(begin = var_3560_begin_0, end = var_3560_end_0, end_mask = var_3560_end_mask_0, x = value_7_cast_fp16)[name = tensor("op_3560_cast_fp16")]; + tensor var_3564_equation_0 = const()[name = tensor("op_3564_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3564_cast_fp16 = einsum(equation = var_3564_equation_0, values = (var_3470_cast_fp16, var_3136_cast_fp16))[name = tensor("op_3564_cast_fp16")]; + tensor var_3565_to_fp16 = const()[name = tensor("op_3565_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_289_cast_fp16 = mul(x = var_3564_cast_fp16, y = var_3565_to_fp16)[name = tensor("aw_chunk_289_cast_fp16")]; + tensor var_3568_equation_0 = const()[name = tensor("op_3568_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3568_cast_fp16 = einsum(equation = var_3568_equation_0, values = (var_3470_cast_fp16, var_3143_cast_fp16))[name = tensor("op_3568_cast_fp16")]; + tensor var_3569_to_fp16 = const()[name = tensor("op_3569_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_291_cast_fp16 = mul(x = var_3568_cast_fp16, y = var_3569_to_fp16)[name = tensor("aw_chunk_291_cast_fp16")]; + tensor var_3572_equation_0 = const()[name = tensor("op_3572_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3572_cast_fp16 = einsum(equation = var_3572_equation_0, values = (var_3470_cast_fp16, var_3150_cast_fp16))[name = tensor("op_3572_cast_fp16")]; + tensor var_3573_to_fp16 = const()[name = tensor("op_3573_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_293_cast_fp16 = mul(x = var_3572_cast_fp16, y = var_3573_to_fp16)[name = tensor("aw_chunk_293_cast_fp16")]; + tensor var_3576_equation_0 = const()[name = tensor("op_3576_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3576_cast_fp16 = einsum(equation = var_3576_equation_0, values = (var_3470_cast_fp16, var_3157_cast_fp16))[name = tensor("op_3576_cast_fp16")]; + tensor var_3577_to_fp16 = const()[name = tensor("op_3577_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_295_cast_fp16 = mul(x = var_3576_cast_fp16, y = var_3577_to_fp16)[name = tensor("aw_chunk_295_cast_fp16")]; + tensor var_3580_equation_0 = const()[name = tensor("op_3580_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3580_cast_fp16 = einsum(equation = var_3580_equation_0, values = (var_3474_cast_fp16, var_3164_cast_fp16))[name = tensor("op_3580_cast_fp16")]; + tensor var_3581_to_fp16 = const()[name = tensor("op_3581_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_297_cast_fp16 = mul(x = var_3580_cast_fp16, y = var_3581_to_fp16)[name = tensor("aw_chunk_297_cast_fp16")]; + tensor var_3584_equation_0 = const()[name = tensor("op_3584_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3584_cast_fp16 = einsum(equation = var_3584_equation_0, values = (var_3474_cast_fp16, var_3171_cast_fp16))[name = tensor("op_3584_cast_fp16")]; + tensor var_3585_to_fp16 = const()[name = tensor("op_3585_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_299_cast_fp16 = mul(x = var_3584_cast_fp16, y = var_3585_to_fp16)[name = tensor("aw_chunk_299_cast_fp16")]; + tensor var_3588_equation_0 = const()[name = tensor("op_3588_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3588_cast_fp16 = einsum(equation = var_3588_equation_0, values = (var_3474_cast_fp16, var_3178_cast_fp16))[name = tensor("op_3588_cast_fp16")]; + tensor var_3589_to_fp16 = const()[name = tensor("op_3589_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_301_cast_fp16 = mul(x = var_3588_cast_fp16, y = var_3589_to_fp16)[name = tensor("aw_chunk_301_cast_fp16")]; + tensor var_3592_equation_0 = const()[name = tensor("op_3592_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3592_cast_fp16 = einsum(equation = var_3592_equation_0, values = (var_3474_cast_fp16, var_3185_cast_fp16))[name = tensor("op_3592_cast_fp16")]; + tensor var_3593_to_fp16 = const()[name = tensor("op_3593_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_303_cast_fp16 = mul(x = var_3592_cast_fp16, y = var_3593_to_fp16)[name = tensor("aw_chunk_303_cast_fp16")]; + tensor var_3596_equation_0 = const()[name = tensor("op_3596_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3596_cast_fp16 = einsum(equation = var_3596_equation_0, values = (var_3478_cast_fp16, var_3192_cast_fp16))[name = tensor("op_3596_cast_fp16")]; + tensor var_3597_to_fp16 = const()[name = tensor("op_3597_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_305_cast_fp16 = mul(x = var_3596_cast_fp16, y = var_3597_to_fp16)[name = tensor("aw_chunk_305_cast_fp16")]; + tensor var_3600_equation_0 = const()[name = tensor("op_3600_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3600_cast_fp16 = einsum(equation = var_3600_equation_0, values = (var_3478_cast_fp16, var_3199_cast_fp16))[name = tensor("op_3600_cast_fp16")]; + tensor var_3601_to_fp16 = const()[name = tensor("op_3601_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_307_cast_fp16 = mul(x = var_3600_cast_fp16, y = var_3601_to_fp16)[name = tensor("aw_chunk_307_cast_fp16")]; + tensor var_3604_equation_0 = const()[name = tensor("op_3604_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3604_cast_fp16 = einsum(equation = var_3604_equation_0, values = (var_3478_cast_fp16, var_3206_cast_fp16))[name = tensor("op_3604_cast_fp16")]; + tensor var_3605_to_fp16 = const()[name = tensor("op_3605_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_309_cast_fp16 = mul(x = var_3604_cast_fp16, y = var_3605_to_fp16)[name = tensor("aw_chunk_309_cast_fp16")]; + tensor var_3608_equation_0 = const()[name = tensor("op_3608_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3608_cast_fp16 = einsum(equation = var_3608_equation_0, values = (var_3478_cast_fp16, var_3213_cast_fp16))[name = tensor("op_3608_cast_fp16")]; + tensor var_3609_to_fp16 = const()[name = tensor("op_3609_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_311_cast_fp16 = mul(x = var_3608_cast_fp16, y = var_3609_to_fp16)[name = tensor("aw_chunk_311_cast_fp16")]; + tensor var_3612_equation_0 = const()[name = tensor("op_3612_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3612_cast_fp16 = einsum(equation = var_3612_equation_0, values = (var_3482_cast_fp16, var_3220_cast_fp16))[name = tensor("op_3612_cast_fp16")]; + tensor var_3613_to_fp16 = const()[name = tensor("op_3613_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_313_cast_fp16 = mul(x = var_3612_cast_fp16, y = var_3613_to_fp16)[name = tensor("aw_chunk_313_cast_fp16")]; + tensor var_3616_equation_0 = const()[name = tensor("op_3616_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3616_cast_fp16 = einsum(equation = var_3616_equation_0, values = (var_3482_cast_fp16, var_3227_cast_fp16))[name = tensor("op_3616_cast_fp16")]; + tensor var_3617_to_fp16 = const()[name = tensor("op_3617_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_315_cast_fp16 = mul(x = var_3616_cast_fp16, y = var_3617_to_fp16)[name = tensor("aw_chunk_315_cast_fp16")]; + tensor var_3620_equation_0 = const()[name = tensor("op_3620_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3620_cast_fp16 = einsum(equation = var_3620_equation_0, values = (var_3482_cast_fp16, var_3234_cast_fp16))[name = tensor("op_3620_cast_fp16")]; + tensor var_3621_to_fp16 = const()[name = tensor("op_3621_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_317_cast_fp16 = mul(x = var_3620_cast_fp16, y = var_3621_to_fp16)[name = tensor("aw_chunk_317_cast_fp16")]; + tensor var_3624_equation_0 = const()[name = tensor("op_3624_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3624_cast_fp16 = einsum(equation = var_3624_equation_0, values = (var_3482_cast_fp16, var_3241_cast_fp16))[name = tensor("op_3624_cast_fp16")]; + tensor var_3625_to_fp16 = const()[name = tensor("op_3625_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_319_cast_fp16 = mul(x = var_3624_cast_fp16, y = var_3625_to_fp16)[name = tensor("aw_chunk_319_cast_fp16")]; + tensor var_3628_equation_0 = const()[name = tensor("op_3628_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3628_cast_fp16 = einsum(equation = var_3628_equation_0, values = (var_3486_cast_fp16, var_3248_cast_fp16))[name = tensor("op_3628_cast_fp16")]; + tensor var_3629_to_fp16 = const()[name = tensor("op_3629_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_321_cast_fp16 = mul(x = var_3628_cast_fp16, y = var_3629_to_fp16)[name = tensor("aw_chunk_321_cast_fp16")]; + tensor var_3632_equation_0 = const()[name = tensor("op_3632_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3632_cast_fp16 = einsum(equation = var_3632_equation_0, values = (var_3486_cast_fp16, var_3255_cast_fp16))[name = tensor("op_3632_cast_fp16")]; + tensor var_3633_to_fp16 = const()[name = tensor("op_3633_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_323_cast_fp16 = mul(x = var_3632_cast_fp16, y = var_3633_to_fp16)[name = tensor("aw_chunk_323_cast_fp16")]; + tensor var_3636_equation_0 = const()[name = tensor("op_3636_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3636_cast_fp16 = einsum(equation = var_3636_equation_0, values = (var_3486_cast_fp16, var_3262_cast_fp16))[name = tensor("op_3636_cast_fp16")]; + tensor var_3637_to_fp16 = const()[name = tensor("op_3637_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_325_cast_fp16 = mul(x = var_3636_cast_fp16, y = var_3637_to_fp16)[name = tensor("aw_chunk_325_cast_fp16")]; + tensor var_3640_equation_0 = const()[name = tensor("op_3640_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3640_cast_fp16 = einsum(equation = var_3640_equation_0, values = (var_3486_cast_fp16, var_3269_cast_fp16))[name = tensor("op_3640_cast_fp16")]; + tensor var_3641_to_fp16 = const()[name = tensor("op_3641_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_327_cast_fp16 = mul(x = var_3640_cast_fp16, y = var_3641_to_fp16)[name = tensor("aw_chunk_327_cast_fp16")]; + tensor var_3644_equation_0 = const()[name = tensor("op_3644_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3644_cast_fp16 = einsum(equation = var_3644_equation_0, values = (var_3490_cast_fp16, var_3276_cast_fp16))[name = tensor("op_3644_cast_fp16")]; + tensor var_3645_to_fp16 = const()[name = tensor("op_3645_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_329_cast_fp16 = mul(x = var_3644_cast_fp16, y = var_3645_to_fp16)[name = tensor("aw_chunk_329_cast_fp16")]; + tensor var_3648_equation_0 = const()[name = tensor("op_3648_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3648_cast_fp16 = einsum(equation = var_3648_equation_0, values = (var_3490_cast_fp16, var_3283_cast_fp16))[name = tensor("op_3648_cast_fp16")]; + tensor var_3649_to_fp16 = const()[name = tensor("op_3649_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_331_cast_fp16 = mul(x = var_3648_cast_fp16, y = var_3649_to_fp16)[name = tensor("aw_chunk_331_cast_fp16")]; + tensor var_3652_equation_0 = const()[name = tensor("op_3652_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3652_cast_fp16 = einsum(equation = var_3652_equation_0, values = (var_3490_cast_fp16, var_3290_cast_fp16))[name = tensor("op_3652_cast_fp16")]; + tensor var_3653_to_fp16 = const()[name = tensor("op_3653_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_333_cast_fp16 = mul(x = var_3652_cast_fp16, y = var_3653_to_fp16)[name = tensor("aw_chunk_333_cast_fp16")]; + tensor var_3656_equation_0 = const()[name = tensor("op_3656_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3656_cast_fp16 = einsum(equation = var_3656_equation_0, values = (var_3490_cast_fp16, var_3297_cast_fp16))[name = tensor("op_3656_cast_fp16")]; + tensor var_3657_to_fp16 = const()[name = tensor("op_3657_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_335_cast_fp16 = mul(x = var_3656_cast_fp16, y = var_3657_to_fp16)[name = tensor("aw_chunk_335_cast_fp16")]; + tensor var_3660_equation_0 = const()[name = tensor("op_3660_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3660_cast_fp16 = einsum(equation = var_3660_equation_0, values = (var_3494_cast_fp16, var_3304_cast_fp16))[name = tensor("op_3660_cast_fp16")]; + tensor var_3661_to_fp16 = const()[name = tensor("op_3661_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_337_cast_fp16 = mul(x = var_3660_cast_fp16, y = var_3661_to_fp16)[name = tensor("aw_chunk_337_cast_fp16")]; + tensor var_3664_equation_0 = const()[name = tensor("op_3664_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3664_cast_fp16 = einsum(equation = var_3664_equation_0, values = (var_3494_cast_fp16, var_3311_cast_fp16))[name = tensor("op_3664_cast_fp16")]; + tensor var_3665_to_fp16 = const()[name = tensor("op_3665_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_339_cast_fp16 = mul(x = var_3664_cast_fp16, y = var_3665_to_fp16)[name = tensor("aw_chunk_339_cast_fp16")]; + tensor var_3668_equation_0 = const()[name = tensor("op_3668_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3668_cast_fp16 = einsum(equation = var_3668_equation_0, values = (var_3494_cast_fp16, var_3318_cast_fp16))[name = tensor("op_3668_cast_fp16")]; + tensor var_3669_to_fp16 = const()[name = tensor("op_3669_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_341_cast_fp16 = mul(x = var_3668_cast_fp16, y = var_3669_to_fp16)[name = tensor("aw_chunk_341_cast_fp16")]; + tensor var_3672_equation_0 = const()[name = tensor("op_3672_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3672_cast_fp16 = einsum(equation = var_3672_equation_0, values = (var_3494_cast_fp16, var_3325_cast_fp16))[name = tensor("op_3672_cast_fp16")]; + tensor var_3673_to_fp16 = const()[name = tensor("op_3673_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_343_cast_fp16 = mul(x = var_3672_cast_fp16, y = var_3673_to_fp16)[name = tensor("aw_chunk_343_cast_fp16")]; + tensor var_3676_equation_0 = const()[name = tensor("op_3676_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3676_cast_fp16 = einsum(equation = var_3676_equation_0, values = (var_3498_cast_fp16, var_3332_cast_fp16))[name = tensor("op_3676_cast_fp16")]; + tensor var_3677_to_fp16 = const()[name = tensor("op_3677_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_345_cast_fp16 = mul(x = var_3676_cast_fp16, y = var_3677_to_fp16)[name = tensor("aw_chunk_345_cast_fp16")]; + tensor var_3680_equation_0 = const()[name = tensor("op_3680_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3680_cast_fp16 = einsum(equation = var_3680_equation_0, values = (var_3498_cast_fp16, var_3339_cast_fp16))[name = tensor("op_3680_cast_fp16")]; + tensor var_3681_to_fp16 = const()[name = tensor("op_3681_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_347_cast_fp16 = mul(x = var_3680_cast_fp16, y = var_3681_to_fp16)[name = tensor("aw_chunk_347_cast_fp16")]; + tensor var_3684_equation_0 = const()[name = tensor("op_3684_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3684_cast_fp16 = einsum(equation = var_3684_equation_0, values = (var_3498_cast_fp16, var_3346_cast_fp16))[name = tensor("op_3684_cast_fp16")]; + tensor var_3685_to_fp16 = const()[name = tensor("op_3685_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_349_cast_fp16 = mul(x = var_3684_cast_fp16, y = var_3685_to_fp16)[name = tensor("aw_chunk_349_cast_fp16")]; + tensor var_3688_equation_0 = const()[name = tensor("op_3688_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3688_cast_fp16 = einsum(equation = var_3688_equation_0, values = (var_3498_cast_fp16, var_3353_cast_fp16))[name = tensor("op_3688_cast_fp16")]; + tensor var_3689_to_fp16 = const()[name = tensor("op_3689_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_351_cast_fp16 = mul(x = var_3688_cast_fp16, y = var_3689_to_fp16)[name = tensor("aw_chunk_351_cast_fp16")]; + tensor var_3692_equation_0 = const()[name = tensor("op_3692_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3692_cast_fp16 = einsum(equation = var_3692_equation_0, values = (var_3502_cast_fp16, var_3360_cast_fp16))[name = tensor("op_3692_cast_fp16")]; + tensor var_3693_to_fp16 = const()[name = tensor("op_3693_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_353_cast_fp16 = mul(x = var_3692_cast_fp16, y = var_3693_to_fp16)[name = tensor("aw_chunk_353_cast_fp16")]; + tensor var_3696_equation_0 = const()[name = tensor("op_3696_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3696_cast_fp16 = einsum(equation = var_3696_equation_0, values = (var_3502_cast_fp16, var_3367_cast_fp16))[name = tensor("op_3696_cast_fp16")]; + tensor var_3697_to_fp16 = const()[name = tensor("op_3697_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_355_cast_fp16 = mul(x = var_3696_cast_fp16, y = var_3697_to_fp16)[name = tensor("aw_chunk_355_cast_fp16")]; + tensor var_3700_equation_0 = const()[name = tensor("op_3700_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3700_cast_fp16 = einsum(equation = var_3700_equation_0, values = (var_3502_cast_fp16, var_3374_cast_fp16))[name = tensor("op_3700_cast_fp16")]; + tensor var_3701_to_fp16 = const()[name = tensor("op_3701_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_357_cast_fp16 = mul(x = var_3700_cast_fp16, y = var_3701_to_fp16)[name = tensor("aw_chunk_357_cast_fp16")]; + tensor var_3704_equation_0 = const()[name = tensor("op_3704_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3704_cast_fp16 = einsum(equation = var_3704_equation_0, values = (var_3502_cast_fp16, var_3381_cast_fp16))[name = tensor("op_3704_cast_fp16")]; + tensor var_3705_to_fp16 = const()[name = tensor("op_3705_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_359_cast_fp16 = mul(x = var_3704_cast_fp16, y = var_3705_to_fp16)[name = tensor("aw_chunk_359_cast_fp16")]; + tensor var_3708_equation_0 = const()[name = tensor("op_3708_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3708_cast_fp16 = einsum(equation = var_3708_equation_0, values = (var_3506_cast_fp16, var_3388_cast_fp16))[name = tensor("op_3708_cast_fp16")]; + tensor var_3709_to_fp16 = const()[name = tensor("op_3709_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_361_cast_fp16 = mul(x = var_3708_cast_fp16, y = var_3709_to_fp16)[name = tensor("aw_chunk_361_cast_fp16")]; + tensor var_3712_equation_0 = const()[name = tensor("op_3712_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3712_cast_fp16 = einsum(equation = var_3712_equation_0, values = (var_3506_cast_fp16, var_3395_cast_fp16))[name = tensor("op_3712_cast_fp16")]; + tensor var_3713_to_fp16 = const()[name = tensor("op_3713_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_363_cast_fp16 = mul(x = var_3712_cast_fp16, y = var_3713_to_fp16)[name = tensor("aw_chunk_363_cast_fp16")]; + tensor var_3716_equation_0 = const()[name = tensor("op_3716_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3716_cast_fp16 = einsum(equation = var_3716_equation_0, values = (var_3506_cast_fp16, var_3402_cast_fp16))[name = tensor("op_3716_cast_fp16")]; + tensor var_3717_to_fp16 = const()[name = tensor("op_3717_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_365_cast_fp16 = mul(x = var_3716_cast_fp16, y = var_3717_to_fp16)[name = tensor("aw_chunk_365_cast_fp16")]; + tensor var_3720_equation_0 = const()[name = tensor("op_3720_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3720_cast_fp16 = einsum(equation = var_3720_equation_0, values = (var_3506_cast_fp16, var_3409_cast_fp16))[name = tensor("op_3720_cast_fp16")]; + tensor var_3721_to_fp16 = const()[name = tensor("op_3721_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_367_cast_fp16 = mul(x = var_3720_cast_fp16, y = var_3721_to_fp16)[name = tensor("aw_chunk_367_cast_fp16")]; + tensor var_3724_equation_0 = const()[name = tensor("op_3724_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3724_cast_fp16 = einsum(equation = var_3724_equation_0, values = (var_3510_cast_fp16, var_3416_cast_fp16))[name = tensor("op_3724_cast_fp16")]; + tensor var_3725_to_fp16 = const()[name = tensor("op_3725_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_369_cast_fp16 = mul(x = var_3724_cast_fp16, y = var_3725_to_fp16)[name = tensor("aw_chunk_369_cast_fp16")]; + tensor var_3728_equation_0 = const()[name = tensor("op_3728_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3728_cast_fp16 = einsum(equation = var_3728_equation_0, values = (var_3510_cast_fp16, var_3423_cast_fp16))[name = tensor("op_3728_cast_fp16")]; + tensor var_3729_to_fp16 = const()[name = tensor("op_3729_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_371_cast_fp16 = mul(x = var_3728_cast_fp16, y = var_3729_to_fp16)[name = tensor("aw_chunk_371_cast_fp16")]; + tensor var_3732_equation_0 = const()[name = tensor("op_3732_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3732_cast_fp16 = einsum(equation = var_3732_equation_0, values = (var_3510_cast_fp16, var_3430_cast_fp16))[name = tensor("op_3732_cast_fp16")]; + tensor var_3733_to_fp16 = const()[name = tensor("op_3733_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_373_cast_fp16 = mul(x = var_3732_cast_fp16, y = var_3733_to_fp16)[name = tensor("aw_chunk_373_cast_fp16")]; + tensor var_3736_equation_0 = const()[name = tensor("op_3736_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3736_cast_fp16 = einsum(equation = var_3736_equation_0, values = (var_3510_cast_fp16, var_3437_cast_fp16))[name = tensor("op_3736_cast_fp16")]; + tensor var_3737_to_fp16 = const()[name = tensor("op_3737_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_375_cast_fp16 = mul(x = var_3736_cast_fp16, y = var_3737_to_fp16)[name = tensor("aw_chunk_375_cast_fp16")]; + tensor var_3740_equation_0 = const()[name = tensor("op_3740_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3740_cast_fp16 = einsum(equation = var_3740_equation_0, values = (var_3514_cast_fp16, var_3444_cast_fp16))[name = tensor("op_3740_cast_fp16")]; + tensor var_3741_to_fp16 = const()[name = tensor("op_3741_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_377_cast_fp16 = mul(x = var_3740_cast_fp16, y = var_3741_to_fp16)[name = tensor("aw_chunk_377_cast_fp16")]; + tensor var_3744_equation_0 = const()[name = tensor("op_3744_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3744_cast_fp16 = einsum(equation = var_3744_equation_0, values = (var_3514_cast_fp16, var_3451_cast_fp16))[name = tensor("op_3744_cast_fp16")]; + tensor var_3745_to_fp16 = const()[name = tensor("op_3745_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_379_cast_fp16 = mul(x = var_3744_cast_fp16, y = var_3745_to_fp16)[name = tensor("aw_chunk_379_cast_fp16")]; + tensor var_3748_equation_0 = const()[name = tensor("op_3748_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3748_cast_fp16 = einsum(equation = var_3748_equation_0, values = (var_3514_cast_fp16, var_3458_cast_fp16))[name = tensor("op_3748_cast_fp16")]; + tensor var_3749_to_fp16 = const()[name = tensor("op_3749_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_381_cast_fp16 = mul(x = var_3748_cast_fp16, y = var_3749_to_fp16)[name = tensor("aw_chunk_381_cast_fp16")]; + tensor var_3752_equation_0 = const()[name = tensor("op_3752_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_3752_cast_fp16 = einsum(equation = var_3752_equation_0, values = (var_3514_cast_fp16, var_3465_cast_fp16))[name = tensor("op_3752_cast_fp16")]; + tensor var_3753_to_fp16 = const()[name = tensor("op_3753_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_383_cast_fp16 = mul(x = var_3752_cast_fp16, y = var_3753_to_fp16)[name = tensor("aw_chunk_383_cast_fp16")]; + tensor var_3755_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_289_cast_fp16)[name = tensor("op_3755_cast_fp16")]; + tensor var_3756_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_291_cast_fp16)[name = tensor("op_3756_cast_fp16")]; + tensor var_3757_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_293_cast_fp16)[name = tensor("op_3757_cast_fp16")]; + tensor var_3758_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_295_cast_fp16)[name = tensor("op_3758_cast_fp16")]; + tensor var_3759_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_297_cast_fp16)[name = tensor("op_3759_cast_fp16")]; + tensor var_3760_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_299_cast_fp16)[name = tensor("op_3760_cast_fp16")]; + tensor var_3761_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_301_cast_fp16)[name = tensor("op_3761_cast_fp16")]; + tensor var_3762_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_303_cast_fp16)[name = tensor("op_3762_cast_fp16")]; + tensor var_3763_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_305_cast_fp16)[name = tensor("op_3763_cast_fp16")]; + tensor var_3764_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_307_cast_fp16)[name = tensor("op_3764_cast_fp16")]; + tensor var_3765_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_309_cast_fp16)[name = tensor("op_3765_cast_fp16")]; + tensor var_3766_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_311_cast_fp16)[name = tensor("op_3766_cast_fp16")]; + tensor var_3767_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_313_cast_fp16)[name = tensor("op_3767_cast_fp16")]; + tensor var_3768_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_315_cast_fp16)[name = tensor("op_3768_cast_fp16")]; + tensor var_3769_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_317_cast_fp16)[name = tensor("op_3769_cast_fp16")]; + tensor var_3770_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_319_cast_fp16)[name = tensor("op_3770_cast_fp16")]; + tensor var_3771_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_321_cast_fp16)[name = tensor("op_3771_cast_fp16")]; + tensor var_3772_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_323_cast_fp16)[name = tensor("op_3772_cast_fp16")]; + tensor var_3773_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_325_cast_fp16)[name = tensor("op_3773_cast_fp16")]; + tensor var_3774_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_327_cast_fp16)[name = tensor("op_3774_cast_fp16")]; + tensor var_3775_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_329_cast_fp16)[name = tensor("op_3775_cast_fp16")]; + tensor var_3776_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_331_cast_fp16)[name = tensor("op_3776_cast_fp16")]; + tensor var_3777_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_333_cast_fp16)[name = tensor("op_3777_cast_fp16")]; + tensor var_3778_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_335_cast_fp16)[name = tensor("op_3778_cast_fp16")]; + tensor var_3779_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_337_cast_fp16)[name = tensor("op_3779_cast_fp16")]; + tensor var_3780_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_339_cast_fp16)[name = tensor("op_3780_cast_fp16")]; + tensor var_3781_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_341_cast_fp16)[name = tensor("op_3781_cast_fp16")]; + tensor var_3782_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_343_cast_fp16)[name = tensor("op_3782_cast_fp16")]; + tensor var_3783_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_345_cast_fp16)[name = tensor("op_3783_cast_fp16")]; + tensor var_3784_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_347_cast_fp16)[name = tensor("op_3784_cast_fp16")]; + tensor var_3785_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_349_cast_fp16)[name = tensor("op_3785_cast_fp16")]; + tensor var_3786_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_351_cast_fp16)[name = tensor("op_3786_cast_fp16")]; + tensor var_3787_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_353_cast_fp16)[name = tensor("op_3787_cast_fp16")]; + tensor var_3788_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_355_cast_fp16)[name = tensor("op_3788_cast_fp16")]; + tensor var_3789_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_357_cast_fp16)[name = tensor("op_3789_cast_fp16")]; + tensor var_3790_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_359_cast_fp16)[name = tensor("op_3790_cast_fp16")]; + tensor var_3791_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_361_cast_fp16)[name = tensor("op_3791_cast_fp16")]; + tensor var_3792_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_363_cast_fp16)[name = tensor("op_3792_cast_fp16")]; + tensor var_3793_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_365_cast_fp16)[name = tensor("op_3793_cast_fp16")]; + tensor var_3794_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_367_cast_fp16)[name = tensor("op_3794_cast_fp16")]; + tensor var_3795_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_369_cast_fp16)[name = tensor("op_3795_cast_fp16")]; + tensor var_3796_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_371_cast_fp16)[name = tensor("op_3796_cast_fp16")]; + tensor var_3797_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_373_cast_fp16)[name = tensor("op_3797_cast_fp16")]; + tensor var_3798_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_375_cast_fp16)[name = tensor("op_3798_cast_fp16")]; + tensor var_3799_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_377_cast_fp16)[name = tensor("op_3799_cast_fp16")]; + tensor var_3800_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_379_cast_fp16)[name = tensor("op_3800_cast_fp16")]; + tensor var_3801_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_381_cast_fp16)[name = tensor("op_3801_cast_fp16")]; + tensor var_3802_cast_fp16 = softmax(axis = var_3028, x = aw_chunk_383_cast_fp16)[name = tensor("op_3802_cast_fp16")]; + tensor var_3804_equation_0 = const()[name = tensor("op_3804_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3804_cast_fp16 = einsum(equation = var_3804_equation_0, values = (var_3516_cast_fp16, var_3755_cast_fp16))[name = tensor("op_3804_cast_fp16")]; + tensor var_3806_equation_0 = const()[name = tensor("op_3806_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3806_cast_fp16 = einsum(equation = var_3806_equation_0, values = (var_3516_cast_fp16, var_3756_cast_fp16))[name = tensor("op_3806_cast_fp16")]; + tensor var_3808_equation_0 = const()[name = tensor("op_3808_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3808_cast_fp16 = einsum(equation = var_3808_equation_0, values = (var_3516_cast_fp16, var_3757_cast_fp16))[name = tensor("op_3808_cast_fp16")]; + tensor var_3810_equation_0 = const()[name = tensor("op_3810_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3810_cast_fp16 = einsum(equation = var_3810_equation_0, values = (var_3516_cast_fp16, var_3758_cast_fp16))[name = tensor("op_3810_cast_fp16")]; + tensor var_3812_equation_0 = const()[name = tensor("op_3812_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3812_cast_fp16 = einsum(equation = var_3812_equation_0, values = (var_3520_cast_fp16, var_3759_cast_fp16))[name = tensor("op_3812_cast_fp16")]; + tensor var_3814_equation_0 = const()[name = tensor("op_3814_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3814_cast_fp16 = einsum(equation = var_3814_equation_0, values = (var_3520_cast_fp16, var_3760_cast_fp16))[name = tensor("op_3814_cast_fp16")]; + tensor var_3816_equation_0 = const()[name = tensor("op_3816_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3816_cast_fp16 = einsum(equation = var_3816_equation_0, values = (var_3520_cast_fp16, var_3761_cast_fp16))[name = tensor("op_3816_cast_fp16")]; + tensor var_3818_equation_0 = const()[name = tensor("op_3818_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3818_cast_fp16 = einsum(equation = var_3818_equation_0, values = (var_3520_cast_fp16, var_3762_cast_fp16))[name = tensor("op_3818_cast_fp16")]; + tensor var_3820_equation_0 = const()[name = tensor("op_3820_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3820_cast_fp16 = einsum(equation = var_3820_equation_0, values = (var_3524_cast_fp16, var_3763_cast_fp16))[name = tensor("op_3820_cast_fp16")]; + tensor var_3822_equation_0 = const()[name = tensor("op_3822_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3822_cast_fp16 = einsum(equation = var_3822_equation_0, values = (var_3524_cast_fp16, var_3764_cast_fp16))[name = tensor("op_3822_cast_fp16")]; + tensor var_3824_equation_0 = const()[name = tensor("op_3824_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3824_cast_fp16 = einsum(equation = var_3824_equation_0, values = (var_3524_cast_fp16, var_3765_cast_fp16))[name = tensor("op_3824_cast_fp16")]; + tensor var_3826_equation_0 = const()[name = tensor("op_3826_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3826_cast_fp16 = einsum(equation = var_3826_equation_0, values = (var_3524_cast_fp16, var_3766_cast_fp16))[name = tensor("op_3826_cast_fp16")]; + tensor var_3828_equation_0 = const()[name = tensor("op_3828_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3828_cast_fp16 = einsum(equation = var_3828_equation_0, values = (var_3528_cast_fp16, var_3767_cast_fp16))[name = tensor("op_3828_cast_fp16")]; + tensor var_3830_equation_0 = const()[name = tensor("op_3830_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3830_cast_fp16 = einsum(equation = var_3830_equation_0, values = (var_3528_cast_fp16, var_3768_cast_fp16))[name = tensor("op_3830_cast_fp16")]; + tensor var_3832_equation_0 = const()[name = tensor("op_3832_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3832_cast_fp16 = einsum(equation = var_3832_equation_0, values = (var_3528_cast_fp16, var_3769_cast_fp16))[name = tensor("op_3832_cast_fp16")]; + tensor var_3834_equation_0 = const()[name = tensor("op_3834_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3834_cast_fp16 = einsum(equation = var_3834_equation_0, values = (var_3528_cast_fp16, var_3770_cast_fp16))[name = tensor("op_3834_cast_fp16")]; + tensor var_3836_equation_0 = const()[name = tensor("op_3836_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3836_cast_fp16 = einsum(equation = var_3836_equation_0, values = (var_3532_cast_fp16, var_3771_cast_fp16))[name = tensor("op_3836_cast_fp16")]; + tensor var_3838_equation_0 = const()[name = tensor("op_3838_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3838_cast_fp16 = einsum(equation = var_3838_equation_0, values = (var_3532_cast_fp16, var_3772_cast_fp16))[name = tensor("op_3838_cast_fp16")]; + tensor var_3840_equation_0 = const()[name = tensor("op_3840_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3840_cast_fp16 = einsum(equation = var_3840_equation_0, values = (var_3532_cast_fp16, var_3773_cast_fp16))[name = tensor("op_3840_cast_fp16")]; + tensor var_3842_equation_0 = const()[name = tensor("op_3842_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3842_cast_fp16 = einsum(equation = var_3842_equation_0, values = (var_3532_cast_fp16, var_3774_cast_fp16))[name = tensor("op_3842_cast_fp16")]; + tensor var_3844_equation_0 = const()[name = tensor("op_3844_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3844_cast_fp16 = einsum(equation = var_3844_equation_0, values = (var_3536_cast_fp16, var_3775_cast_fp16))[name = tensor("op_3844_cast_fp16")]; + tensor var_3846_equation_0 = const()[name = tensor("op_3846_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3846_cast_fp16 = einsum(equation = var_3846_equation_0, values = (var_3536_cast_fp16, var_3776_cast_fp16))[name = tensor("op_3846_cast_fp16")]; + tensor var_3848_equation_0 = const()[name = tensor("op_3848_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3848_cast_fp16 = einsum(equation = var_3848_equation_0, values = (var_3536_cast_fp16, var_3777_cast_fp16))[name = tensor("op_3848_cast_fp16")]; + tensor var_3850_equation_0 = const()[name = tensor("op_3850_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3850_cast_fp16 = einsum(equation = var_3850_equation_0, values = (var_3536_cast_fp16, var_3778_cast_fp16))[name = tensor("op_3850_cast_fp16")]; + tensor var_3852_equation_0 = const()[name = tensor("op_3852_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3852_cast_fp16 = einsum(equation = var_3852_equation_0, values = (var_3540_cast_fp16, var_3779_cast_fp16))[name = tensor("op_3852_cast_fp16")]; + tensor var_3854_equation_0 = const()[name = tensor("op_3854_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3854_cast_fp16 = einsum(equation = var_3854_equation_0, values = (var_3540_cast_fp16, var_3780_cast_fp16))[name = tensor("op_3854_cast_fp16")]; + tensor var_3856_equation_0 = const()[name = tensor("op_3856_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3856_cast_fp16 = einsum(equation = var_3856_equation_0, values = (var_3540_cast_fp16, var_3781_cast_fp16))[name = tensor("op_3856_cast_fp16")]; + tensor var_3858_equation_0 = const()[name = tensor("op_3858_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3858_cast_fp16 = einsum(equation = var_3858_equation_0, values = (var_3540_cast_fp16, var_3782_cast_fp16))[name = tensor("op_3858_cast_fp16")]; + tensor var_3860_equation_0 = const()[name = tensor("op_3860_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3860_cast_fp16 = einsum(equation = var_3860_equation_0, values = (var_3544_cast_fp16, var_3783_cast_fp16))[name = tensor("op_3860_cast_fp16")]; + tensor var_3862_equation_0 = const()[name = tensor("op_3862_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3862_cast_fp16 = einsum(equation = var_3862_equation_0, values = (var_3544_cast_fp16, var_3784_cast_fp16))[name = tensor("op_3862_cast_fp16")]; + tensor var_3864_equation_0 = const()[name = tensor("op_3864_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3864_cast_fp16 = einsum(equation = var_3864_equation_0, values = (var_3544_cast_fp16, var_3785_cast_fp16))[name = tensor("op_3864_cast_fp16")]; + tensor var_3866_equation_0 = const()[name = tensor("op_3866_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3866_cast_fp16 = einsum(equation = var_3866_equation_0, values = (var_3544_cast_fp16, var_3786_cast_fp16))[name = tensor("op_3866_cast_fp16")]; + tensor var_3868_equation_0 = const()[name = tensor("op_3868_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3868_cast_fp16 = einsum(equation = var_3868_equation_0, values = (var_3548_cast_fp16, var_3787_cast_fp16))[name = tensor("op_3868_cast_fp16")]; + tensor var_3870_equation_0 = const()[name = tensor("op_3870_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3870_cast_fp16 = einsum(equation = var_3870_equation_0, values = (var_3548_cast_fp16, var_3788_cast_fp16))[name = tensor("op_3870_cast_fp16")]; + tensor var_3872_equation_0 = const()[name = tensor("op_3872_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3872_cast_fp16 = einsum(equation = var_3872_equation_0, values = (var_3548_cast_fp16, var_3789_cast_fp16))[name = tensor("op_3872_cast_fp16")]; + tensor var_3874_equation_0 = const()[name = tensor("op_3874_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3874_cast_fp16 = einsum(equation = var_3874_equation_0, values = (var_3548_cast_fp16, var_3790_cast_fp16))[name = tensor("op_3874_cast_fp16")]; + tensor var_3876_equation_0 = const()[name = tensor("op_3876_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3876_cast_fp16 = einsum(equation = var_3876_equation_0, values = (var_3552_cast_fp16, var_3791_cast_fp16))[name = tensor("op_3876_cast_fp16")]; + tensor var_3878_equation_0 = const()[name = tensor("op_3878_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3878_cast_fp16 = einsum(equation = var_3878_equation_0, values = (var_3552_cast_fp16, var_3792_cast_fp16))[name = tensor("op_3878_cast_fp16")]; + tensor var_3880_equation_0 = const()[name = tensor("op_3880_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3880_cast_fp16 = einsum(equation = var_3880_equation_0, values = (var_3552_cast_fp16, var_3793_cast_fp16))[name = tensor("op_3880_cast_fp16")]; + tensor var_3882_equation_0 = const()[name = tensor("op_3882_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3882_cast_fp16 = einsum(equation = var_3882_equation_0, values = (var_3552_cast_fp16, var_3794_cast_fp16))[name = tensor("op_3882_cast_fp16")]; + tensor var_3884_equation_0 = const()[name = tensor("op_3884_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3884_cast_fp16 = einsum(equation = var_3884_equation_0, values = (var_3556_cast_fp16, var_3795_cast_fp16))[name = tensor("op_3884_cast_fp16")]; + tensor var_3886_equation_0 = const()[name = tensor("op_3886_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3886_cast_fp16 = einsum(equation = var_3886_equation_0, values = (var_3556_cast_fp16, var_3796_cast_fp16))[name = tensor("op_3886_cast_fp16")]; + tensor var_3888_equation_0 = const()[name = tensor("op_3888_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3888_cast_fp16 = einsum(equation = var_3888_equation_0, values = (var_3556_cast_fp16, var_3797_cast_fp16))[name = tensor("op_3888_cast_fp16")]; + tensor var_3890_equation_0 = const()[name = tensor("op_3890_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3890_cast_fp16 = einsum(equation = var_3890_equation_0, values = (var_3556_cast_fp16, var_3798_cast_fp16))[name = tensor("op_3890_cast_fp16")]; + tensor var_3892_equation_0 = const()[name = tensor("op_3892_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3892_cast_fp16 = einsum(equation = var_3892_equation_0, values = (var_3560_cast_fp16, var_3799_cast_fp16))[name = tensor("op_3892_cast_fp16")]; + tensor var_3894_equation_0 = const()[name = tensor("op_3894_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3894_cast_fp16 = einsum(equation = var_3894_equation_0, values = (var_3560_cast_fp16, var_3800_cast_fp16))[name = tensor("op_3894_cast_fp16")]; + tensor var_3896_equation_0 = const()[name = tensor("op_3896_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3896_cast_fp16 = einsum(equation = var_3896_equation_0, values = (var_3560_cast_fp16, var_3801_cast_fp16))[name = tensor("op_3896_cast_fp16")]; + tensor var_3898_equation_0 = const()[name = tensor("op_3898_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_3898_cast_fp16 = einsum(equation = var_3898_equation_0, values = (var_3560_cast_fp16, var_3802_cast_fp16))[name = tensor("op_3898_cast_fp16")]; + tensor var_3900_interleave_0 = const()[name = tensor("op_3900_interleave_0"), val = tensor(false)]; + tensor var_3900_cast_fp16 = concat(axis = var_3011, interleave = var_3900_interleave_0, values = (var_3804_cast_fp16, var_3806_cast_fp16, var_3808_cast_fp16, var_3810_cast_fp16))[name = tensor("op_3900_cast_fp16")]; + tensor var_3902_interleave_0 = const()[name = tensor("op_3902_interleave_0"), val = tensor(false)]; + tensor var_3902_cast_fp16 = concat(axis = var_3011, interleave = var_3902_interleave_0, values = (var_3812_cast_fp16, var_3814_cast_fp16, var_3816_cast_fp16, var_3818_cast_fp16))[name = tensor("op_3902_cast_fp16")]; + tensor var_3904_interleave_0 = const()[name = tensor("op_3904_interleave_0"), val = tensor(false)]; + tensor var_3904_cast_fp16 = concat(axis = var_3011, interleave = var_3904_interleave_0, values = (var_3820_cast_fp16, var_3822_cast_fp16, var_3824_cast_fp16, var_3826_cast_fp16))[name = tensor("op_3904_cast_fp16")]; + tensor var_3906_interleave_0 = const()[name = tensor("op_3906_interleave_0"), val = tensor(false)]; + tensor var_3906_cast_fp16 = concat(axis = var_3011, interleave = var_3906_interleave_0, values = (var_3828_cast_fp16, var_3830_cast_fp16, var_3832_cast_fp16, var_3834_cast_fp16))[name = tensor("op_3906_cast_fp16")]; + tensor var_3908_interleave_0 = const()[name = tensor("op_3908_interleave_0"), val = tensor(false)]; + tensor var_3908_cast_fp16 = concat(axis = var_3011, interleave = var_3908_interleave_0, values = (var_3836_cast_fp16, var_3838_cast_fp16, var_3840_cast_fp16, var_3842_cast_fp16))[name = tensor("op_3908_cast_fp16")]; + tensor var_3910_interleave_0 = const()[name = tensor("op_3910_interleave_0"), val = tensor(false)]; + tensor var_3910_cast_fp16 = concat(axis = var_3011, interleave = var_3910_interleave_0, values = (var_3844_cast_fp16, var_3846_cast_fp16, var_3848_cast_fp16, var_3850_cast_fp16))[name = tensor("op_3910_cast_fp16")]; + tensor var_3912_interleave_0 = const()[name = tensor("op_3912_interleave_0"), val = tensor(false)]; + tensor var_3912_cast_fp16 = concat(axis = var_3011, interleave = var_3912_interleave_0, values = (var_3852_cast_fp16, var_3854_cast_fp16, var_3856_cast_fp16, var_3858_cast_fp16))[name = tensor("op_3912_cast_fp16")]; + tensor var_3914_interleave_0 = const()[name = tensor("op_3914_interleave_0"), val = tensor(false)]; + tensor var_3914_cast_fp16 = concat(axis = var_3011, interleave = var_3914_interleave_0, values = (var_3860_cast_fp16, var_3862_cast_fp16, var_3864_cast_fp16, var_3866_cast_fp16))[name = tensor("op_3914_cast_fp16")]; + tensor var_3916_interleave_0 = const()[name = tensor("op_3916_interleave_0"), val = tensor(false)]; + tensor var_3916_cast_fp16 = concat(axis = var_3011, interleave = var_3916_interleave_0, values = (var_3868_cast_fp16, var_3870_cast_fp16, var_3872_cast_fp16, var_3874_cast_fp16))[name = tensor("op_3916_cast_fp16")]; + tensor var_3918_interleave_0 = const()[name = tensor("op_3918_interleave_0"), val = tensor(false)]; + tensor var_3918_cast_fp16 = concat(axis = var_3011, interleave = var_3918_interleave_0, values = (var_3876_cast_fp16, var_3878_cast_fp16, var_3880_cast_fp16, var_3882_cast_fp16))[name = tensor("op_3918_cast_fp16")]; + tensor var_3920_interleave_0 = const()[name = tensor("op_3920_interleave_0"), val = tensor(false)]; + tensor var_3920_cast_fp16 = concat(axis = var_3011, interleave = var_3920_interleave_0, values = (var_3884_cast_fp16, var_3886_cast_fp16, var_3888_cast_fp16, var_3890_cast_fp16))[name = tensor("op_3920_cast_fp16")]; + tensor var_3922_interleave_0 = const()[name = tensor("op_3922_interleave_0"), val = tensor(false)]; + tensor var_3922_cast_fp16 = concat(axis = var_3011, interleave = var_3922_interleave_0, values = (var_3892_cast_fp16, var_3894_cast_fp16, var_3896_cast_fp16, var_3898_cast_fp16))[name = tensor("op_3922_cast_fp16")]; + tensor input_25_interleave_0 = const()[name = tensor("input_25_interleave_0"), val = tensor(false)]; + tensor input_25_cast_fp16 = concat(axis = var_3028, interleave = input_25_interleave_0, values = (var_3900_cast_fp16, var_3902_cast_fp16, var_3904_cast_fp16, var_3906_cast_fp16, var_3908_cast_fp16, var_3910_cast_fp16, var_3912_cast_fp16, var_3914_cast_fp16, var_3916_cast_fp16, var_3918_cast_fp16, var_3920_cast_fp16, var_3922_cast_fp16))[name = tensor("input_25_cast_fp16")]; + tensor var_3927 = const()[name = tensor("op_3927"), val = tensor([1, 1])]; + tensor var_3929 = const()[name = tensor("op_3929"), val = tensor([1, 1])]; + tensor obj_15_pad_type_0 = const()[name = tensor("obj_15_pad_type_0"), val = tensor("custom")]; + tensor obj_15_pad_0 = const()[name = tensor("obj_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52289280)))]; + tensor layers_3_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53468992)))]; + tensor obj_15_cast_fp16 = conv(bias = layers_3_self_attn_o_proj_bias_to_fp16, dilations = var_3929, groups = var_3028, pad = obj_15_pad_0, pad_type = obj_15_pad_type_0, strides = var_3927, weight = layers_3_self_attn_o_proj_weight_to_fp16, x = input_25_cast_fp16)[name = tensor("obj_15_cast_fp16")]; + tensor inputs_15_cast_fp16 = add(x = inputs_13_cast_fp16, y = obj_15_cast_fp16)[name = tensor("inputs_15_cast_fp16")]; + tensor var_3935 = const()[name = tensor("op_3935"), val = tensor([1])]; + tensor channels_mean_15_cast_fp16 = reduce_mean(axes = var_3935, keep_dims = var_3029, x = inputs_15_cast_fp16)[name = tensor("channels_mean_15_cast_fp16")]; + tensor zero_mean_15_cast_fp16 = sub(x = inputs_15_cast_fp16, y = channels_mean_15_cast_fp16)[name = tensor("zero_mean_15_cast_fp16")]; + tensor zero_mean_sq_15_cast_fp16 = mul(x = zero_mean_15_cast_fp16, y = zero_mean_15_cast_fp16)[name = tensor("zero_mean_sq_15_cast_fp16")]; + tensor var_3939 = const()[name = tensor("op_3939"), val = tensor([1])]; + tensor var_3940_cast_fp16 = reduce_mean(axes = var_3939, keep_dims = var_3029, x = zero_mean_sq_15_cast_fp16)[name = tensor("op_3940_cast_fp16")]; + tensor var_3941_to_fp16 = const()[name = tensor("op_3941_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_3942_cast_fp16 = add(x = var_3940_cast_fp16, y = var_3941_to_fp16)[name = tensor("op_3942_cast_fp16")]; + tensor denom_15_epsilon_0_to_fp16 = const()[name = tensor("denom_15_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_15_cast_fp16 = rsqrt(epsilon = denom_15_epsilon_0_to_fp16, x = var_3942_cast_fp16)[name = tensor("denom_15_cast_fp16")]; + tensor out_15_cast_fp16 = mul(x = zero_mean_15_cast_fp16, y = denom_15_cast_fp16)[name = tensor("out_15_cast_fp16")]; + tensor input_27_gamma_0_to_fp16 = const()[name = tensor("input_27_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53470592)))]; + tensor input_27_beta_0_to_fp16 = const()[name = tensor("input_27_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53472192)))]; + tensor input_27_epsilon_0_to_fp16 = const()[name = tensor("input_27_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_27_cast_fp16 = batch_norm(beta = input_27_beta_0_to_fp16, epsilon = input_27_epsilon_0_to_fp16, gamma = input_27_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_15_cast_fp16)[name = tensor("input_27_cast_fp16")]; + tensor var_3953 = const()[name = tensor("op_3953"), val = tensor([1, 1])]; + tensor var_3955 = const()[name = tensor("op_3955"), val = tensor([1, 1])]; + tensor input_29_pad_type_0 = const()[name = tensor("input_29_pad_type_0"), val = tensor("custom")]; + tensor input_29_pad_0 = const()[name = tensor("input_29_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_fc1_weight_to_fp16 = const()[name = tensor("layers_3_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53473792)))]; + tensor layers_3_fc1_bias_to_fp16 = const()[name = tensor("layers_3_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(58192448)))]; + tensor input_29_cast_fp16 = conv(bias = layers_3_fc1_bias_to_fp16, dilations = var_3955, groups = var_3028, pad = input_29_pad_0, pad_type = input_29_pad_type_0, strides = var_3953, weight = layers_3_fc1_weight_to_fp16, x = input_27_cast_fp16)[name = tensor("input_29_cast_fp16")]; + tensor input_31_mode_0 = const()[name = tensor("input_31_mode_0"), val = tensor("EXACT")]; + tensor input_31_cast_fp16 = gelu(mode = input_31_mode_0, x = input_29_cast_fp16)[name = tensor("input_31_cast_fp16")]; + tensor var_3961 = const()[name = tensor("op_3961"), val = tensor([1, 1])]; + tensor var_3963 = const()[name = tensor("op_3963"), val = tensor([1, 1])]; + tensor hidden_states_11_pad_type_0 = const()[name = tensor("hidden_states_11_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_11_pad_0 = const()[name = tensor("hidden_states_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_fc2_weight_to_fp16 = const()[name = tensor("layers_3_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(58198656)))]; + tensor layers_3_fc2_bias_to_fp16 = const()[name = tensor("layers_3_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62917312)))]; + tensor hidden_states_11_cast_fp16 = conv(bias = layers_3_fc2_bias_to_fp16, dilations = var_3963, groups = var_3028, pad = hidden_states_11_pad_0, pad_type = hidden_states_11_pad_type_0, strides = var_3961, weight = layers_3_fc2_weight_to_fp16, x = input_31_cast_fp16)[name = tensor("hidden_states_11_cast_fp16")]; + tensor inputs_17_cast_fp16 = add(x = inputs_15_cast_fp16, y = hidden_states_11_cast_fp16)[name = tensor("inputs_17_cast_fp16")]; + tensor var_3970 = const()[name = tensor("op_3970"), val = tensor(3)]; + tensor var_3987 = const()[name = tensor("op_3987"), val = tensor(1)]; + tensor var_3988 = const()[name = tensor("op_3988"), val = tensor(true)]; + tensor var_3998 = const()[name = tensor("op_3998"), val = tensor([1])]; + tensor channels_mean_17_cast_fp16 = reduce_mean(axes = var_3998, keep_dims = var_3988, x = inputs_17_cast_fp16)[name = tensor("channels_mean_17_cast_fp16")]; + tensor zero_mean_17_cast_fp16 = sub(x = inputs_17_cast_fp16, y = channels_mean_17_cast_fp16)[name = tensor("zero_mean_17_cast_fp16")]; + tensor zero_mean_sq_17_cast_fp16 = mul(x = zero_mean_17_cast_fp16, y = zero_mean_17_cast_fp16)[name = tensor("zero_mean_sq_17_cast_fp16")]; + tensor var_4002 = const()[name = tensor("op_4002"), val = tensor([1])]; + tensor var_4003_cast_fp16 = reduce_mean(axes = var_4002, keep_dims = var_3988, x = zero_mean_sq_17_cast_fp16)[name = tensor("op_4003_cast_fp16")]; + tensor var_4004_to_fp16 = const()[name = tensor("op_4004_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_4005_cast_fp16 = add(x = var_4003_cast_fp16, y = var_4004_to_fp16)[name = tensor("op_4005_cast_fp16")]; + tensor denom_17_epsilon_0_to_fp16 = const()[name = tensor("denom_17_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_17_cast_fp16 = rsqrt(epsilon = denom_17_epsilon_0_to_fp16, x = var_4005_cast_fp16)[name = tensor("denom_17_cast_fp16")]; + tensor out_17_cast_fp16 = mul(x = zero_mean_17_cast_fp16, y = denom_17_cast_fp16)[name = tensor("out_17_cast_fp16")]; + tensor obj_17_gamma_0_to_fp16 = const()[name = tensor("obj_17_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62918912)))]; + tensor obj_17_beta_0_to_fp16 = const()[name = tensor("obj_17_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62920512)))]; + tensor obj_17_epsilon_0_to_fp16 = const()[name = tensor("obj_17_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_17_cast_fp16 = batch_norm(beta = obj_17_beta_0_to_fp16, epsilon = obj_17_epsilon_0_to_fp16, gamma = obj_17_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_17_cast_fp16)[name = tensor("obj_17_cast_fp16")]; + tensor var_4020 = const()[name = tensor("op_4020"), val = tensor([1, 1])]; + tensor var_4022 = const()[name = tensor("op_4022"), val = tensor([1, 1])]; + tensor query_9_pad_type_0 = const()[name = tensor("query_9_pad_type_0"), val = tensor("custom")]; + tensor query_9_pad_0 = const()[name = tensor("query_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62922112)))]; + tensor layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64101824)))]; + tensor query_9_cast_fp16 = conv(bias = layers_4_self_attn_q_proj_bias_to_fp16, dilations = var_4022, groups = var_3987, pad = query_9_pad_0, pad_type = query_9_pad_type_0, strides = var_4020, weight = layers_4_self_attn_q_proj_weight_to_fp16, x = obj_17_cast_fp16)[name = tensor("query_9_cast_fp16")]; + tensor var_4026 = const()[name = tensor("op_4026"), val = tensor([1, 1])]; + tensor var_4028 = const()[name = tensor("op_4028"), val = tensor([1, 1])]; + tensor key_9_pad_type_0 = const()[name = tensor("key_9_pad_type_0"), val = tensor("custom")]; + tensor key_9_pad_0 = const()[name = tensor("key_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64103424)))]; + tensor key_9_cast_fp16 = conv(dilations = var_4028, groups = var_3987, pad = key_9_pad_0, pad_type = key_9_pad_type_0, strides = var_4026, weight = layers_4_self_attn_k_proj_weight_to_fp16, x = obj_17_cast_fp16)[name = tensor("key_9_cast_fp16")]; + tensor var_4033 = const()[name = tensor("op_4033"), val = tensor([1, 1])]; + tensor var_4035 = const()[name = tensor("op_4035"), val = tensor([1, 1])]; + tensor value_9_pad_type_0 = const()[name = tensor("value_9_pad_type_0"), val = tensor("custom")]; + tensor value_9_pad_0 = const()[name = tensor("value_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65283136)))]; + tensor layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66462848)))]; + tensor value_9_cast_fp16 = conv(bias = layers_4_self_attn_v_proj_bias_to_fp16, dilations = var_4035, groups = var_3987, pad = value_9_pad_0, pad_type = value_9_pad_type_0, strides = var_4033, weight = layers_4_self_attn_v_proj_weight_to_fp16, x = obj_17_cast_fp16)[name = tensor("value_9_cast_fp16")]; + tensor var_4042_begin_0 = const()[name = tensor("op_4042_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4042_end_0 = const()[name = tensor("op_4042_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_4042_end_mask_0 = const()[name = tensor("op_4042_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4042_cast_fp16 = slice_by_index(begin = var_4042_begin_0, end = var_4042_end_0, end_mask = var_4042_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_4042_cast_fp16")]; + tensor var_4046_begin_0 = const()[name = tensor("op_4046_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_4046_end_0 = const()[name = tensor("op_4046_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_4046_end_mask_0 = const()[name = tensor("op_4046_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4046_cast_fp16 = slice_by_index(begin = var_4046_begin_0, end = var_4046_end_0, end_mask = var_4046_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_4046_cast_fp16")]; + tensor var_4050_begin_0 = const()[name = tensor("op_4050_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_4050_end_0 = const()[name = tensor("op_4050_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_4050_end_mask_0 = const()[name = tensor("op_4050_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4050_cast_fp16 = slice_by_index(begin = var_4050_begin_0, end = var_4050_end_0, end_mask = var_4050_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_4050_cast_fp16")]; + tensor var_4054_begin_0 = const()[name = tensor("op_4054_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_4054_end_0 = const()[name = tensor("op_4054_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_4054_end_mask_0 = const()[name = tensor("op_4054_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4054_cast_fp16 = slice_by_index(begin = var_4054_begin_0, end = var_4054_end_0, end_mask = var_4054_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_4054_cast_fp16")]; + tensor var_4058_begin_0 = const()[name = tensor("op_4058_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_4058_end_0 = const()[name = tensor("op_4058_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_4058_end_mask_0 = const()[name = tensor("op_4058_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4058_cast_fp16 = slice_by_index(begin = var_4058_begin_0, end = var_4058_end_0, end_mask = var_4058_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_4058_cast_fp16")]; + tensor var_4062_begin_0 = const()[name = tensor("op_4062_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_4062_end_0 = const()[name = tensor("op_4062_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_4062_end_mask_0 = const()[name = tensor("op_4062_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4062_cast_fp16 = slice_by_index(begin = var_4062_begin_0, end = var_4062_end_0, end_mask = var_4062_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_4062_cast_fp16")]; + tensor var_4066_begin_0 = const()[name = tensor("op_4066_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_4066_end_0 = const()[name = tensor("op_4066_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_4066_end_mask_0 = const()[name = tensor("op_4066_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4066_cast_fp16 = slice_by_index(begin = var_4066_begin_0, end = var_4066_end_0, end_mask = var_4066_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_4066_cast_fp16")]; + tensor var_4070_begin_0 = const()[name = tensor("op_4070_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_4070_end_0 = const()[name = tensor("op_4070_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_4070_end_mask_0 = const()[name = tensor("op_4070_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4070_cast_fp16 = slice_by_index(begin = var_4070_begin_0, end = var_4070_end_0, end_mask = var_4070_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_4070_cast_fp16")]; + tensor var_4074_begin_0 = const()[name = tensor("op_4074_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_4074_end_0 = const()[name = tensor("op_4074_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_4074_end_mask_0 = const()[name = tensor("op_4074_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4074_cast_fp16 = slice_by_index(begin = var_4074_begin_0, end = var_4074_end_0, end_mask = var_4074_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_4074_cast_fp16")]; + tensor var_4078_begin_0 = const()[name = tensor("op_4078_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_4078_end_0 = const()[name = tensor("op_4078_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_4078_end_mask_0 = const()[name = tensor("op_4078_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4078_cast_fp16 = slice_by_index(begin = var_4078_begin_0, end = var_4078_end_0, end_mask = var_4078_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_4078_cast_fp16")]; + tensor var_4082_begin_0 = const()[name = tensor("op_4082_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_4082_end_0 = const()[name = tensor("op_4082_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_4082_end_mask_0 = const()[name = tensor("op_4082_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4082_cast_fp16 = slice_by_index(begin = var_4082_begin_0, end = var_4082_end_0, end_mask = var_4082_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_4082_cast_fp16")]; + tensor var_4086_begin_0 = const()[name = tensor("op_4086_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_4086_end_0 = const()[name = tensor("op_4086_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_4086_end_mask_0 = const()[name = tensor("op_4086_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4086_cast_fp16 = slice_by_index(begin = var_4086_begin_0, end = var_4086_end_0, end_mask = var_4086_end_mask_0, x = query_9_cast_fp16)[name = tensor("op_4086_cast_fp16")]; + tensor var_4095_begin_0 = const()[name = tensor("op_4095_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4095_end_0 = const()[name = tensor("op_4095_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_4095_end_mask_0 = const()[name = tensor("op_4095_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4095_cast_fp16 = slice_by_index(begin = var_4095_begin_0, end = var_4095_end_0, end_mask = var_4095_end_mask_0, x = var_4042_cast_fp16)[name = tensor("op_4095_cast_fp16")]; + tensor var_4102_begin_0 = const()[name = tensor("op_4102_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_4102_end_0 = const()[name = tensor("op_4102_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_4102_end_mask_0 = const()[name = tensor("op_4102_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4102_cast_fp16 = slice_by_index(begin = var_4102_begin_0, end = var_4102_end_0, end_mask = var_4102_end_mask_0, x = var_4042_cast_fp16)[name = tensor("op_4102_cast_fp16")]; + tensor var_4109_begin_0 = const()[name = tensor("op_4109_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_4109_end_0 = const()[name = tensor("op_4109_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_4109_end_mask_0 = const()[name = tensor("op_4109_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4109_cast_fp16 = slice_by_index(begin = var_4109_begin_0, end = var_4109_end_0, end_mask = var_4109_end_mask_0, x = var_4042_cast_fp16)[name = tensor("op_4109_cast_fp16")]; + tensor var_4116_begin_0 = const()[name = tensor("op_4116_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_4116_end_0 = const()[name = tensor("op_4116_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_4116_end_mask_0 = const()[name = tensor("op_4116_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4116_cast_fp16 = slice_by_index(begin = var_4116_begin_0, end = var_4116_end_0, end_mask = var_4116_end_mask_0, x = var_4042_cast_fp16)[name = tensor("op_4116_cast_fp16")]; + tensor var_4123_begin_0 = const()[name = tensor("op_4123_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4123_end_0 = const()[name = tensor("op_4123_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_4123_end_mask_0 = const()[name = tensor("op_4123_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4123_cast_fp16 = slice_by_index(begin = var_4123_begin_0, end = var_4123_end_0, end_mask = var_4123_end_mask_0, x = var_4046_cast_fp16)[name = tensor("op_4123_cast_fp16")]; + tensor var_4130_begin_0 = const()[name = tensor("op_4130_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_4130_end_0 = const()[name = tensor("op_4130_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_4130_end_mask_0 = const()[name = tensor("op_4130_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4130_cast_fp16 = slice_by_index(begin = var_4130_begin_0, end = var_4130_end_0, end_mask = var_4130_end_mask_0, x = var_4046_cast_fp16)[name = tensor("op_4130_cast_fp16")]; + tensor var_4137_begin_0 = const()[name = tensor("op_4137_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_4137_end_0 = const()[name = tensor("op_4137_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_4137_end_mask_0 = const()[name = tensor("op_4137_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4137_cast_fp16 = slice_by_index(begin = var_4137_begin_0, end = var_4137_end_0, end_mask = var_4137_end_mask_0, x = var_4046_cast_fp16)[name = tensor("op_4137_cast_fp16")]; + tensor var_4144_begin_0 = const()[name = tensor("op_4144_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_4144_end_0 = const()[name = tensor("op_4144_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_4144_end_mask_0 = const()[name = tensor("op_4144_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4144_cast_fp16 = slice_by_index(begin = var_4144_begin_0, end = var_4144_end_0, end_mask = var_4144_end_mask_0, x = var_4046_cast_fp16)[name = tensor("op_4144_cast_fp16")]; + tensor var_4151_begin_0 = const()[name = tensor("op_4151_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4151_end_0 = const()[name = tensor("op_4151_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_4151_end_mask_0 = const()[name = tensor("op_4151_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4151_cast_fp16 = slice_by_index(begin = var_4151_begin_0, end = var_4151_end_0, end_mask = var_4151_end_mask_0, x = var_4050_cast_fp16)[name = tensor("op_4151_cast_fp16")]; + tensor var_4158_begin_0 = const()[name = tensor("op_4158_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_4158_end_0 = const()[name = tensor("op_4158_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_4158_end_mask_0 = const()[name = tensor("op_4158_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4158_cast_fp16 = slice_by_index(begin = var_4158_begin_0, end = var_4158_end_0, end_mask = var_4158_end_mask_0, x = var_4050_cast_fp16)[name = tensor("op_4158_cast_fp16")]; + tensor var_4165_begin_0 = const()[name = tensor("op_4165_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_4165_end_0 = const()[name = tensor("op_4165_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_4165_end_mask_0 = const()[name = tensor("op_4165_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4165_cast_fp16 = slice_by_index(begin = var_4165_begin_0, end = var_4165_end_0, end_mask = var_4165_end_mask_0, x = var_4050_cast_fp16)[name = tensor("op_4165_cast_fp16")]; + tensor var_4172_begin_0 = const()[name = tensor("op_4172_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_4172_end_0 = const()[name = tensor("op_4172_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_4172_end_mask_0 = const()[name = tensor("op_4172_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4172_cast_fp16 = slice_by_index(begin = var_4172_begin_0, end = var_4172_end_0, end_mask = var_4172_end_mask_0, x = var_4050_cast_fp16)[name = tensor("op_4172_cast_fp16")]; + tensor var_4179_begin_0 = const()[name = tensor("op_4179_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4179_end_0 = const()[name = tensor("op_4179_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_4179_end_mask_0 = const()[name = tensor("op_4179_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4179_cast_fp16 = slice_by_index(begin = var_4179_begin_0, end = var_4179_end_0, end_mask = var_4179_end_mask_0, x = var_4054_cast_fp16)[name = tensor("op_4179_cast_fp16")]; + tensor var_4186_begin_0 = const()[name = tensor("op_4186_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_4186_end_0 = const()[name = tensor("op_4186_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_4186_end_mask_0 = const()[name = tensor("op_4186_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4186_cast_fp16 = slice_by_index(begin = var_4186_begin_0, end = var_4186_end_0, end_mask = var_4186_end_mask_0, x = var_4054_cast_fp16)[name = tensor("op_4186_cast_fp16")]; + tensor var_4193_begin_0 = const()[name = tensor("op_4193_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_4193_end_0 = const()[name = tensor("op_4193_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_4193_end_mask_0 = const()[name = tensor("op_4193_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4193_cast_fp16 = slice_by_index(begin = var_4193_begin_0, end = var_4193_end_0, end_mask = var_4193_end_mask_0, x = var_4054_cast_fp16)[name = tensor("op_4193_cast_fp16")]; + tensor var_4200_begin_0 = const()[name = tensor("op_4200_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_4200_end_0 = const()[name = tensor("op_4200_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_4200_end_mask_0 = const()[name = tensor("op_4200_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4200_cast_fp16 = slice_by_index(begin = var_4200_begin_0, end = var_4200_end_0, end_mask = var_4200_end_mask_0, x = var_4054_cast_fp16)[name = tensor("op_4200_cast_fp16")]; + tensor var_4207_begin_0 = const()[name = tensor("op_4207_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4207_end_0 = const()[name = tensor("op_4207_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_4207_end_mask_0 = const()[name = tensor("op_4207_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4207_cast_fp16 = slice_by_index(begin = var_4207_begin_0, end = var_4207_end_0, end_mask = var_4207_end_mask_0, x = var_4058_cast_fp16)[name = tensor("op_4207_cast_fp16")]; + tensor var_4214_begin_0 = const()[name = tensor("op_4214_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_4214_end_0 = const()[name = tensor("op_4214_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_4214_end_mask_0 = const()[name = tensor("op_4214_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4214_cast_fp16 = slice_by_index(begin = var_4214_begin_0, end = var_4214_end_0, end_mask = var_4214_end_mask_0, x = var_4058_cast_fp16)[name = tensor("op_4214_cast_fp16")]; + tensor var_4221_begin_0 = const()[name = tensor("op_4221_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_4221_end_0 = const()[name = tensor("op_4221_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_4221_end_mask_0 = const()[name = tensor("op_4221_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4221_cast_fp16 = slice_by_index(begin = var_4221_begin_0, end = var_4221_end_0, end_mask = var_4221_end_mask_0, x = var_4058_cast_fp16)[name = tensor("op_4221_cast_fp16")]; + tensor var_4228_begin_0 = const()[name = tensor("op_4228_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_4228_end_0 = const()[name = tensor("op_4228_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_4228_end_mask_0 = const()[name = tensor("op_4228_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4228_cast_fp16 = slice_by_index(begin = var_4228_begin_0, end = var_4228_end_0, end_mask = var_4228_end_mask_0, x = var_4058_cast_fp16)[name = tensor("op_4228_cast_fp16")]; + tensor var_4235_begin_0 = const()[name = tensor("op_4235_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4235_end_0 = const()[name = tensor("op_4235_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_4235_end_mask_0 = const()[name = tensor("op_4235_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4235_cast_fp16 = slice_by_index(begin = var_4235_begin_0, end = var_4235_end_0, end_mask = var_4235_end_mask_0, x = var_4062_cast_fp16)[name = tensor("op_4235_cast_fp16")]; + tensor var_4242_begin_0 = const()[name = tensor("op_4242_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_4242_end_0 = const()[name = tensor("op_4242_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_4242_end_mask_0 = const()[name = tensor("op_4242_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4242_cast_fp16 = slice_by_index(begin = var_4242_begin_0, end = var_4242_end_0, end_mask = var_4242_end_mask_0, x = var_4062_cast_fp16)[name = tensor("op_4242_cast_fp16")]; + tensor var_4249_begin_0 = const()[name = tensor("op_4249_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_4249_end_0 = const()[name = tensor("op_4249_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_4249_end_mask_0 = const()[name = tensor("op_4249_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4249_cast_fp16 = slice_by_index(begin = var_4249_begin_0, end = var_4249_end_0, end_mask = var_4249_end_mask_0, x = var_4062_cast_fp16)[name = tensor("op_4249_cast_fp16")]; + tensor var_4256_begin_0 = const()[name = tensor("op_4256_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_4256_end_0 = const()[name = tensor("op_4256_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_4256_end_mask_0 = const()[name = tensor("op_4256_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4256_cast_fp16 = slice_by_index(begin = var_4256_begin_0, end = var_4256_end_0, end_mask = var_4256_end_mask_0, x = var_4062_cast_fp16)[name = tensor("op_4256_cast_fp16")]; + tensor var_4263_begin_0 = const()[name = tensor("op_4263_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4263_end_0 = const()[name = tensor("op_4263_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_4263_end_mask_0 = const()[name = tensor("op_4263_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4263_cast_fp16 = slice_by_index(begin = var_4263_begin_0, end = var_4263_end_0, end_mask = var_4263_end_mask_0, x = var_4066_cast_fp16)[name = tensor("op_4263_cast_fp16")]; + tensor var_4270_begin_0 = const()[name = tensor("op_4270_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_4270_end_0 = const()[name = tensor("op_4270_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_4270_end_mask_0 = const()[name = tensor("op_4270_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4270_cast_fp16 = slice_by_index(begin = var_4270_begin_0, end = var_4270_end_0, end_mask = var_4270_end_mask_0, x = var_4066_cast_fp16)[name = tensor("op_4270_cast_fp16")]; + tensor var_4277_begin_0 = const()[name = tensor("op_4277_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_4277_end_0 = const()[name = tensor("op_4277_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_4277_end_mask_0 = const()[name = tensor("op_4277_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4277_cast_fp16 = slice_by_index(begin = var_4277_begin_0, end = var_4277_end_0, end_mask = var_4277_end_mask_0, x = var_4066_cast_fp16)[name = tensor("op_4277_cast_fp16")]; + tensor var_4284_begin_0 = const()[name = tensor("op_4284_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_4284_end_0 = const()[name = tensor("op_4284_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_4284_end_mask_0 = const()[name = tensor("op_4284_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4284_cast_fp16 = slice_by_index(begin = var_4284_begin_0, end = var_4284_end_0, end_mask = var_4284_end_mask_0, x = var_4066_cast_fp16)[name = tensor("op_4284_cast_fp16")]; + tensor var_4291_begin_0 = const()[name = tensor("op_4291_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4291_end_0 = const()[name = tensor("op_4291_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_4291_end_mask_0 = const()[name = tensor("op_4291_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4291_cast_fp16 = slice_by_index(begin = var_4291_begin_0, end = var_4291_end_0, end_mask = var_4291_end_mask_0, x = var_4070_cast_fp16)[name = tensor("op_4291_cast_fp16")]; + tensor var_4298_begin_0 = const()[name = tensor("op_4298_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_4298_end_0 = const()[name = tensor("op_4298_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_4298_end_mask_0 = const()[name = tensor("op_4298_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4298_cast_fp16 = slice_by_index(begin = var_4298_begin_0, end = var_4298_end_0, end_mask = var_4298_end_mask_0, x = var_4070_cast_fp16)[name = tensor("op_4298_cast_fp16")]; + tensor var_4305_begin_0 = const()[name = tensor("op_4305_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_4305_end_0 = const()[name = tensor("op_4305_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_4305_end_mask_0 = const()[name = tensor("op_4305_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4305_cast_fp16 = slice_by_index(begin = var_4305_begin_0, end = var_4305_end_0, end_mask = var_4305_end_mask_0, x = var_4070_cast_fp16)[name = tensor("op_4305_cast_fp16")]; + tensor var_4312_begin_0 = const()[name = tensor("op_4312_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_4312_end_0 = const()[name = tensor("op_4312_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_4312_end_mask_0 = const()[name = tensor("op_4312_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4312_cast_fp16 = slice_by_index(begin = var_4312_begin_0, end = var_4312_end_0, end_mask = var_4312_end_mask_0, x = var_4070_cast_fp16)[name = tensor("op_4312_cast_fp16")]; + tensor var_4319_begin_0 = const()[name = tensor("op_4319_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4319_end_0 = const()[name = tensor("op_4319_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_4319_end_mask_0 = const()[name = tensor("op_4319_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4319_cast_fp16 = slice_by_index(begin = var_4319_begin_0, end = var_4319_end_0, end_mask = var_4319_end_mask_0, x = var_4074_cast_fp16)[name = tensor("op_4319_cast_fp16")]; + tensor var_4326_begin_0 = const()[name = tensor("op_4326_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_4326_end_0 = const()[name = tensor("op_4326_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_4326_end_mask_0 = const()[name = tensor("op_4326_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4326_cast_fp16 = slice_by_index(begin = var_4326_begin_0, end = var_4326_end_0, end_mask = var_4326_end_mask_0, x = var_4074_cast_fp16)[name = tensor("op_4326_cast_fp16")]; + tensor var_4333_begin_0 = const()[name = tensor("op_4333_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_4333_end_0 = const()[name = tensor("op_4333_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_4333_end_mask_0 = const()[name = tensor("op_4333_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4333_cast_fp16 = slice_by_index(begin = var_4333_begin_0, end = var_4333_end_0, end_mask = var_4333_end_mask_0, x = var_4074_cast_fp16)[name = tensor("op_4333_cast_fp16")]; + tensor var_4340_begin_0 = const()[name = tensor("op_4340_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_4340_end_0 = const()[name = tensor("op_4340_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_4340_end_mask_0 = const()[name = tensor("op_4340_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4340_cast_fp16 = slice_by_index(begin = var_4340_begin_0, end = var_4340_end_0, end_mask = var_4340_end_mask_0, x = var_4074_cast_fp16)[name = tensor("op_4340_cast_fp16")]; + tensor var_4347_begin_0 = const()[name = tensor("op_4347_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4347_end_0 = const()[name = tensor("op_4347_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_4347_end_mask_0 = const()[name = tensor("op_4347_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4347_cast_fp16 = slice_by_index(begin = var_4347_begin_0, end = var_4347_end_0, end_mask = var_4347_end_mask_0, x = var_4078_cast_fp16)[name = tensor("op_4347_cast_fp16")]; + tensor var_4354_begin_0 = const()[name = tensor("op_4354_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_4354_end_0 = const()[name = tensor("op_4354_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_4354_end_mask_0 = const()[name = tensor("op_4354_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4354_cast_fp16 = slice_by_index(begin = var_4354_begin_0, end = var_4354_end_0, end_mask = var_4354_end_mask_0, x = var_4078_cast_fp16)[name = tensor("op_4354_cast_fp16")]; + tensor var_4361_begin_0 = const()[name = tensor("op_4361_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_4361_end_0 = const()[name = tensor("op_4361_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_4361_end_mask_0 = const()[name = tensor("op_4361_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4361_cast_fp16 = slice_by_index(begin = var_4361_begin_0, end = var_4361_end_0, end_mask = var_4361_end_mask_0, x = var_4078_cast_fp16)[name = tensor("op_4361_cast_fp16")]; + tensor var_4368_begin_0 = const()[name = tensor("op_4368_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_4368_end_0 = const()[name = tensor("op_4368_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_4368_end_mask_0 = const()[name = tensor("op_4368_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4368_cast_fp16 = slice_by_index(begin = var_4368_begin_0, end = var_4368_end_0, end_mask = var_4368_end_mask_0, x = var_4078_cast_fp16)[name = tensor("op_4368_cast_fp16")]; + tensor var_4375_begin_0 = const()[name = tensor("op_4375_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4375_end_0 = const()[name = tensor("op_4375_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_4375_end_mask_0 = const()[name = tensor("op_4375_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4375_cast_fp16 = slice_by_index(begin = var_4375_begin_0, end = var_4375_end_0, end_mask = var_4375_end_mask_0, x = var_4082_cast_fp16)[name = tensor("op_4375_cast_fp16")]; + tensor var_4382_begin_0 = const()[name = tensor("op_4382_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_4382_end_0 = const()[name = tensor("op_4382_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_4382_end_mask_0 = const()[name = tensor("op_4382_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4382_cast_fp16 = slice_by_index(begin = var_4382_begin_0, end = var_4382_end_0, end_mask = var_4382_end_mask_0, x = var_4082_cast_fp16)[name = tensor("op_4382_cast_fp16")]; + tensor var_4389_begin_0 = const()[name = tensor("op_4389_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_4389_end_0 = const()[name = tensor("op_4389_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_4389_end_mask_0 = const()[name = tensor("op_4389_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4389_cast_fp16 = slice_by_index(begin = var_4389_begin_0, end = var_4389_end_0, end_mask = var_4389_end_mask_0, x = var_4082_cast_fp16)[name = tensor("op_4389_cast_fp16")]; + tensor var_4396_begin_0 = const()[name = tensor("op_4396_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_4396_end_0 = const()[name = tensor("op_4396_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_4396_end_mask_0 = const()[name = tensor("op_4396_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4396_cast_fp16 = slice_by_index(begin = var_4396_begin_0, end = var_4396_end_0, end_mask = var_4396_end_mask_0, x = var_4082_cast_fp16)[name = tensor("op_4396_cast_fp16")]; + tensor var_4403_begin_0 = const()[name = tensor("op_4403_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4403_end_0 = const()[name = tensor("op_4403_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_4403_end_mask_0 = const()[name = tensor("op_4403_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4403_cast_fp16 = slice_by_index(begin = var_4403_begin_0, end = var_4403_end_0, end_mask = var_4403_end_mask_0, x = var_4086_cast_fp16)[name = tensor("op_4403_cast_fp16")]; + tensor var_4410_begin_0 = const()[name = tensor("op_4410_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_4410_end_0 = const()[name = tensor("op_4410_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_4410_end_mask_0 = const()[name = tensor("op_4410_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4410_cast_fp16 = slice_by_index(begin = var_4410_begin_0, end = var_4410_end_0, end_mask = var_4410_end_mask_0, x = var_4086_cast_fp16)[name = tensor("op_4410_cast_fp16")]; + tensor var_4417_begin_0 = const()[name = tensor("op_4417_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_4417_end_0 = const()[name = tensor("op_4417_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_4417_end_mask_0 = const()[name = tensor("op_4417_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4417_cast_fp16 = slice_by_index(begin = var_4417_begin_0, end = var_4417_end_0, end_mask = var_4417_end_mask_0, x = var_4086_cast_fp16)[name = tensor("op_4417_cast_fp16")]; + tensor var_4424_begin_0 = const()[name = tensor("op_4424_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_4424_end_0 = const()[name = tensor("op_4424_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_4424_end_mask_0 = const()[name = tensor("op_4424_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4424_cast_fp16 = slice_by_index(begin = var_4424_begin_0, end = var_4424_end_0, end_mask = var_4424_end_mask_0, x = var_4086_cast_fp16)[name = tensor("op_4424_cast_fp16")]; + tensor k_9_perm_0 = const()[name = tensor("k_9_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_4429_begin_0 = const()[name = tensor("op_4429_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4429_end_0 = const()[name = tensor("op_4429_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_4429_end_mask_0 = const()[name = tensor("op_4429_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_7 = transpose(perm = k_9_perm_0, x = key_9_cast_fp16)[name = tensor("transpose_7")]; + tensor var_4429_cast_fp16 = slice_by_index(begin = var_4429_begin_0, end = var_4429_end_0, end_mask = var_4429_end_mask_0, x = transpose_7)[name = tensor("op_4429_cast_fp16")]; + tensor var_4433_begin_0 = const()[name = tensor("op_4433_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_4433_end_0 = const()[name = tensor("op_4433_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_4433_end_mask_0 = const()[name = tensor("op_4433_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4433_cast_fp16 = slice_by_index(begin = var_4433_begin_0, end = var_4433_end_0, end_mask = var_4433_end_mask_0, x = transpose_7)[name = tensor("op_4433_cast_fp16")]; + tensor var_4437_begin_0 = const()[name = tensor("op_4437_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_4437_end_0 = const()[name = tensor("op_4437_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_4437_end_mask_0 = const()[name = tensor("op_4437_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4437_cast_fp16 = slice_by_index(begin = var_4437_begin_0, end = var_4437_end_0, end_mask = var_4437_end_mask_0, x = transpose_7)[name = tensor("op_4437_cast_fp16")]; + tensor var_4441_begin_0 = const()[name = tensor("op_4441_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_4441_end_0 = const()[name = tensor("op_4441_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_4441_end_mask_0 = const()[name = tensor("op_4441_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4441_cast_fp16 = slice_by_index(begin = var_4441_begin_0, end = var_4441_end_0, end_mask = var_4441_end_mask_0, x = transpose_7)[name = tensor("op_4441_cast_fp16")]; + tensor var_4445_begin_0 = const()[name = tensor("op_4445_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_4445_end_0 = const()[name = tensor("op_4445_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_4445_end_mask_0 = const()[name = tensor("op_4445_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4445_cast_fp16 = slice_by_index(begin = var_4445_begin_0, end = var_4445_end_0, end_mask = var_4445_end_mask_0, x = transpose_7)[name = tensor("op_4445_cast_fp16")]; + tensor var_4449_begin_0 = const()[name = tensor("op_4449_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_4449_end_0 = const()[name = tensor("op_4449_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_4449_end_mask_0 = const()[name = tensor("op_4449_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4449_cast_fp16 = slice_by_index(begin = var_4449_begin_0, end = var_4449_end_0, end_mask = var_4449_end_mask_0, x = transpose_7)[name = tensor("op_4449_cast_fp16")]; + tensor var_4453_begin_0 = const()[name = tensor("op_4453_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_4453_end_0 = const()[name = tensor("op_4453_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_4453_end_mask_0 = const()[name = tensor("op_4453_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4453_cast_fp16 = slice_by_index(begin = var_4453_begin_0, end = var_4453_end_0, end_mask = var_4453_end_mask_0, x = transpose_7)[name = tensor("op_4453_cast_fp16")]; + tensor var_4457_begin_0 = const()[name = tensor("op_4457_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_4457_end_0 = const()[name = tensor("op_4457_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_4457_end_mask_0 = const()[name = tensor("op_4457_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4457_cast_fp16 = slice_by_index(begin = var_4457_begin_0, end = var_4457_end_0, end_mask = var_4457_end_mask_0, x = transpose_7)[name = tensor("op_4457_cast_fp16")]; + tensor var_4461_begin_0 = const()[name = tensor("op_4461_begin_0"), val = tensor([0, 0, 0, 512])]; + tensor var_4461_end_0 = const()[name = tensor("op_4461_end_0"), val = tensor([1, 1500, 1, 576])]; + tensor var_4461_end_mask_0 = const()[name = tensor("op_4461_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4461_cast_fp16 = slice_by_index(begin = var_4461_begin_0, end = var_4461_end_0, end_mask = var_4461_end_mask_0, x = transpose_7)[name = tensor("op_4461_cast_fp16")]; + tensor var_4465_begin_0 = const()[name = tensor("op_4465_begin_0"), val = tensor([0, 0, 0, 576])]; + tensor var_4465_end_0 = const()[name = tensor("op_4465_end_0"), val = tensor([1, 1500, 1, 640])]; + tensor var_4465_end_mask_0 = const()[name = tensor("op_4465_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4465_cast_fp16 = slice_by_index(begin = var_4465_begin_0, end = var_4465_end_0, end_mask = var_4465_end_mask_0, x = transpose_7)[name = tensor("op_4465_cast_fp16")]; + tensor var_4469_begin_0 = const()[name = tensor("op_4469_begin_0"), val = tensor([0, 0, 0, 640])]; + tensor var_4469_end_0 = const()[name = tensor("op_4469_end_0"), val = tensor([1, 1500, 1, 704])]; + tensor var_4469_end_mask_0 = const()[name = tensor("op_4469_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4469_cast_fp16 = slice_by_index(begin = var_4469_begin_0, end = var_4469_end_0, end_mask = var_4469_end_mask_0, x = transpose_7)[name = tensor("op_4469_cast_fp16")]; + tensor var_4473_begin_0 = const()[name = tensor("op_4473_begin_0"), val = tensor([0, 0, 0, 704])]; + tensor var_4473_end_0 = const()[name = tensor("op_4473_end_0"), val = tensor([1, 1500, 1, 768])]; + tensor var_4473_end_mask_0 = const()[name = tensor("op_4473_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_4473_cast_fp16 = slice_by_index(begin = var_4473_begin_0, end = var_4473_end_0, end_mask = var_4473_end_mask_0, x = transpose_7)[name = tensor("op_4473_cast_fp16")]; + tensor var_4475_begin_0 = const()[name = tensor("op_4475_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_4475_end_0 = const()[name = tensor("op_4475_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_4475_end_mask_0 = const()[name = tensor("op_4475_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4475_cast_fp16 = slice_by_index(begin = var_4475_begin_0, end = var_4475_end_0, end_mask = var_4475_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_4475_cast_fp16")]; + tensor var_4479_begin_0 = const()[name = tensor("op_4479_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_4479_end_0 = const()[name = tensor("op_4479_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_4479_end_mask_0 = const()[name = tensor("op_4479_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4479_cast_fp16 = slice_by_index(begin = var_4479_begin_0, end = var_4479_end_0, end_mask = var_4479_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_4479_cast_fp16")]; + tensor var_4483_begin_0 = const()[name = tensor("op_4483_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_4483_end_0 = const()[name = tensor("op_4483_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_4483_end_mask_0 = const()[name = tensor("op_4483_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4483_cast_fp16 = slice_by_index(begin = var_4483_begin_0, end = var_4483_end_0, end_mask = var_4483_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_4483_cast_fp16")]; + tensor var_4487_begin_0 = const()[name = tensor("op_4487_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_4487_end_0 = const()[name = tensor("op_4487_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_4487_end_mask_0 = const()[name = tensor("op_4487_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4487_cast_fp16 = slice_by_index(begin = var_4487_begin_0, end = var_4487_end_0, end_mask = var_4487_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_4487_cast_fp16")]; + tensor var_4491_begin_0 = const()[name = tensor("op_4491_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_4491_end_0 = const()[name = tensor("op_4491_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_4491_end_mask_0 = const()[name = tensor("op_4491_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4491_cast_fp16 = slice_by_index(begin = var_4491_begin_0, end = var_4491_end_0, end_mask = var_4491_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_4491_cast_fp16")]; + tensor var_4495_begin_0 = const()[name = tensor("op_4495_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_4495_end_0 = const()[name = tensor("op_4495_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_4495_end_mask_0 = const()[name = tensor("op_4495_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4495_cast_fp16 = slice_by_index(begin = var_4495_begin_0, end = var_4495_end_0, end_mask = var_4495_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_4495_cast_fp16")]; + tensor var_4499_begin_0 = const()[name = tensor("op_4499_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_4499_end_0 = const()[name = tensor("op_4499_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_4499_end_mask_0 = const()[name = tensor("op_4499_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4499_cast_fp16 = slice_by_index(begin = var_4499_begin_0, end = var_4499_end_0, end_mask = var_4499_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_4499_cast_fp16")]; + tensor var_4503_begin_0 = const()[name = tensor("op_4503_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_4503_end_0 = const()[name = tensor("op_4503_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_4503_end_mask_0 = const()[name = tensor("op_4503_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4503_cast_fp16 = slice_by_index(begin = var_4503_begin_0, end = var_4503_end_0, end_mask = var_4503_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_4503_cast_fp16")]; + tensor var_4507_begin_0 = const()[name = tensor("op_4507_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_4507_end_0 = const()[name = tensor("op_4507_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_4507_end_mask_0 = const()[name = tensor("op_4507_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4507_cast_fp16 = slice_by_index(begin = var_4507_begin_0, end = var_4507_end_0, end_mask = var_4507_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_4507_cast_fp16")]; + tensor var_4511_begin_0 = const()[name = tensor("op_4511_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_4511_end_0 = const()[name = tensor("op_4511_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_4511_end_mask_0 = const()[name = tensor("op_4511_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4511_cast_fp16 = slice_by_index(begin = var_4511_begin_0, end = var_4511_end_0, end_mask = var_4511_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_4511_cast_fp16")]; + tensor var_4515_begin_0 = const()[name = tensor("op_4515_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_4515_end_0 = const()[name = tensor("op_4515_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_4515_end_mask_0 = const()[name = tensor("op_4515_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4515_cast_fp16 = slice_by_index(begin = var_4515_begin_0, end = var_4515_end_0, end_mask = var_4515_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_4515_cast_fp16")]; + tensor var_4519_begin_0 = const()[name = tensor("op_4519_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_4519_end_0 = const()[name = tensor("op_4519_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_4519_end_mask_0 = const()[name = tensor("op_4519_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_4519_cast_fp16 = slice_by_index(begin = var_4519_begin_0, end = var_4519_end_0, end_mask = var_4519_end_mask_0, x = value_9_cast_fp16)[name = tensor("op_4519_cast_fp16")]; + tensor var_4523_equation_0 = const()[name = tensor("op_4523_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4523_cast_fp16 = einsum(equation = var_4523_equation_0, values = (var_4429_cast_fp16, var_4095_cast_fp16))[name = tensor("op_4523_cast_fp16")]; + tensor var_4524_to_fp16 = const()[name = tensor("op_4524_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_385_cast_fp16 = mul(x = var_4523_cast_fp16, y = var_4524_to_fp16)[name = tensor("aw_chunk_385_cast_fp16")]; + tensor var_4527_equation_0 = const()[name = tensor("op_4527_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4527_cast_fp16 = einsum(equation = var_4527_equation_0, values = (var_4429_cast_fp16, var_4102_cast_fp16))[name = tensor("op_4527_cast_fp16")]; + tensor var_4528_to_fp16 = const()[name = tensor("op_4528_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_387_cast_fp16 = mul(x = var_4527_cast_fp16, y = var_4528_to_fp16)[name = tensor("aw_chunk_387_cast_fp16")]; + tensor var_4531_equation_0 = const()[name = tensor("op_4531_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4531_cast_fp16 = einsum(equation = var_4531_equation_0, values = (var_4429_cast_fp16, var_4109_cast_fp16))[name = tensor("op_4531_cast_fp16")]; + tensor var_4532_to_fp16 = const()[name = tensor("op_4532_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_389_cast_fp16 = mul(x = var_4531_cast_fp16, y = var_4532_to_fp16)[name = tensor("aw_chunk_389_cast_fp16")]; + tensor var_4535_equation_0 = const()[name = tensor("op_4535_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4535_cast_fp16 = einsum(equation = var_4535_equation_0, values = (var_4429_cast_fp16, var_4116_cast_fp16))[name = tensor("op_4535_cast_fp16")]; + tensor var_4536_to_fp16 = const()[name = tensor("op_4536_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_391_cast_fp16 = mul(x = var_4535_cast_fp16, y = var_4536_to_fp16)[name = tensor("aw_chunk_391_cast_fp16")]; + tensor var_4539_equation_0 = const()[name = tensor("op_4539_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4539_cast_fp16 = einsum(equation = var_4539_equation_0, values = (var_4433_cast_fp16, var_4123_cast_fp16))[name = tensor("op_4539_cast_fp16")]; + tensor var_4540_to_fp16 = const()[name = tensor("op_4540_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_393_cast_fp16 = mul(x = var_4539_cast_fp16, y = var_4540_to_fp16)[name = tensor("aw_chunk_393_cast_fp16")]; + tensor var_4543_equation_0 = const()[name = tensor("op_4543_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4543_cast_fp16 = einsum(equation = var_4543_equation_0, values = (var_4433_cast_fp16, var_4130_cast_fp16))[name = tensor("op_4543_cast_fp16")]; + tensor var_4544_to_fp16 = const()[name = tensor("op_4544_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_395_cast_fp16 = mul(x = var_4543_cast_fp16, y = var_4544_to_fp16)[name = tensor("aw_chunk_395_cast_fp16")]; + tensor var_4547_equation_0 = const()[name = tensor("op_4547_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4547_cast_fp16 = einsum(equation = var_4547_equation_0, values = (var_4433_cast_fp16, var_4137_cast_fp16))[name = tensor("op_4547_cast_fp16")]; + tensor var_4548_to_fp16 = const()[name = tensor("op_4548_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_397_cast_fp16 = mul(x = var_4547_cast_fp16, y = var_4548_to_fp16)[name = tensor("aw_chunk_397_cast_fp16")]; + tensor var_4551_equation_0 = const()[name = tensor("op_4551_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4551_cast_fp16 = einsum(equation = var_4551_equation_0, values = (var_4433_cast_fp16, var_4144_cast_fp16))[name = tensor("op_4551_cast_fp16")]; + tensor var_4552_to_fp16 = const()[name = tensor("op_4552_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_399_cast_fp16 = mul(x = var_4551_cast_fp16, y = var_4552_to_fp16)[name = tensor("aw_chunk_399_cast_fp16")]; + tensor var_4555_equation_0 = const()[name = tensor("op_4555_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4555_cast_fp16 = einsum(equation = var_4555_equation_0, values = (var_4437_cast_fp16, var_4151_cast_fp16))[name = tensor("op_4555_cast_fp16")]; + tensor var_4556_to_fp16 = const()[name = tensor("op_4556_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_401_cast_fp16 = mul(x = var_4555_cast_fp16, y = var_4556_to_fp16)[name = tensor("aw_chunk_401_cast_fp16")]; + tensor var_4559_equation_0 = const()[name = tensor("op_4559_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4559_cast_fp16 = einsum(equation = var_4559_equation_0, values = (var_4437_cast_fp16, var_4158_cast_fp16))[name = tensor("op_4559_cast_fp16")]; + tensor var_4560_to_fp16 = const()[name = tensor("op_4560_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_403_cast_fp16 = mul(x = var_4559_cast_fp16, y = var_4560_to_fp16)[name = tensor("aw_chunk_403_cast_fp16")]; + tensor var_4563_equation_0 = const()[name = tensor("op_4563_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4563_cast_fp16 = einsum(equation = var_4563_equation_0, values = (var_4437_cast_fp16, var_4165_cast_fp16))[name = tensor("op_4563_cast_fp16")]; + tensor var_4564_to_fp16 = const()[name = tensor("op_4564_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_405_cast_fp16 = mul(x = var_4563_cast_fp16, y = var_4564_to_fp16)[name = tensor("aw_chunk_405_cast_fp16")]; + tensor var_4567_equation_0 = const()[name = tensor("op_4567_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4567_cast_fp16 = einsum(equation = var_4567_equation_0, values = (var_4437_cast_fp16, var_4172_cast_fp16))[name = tensor("op_4567_cast_fp16")]; + tensor var_4568_to_fp16 = const()[name = tensor("op_4568_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_407_cast_fp16 = mul(x = var_4567_cast_fp16, y = var_4568_to_fp16)[name = tensor("aw_chunk_407_cast_fp16")]; + tensor var_4571_equation_0 = const()[name = tensor("op_4571_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4571_cast_fp16 = einsum(equation = var_4571_equation_0, values = (var_4441_cast_fp16, var_4179_cast_fp16))[name = tensor("op_4571_cast_fp16")]; + tensor var_4572_to_fp16 = const()[name = tensor("op_4572_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_409_cast_fp16 = mul(x = var_4571_cast_fp16, y = var_4572_to_fp16)[name = tensor("aw_chunk_409_cast_fp16")]; + tensor var_4575_equation_0 = const()[name = tensor("op_4575_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4575_cast_fp16 = einsum(equation = var_4575_equation_0, values = (var_4441_cast_fp16, var_4186_cast_fp16))[name = tensor("op_4575_cast_fp16")]; + tensor var_4576_to_fp16 = const()[name = tensor("op_4576_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_411_cast_fp16 = mul(x = var_4575_cast_fp16, y = var_4576_to_fp16)[name = tensor("aw_chunk_411_cast_fp16")]; + tensor var_4579_equation_0 = const()[name = tensor("op_4579_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4579_cast_fp16 = einsum(equation = var_4579_equation_0, values = (var_4441_cast_fp16, var_4193_cast_fp16))[name = tensor("op_4579_cast_fp16")]; + tensor var_4580_to_fp16 = const()[name = tensor("op_4580_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_413_cast_fp16 = mul(x = var_4579_cast_fp16, y = var_4580_to_fp16)[name = tensor("aw_chunk_413_cast_fp16")]; + tensor var_4583_equation_0 = const()[name = tensor("op_4583_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4583_cast_fp16 = einsum(equation = var_4583_equation_0, values = (var_4441_cast_fp16, var_4200_cast_fp16))[name = tensor("op_4583_cast_fp16")]; + tensor var_4584_to_fp16 = const()[name = tensor("op_4584_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_415_cast_fp16 = mul(x = var_4583_cast_fp16, y = var_4584_to_fp16)[name = tensor("aw_chunk_415_cast_fp16")]; + tensor var_4587_equation_0 = const()[name = tensor("op_4587_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4587_cast_fp16 = einsum(equation = var_4587_equation_0, values = (var_4445_cast_fp16, var_4207_cast_fp16))[name = tensor("op_4587_cast_fp16")]; + tensor var_4588_to_fp16 = const()[name = tensor("op_4588_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_417_cast_fp16 = mul(x = var_4587_cast_fp16, y = var_4588_to_fp16)[name = tensor("aw_chunk_417_cast_fp16")]; + tensor var_4591_equation_0 = const()[name = tensor("op_4591_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4591_cast_fp16 = einsum(equation = var_4591_equation_0, values = (var_4445_cast_fp16, var_4214_cast_fp16))[name = tensor("op_4591_cast_fp16")]; + tensor var_4592_to_fp16 = const()[name = tensor("op_4592_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_419_cast_fp16 = mul(x = var_4591_cast_fp16, y = var_4592_to_fp16)[name = tensor("aw_chunk_419_cast_fp16")]; + tensor var_4595_equation_0 = const()[name = tensor("op_4595_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4595_cast_fp16 = einsum(equation = var_4595_equation_0, values = (var_4445_cast_fp16, var_4221_cast_fp16))[name = tensor("op_4595_cast_fp16")]; + tensor var_4596_to_fp16 = const()[name = tensor("op_4596_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_421_cast_fp16 = mul(x = var_4595_cast_fp16, y = var_4596_to_fp16)[name = tensor("aw_chunk_421_cast_fp16")]; + tensor var_4599_equation_0 = const()[name = tensor("op_4599_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4599_cast_fp16 = einsum(equation = var_4599_equation_0, values = (var_4445_cast_fp16, var_4228_cast_fp16))[name = tensor("op_4599_cast_fp16")]; + tensor var_4600_to_fp16 = const()[name = tensor("op_4600_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_423_cast_fp16 = mul(x = var_4599_cast_fp16, y = var_4600_to_fp16)[name = tensor("aw_chunk_423_cast_fp16")]; + tensor var_4603_equation_0 = const()[name = tensor("op_4603_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4603_cast_fp16 = einsum(equation = var_4603_equation_0, values = (var_4449_cast_fp16, var_4235_cast_fp16))[name = tensor("op_4603_cast_fp16")]; + tensor var_4604_to_fp16 = const()[name = tensor("op_4604_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_425_cast_fp16 = mul(x = var_4603_cast_fp16, y = var_4604_to_fp16)[name = tensor("aw_chunk_425_cast_fp16")]; + tensor var_4607_equation_0 = const()[name = tensor("op_4607_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4607_cast_fp16 = einsum(equation = var_4607_equation_0, values = (var_4449_cast_fp16, var_4242_cast_fp16))[name = tensor("op_4607_cast_fp16")]; + tensor var_4608_to_fp16 = const()[name = tensor("op_4608_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_427_cast_fp16 = mul(x = var_4607_cast_fp16, y = var_4608_to_fp16)[name = tensor("aw_chunk_427_cast_fp16")]; + tensor var_4611_equation_0 = const()[name = tensor("op_4611_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4611_cast_fp16 = einsum(equation = var_4611_equation_0, values = (var_4449_cast_fp16, var_4249_cast_fp16))[name = tensor("op_4611_cast_fp16")]; + tensor var_4612_to_fp16 = const()[name = tensor("op_4612_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_429_cast_fp16 = mul(x = var_4611_cast_fp16, y = var_4612_to_fp16)[name = tensor("aw_chunk_429_cast_fp16")]; + tensor var_4615_equation_0 = const()[name = tensor("op_4615_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4615_cast_fp16 = einsum(equation = var_4615_equation_0, values = (var_4449_cast_fp16, var_4256_cast_fp16))[name = tensor("op_4615_cast_fp16")]; + tensor var_4616_to_fp16 = const()[name = tensor("op_4616_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_431_cast_fp16 = mul(x = var_4615_cast_fp16, y = var_4616_to_fp16)[name = tensor("aw_chunk_431_cast_fp16")]; + tensor var_4619_equation_0 = const()[name = tensor("op_4619_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4619_cast_fp16 = einsum(equation = var_4619_equation_0, values = (var_4453_cast_fp16, var_4263_cast_fp16))[name = tensor("op_4619_cast_fp16")]; + tensor var_4620_to_fp16 = const()[name = tensor("op_4620_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_433_cast_fp16 = mul(x = var_4619_cast_fp16, y = var_4620_to_fp16)[name = tensor("aw_chunk_433_cast_fp16")]; + tensor var_4623_equation_0 = const()[name = tensor("op_4623_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4623_cast_fp16 = einsum(equation = var_4623_equation_0, values = (var_4453_cast_fp16, var_4270_cast_fp16))[name = tensor("op_4623_cast_fp16")]; + tensor var_4624_to_fp16 = const()[name = tensor("op_4624_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_435_cast_fp16 = mul(x = var_4623_cast_fp16, y = var_4624_to_fp16)[name = tensor("aw_chunk_435_cast_fp16")]; + tensor var_4627_equation_0 = const()[name = tensor("op_4627_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4627_cast_fp16 = einsum(equation = var_4627_equation_0, values = (var_4453_cast_fp16, var_4277_cast_fp16))[name = tensor("op_4627_cast_fp16")]; + tensor var_4628_to_fp16 = const()[name = tensor("op_4628_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_437_cast_fp16 = mul(x = var_4627_cast_fp16, y = var_4628_to_fp16)[name = tensor("aw_chunk_437_cast_fp16")]; + tensor var_4631_equation_0 = const()[name = tensor("op_4631_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4631_cast_fp16 = einsum(equation = var_4631_equation_0, values = (var_4453_cast_fp16, var_4284_cast_fp16))[name = tensor("op_4631_cast_fp16")]; + tensor var_4632_to_fp16 = const()[name = tensor("op_4632_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_439_cast_fp16 = mul(x = var_4631_cast_fp16, y = var_4632_to_fp16)[name = tensor("aw_chunk_439_cast_fp16")]; + tensor var_4635_equation_0 = const()[name = tensor("op_4635_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4635_cast_fp16 = einsum(equation = var_4635_equation_0, values = (var_4457_cast_fp16, var_4291_cast_fp16))[name = tensor("op_4635_cast_fp16")]; + tensor var_4636_to_fp16 = const()[name = tensor("op_4636_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_441_cast_fp16 = mul(x = var_4635_cast_fp16, y = var_4636_to_fp16)[name = tensor("aw_chunk_441_cast_fp16")]; + tensor var_4639_equation_0 = const()[name = tensor("op_4639_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4639_cast_fp16 = einsum(equation = var_4639_equation_0, values = (var_4457_cast_fp16, var_4298_cast_fp16))[name = tensor("op_4639_cast_fp16")]; + tensor var_4640_to_fp16 = const()[name = tensor("op_4640_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_443_cast_fp16 = mul(x = var_4639_cast_fp16, y = var_4640_to_fp16)[name = tensor("aw_chunk_443_cast_fp16")]; + tensor var_4643_equation_0 = const()[name = tensor("op_4643_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4643_cast_fp16 = einsum(equation = var_4643_equation_0, values = (var_4457_cast_fp16, var_4305_cast_fp16))[name = tensor("op_4643_cast_fp16")]; + tensor var_4644_to_fp16 = const()[name = tensor("op_4644_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_445_cast_fp16 = mul(x = var_4643_cast_fp16, y = var_4644_to_fp16)[name = tensor("aw_chunk_445_cast_fp16")]; + tensor var_4647_equation_0 = const()[name = tensor("op_4647_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4647_cast_fp16 = einsum(equation = var_4647_equation_0, values = (var_4457_cast_fp16, var_4312_cast_fp16))[name = tensor("op_4647_cast_fp16")]; + tensor var_4648_to_fp16 = const()[name = tensor("op_4648_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_447_cast_fp16 = mul(x = var_4647_cast_fp16, y = var_4648_to_fp16)[name = tensor("aw_chunk_447_cast_fp16")]; + tensor var_4651_equation_0 = const()[name = tensor("op_4651_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4651_cast_fp16 = einsum(equation = var_4651_equation_0, values = (var_4461_cast_fp16, var_4319_cast_fp16))[name = tensor("op_4651_cast_fp16")]; + tensor var_4652_to_fp16 = const()[name = tensor("op_4652_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_449_cast_fp16 = mul(x = var_4651_cast_fp16, y = var_4652_to_fp16)[name = tensor("aw_chunk_449_cast_fp16")]; + tensor var_4655_equation_0 = const()[name = tensor("op_4655_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4655_cast_fp16 = einsum(equation = var_4655_equation_0, values = (var_4461_cast_fp16, var_4326_cast_fp16))[name = tensor("op_4655_cast_fp16")]; + tensor var_4656_to_fp16 = const()[name = tensor("op_4656_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_451_cast_fp16 = mul(x = var_4655_cast_fp16, y = var_4656_to_fp16)[name = tensor("aw_chunk_451_cast_fp16")]; + tensor var_4659_equation_0 = const()[name = tensor("op_4659_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4659_cast_fp16 = einsum(equation = var_4659_equation_0, values = (var_4461_cast_fp16, var_4333_cast_fp16))[name = tensor("op_4659_cast_fp16")]; + tensor var_4660_to_fp16 = const()[name = tensor("op_4660_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_453_cast_fp16 = mul(x = var_4659_cast_fp16, y = var_4660_to_fp16)[name = tensor("aw_chunk_453_cast_fp16")]; + tensor var_4663_equation_0 = const()[name = tensor("op_4663_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4663_cast_fp16 = einsum(equation = var_4663_equation_0, values = (var_4461_cast_fp16, var_4340_cast_fp16))[name = tensor("op_4663_cast_fp16")]; + tensor var_4664_to_fp16 = const()[name = tensor("op_4664_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_455_cast_fp16 = mul(x = var_4663_cast_fp16, y = var_4664_to_fp16)[name = tensor("aw_chunk_455_cast_fp16")]; + tensor var_4667_equation_0 = const()[name = tensor("op_4667_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4667_cast_fp16 = einsum(equation = var_4667_equation_0, values = (var_4465_cast_fp16, var_4347_cast_fp16))[name = tensor("op_4667_cast_fp16")]; + tensor var_4668_to_fp16 = const()[name = tensor("op_4668_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_457_cast_fp16 = mul(x = var_4667_cast_fp16, y = var_4668_to_fp16)[name = tensor("aw_chunk_457_cast_fp16")]; + tensor var_4671_equation_0 = const()[name = tensor("op_4671_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4671_cast_fp16 = einsum(equation = var_4671_equation_0, values = (var_4465_cast_fp16, var_4354_cast_fp16))[name = tensor("op_4671_cast_fp16")]; + tensor var_4672_to_fp16 = const()[name = tensor("op_4672_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_459_cast_fp16 = mul(x = var_4671_cast_fp16, y = var_4672_to_fp16)[name = tensor("aw_chunk_459_cast_fp16")]; + tensor var_4675_equation_0 = const()[name = tensor("op_4675_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4675_cast_fp16 = einsum(equation = var_4675_equation_0, values = (var_4465_cast_fp16, var_4361_cast_fp16))[name = tensor("op_4675_cast_fp16")]; + tensor var_4676_to_fp16 = const()[name = tensor("op_4676_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_461_cast_fp16 = mul(x = var_4675_cast_fp16, y = var_4676_to_fp16)[name = tensor("aw_chunk_461_cast_fp16")]; + tensor var_4679_equation_0 = const()[name = tensor("op_4679_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4679_cast_fp16 = einsum(equation = var_4679_equation_0, values = (var_4465_cast_fp16, var_4368_cast_fp16))[name = tensor("op_4679_cast_fp16")]; + tensor var_4680_to_fp16 = const()[name = tensor("op_4680_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_463_cast_fp16 = mul(x = var_4679_cast_fp16, y = var_4680_to_fp16)[name = tensor("aw_chunk_463_cast_fp16")]; + tensor var_4683_equation_0 = const()[name = tensor("op_4683_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4683_cast_fp16 = einsum(equation = var_4683_equation_0, values = (var_4469_cast_fp16, var_4375_cast_fp16))[name = tensor("op_4683_cast_fp16")]; + tensor var_4684_to_fp16 = const()[name = tensor("op_4684_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_465_cast_fp16 = mul(x = var_4683_cast_fp16, y = var_4684_to_fp16)[name = tensor("aw_chunk_465_cast_fp16")]; + tensor var_4687_equation_0 = const()[name = tensor("op_4687_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4687_cast_fp16 = einsum(equation = var_4687_equation_0, values = (var_4469_cast_fp16, var_4382_cast_fp16))[name = tensor("op_4687_cast_fp16")]; + tensor var_4688_to_fp16 = const()[name = tensor("op_4688_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_467_cast_fp16 = mul(x = var_4687_cast_fp16, y = var_4688_to_fp16)[name = tensor("aw_chunk_467_cast_fp16")]; + tensor var_4691_equation_0 = const()[name = tensor("op_4691_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4691_cast_fp16 = einsum(equation = var_4691_equation_0, values = (var_4469_cast_fp16, var_4389_cast_fp16))[name = tensor("op_4691_cast_fp16")]; + tensor var_4692_to_fp16 = const()[name = tensor("op_4692_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_469_cast_fp16 = mul(x = var_4691_cast_fp16, y = var_4692_to_fp16)[name = tensor("aw_chunk_469_cast_fp16")]; + tensor var_4695_equation_0 = const()[name = tensor("op_4695_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4695_cast_fp16 = einsum(equation = var_4695_equation_0, values = (var_4469_cast_fp16, var_4396_cast_fp16))[name = tensor("op_4695_cast_fp16")]; + tensor var_4696_to_fp16 = const()[name = tensor("op_4696_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_471_cast_fp16 = mul(x = var_4695_cast_fp16, y = var_4696_to_fp16)[name = tensor("aw_chunk_471_cast_fp16")]; + tensor var_4699_equation_0 = const()[name = tensor("op_4699_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4699_cast_fp16 = einsum(equation = var_4699_equation_0, values = (var_4473_cast_fp16, var_4403_cast_fp16))[name = tensor("op_4699_cast_fp16")]; + tensor var_4700_to_fp16 = const()[name = tensor("op_4700_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_473_cast_fp16 = mul(x = var_4699_cast_fp16, y = var_4700_to_fp16)[name = tensor("aw_chunk_473_cast_fp16")]; + tensor var_4703_equation_0 = const()[name = tensor("op_4703_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4703_cast_fp16 = einsum(equation = var_4703_equation_0, values = (var_4473_cast_fp16, var_4410_cast_fp16))[name = tensor("op_4703_cast_fp16")]; + tensor var_4704_to_fp16 = const()[name = tensor("op_4704_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_475_cast_fp16 = mul(x = var_4703_cast_fp16, y = var_4704_to_fp16)[name = tensor("aw_chunk_475_cast_fp16")]; + tensor var_4707_equation_0 = const()[name = tensor("op_4707_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4707_cast_fp16 = einsum(equation = var_4707_equation_0, values = (var_4473_cast_fp16, var_4417_cast_fp16))[name = tensor("op_4707_cast_fp16")]; + tensor var_4708_to_fp16 = const()[name = tensor("op_4708_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_477_cast_fp16 = mul(x = var_4707_cast_fp16, y = var_4708_to_fp16)[name = tensor("aw_chunk_477_cast_fp16")]; + tensor var_4711_equation_0 = const()[name = tensor("op_4711_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_4711_cast_fp16 = einsum(equation = var_4711_equation_0, values = (var_4473_cast_fp16, var_4424_cast_fp16))[name = tensor("op_4711_cast_fp16")]; + tensor var_4712_to_fp16 = const()[name = tensor("op_4712_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_479_cast_fp16 = mul(x = var_4711_cast_fp16, y = var_4712_to_fp16)[name = tensor("aw_chunk_479_cast_fp16")]; + tensor var_4714_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_385_cast_fp16)[name = tensor("op_4714_cast_fp16")]; + tensor var_4715_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_387_cast_fp16)[name = tensor("op_4715_cast_fp16")]; + tensor var_4716_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_389_cast_fp16)[name = tensor("op_4716_cast_fp16")]; + tensor var_4717_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_391_cast_fp16)[name = tensor("op_4717_cast_fp16")]; + tensor var_4718_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_393_cast_fp16)[name = tensor("op_4718_cast_fp16")]; + tensor var_4719_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_395_cast_fp16)[name = tensor("op_4719_cast_fp16")]; + tensor var_4720_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_397_cast_fp16)[name = tensor("op_4720_cast_fp16")]; + tensor var_4721_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_399_cast_fp16)[name = tensor("op_4721_cast_fp16")]; + tensor var_4722_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_401_cast_fp16)[name = tensor("op_4722_cast_fp16")]; + tensor var_4723_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_403_cast_fp16)[name = tensor("op_4723_cast_fp16")]; + tensor var_4724_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_405_cast_fp16)[name = tensor("op_4724_cast_fp16")]; + tensor var_4725_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_407_cast_fp16)[name = tensor("op_4725_cast_fp16")]; + tensor var_4726_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_409_cast_fp16)[name = tensor("op_4726_cast_fp16")]; + tensor var_4727_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_411_cast_fp16)[name = tensor("op_4727_cast_fp16")]; + tensor var_4728_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_413_cast_fp16)[name = tensor("op_4728_cast_fp16")]; + tensor var_4729_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_415_cast_fp16)[name = tensor("op_4729_cast_fp16")]; + tensor var_4730_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_417_cast_fp16)[name = tensor("op_4730_cast_fp16")]; + tensor var_4731_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_419_cast_fp16)[name = tensor("op_4731_cast_fp16")]; + tensor var_4732_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_421_cast_fp16)[name = tensor("op_4732_cast_fp16")]; + tensor var_4733_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_423_cast_fp16)[name = tensor("op_4733_cast_fp16")]; + tensor var_4734_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_425_cast_fp16)[name = tensor("op_4734_cast_fp16")]; + tensor var_4735_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_427_cast_fp16)[name = tensor("op_4735_cast_fp16")]; + tensor var_4736_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_429_cast_fp16)[name = tensor("op_4736_cast_fp16")]; + tensor var_4737_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_431_cast_fp16)[name = tensor("op_4737_cast_fp16")]; + tensor var_4738_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_433_cast_fp16)[name = tensor("op_4738_cast_fp16")]; + tensor var_4739_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_435_cast_fp16)[name = tensor("op_4739_cast_fp16")]; + tensor var_4740_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_437_cast_fp16)[name = tensor("op_4740_cast_fp16")]; + tensor var_4741_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_439_cast_fp16)[name = tensor("op_4741_cast_fp16")]; + tensor var_4742_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_441_cast_fp16)[name = tensor("op_4742_cast_fp16")]; + tensor var_4743_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_443_cast_fp16)[name = tensor("op_4743_cast_fp16")]; + tensor var_4744_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_445_cast_fp16)[name = tensor("op_4744_cast_fp16")]; + tensor var_4745_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_447_cast_fp16)[name = tensor("op_4745_cast_fp16")]; + tensor var_4746_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_449_cast_fp16)[name = tensor("op_4746_cast_fp16")]; + tensor var_4747_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_451_cast_fp16)[name = tensor("op_4747_cast_fp16")]; + tensor var_4748_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_453_cast_fp16)[name = tensor("op_4748_cast_fp16")]; + tensor var_4749_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_455_cast_fp16)[name = tensor("op_4749_cast_fp16")]; + tensor var_4750_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_457_cast_fp16)[name = tensor("op_4750_cast_fp16")]; + tensor var_4751_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_459_cast_fp16)[name = tensor("op_4751_cast_fp16")]; + tensor var_4752_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_461_cast_fp16)[name = tensor("op_4752_cast_fp16")]; + tensor var_4753_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_463_cast_fp16)[name = tensor("op_4753_cast_fp16")]; + tensor var_4754_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_465_cast_fp16)[name = tensor("op_4754_cast_fp16")]; + tensor var_4755_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_467_cast_fp16)[name = tensor("op_4755_cast_fp16")]; + tensor var_4756_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_469_cast_fp16)[name = tensor("op_4756_cast_fp16")]; + tensor var_4757_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_471_cast_fp16)[name = tensor("op_4757_cast_fp16")]; + tensor var_4758_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_473_cast_fp16)[name = tensor("op_4758_cast_fp16")]; + tensor var_4759_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_475_cast_fp16)[name = tensor("op_4759_cast_fp16")]; + tensor var_4760_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_477_cast_fp16)[name = tensor("op_4760_cast_fp16")]; + tensor var_4761_cast_fp16 = softmax(axis = var_3987, x = aw_chunk_479_cast_fp16)[name = tensor("op_4761_cast_fp16")]; + tensor var_4763_equation_0 = const()[name = tensor("op_4763_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4763_cast_fp16 = einsum(equation = var_4763_equation_0, values = (var_4475_cast_fp16, var_4714_cast_fp16))[name = tensor("op_4763_cast_fp16")]; + tensor var_4765_equation_0 = const()[name = tensor("op_4765_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4765_cast_fp16 = einsum(equation = var_4765_equation_0, values = (var_4475_cast_fp16, var_4715_cast_fp16))[name = tensor("op_4765_cast_fp16")]; + tensor var_4767_equation_0 = const()[name = tensor("op_4767_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4767_cast_fp16 = einsum(equation = var_4767_equation_0, values = (var_4475_cast_fp16, var_4716_cast_fp16))[name = tensor("op_4767_cast_fp16")]; + tensor var_4769_equation_0 = const()[name = tensor("op_4769_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4769_cast_fp16 = einsum(equation = var_4769_equation_0, values = (var_4475_cast_fp16, var_4717_cast_fp16))[name = tensor("op_4769_cast_fp16")]; + tensor var_4771_equation_0 = const()[name = tensor("op_4771_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4771_cast_fp16 = einsum(equation = var_4771_equation_0, values = (var_4479_cast_fp16, var_4718_cast_fp16))[name = tensor("op_4771_cast_fp16")]; + tensor var_4773_equation_0 = const()[name = tensor("op_4773_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4773_cast_fp16 = einsum(equation = var_4773_equation_0, values = (var_4479_cast_fp16, var_4719_cast_fp16))[name = tensor("op_4773_cast_fp16")]; + tensor var_4775_equation_0 = const()[name = tensor("op_4775_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4775_cast_fp16 = einsum(equation = var_4775_equation_0, values = (var_4479_cast_fp16, var_4720_cast_fp16))[name = tensor("op_4775_cast_fp16")]; + tensor var_4777_equation_0 = const()[name = tensor("op_4777_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4777_cast_fp16 = einsum(equation = var_4777_equation_0, values = (var_4479_cast_fp16, var_4721_cast_fp16))[name = tensor("op_4777_cast_fp16")]; + tensor var_4779_equation_0 = const()[name = tensor("op_4779_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4779_cast_fp16 = einsum(equation = var_4779_equation_0, values = (var_4483_cast_fp16, var_4722_cast_fp16))[name = tensor("op_4779_cast_fp16")]; + tensor var_4781_equation_0 = const()[name = tensor("op_4781_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4781_cast_fp16 = einsum(equation = var_4781_equation_0, values = (var_4483_cast_fp16, var_4723_cast_fp16))[name = tensor("op_4781_cast_fp16")]; + tensor var_4783_equation_0 = const()[name = tensor("op_4783_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4783_cast_fp16 = einsum(equation = var_4783_equation_0, values = (var_4483_cast_fp16, var_4724_cast_fp16))[name = tensor("op_4783_cast_fp16")]; + tensor var_4785_equation_0 = const()[name = tensor("op_4785_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4785_cast_fp16 = einsum(equation = var_4785_equation_0, values = (var_4483_cast_fp16, var_4725_cast_fp16))[name = tensor("op_4785_cast_fp16")]; + tensor var_4787_equation_0 = const()[name = tensor("op_4787_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4787_cast_fp16 = einsum(equation = var_4787_equation_0, values = (var_4487_cast_fp16, var_4726_cast_fp16))[name = tensor("op_4787_cast_fp16")]; + tensor var_4789_equation_0 = const()[name = tensor("op_4789_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4789_cast_fp16 = einsum(equation = var_4789_equation_0, values = (var_4487_cast_fp16, var_4727_cast_fp16))[name = tensor("op_4789_cast_fp16")]; + tensor var_4791_equation_0 = const()[name = tensor("op_4791_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4791_cast_fp16 = einsum(equation = var_4791_equation_0, values = (var_4487_cast_fp16, var_4728_cast_fp16))[name = tensor("op_4791_cast_fp16")]; + tensor var_4793_equation_0 = const()[name = tensor("op_4793_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4793_cast_fp16 = einsum(equation = var_4793_equation_0, values = (var_4487_cast_fp16, var_4729_cast_fp16))[name = tensor("op_4793_cast_fp16")]; + tensor var_4795_equation_0 = const()[name = tensor("op_4795_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4795_cast_fp16 = einsum(equation = var_4795_equation_0, values = (var_4491_cast_fp16, var_4730_cast_fp16))[name = tensor("op_4795_cast_fp16")]; + tensor var_4797_equation_0 = const()[name = tensor("op_4797_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4797_cast_fp16 = einsum(equation = var_4797_equation_0, values = (var_4491_cast_fp16, var_4731_cast_fp16))[name = tensor("op_4797_cast_fp16")]; + tensor var_4799_equation_0 = const()[name = tensor("op_4799_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4799_cast_fp16 = einsum(equation = var_4799_equation_0, values = (var_4491_cast_fp16, var_4732_cast_fp16))[name = tensor("op_4799_cast_fp16")]; + tensor var_4801_equation_0 = const()[name = tensor("op_4801_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4801_cast_fp16 = einsum(equation = var_4801_equation_0, values = (var_4491_cast_fp16, var_4733_cast_fp16))[name = tensor("op_4801_cast_fp16")]; + tensor var_4803_equation_0 = const()[name = tensor("op_4803_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4803_cast_fp16 = einsum(equation = var_4803_equation_0, values = (var_4495_cast_fp16, var_4734_cast_fp16))[name = tensor("op_4803_cast_fp16")]; + tensor var_4805_equation_0 = const()[name = tensor("op_4805_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4805_cast_fp16 = einsum(equation = var_4805_equation_0, values = (var_4495_cast_fp16, var_4735_cast_fp16))[name = tensor("op_4805_cast_fp16")]; + tensor var_4807_equation_0 = const()[name = tensor("op_4807_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4807_cast_fp16 = einsum(equation = var_4807_equation_0, values = (var_4495_cast_fp16, var_4736_cast_fp16))[name = tensor("op_4807_cast_fp16")]; + tensor var_4809_equation_0 = const()[name = tensor("op_4809_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4809_cast_fp16 = einsum(equation = var_4809_equation_0, values = (var_4495_cast_fp16, var_4737_cast_fp16))[name = tensor("op_4809_cast_fp16")]; + tensor var_4811_equation_0 = const()[name = tensor("op_4811_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4811_cast_fp16 = einsum(equation = var_4811_equation_0, values = (var_4499_cast_fp16, var_4738_cast_fp16))[name = tensor("op_4811_cast_fp16")]; + tensor var_4813_equation_0 = const()[name = tensor("op_4813_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4813_cast_fp16 = einsum(equation = var_4813_equation_0, values = (var_4499_cast_fp16, var_4739_cast_fp16))[name = tensor("op_4813_cast_fp16")]; + tensor var_4815_equation_0 = const()[name = tensor("op_4815_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4815_cast_fp16 = einsum(equation = var_4815_equation_0, values = (var_4499_cast_fp16, var_4740_cast_fp16))[name = tensor("op_4815_cast_fp16")]; + tensor var_4817_equation_0 = const()[name = tensor("op_4817_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4817_cast_fp16 = einsum(equation = var_4817_equation_0, values = (var_4499_cast_fp16, var_4741_cast_fp16))[name = tensor("op_4817_cast_fp16")]; + tensor var_4819_equation_0 = const()[name = tensor("op_4819_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4819_cast_fp16 = einsum(equation = var_4819_equation_0, values = (var_4503_cast_fp16, var_4742_cast_fp16))[name = tensor("op_4819_cast_fp16")]; + tensor var_4821_equation_0 = const()[name = tensor("op_4821_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4821_cast_fp16 = einsum(equation = var_4821_equation_0, values = (var_4503_cast_fp16, var_4743_cast_fp16))[name = tensor("op_4821_cast_fp16")]; + tensor var_4823_equation_0 = const()[name = tensor("op_4823_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4823_cast_fp16 = einsum(equation = var_4823_equation_0, values = (var_4503_cast_fp16, var_4744_cast_fp16))[name = tensor("op_4823_cast_fp16")]; + tensor var_4825_equation_0 = const()[name = tensor("op_4825_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4825_cast_fp16 = einsum(equation = var_4825_equation_0, values = (var_4503_cast_fp16, var_4745_cast_fp16))[name = tensor("op_4825_cast_fp16")]; + tensor var_4827_equation_0 = const()[name = tensor("op_4827_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4827_cast_fp16 = einsum(equation = var_4827_equation_0, values = (var_4507_cast_fp16, var_4746_cast_fp16))[name = tensor("op_4827_cast_fp16")]; + tensor var_4829_equation_0 = const()[name = tensor("op_4829_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4829_cast_fp16 = einsum(equation = var_4829_equation_0, values = (var_4507_cast_fp16, var_4747_cast_fp16))[name = tensor("op_4829_cast_fp16")]; + tensor var_4831_equation_0 = const()[name = tensor("op_4831_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4831_cast_fp16 = einsum(equation = var_4831_equation_0, values = (var_4507_cast_fp16, var_4748_cast_fp16))[name = tensor("op_4831_cast_fp16")]; + tensor var_4833_equation_0 = const()[name = tensor("op_4833_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4833_cast_fp16 = einsum(equation = var_4833_equation_0, values = (var_4507_cast_fp16, var_4749_cast_fp16))[name = tensor("op_4833_cast_fp16")]; + tensor var_4835_equation_0 = const()[name = tensor("op_4835_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4835_cast_fp16 = einsum(equation = var_4835_equation_0, values = (var_4511_cast_fp16, var_4750_cast_fp16))[name = tensor("op_4835_cast_fp16")]; + tensor var_4837_equation_0 = const()[name = tensor("op_4837_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4837_cast_fp16 = einsum(equation = var_4837_equation_0, values = (var_4511_cast_fp16, var_4751_cast_fp16))[name = tensor("op_4837_cast_fp16")]; + tensor var_4839_equation_0 = const()[name = tensor("op_4839_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4839_cast_fp16 = einsum(equation = var_4839_equation_0, values = (var_4511_cast_fp16, var_4752_cast_fp16))[name = tensor("op_4839_cast_fp16")]; + tensor var_4841_equation_0 = const()[name = tensor("op_4841_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4841_cast_fp16 = einsum(equation = var_4841_equation_0, values = (var_4511_cast_fp16, var_4753_cast_fp16))[name = tensor("op_4841_cast_fp16")]; + tensor var_4843_equation_0 = const()[name = tensor("op_4843_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4843_cast_fp16 = einsum(equation = var_4843_equation_0, values = (var_4515_cast_fp16, var_4754_cast_fp16))[name = tensor("op_4843_cast_fp16")]; + tensor var_4845_equation_0 = const()[name = tensor("op_4845_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4845_cast_fp16 = einsum(equation = var_4845_equation_0, values = (var_4515_cast_fp16, var_4755_cast_fp16))[name = tensor("op_4845_cast_fp16")]; + tensor var_4847_equation_0 = const()[name = tensor("op_4847_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4847_cast_fp16 = einsum(equation = var_4847_equation_0, values = (var_4515_cast_fp16, var_4756_cast_fp16))[name = tensor("op_4847_cast_fp16")]; + tensor var_4849_equation_0 = const()[name = tensor("op_4849_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4849_cast_fp16 = einsum(equation = var_4849_equation_0, values = (var_4515_cast_fp16, var_4757_cast_fp16))[name = tensor("op_4849_cast_fp16")]; + tensor var_4851_equation_0 = const()[name = tensor("op_4851_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4851_cast_fp16 = einsum(equation = var_4851_equation_0, values = (var_4519_cast_fp16, var_4758_cast_fp16))[name = tensor("op_4851_cast_fp16")]; + tensor var_4853_equation_0 = const()[name = tensor("op_4853_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4853_cast_fp16 = einsum(equation = var_4853_equation_0, values = (var_4519_cast_fp16, var_4759_cast_fp16))[name = tensor("op_4853_cast_fp16")]; + tensor var_4855_equation_0 = const()[name = tensor("op_4855_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4855_cast_fp16 = einsum(equation = var_4855_equation_0, values = (var_4519_cast_fp16, var_4760_cast_fp16))[name = tensor("op_4855_cast_fp16")]; + tensor var_4857_equation_0 = const()[name = tensor("op_4857_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_4857_cast_fp16 = einsum(equation = var_4857_equation_0, values = (var_4519_cast_fp16, var_4761_cast_fp16))[name = tensor("op_4857_cast_fp16")]; + tensor var_4859_interleave_0 = const()[name = tensor("op_4859_interleave_0"), val = tensor(false)]; + tensor var_4859_cast_fp16 = concat(axis = var_3970, interleave = var_4859_interleave_0, values = (var_4763_cast_fp16, var_4765_cast_fp16, var_4767_cast_fp16, var_4769_cast_fp16))[name = tensor("op_4859_cast_fp16")]; + tensor var_4861_interleave_0 = const()[name = tensor("op_4861_interleave_0"), val = tensor(false)]; + tensor var_4861_cast_fp16 = concat(axis = var_3970, interleave = var_4861_interleave_0, values = (var_4771_cast_fp16, var_4773_cast_fp16, var_4775_cast_fp16, var_4777_cast_fp16))[name = tensor("op_4861_cast_fp16")]; + tensor var_4863_interleave_0 = const()[name = tensor("op_4863_interleave_0"), val = tensor(false)]; + tensor var_4863_cast_fp16 = concat(axis = var_3970, interleave = var_4863_interleave_0, values = (var_4779_cast_fp16, var_4781_cast_fp16, var_4783_cast_fp16, var_4785_cast_fp16))[name = tensor("op_4863_cast_fp16")]; + tensor var_4865_interleave_0 = const()[name = tensor("op_4865_interleave_0"), val = tensor(false)]; + tensor var_4865_cast_fp16 = concat(axis = var_3970, interleave = var_4865_interleave_0, values = (var_4787_cast_fp16, var_4789_cast_fp16, var_4791_cast_fp16, var_4793_cast_fp16))[name = tensor("op_4865_cast_fp16")]; + tensor var_4867_interleave_0 = const()[name = tensor("op_4867_interleave_0"), val = tensor(false)]; + tensor var_4867_cast_fp16 = concat(axis = var_3970, interleave = var_4867_interleave_0, values = (var_4795_cast_fp16, var_4797_cast_fp16, var_4799_cast_fp16, var_4801_cast_fp16))[name = tensor("op_4867_cast_fp16")]; + tensor var_4869_interleave_0 = const()[name = tensor("op_4869_interleave_0"), val = tensor(false)]; + tensor var_4869_cast_fp16 = concat(axis = var_3970, interleave = var_4869_interleave_0, values = (var_4803_cast_fp16, var_4805_cast_fp16, var_4807_cast_fp16, var_4809_cast_fp16))[name = tensor("op_4869_cast_fp16")]; + tensor var_4871_interleave_0 = const()[name = tensor("op_4871_interleave_0"), val = tensor(false)]; + tensor var_4871_cast_fp16 = concat(axis = var_3970, interleave = var_4871_interleave_0, values = (var_4811_cast_fp16, var_4813_cast_fp16, var_4815_cast_fp16, var_4817_cast_fp16))[name = tensor("op_4871_cast_fp16")]; + tensor var_4873_interleave_0 = const()[name = tensor("op_4873_interleave_0"), val = tensor(false)]; + tensor var_4873_cast_fp16 = concat(axis = var_3970, interleave = var_4873_interleave_0, values = (var_4819_cast_fp16, var_4821_cast_fp16, var_4823_cast_fp16, var_4825_cast_fp16))[name = tensor("op_4873_cast_fp16")]; + tensor var_4875_interleave_0 = const()[name = tensor("op_4875_interleave_0"), val = tensor(false)]; + tensor var_4875_cast_fp16 = concat(axis = var_3970, interleave = var_4875_interleave_0, values = (var_4827_cast_fp16, var_4829_cast_fp16, var_4831_cast_fp16, var_4833_cast_fp16))[name = tensor("op_4875_cast_fp16")]; + tensor var_4877_interleave_0 = const()[name = tensor("op_4877_interleave_0"), val = tensor(false)]; + tensor var_4877_cast_fp16 = concat(axis = var_3970, interleave = var_4877_interleave_0, values = (var_4835_cast_fp16, var_4837_cast_fp16, var_4839_cast_fp16, var_4841_cast_fp16))[name = tensor("op_4877_cast_fp16")]; + tensor var_4879_interleave_0 = const()[name = tensor("op_4879_interleave_0"), val = tensor(false)]; + tensor var_4879_cast_fp16 = concat(axis = var_3970, interleave = var_4879_interleave_0, values = (var_4843_cast_fp16, var_4845_cast_fp16, var_4847_cast_fp16, var_4849_cast_fp16))[name = tensor("op_4879_cast_fp16")]; + tensor var_4881_interleave_0 = const()[name = tensor("op_4881_interleave_0"), val = tensor(false)]; + tensor var_4881_cast_fp16 = concat(axis = var_3970, interleave = var_4881_interleave_0, values = (var_4851_cast_fp16, var_4853_cast_fp16, var_4855_cast_fp16, var_4857_cast_fp16))[name = tensor("op_4881_cast_fp16")]; + tensor input_33_interleave_0 = const()[name = tensor("input_33_interleave_0"), val = tensor(false)]; + tensor input_33_cast_fp16 = concat(axis = var_3987, interleave = input_33_interleave_0, values = (var_4859_cast_fp16, var_4861_cast_fp16, var_4863_cast_fp16, var_4865_cast_fp16, var_4867_cast_fp16, var_4869_cast_fp16, var_4871_cast_fp16, var_4873_cast_fp16, var_4875_cast_fp16, var_4877_cast_fp16, var_4879_cast_fp16, var_4881_cast_fp16))[name = tensor("input_33_cast_fp16")]; + tensor var_4886 = const()[name = tensor("op_4886"), val = tensor([1, 1])]; + tensor var_4888 = const()[name = tensor("op_4888"), val = tensor([1, 1])]; + tensor obj_19_pad_type_0 = const()[name = tensor("obj_19_pad_type_0"), val = tensor("custom")]; + tensor obj_19_pad_0 = const()[name = tensor("obj_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66464448)))]; + tensor layers_4_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67644160)))]; + tensor obj_19_cast_fp16 = conv(bias = layers_4_self_attn_o_proj_bias_to_fp16, dilations = var_4888, groups = var_3987, pad = obj_19_pad_0, pad_type = obj_19_pad_type_0, strides = var_4886, weight = layers_4_self_attn_o_proj_weight_to_fp16, x = input_33_cast_fp16)[name = tensor("obj_19_cast_fp16")]; + tensor inputs_19_cast_fp16 = add(x = inputs_17_cast_fp16, y = obj_19_cast_fp16)[name = tensor("inputs_19_cast_fp16")]; + tensor var_4894 = const()[name = tensor("op_4894"), val = tensor([1])]; + tensor channels_mean_19_cast_fp16 = reduce_mean(axes = var_4894, keep_dims = var_3988, x = inputs_19_cast_fp16)[name = tensor("channels_mean_19_cast_fp16")]; + tensor zero_mean_19_cast_fp16 = sub(x = inputs_19_cast_fp16, y = channels_mean_19_cast_fp16)[name = tensor("zero_mean_19_cast_fp16")]; + tensor zero_mean_sq_19_cast_fp16 = mul(x = zero_mean_19_cast_fp16, y = zero_mean_19_cast_fp16)[name = tensor("zero_mean_sq_19_cast_fp16")]; + tensor var_4898 = const()[name = tensor("op_4898"), val = tensor([1])]; + tensor var_4899_cast_fp16 = reduce_mean(axes = var_4898, keep_dims = var_3988, x = zero_mean_sq_19_cast_fp16)[name = tensor("op_4899_cast_fp16")]; + tensor var_4900_to_fp16 = const()[name = tensor("op_4900_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_4901_cast_fp16 = add(x = var_4899_cast_fp16, y = var_4900_to_fp16)[name = tensor("op_4901_cast_fp16")]; + tensor denom_19_epsilon_0_to_fp16 = const()[name = tensor("denom_19_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_19_cast_fp16 = rsqrt(epsilon = denom_19_epsilon_0_to_fp16, x = var_4901_cast_fp16)[name = tensor("denom_19_cast_fp16")]; + tensor out_19_cast_fp16 = mul(x = zero_mean_19_cast_fp16, y = denom_19_cast_fp16)[name = tensor("out_19_cast_fp16")]; + tensor input_35_gamma_0_to_fp16 = const()[name = tensor("input_35_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67645760)))]; + tensor input_35_beta_0_to_fp16 = const()[name = tensor("input_35_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67647360)))]; + tensor input_35_epsilon_0_to_fp16 = const()[name = tensor("input_35_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_35_cast_fp16 = batch_norm(beta = input_35_beta_0_to_fp16, epsilon = input_35_epsilon_0_to_fp16, gamma = input_35_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_19_cast_fp16)[name = tensor("input_35_cast_fp16")]; + tensor var_4912 = const()[name = tensor("op_4912"), val = tensor([1, 1])]; + tensor var_4914 = const()[name = tensor("op_4914"), val = tensor([1, 1])]; + tensor input_37_pad_type_0 = const()[name = tensor("input_37_pad_type_0"), val = tensor("custom")]; + tensor input_37_pad_0 = const()[name = tensor("input_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_fc1_weight_to_fp16 = const()[name = tensor("layers_4_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67648960)))]; + tensor layers_4_fc1_bias_to_fp16 = const()[name = tensor("layers_4_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72367616)))]; + tensor input_37_cast_fp16 = conv(bias = layers_4_fc1_bias_to_fp16, dilations = var_4914, groups = var_3987, pad = input_37_pad_0, pad_type = input_37_pad_type_0, strides = var_4912, weight = layers_4_fc1_weight_to_fp16, x = input_35_cast_fp16)[name = tensor("input_37_cast_fp16")]; + tensor input_39_mode_0 = const()[name = tensor("input_39_mode_0"), val = tensor("EXACT")]; + tensor input_39_cast_fp16 = gelu(mode = input_39_mode_0, x = input_37_cast_fp16)[name = tensor("input_39_cast_fp16")]; + tensor var_4920 = const()[name = tensor("op_4920"), val = tensor([1, 1])]; + tensor var_4922 = const()[name = tensor("op_4922"), val = tensor([1, 1])]; + tensor hidden_states_13_pad_type_0 = const()[name = tensor("hidden_states_13_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_13_pad_0 = const()[name = tensor("hidden_states_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_fc2_weight_to_fp16 = const()[name = tensor("layers_4_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72373824)))]; + tensor layers_4_fc2_bias_to_fp16 = const()[name = tensor("layers_4_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77092480)))]; + tensor hidden_states_13_cast_fp16 = conv(bias = layers_4_fc2_bias_to_fp16, dilations = var_4922, groups = var_3987, pad = hidden_states_13_pad_0, pad_type = hidden_states_13_pad_type_0, strides = var_4920, weight = layers_4_fc2_weight_to_fp16, x = input_39_cast_fp16)[name = tensor("hidden_states_13_cast_fp16")]; + tensor inputs_21_cast_fp16 = add(x = inputs_19_cast_fp16, y = hidden_states_13_cast_fp16)[name = tensor("inputs_21_cast_fp16")]; + tensor var_4929 = const()[name = tensor("op_4929"), val = tensor(3)]; + tensor var_4946 = const()[name = tensor("op_4946"), val = tensor(1)]; + tensor var_4947 = const()[name = tensor("op_4947"), val = tensor(true)]; + tensor var_4957 = const()[name = tensor("op_4957"), val = tensor([1])]; + tensor channels_mean_21_cast_fp16 = reduce_mean(axes = var_4957, keep_dims = var_4947, x = inputs_21_cast_fp16)[name = tensor("channels_mean_21_cast_fp16")]; + tensor zero_mean_21_cast_fp16 = sub(x = inputs_21_cast_fp16, y = channels_mean_21_cast_fp16)[name = tensor("zero_mean_21_cast_fp16")]; + tensor zero_mean_sq_21_cast_fp16 = mul(x = zero_mean_21_cast_fp16, y = zero_mean_21_cast_fp16)[name = tensor("zero_mean_sq_21_cast_fp16")]; + tensor var_4961 = const()[name = tensor("op_4961"), val = tensor([1])]; + tensor var_4962_cast_fp16 = reduce_mean(axes = var_4961, keep_dims = var_4947, x = zero_mean_sq_21_cast_fp16)[name = tensor("op_4962_cast_fp16")]; + tensor var_4963_to_fp16 = const()[name = tensor("op_4963_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_4964_cast_fp16 = add(x = var_4962_cast_fp16, y = var_4963_to_fp16)[name = tensor("op_4964_cast_fp16")]; + tensor denom_21_epsilon_0_to_fp16 = const()[name = tensor("denom_21_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_21_cast_fp16 = rsqrt(epsilon = denom_21_epsilon_0_to_fp16, x = var_4964_cast_fp16)[name = tensor("denom_21_cast_fp16")]; + tensor out_21_cast_fp16 = mul(x = zero_mean_21_cast_fp16, y = denom_21_cast_fp16)[name = tensor("out_21_cast_fp16")]; + tensor obj_21_gamma_0_to_fp16 = const()[name = tensor("obj_21_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77094080)))]; + tensor obj_21_beta_0_to_fp16 = const()[name = tensor("obj_21_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77095680)))]; + tensor obj_21_epsilon_0_to_fp16 = const()[name = tensor("obj_21_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_21_cast_fp16 = batch_norm(beta = obj_21_beta_0_to_fp16, epsilon = obj_21_epsilon_0_to_fp16, gamma = obj_21_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_21_cast_fp16)[name = tensor("obj_21_cast_fp16")]; + tensor var_4979 = const()[name = tensor("op_4979"), val = tensor([1, 1])]; + tensor var_4981 = const()[name = tensor("op_4981"), val = tensor([1, 1])]; + tensor query_11_pad_type_0 = const()[name = tensor("query_11_pad_type_0"), val = tensor("custom")]; + tensor query_11_pad_0 = const()[name = tensor("query_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77097280)))]; + tensor layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78276992)))]; + tensor query_11_cast_fp16 = conv(bias = layers_5_self_attn_q_proj_bias_to_fp16, dilations = var_4981, groups = var_4946, pad = query_11_pad_0, pad_type = query_11_pad_type_0, strides = var_4979, weight = layers_5_self_attn_q_proj_weight_to_fp16, x = obj_21_cast_fp16)[name = tensor("query_11_cast_fp16")]; + tensor var_4985 = const()[name = tensor("op_4985"), val = tensor([1, 1])]; + tensor var_4987 = const()[name = tensor("op_4987"), val = tensor([1, 1])]; + tensor key_11_pad_type_0 = const()[name = tensor("key_11_pad_type_0"), val = tensor("custom")]; + tensor key_11_pad_0 = const()[name = tensor("key_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78278592)))]; + tensor key_11_cast_fp16 = conv(dilations = var_4987, groups = var_4946, pad = key_11_pad_0, pad_type = key_11_pad_type_0, strides = var_4985, weight = layers_5_self_attn_k_proj_weight_to_fp16, x = obj_21_cast_fp16)[name = tensor("key_11_cast_fp16")]; + tensor var_4992 = const()[name = tensor("op_4992"), val = tensor([1, 1])]; + tensor var_4994 = const()[name = tensor("op_4994"), val = tensor([1, 1])]; + tensor value_11_pad_type_0 = const()[name = tensor("value_11_pad_type_0"), val = tensor("custom")]; + tensor value_11_pad_0 = const()[name = tensor("value_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79458304)))]; + tensor layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80638016)))]; + tensor value_11_cast_fp16 = conv(bias = layers_5_self_attn_v_proj_bias_to_fp16, dilations = var_4994, groups = var_4946, pad = value_11_pad_0, pad_type = value_11_pad_type_0, strides = var_4992, weight = layers_5_self_attn_v_proj_weight_to_fp16, x = obj_21_cast_fp16)[name = tensor("value_11_cast_fp16")]; + tensor var_5001_begin_0 = const()[name = tensor("op_5001_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5001_end_0 = const()[name = tensor("op_5001_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5001_end_mask_0 = const()[name = tensor("op_5001_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5001_cast_fp16 = slice_by_index(begin = var_5001_begin_0, end = var_5001_end_0, end_mask = var_5001_end_mask_0, x = query_11_cast_fp16)[name = tensor("op_5001_cast_fp16")]; + tensor var_5005_begin_0 = const()[name = tensor("op_5005_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_5005_end_0 = const()[name = tensor("op_5005_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_5005_end_mask_0 = const()[name = tensor("op_5005_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5005_cast_fp16 = slice_by_index(begin = var_5005_begin_0, end = var_5005_end_0, end_mask = var_5005_end_mask_0, x = query_11_cast_fp16)[name = tensor("op_5005_cast_fp16")]; + tensor var_5009_begin_0 = const()[name = tensor("op_5009_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_5009_end_0 = const()[name = tensor("op_5009_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_5009_end_mask_0 = const()[name = tensor("op_5009_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5009_cast_fp16 = slice_by_index(begin = var_5009_begin_0, end = var_5009_end_0, end_mask = var_5009_end_mask_0, x = query_11_cast_fp16)[name = tensor("op_5009_cast_fp16")]; + tensor var_5013_begin_0 = const()[name = tensor("op_5013_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_5013_end_0 = const()[name = tensor("op_5013_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_5013_end_mask_0 = const()[name = tensor("op_5013_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5013_cast_fp16 = slice_by_index(begin = var_5013_begin_0, end = var_5013_end_0, end_mask = var_5013_end_mask_0, x = query_11_cast_fp16)[name = tensor("op_5013_cast_fp16")]; + tensor var_5017_begin_0 = const()[name = tensor("op_5017_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_5017_end_0 = const()[name = tensor("op_5017_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_5017_end_mask_0 = const()[name = tensor("op_5017_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5017_cast_fp16 = slice_by_index(begin = var_5017_begin_0, end = var_5017_end_0, end_mask = var_5017_end_mask_0, x = query_11_cast_fp16)[name = tensor("op_5017_cast_fp16")]; + tensor var_5021_begin_0 = const()[name = tensor("op_5021_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_5021_end_0 = const()[name = tensor("op_5021_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_5021_end_mask_0 = const()[name = tensor("op_5021_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5021_cast_fp16 = slice_by_index(begin = var_5021_begin_0, end = var_5021_end_0, end_mask = var_5021_end_mask_0, x = query_11_cast_fp16)[name = tensor("op_5021_cast_fp16")]; + tensor var_5025_begin_0 = const()[name = tensor("op_5025_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_5025_end_0 = const()[name = tensor("op_5025_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_5025_end_mask_0 = const()[name = tensor("op_5025_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5025_cast_fp16 = slice_by_index(begin = var_5025_begin_0, end = var_5025_end_0, end_mask = var_5025_end_mask_0, x = query_11_cast_fp16)[name = tensor("op_5025_cast_fp16")]; + tensor var_5029_begin_0 = const()[name = tensor("op_5029_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_5029_end_0 = const()[name = tensor("op_5029_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_5029_end_mask_0 = const()[name = tensor("op_5029_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5029_cast_fp16 = slice_by_index(begin = var_5029_begin_0, end = var_5029_end_0, end_mask = var_5029_end_mask_0, x = query_11_cast_fp16)[name = tensor("op_5029_cast_fp16")]; + tensor var_5033_begin_0 = const()[name = tensor("op_5033_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_5033_end_0 = const()[name = tensor("op_5033_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_5033_end_mask_0 = const()[name = tensor("op_5033_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5033_cast_fp16 = slice_by_index(begin = var_5033_begin_0, end = var_5033_end_0, end_mask = var_5033_end_mask_0, x = query_11_cast_fp16)[name = tensor("op_5033_cast_fp16")]; + tensor var_5037_begin_0 = const()[name = tensor("op_5037_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_5037_end_0 = const()[name = tensor("op_5037_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_5037_end_mask_0 = const()[name = tensor("op_5037_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5037_cast_fp16 = slice_by_index(begin = var_5037_begin_0, end = var_5037_end_0, end_mask = var_5037_end_mask_0, x = query_11_cast_fp16)[name = tensor("op_5037_cast_fp16")]; + tensor var_5041_begin_0 = const()[name = tensor("op_5041_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_5041_end_0 = const()[name = tensor("op_5041_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_5041_end_mask_0 = const()[name = tensor("op_5041_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5041_cast_fp16 = slice_by_index(begin = var_5041_begin_0, end = var_5041_end_0, end_mask = var_5041_end_mask_0, x = query_11_cast_fp16)[name = tensor("op_5041_cast_fp16")]; + tensor var_5045_begin_0 = const()[name = tensor("op_5045_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_5045_end_0 = const()[name = tensor("op_5045_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_5045_end_mask_0 = const()[name = tensor("op_5045_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5045_cast_fp16 = slice_by_index(begin = var_5045_begin_0, end = var_5045_end_0, end_mask = var_5045_end_mask_0, x = query_11_cast_fp16)[name = tensor("op_5045_cast_fp16")]; + tensor var_5054_begin_0 = const()[name = tensor("op_5054_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5054_end_0 = const()[name = tensor("op_5054_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_5054_end_mask_0 = const()[name = tensor("op_5054_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5054_cast_fp16 = slice_by_index(begin = var_5054_begin_0, end = var_5054_end_0, end_mask = var_5054_end_mask_0, x = var_5001_cast_fp16)[name = tensor("op_5054_cast_fp16")]; + tensor var_5061_begin_0 = const()[name = tensor("op_5061_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_5061_end_0 = const()[name = tensor("op_5061_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_5061_end_mask_0 = const()[name = tensor("op_5061_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5061_cast_fp16 = slice_by_index(begin = var_5061_begin_0, end = var_5061_end_0, end_mask = var_5061_end_mask_0, x = var_5001_cast_fp16)[name = tensor("op_5061_cast_fp16")]; + tensor var_5068_begin_0 = const()[name = tensor("op_5068_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_5068_end_0 = const()[name = tensor("op_5068_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_5068_end_mask_0 = const()[name = tensor("op_5068_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5068_cast_fp16 = slice_by_index(begin = var_5068_begin_0, end = var_5068_end_0, end_mask = var_5068_end_mask_0, x = var_5001_cast_fp16)[name = tensor("op_5068_cast_fp16")]; + tensor var_5075_begin_0 = const()[name = tensor("op_5075_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_5075_end_0 = const()[name = tensor("op_5075_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5075_end_mask_0 = const()[name = tensor("op_5075_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5075_cast_fp16 = slice_by_index(begin = var_5075_begin_0, end = var_5075_end_0, end_mask = var_5075_end_mask_0, x = var_5001_cast_fp16)[name = tensor("op_5075_cast_fp16")]; + tensor var_5082_begin_0 = const()[name = tensor("op_5082_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5082_end_0 = const()[name = tensor("op_5082_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_5082_end_mask_0 = const()[name = tensor("op_5082_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5082_cast_fp16 = slice_by_index(begin = var_5082_begin_0, end = var_5082_end_0, end_mask = var_5082_end_mask_0, x = var_5005_cast_fp16)[name = tensor("op_5082_cast_fp16")]; + tensor var_5089_begin_0 = const()[name = tensor("op_5089_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_5089_end_0 = const()[name = tensor("op_5089_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_5089_end_mask_0 = const()[name = tensor("op_5089_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5089_cast_fp16 = slice_by_index(begin = var_5089_begin_0, end = var_5089_end_0, end_mask = var_5089_end_mask_0, x = var_5005_cast_fp16)[name = tensor("op_5089_cast_fp16")]; + tensor var_5096_begin_0 = const()[name = tensor("op_5096_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_5096_end_0 = const()[name = tensor("op_5096_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_5096_end_mask_0 = const()[name = tensor("op_5096_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5096_cast_fp16 = slice_by_index(begin = var_5096_begin_0, end = var_5096_end_0, end_mask = var_5096_end_mask_0, x = var_5005_cast_fp16)[name = tensor("op_5096_cast_fp16")]; + tensor var_5103_begin_0 = const()[name = tensor("op_5103_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_5103_end_0 = const()[name = tensor("op_5103_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5103_end_mask_0 = const()[name = tensor("op_5103_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5103_cast_fp16 = slice_by_index(begin = var_5103_begin_0, end = var_5103_end_0, end_mask = var_5103_end_mask_0, x = var_5005_cast_fp16)[name = tensor("op_5103_cast_fp16")]; + tensor var_5110_begin_0 = const()[name = tensor("op_5110_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5110_end_0 = const()[name = tensor("op_5110_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_5110_end_mask_0 = const()[name = tensor("op_5110_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5110_cast_fp16 = slice_by_index(begin = var_5110_begin_0, end = var_5110_end_0, end_mask = var_5110_end_mask_0, x = var_5009_cast_fp16)[name = tensor("op_5110_cast_fp16")]; + tensor var_5117_begin_0 = const()[name = tensor("op_5117_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_5117_end_0 = const()[name = tensor("op_5117_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_5117_end_mask_0 = const()[name = tensor("op_5117_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5117_cast_fp16 = slice_by_index(begin = var_5117_begin_0, end = var_5117_end_0, end_mask = var_5117_end_mask_0, x = var_5009_cast_fp16)[name = tensor("op_5117_cast_fp16")]; + tensor var_5124_begin_0 = const()[name = tensor("op_5124_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_5124_end_0 = const()[name = tensor("op_5124_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_5124_end_mask_0 = const()[name = tensor("op_5124_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5124_cast_fp16 = slice_by_index(begin = var_5124_begin_0, end = var_5124_end_0, end_mask = var_5124_end_mask_0, x = var_5009_cast_fp16)[name = tensor("op_5124_cast_fp16")]; + tensor var_5131_begin_0 = const()[name = tensor("op_5131_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_5131_end_0 = const()[name = tensor("op_5131_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5131_end_mask_0 = const()[name = tensor("op_5131_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5131_cast_fp16 = slice_by_index(begin = var_5131_begin_0, end = var_5131_end_0, end_mask = var_5131_end_mask_0, x = var_5009_cast_fp16)[name = tensor("op_5131_cast_fp16")]; + tensor var_5138_begin_0 = const()[name = tensor("op_5138_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5138_end_0 = const()[name = tensor("op_5138_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_5138_end_mask_0 = const()[name = tensor("op_5138_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5138_cast_fp16 = slice_by_index(begin = var_5138_begin_0, end = var_5138_end_0, end_mask = var_5138_end_mask_0, x = var_5013_cast_fp16)[name = tensor("op_5138_cast_fp16")]; + tensor var_5145_begin_0 = const()[name = tensor("op_5145_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_5145_end_0 = const()[name = tensor("op_5145_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_5145_end_mask_0 = const()[name = tensor("op_5145_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5145_cast_fp16 = slice_by_index(begin = var_5145_begin_0, end = var_5145_end_0, end_mask = var_5145_end_mask_0, x = var_5013_cast_fp16)[name = tensor("op_5145_cast_fp16")]; + tensor var_5152_begin_0 = const()[name = tensor("op_5152_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_5152_end_0 = const()[name = tensor("op_5152_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_5152_end_mask_0 = const()[name = tensor("op_5152_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5152_cast_fp16 = slice_by_index(begin = var_5152_begin_0, end = var_5152_end_0, end_mask = var_5152_end_mask_0, x = var_5013_cast_fp16)[name = tensor("op_5152_cast_fp16")]; + tensor var_5159_begin_0 = const()[name = tensor("op_5159_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_5159_end_0 = const()[name = tensor("op_5159_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5159_end_mask_0 = const()[name = tensor("op_5159_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5159_cast_fp16 = slice_by_index(begin = var_5159_begin_0, end = var_5159_end_0, end_mask = var_5159_end_mask_0, x = var_5013_cast_fp16)[name = tensor("op_5159_cast_fp16")]; + tensor var_5166_begin_0 = const()[name = tensor("op_5166_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5166_end_0 = const()[name = tensor("op_5166_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_5166_end_mask_0 = const()[name = tensor("op_5166_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5166_cast_fp16 = slice_by_index(begin = var_5166_begin_0, end = var_5166_end_0, end_mask = var_5166_end_mask_0, x = var_5017_cast_fp16)[name = tensor("op_5166_cast_fp16")]; + tensor var_5173_begin_0 = const()[name = tensor("op_5173_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_5173_end_0 = const()[name = tensor("op_5173_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_5173_end_mask_0 = const()[name = tensor("op_5173_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5173_cast_fp16 = slice_by_index(begin = var_5173_begin_0, end = var_5173_end_0, end_mask = var_5173_end_mask_0, x = var_5017_cast_fp16)[name = tensor("op_5173_cast_fp16")]; + tensor var_5180_begin_0 = const()[name = tensor("op_5180_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_5180_end_0 = const()[name = tensor("op_5180_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_5180_end_mask_0 = const()[name = tensor("op_5180_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5180_cast_fp16 = slice_by_index(begin = var_5180_begin_0, end = var_5180_end_0, end_mask = var_5180_end_mask_0, x = var_5017_cast_fp16)[name = tensor("op_5180_cast_fp16")]; + tensor var_5187_begin_0 = const()[name = tensor("op_5187_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_5187_end_0 = const()[name = tensor("op_5187_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5187_end_mask_0 = const()[name = tensor("op_5187_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5187_cast_fp16 = slice_by_index(begin = var_5187_begin_0, end = var_5187_end_0, end_mask = var_5187_end_mask_0, x = var_5017_cast_fp16)[name = tensor("op_5187_cast_fp16")]; + tensor var_5194_begin_0 = const()[name = tensor("op_5194_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5194_end_0 = const()[name = tensor("op_5194_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_5194_end_mask_0 = const()[name = tensor("op_5194_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5194_cast_fp16 = slice_by_index(begin = var_5194_begin_0, end = var_5194_end_0, end_mask = var_5194_end_mask_0, x = var_5021_cast_fp16)[name = tensor("op_5194_cast_fp16")]; + tensor var_5201_begin_0 = const()[name = tensor("op_5201_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_5201_end_0 = const()[name = tensor("op_5201_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_5201_end_mask_0 = const()[name = tensor("op_5201_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5201_cast_fp16 = slice_by_index(begin = var_5201_begin_0, end = var_5201_end_0, end_mask = var_5201_end_mask_0, x = var_5021_cast_fp16)[name = tensor("op_5201_cast_fp16")]; + tensor var_5208_begin_0 = const()[name = tensor("op_5208_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_5208_end_0 = const()[name = tensor("op_5208_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_5208_end_mask_0 = const()[name = tensor("op_5208_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5208_cast_fp16 = slice_by_index(begin = var_5208_begin_0, end = var_5208_end_0, end_mask = var_5208_end_mask_0, x = var_5021_cast_fp16)[name = tensor("op_5208_cast_fp16")]; + tensor var_5215_begin_0 = const()[name = tensor("op_5215_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_5215_end_0 = const()[name = tensor("op_5215_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5215_end_mask_0 = const()[name = tensor("op_5215_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5215_cast_fp16 = slice_by_index(begin = var_5215_begin_0, end = var_5215_end_0, end_mask = var_5215_end_mask_0, x = var_5021_cast_fp16)[name = tensor("op_5215_cast_fp16")]; + tensor var_5222_begin_0 = const()[name = tensor("op_5222_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5222_end_0 = const()[name = tensor("op_5222_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_5222_end_mask_0 = const()[name = tensor("op_5222_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5222_cast_fp16 = slice_by_index(begin = var_5222_begin_0, end = var_5222_end_0, end_mask = var_5222_end_mask_0, x = var_5025_cast_fp16)[name = tensor("op_5222_cast_fp16")]; + tensor var_5229_begin_0 = const()[name = tensor("op_5229_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_5229_end_0 = const()[name = tensor("op_5229_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_5229_end_mask_0 = const()[name = tensor("op_5229_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5229_cast_fp16 = slice_by_index(begin = var_5229_begin_0, end = var_5229_end_0, end_mask = var_5229_end_mask_0, x = var_5025_cast_fp16)[name = tensor("op_5229_cast_fp16")]; + tensor var_5236_begin_0 = const()[name = tensor("op_5236_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_5236_end_0 = const()[name = tensor("op_5236_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_5236_end_mask_0 = const()[name = tensor("op_5236_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5236_cast_fp16 = slice_by_index(begin = var_5236_begin_0, end = var_5236_end_0, end_mask = var_5236_end_mask_0, x = var_5025_cast_fp16)[name = tensor("op_5236_cast_fp16")]; + tensor var_5243_begin_0 = const()[name = tensor("op_5243_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_5243_end_0 = const()[name = tensor("op_5243_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5243_end_mask_0 = const()[name = tensor("op_5243_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5243_cast_fp16 = slice_by_index(begin = var_5243_begin_0, end = var_5243_end_0, end_mask = var_5243_end_mask_0, x = var_5025_cast_fp16)[name = tensor("op_5243_cast_fp16")]; + tensor var_5250_begin_0 = const()[name = tensor("op_5250_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5250_end_0 = const()[name = tensor("op_5250_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_5250_end_mask_0 = const()[name = tensor("op_5250_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5250_cast_fp16 = slice_by_index(begin = var_5250_begin_0, end = var_5250_end_0, end_mask = var_5250_end_mask_0, x = var_5029_cast_fp16)[name = tensor("op_5250_cast_fp16")]; + tensor var_5257_begin_0 = const()[name = tensor("op_5257_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_5257_end_0 = const()[name = tensor("op_5257_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_5257_end_mask_0 = const()[name = tensor("op_5257_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5257_cast_fp16 = slice_by_index(begin = var_5257_begin_0, end = var_5257_end_0, end_mask = var_5257_end_mask_0, x = var_5029_cast_fp16)[name = tensor("op_5257_cast_fp16")]; + tensor var_5264_begin_0 = const()[name = tensor("op_5264_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_5264_end_0 = const()[name = tensor("op_5264_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_5264_end_mask_0 = const()[name = tensor("op_5264_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5264_cast_fp16 = slice_by_index(begin = var_5264_begin_0, end = var_5264_end_0, end_mask = var_5264_end_mask_0, x = var_5029_cast_fp16)[name = tensor("op_5264_cast_fp16")]; + tensor var_5271_begin_0 = const()[name = tensor("op_5271_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_5271_end_0 = const()[name = tensor("op_5271_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5271_end_mask_0 = const()[name = tensor("op_5271_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5271_cast_fp16 = slice_by_index(begin = var_5271_begin_0, end = var_5271_end_0, end_mask = var_5271_end_mask_0, x = var_5029_cast_fp16)[name = tensor("op_5271_cast_fp16")]; + tensor var_5278_begin_0 = const()[name = tensor("op_5278_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5278_end_0 = const()[name = tensor("op_5278_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_5278_end_mask_0 = const()[name = tensor("op_5278_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5278_cast_fp16 = slice_by_index(begin = var_5278_begin_0, end = var_5278_end_0, end_mask = var_5278_end_mask_0, x = var_5033_cast_fp16)[name = tensor("op_5278_cast_fp16")]; + tensor var_5285_begin_0 = const()[name = tensor("op_5285_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_5285_end_0 = const()[name = tensor("op_5285_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_5285_end_mask_0 = const()[name = tensor("op_5285_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5285_cast_fp16 = slice_by_index(begin = var_5285_begin_0, end = var_5285_end_0, end_mask = var_5285_end_mask_0, x = var_5033_cast_fp16)[name = tensor("op_5285_cast_fp16")]; + tensor var_5292_begin_0 = const()[name = tensor("op_5292_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_5292_end_0 = const()[name = tensor("op_5292_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_5292_end_mask_0 = const()[name = tensor("op_5292_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5292_cast_fp16 = slice_by_index(begin = var_5292_begin_0, end = var_5292_end_0, end_mask = var_5292_end_mask_0, x = var_5033_cast_fp16)[name = tensor("op_5292_cast_fp16")]; + tensor var_5299_begin_0 = const()[name = tensor("op_5299_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_5299_end_0 = const()[name = tensor("op_5299_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5299_end_mask_0 = const()[name = tensor("op_5299_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5299_cast_fp16 = slice_by_index(begin = var_5299_begin_0, end = var_5299_end_0, end_mask = var_5299_end_mask_0, x = var_5033_cast_fp16)[name = tensor("op_5299_cast_fp16")]; + tensor var_5306_begin_0 = const()[name = tensor("op_5306_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5306_end_0 = const()[name = tensor("op_5306_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_5306_end_mask_0 = const()[name = tensor("op_5306_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5306_cast_fp16 = slice_by_index(begin = var_5306_begin_0, end = var_5306_end_0, end_mask = var_5306_end_mask_0, x = var_5037_cast_fp16)[name = tensor("op_5306_cast_fp16")]; + tensor var_5313_begin_0 = const()[name = tensor("op_5313_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_5313_end_0 = const()[name = tensor("op_5313_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_5313_end_mask_0 = const()[name = tensor("op_5313_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5313_cast_fp16 = slice_by_index(begin = var_5313_begin_0, end = var_5313_end_0, end_mask = var_5313_end_mask_0, x = var_5037_cast_fp16)[name = tensor("op_5313_cast_fp16")]; + tensor var_5320_begin_0 = const()[name = tensor("op_5320_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_5320_end_0 = const()[name = tensor("op_5320_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_5320_end_mask_0 = const()[name = tensor("op_5320_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5320_cast_fp16 = slice_by_index(begin = var_5320_begin_0, end = var_5320_end_0, end_mask = var_5320_end_mask_0, x = var_5037_cast_fp16)[name = tensor("op_5320_cast_fp16")]; + tensor var_5327_begin_0 = const()[name = tensor("op_5327_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_5327_end_0 = const()[name = tensor("op_5327_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5327_end_mask_0 = const()[name = tensor("op_5327_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5327_cast_fp16 = slice_by_index(begin = var_5327_begin_0, end = var_5327_end_0, end_mask = var_5327_end_mask_0, x = var_5037_cast_fp16)[name = tensor("op_5327_cast_fp16")]; + tensor var_5334_begin_0 = const()[name = tensor("op_5334_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5334_end_0 = const()[name = tensor("op_5334_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_5334_end_mask_0 = const()[name = tensor("op_5334_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5334_cast_fp16 = slice_by_index(begin = var_5334_begin_0, end = var_5334_end_0, end_mask = var_5334_end_mask_0, x = var_5041_cast_fp16)[name = tensor("op_5334_cast_fp16")]; + tensor var_5341_begin_0 = const()[name = tensor("op_5341_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_5341_end_0 = const()[name = tensor("op_5341_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_5341_end_mask_0 = const()[name = tensor("op_5341_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5341_cast_fp16 = slice_by_index(begin = var_5341_begin_0, end = var_5341_end_0, end_mask = var_5341_end_mask_0, x = var_5041_cast_fp16)[name = tensor("op_5341_cast_fp16")]; + tensor var_5348_begin_0 = const()[name = tensor("op_5348_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_5348_end_0 = const()[name = tensor("op_5348_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_5348_end_mask_0 = const()[name = tensor("op_5348_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5348_cast_fp16 = slice_by_index(begin = var_5348_begin_0, end = var_5348_end_0, end_mask = var_5348_end_mask_0, x = var_5041_cast_fp16)[name = tensor("op_5348_cast_fp16")]; + tensor var_5355_begin_0 = const()[name = tensor("op_5355_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_5355_end_0 = const()[name = tensor("op_5355_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5355_end_mask_0 = const()[name = tensor("op_5355_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5355_cast_fp16 = slice_by_index(begin = var_5355_begin_0, end = var_5355_end_0, end_mask = var_5355_end_mask_0, x = var_5041_cast_fp16)[name = tensor("op_5355_cast_fp16")]; + tensor var_5362_begin_0 = const()[name = tensor("op_5362_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5362_end_0 = const()[name = tensor("op_5362_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_5362_end_mask_0 = const()[name = tensor("op_5362_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5362_cast_fp16 = slice_by_index(begin = var_5362_begin_0, end = var_5362_end_0, end_mask = var_5362_end_mask_0, x = var_5045_cast_fp16)[name = tensor("op_5362_cast_fp16")]; + tensor var_5369_begin_0 = const()[name = tensor("op_5369_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_5369_end_0 = const()[name = tensor("op_5369_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_5369_end_mask_0 = const()[name = tensor("op_5369_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5369_cast_fp16 = slice_by_index(begin = var_5369_begin_0, end = var_5369_end_0, end_mask = var_5369_end_mask_0, x = var_5045_cast_fp16)[name = tensor("op_5369_cast_fp16")]; + tensor var_5376_begin_0 = const()[name = tensor("op_5376_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_5376_end_0 = const()[name = tensor("op_5376_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_5376_end_mask_0 = const()[name = tensor("op_5376_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5376_cast_fp16 = slice_by_index(begin = var_5376_begin_0, end = var_5376_end_0, end_mask = var_5376_end_mask_0, x = var_5045_cast_fp16)[name = tensor("op_5376_cast_fp16")]; + tensor var_5383_begin_0 = const()[name = tensor("op_5383_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_5383_end_0 = const()[name = tensor("op_5383_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5383_end_mask_0 = const()[name = tensor("op_5383_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5383_cast_fp16 = slice_by_index(begin = var_5383_begin_0, end = var_5383_end_0, end_mask = var_5383_end_mask_0, x = var_5045_cast_fp16)[name = tensor("op_5383_cast_fp16")]; + tensor k_11_perm_0 = const()[name = tensor("k_11_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_5388_begin_0 = const()[name = tensor("op_5388_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5388_end_0 = const()[name = tensor("op_5388_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_5388_end_mask_0 = const()[name = tensor("op_5388_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_6 = transpose(perm = k_11_perm_0, x = key_11_cast_fp16)[name = tensor("transpose_6")]; + tensor var_5388_cast_fp16 = slice_by_index(begin = var_5388_begin_0, end = var_5388_end_0, end_mask = var_5388_end_mask_0, x = transpose_6)[name = tensor("op_5388_cast_fp16")]; + tensor var_5392_begin_0 = const()[name = tensor("op_5392_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_5392_end_0 = const()[name = tensor("op_5392_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_5392_end_mask_0 = const()[name = tensor("op_5392_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5392_cast_fp16 = slice_by_index(begin = var_5392_begin_0, end = var_5392_end_0, end_mask = var_5392_end_mask_0, x = transpose_6)[name = tensor("op_5392_cast_fp16")]; + tensor var_5396_begin_0 = const()[name = tensor("op_5396_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_5396_end_0 = const()[name = tensor("op_5396_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_5396_end_mask_0 = const()[name = tensor("op_5396_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5396_cast_fp16 = slice_by_index(begin = var_5396_begin_0, end = var_5396_end_0, end_mask = var_5396_end_mask_0, x = transpose_6)[name = tensor("op_5396_cast_fp16")]; + tensor var_5400_begin_0 = const()[name = tensor("op_5400_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_5400_end_0 = const()[name = tensor("op_5400_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_5400_end_mask_0 = const()[name = tensor("op_5400_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5400_cast_fp16 = slice_by_index(begin = var_5400_begin_0, end = var_5400_end_0, end_mask = var_5400_end_mask_0, x = transpose_6)[name = tensor("op_5400_cast_fp16")]; + tensor var_5404_begin_0 = const()[name = tensor("op_5404_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_5404_end_0 = const()[name = tensor("op_5404_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_5404_end_mask_0 = const()[name = tensor("op_5404_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5404_cast_fp16 = slice_by_index(begin = var_5404_begin_0, end = var_5404_end_0, end_mask = var_5404_end_mask_0, x = transpose_6)[name = tensor("op_5404_cast_fp16")]; + tensor var_5408_begin_0 = const()[name = tensor("op_5408_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_5408_end_0 = const()[name = tensor("op_5408_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_5408_end_mask_0 = const()[name = tensor("op_5408_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5408_cast_fp16 = slice_by_index(begin = var_5408_begin_0, end = var_5408_end_0, end_mask = var_5408_end_mask_0, x = transpose_6)[name = tensor("op_5408_cast_fp16")]; + tensor var_5412_begin_0 = const()[name = tensor("op_5412_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_5412_end_0 = const()[name = tensor("op_5412_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_5412_end_mask_0 = const()[name = tensor("op_5412_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5412_cast_fp16 = slice_by_index(begin = var_5412_begin_0, end = var_5412_end_0, end_mask = var_5412_end_mask_0, x = transpose_6)[name = tensor("op_5412_cast_fp16")]; + tensor var_5416_begin_0 = const()[name = tensor("op_5416_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_5416_end_0 = const()[name = tensor("op_5416_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_5416_end_mask_0 = const()[name = tensor("op_5416_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5416_cast_fp16 = slice_by_index(begin = var_5416_begin_0, end = var_5416_end_0, end_mask = var_5416_end_mask_0, x = transpose_6)[name = tensor("op_5416_cast_fp16")]; + tensor var_5420_begin_0 = const()[name = tensor("op_5420_begin_0"), val = tensor([0, 0, 0, 512])]; + tensor var_5420_end_0 = const()[name = tensor("op_5420_end_0"), val = tensor([1, 1500, 1, 576])]; + tensor var_5420_end_mask_0 = const()[name = tensor("op_5420_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5420_cast_fp16 = slice_by_index(begin = var_5420_begin_0, end = var_5420_end_0, end_mask = var_5420_end_mask_0, x = transpose_6)[name = tensor("op_5420_cast_fp16")]; + tensor var_5424_begin_0 = const()[name = tensor("op_5424_begin_0"), val = tensor([0, 0, 0, 576])]; + tensor var_5424_end_0 = const()[name = tensor("op_5424_end_0"), val = tensor([1, 1500, 1, 640])]; + tensor var_5424_end_mask_0 = const()[name = tensor("op_5424_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5424_cast_fp16 = slice_by_index(begin = var_5424_begin_0, end = var_5424_end_0, end_mask = var_5424_end_mask_0, x = transpose_6)[name = tensor("op_5424_cast_fp16")]; + tensor var_5428_begin_0 = const()[name = tensor("op_5428_begin_0"), val = tensor([0, 0, 0, 640])]; + tensor var_5428_end_0 = const()[name = tensor("op_5428_end_0"), val = tensor([1, 1500, 1, 704])]; + tensor var_5428_end_mask_0 = const()[name = tensor("op_5428_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5428_cast_fp16 = slice_by_index(begin = var_5428_begin_0, end = var_5428_end_0, end_mask = var_5428_end_mask_0, x = transpose_6)[name = tensor("op_5428_cast_fp16")]; + tensor var_5432_begin_0 = const()[name = tensor("op_5432_begin_0"), val = tensor([0, 0, 0, 704])]; + tensor var_5432_end_0 = const()[name = tensor("op_5432_end_0"), val = tensor([1, 1500, 1, 768])]; + tensor var_5432_end_mask_0 = const()[name = tensor("op_5432_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_5432_cast_fp16 = slice_by_index(begin = var_5432_begin_0, end = var_5432_end_0, end_mask = var_5432_end_mask_0, x = transpose_6)[name = tensor("op_5432_cast_fp16")]; + tensor var_5434_begin_0 = const()[name = tensor("op_5434_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5434_end_0 = const()[name = tensor("op_5434_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5434_end_mask_0 = const()[name = tensor("op_5434_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5434_cast_fp16 = slice_by_index(begin = var_5434_begin_0, end = var_5434_end_0, end_mask = var_5434_end_mask_0, x = value_11_cast_fp16)[name = tensor("op_5434_cast_fp16")]; + tensor var_5438_begin_0 = const()[name = tensor("op_5438_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_5438_end_0 = const()[name = tensor("op_5438_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_5438_end_mask_0 = const()[name = tensor("op_5438_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5438_cast_fp16 = slice_by_index(begin = var_5438_begin_0, end = var_5438_end_0, end_mask = var_5438_end_mask_0, x = value_11_cast_fp16)[name = tensor("op_5438_cast_fp16")]; + tensor var_5442_begin_0 = const()[name = tensor("op_5442_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_5442_end_0 = const()[name = tensor("op_5442_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_5442_end_mask_0 = const()[name = tensor("op_5442_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5442_cast_fp16 = slice_by_index(begin = var_5442_begin_0, end = var_5442_end_0, end_mask = var_5442_end_mask_0, x = value_11_cast_fp16)[name = tensor("op_5442_cast_fp16")]; + tensor var_5446_begin_0 = const()[name = tensor("op_5446_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_5446_end_0 = const()[name = tensor("op_5446_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_5446_end_mask_0 = const()[name = tensor("op_5446_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5446_cast_fp16 = slice_by_index(begin = var_5446_begin_0, end = var_5446_end_0, end_mask = var_5446_end_mask_0, x = value_11_cast_fp16)[name = tensor("op_5446_cast_fp16")]; + tensor var_5450_begin_0 = const()[name = tensor("op_5450_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_5450_end_0 = const()[name = tensor("op_5450_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_5450_end_mask_0 = const()[name = tensor("op_5450_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5450_cast_fp16 = slice_by_index(begin = var_5450_begin_0, end = var_5450_end_0, end_mask = var_5450_end_mask_0, x = value_11_cast_fp16)[name = tensor("op_5450_cast_fp16")]; + tensor var_5454_begin_0 = const()[name = tensor("op_5454_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_5454_end_0 = const()[name = tensor("op_5454_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_5454_end_mask_0 = const()[name = tensor("op_5454_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5454_cast_fp16 = slice_by_index(begin = var_5454_begin_0, end = var_5454_end_0, end_mask = var_5454_end_mask_0, x = value_11_cast_fp16)[name = tensor("op_5454_cast_fp16")]; + tensor var_5458_begin_0 = const()[name = tensor("op_5458_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_5458_end_0 = const()[name = tensor("op_5458_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_5458_end_mask_0 = const()[name = tensor("op_5458_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5458_cast_fp16 = slice_by_index(begin = var_5458_begin_0, end = var_5458_end_0, end_mask = var_5458_end_mask_0, x = value_11_cast_fp16)[name = tensor("op_5458_cast_fp16")]; + tensor var_5462_begin_0 = const()[name = tensor("op_5462_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_5462_end_0 = const()[name = tensor("op_5462_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_5462_end_mask_0 = const()[name = tensor("op_5462_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5462_cast_fp16 = slice_by_index(begin = var_5462_begin_0, end = var_5462_end_0, end_mask = var_5462_end_mask_0, x = value_11_cast_fp16)[name = tensor("op_5462_cast_fp16")]; + tensor var_5466_begin_0 = const()[name = tensor("op_5466_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_5466_end_0 = const()[name = tensor("op_5466_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_5466_end_mask_0 = const()[name = tensor("op_5466_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5466_cast_fp16 = slice_by_index(begin = var_5466_begin_0, end = var_5466_end_0, end_mask = var_5466_end_mask_0, x = value_11_cast_fp16)[name = tensor("op_5466_cast_fp16")]; + tensor var_5470_begin_0 = const()[name = tensor("op_5470_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_5470_end_0 = const()[name = tensor("op_5470_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_5470_end_mask_0 = const()[name = tensor("op_5470_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5470_cast_fp16 = slice_by_index(begin = var_5470_begin_0, end = var_5470_end_0, end_mask = var_5470_end_mask_0, x = value_11_cast_fp16)[name = tensor("op_5470_cast_fp16")]; + tensor var_5474_begin_0 = const()[name = tensor("op_5474_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_5474_end_0 = const()[name = tensor("op_5474_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_5474_end_mask_0 = const()[name = tensor("op_5474_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5474_cast_fp16 = slice_by_index(begin = var_5474_begin_0, end = var_5474_end_0, end_mask = var_5474_end_mask_0, x = value_11_cast_fp16)[name = tensor("op_5474_cast_fp16")]; + tensor var_5478_begin_0 = const()[name = tensor("op_5478_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_5478_end_0 = const()[name = tensor("op_5478_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_5478_end_mask_0 = const()[name = tensor("op_5478_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5478_cast_fp16 = slice_by_index(begin = var_5478_begin_0, end = var_5478_end_0, end_mask = var_5478_end_mask_0, x = value_11_cast_fp16)[name = tensor("op_5478_cast_fp16")]; + tensor var_5482_equation_0 = const()[name = tensor("op_5482_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5482_cast_fp16 = einsum(equation = var_5482_equation_0, values = (var_5388_cast_fp16, var_5054_cast_fp16))[name = tensor("op_5482_cast_fp16")]; + tensor var_5483_to_fp16 = const()[name = tensor("op_5483_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_481_cast_fp16 = mul(x = var_5482_cast_fp16, y = var_5483_to_fp16)[name = tensor("aw_chunk_481_cast_fp16")]; + tensor var_5486_equation_0 = const()[name = tensor("op_5486_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5486_cast_fp16 = einsum(equation = var_5486_equation_0, values = (var_5388_cast_fp16, var_5061_cast_fp16))[name = tensor("op_5486_cast_fp16")]; + tensor var_5487_to_fp16 = const()[name = tensor("op_5487_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_483_cast_fp16 = mul(x = var_5486_cast_fp16, y = var_5487_to_fp16)[name = tensor("aw_chunk_483_cast_fp16")]; + tensor var_5490_equation_0 = const()[name = tensor("op_5490_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5490_cast_fp16 = einsum(equation = var_5490_equation_0, values = (var_5388_cast_fp16, var_5068_cast_fp16))[name = tensor("op_5490_cast_fp16")]; + tensor var_5491_to_fp16 = const()[name = tensor("op_5491_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_485_cast_fp16 = mul(x = var_5490_cast_fp16, y = var_5491_to_fp16)[name = tensor("aw_chunk_485_cast_fp16")]; + tensor var_5494_equation_0 = const()[name = tensor("op_5494_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5494_cast_fp16 = einsum(equation = var_5494_equation_0, values = (var_5388_cast_fp16, var_5075_cast_fp16))[name = tensor("op_5494_cast_fp16")]; + tensor var_5495_to_fp16 = const()[name = tensor("op_5495_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_487_cast_fp16 = mul(x = var_5494_cast_fp16, y = var_5495_to_fp16)[name = tensor("aw_chunk_487_cast_fp16")]; + tensor var_5498_equation_0 = const()[name = tensor("op_5498_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5498_cast_fp16 = einsum(equation = var_5498_equation_0, values = (var_5392_cast_fp16, var_5082_cast_fp16))[name = tensor("op_5498_cast_fp16")]; + tensor var_5499_to_fp16 = const()[name = tensor("op_5499_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_489_cast_fp16 = mul(x = var_5498_cast_fp16, y = var_5499_to_fp16)[name = tensor("aw_chunk_489_cast_fp16")]; + tensor var_5502_equation_0 = const()[name = tensor("op_5502_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5502_cast_fp16 = einsum(equation = var_5502_equation_0, values = (var_5392_cast_fp16, var_5089_cast_fp16))[name = tensor("op_5502_cast_fp16")]; + tensor var_5503_to_fp16 = const()[name = tensor("op_5503_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_491_cast_fp16 = mul(x = var_5502_cast_fp16, y = var_5503_to_fp16)[name = tensor("aw_chunk_491_cast_fp16")]; + tensor var_5506_equation_0 = const()[name = tensor("op_5506_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5506_cast_fp16 = einsum(equation = var_5506_equation_0, values = (var_5392_cast_fp16, var_5096_cast_fp16))[name = tensor("op_5506_cast_fp16")]; + tensor var_5507_to_fp16 = const()[name = tensor("op_5507_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_493_cast_fp16 = mul(x = var_5506_cast_fp16, y = var_5507_to_fp16)[name = tensor("aw_chunk_493_cast_fp16")]; + tensor var_5510_equation_0 = const()[name = tensor("op_5510_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5510_cast_fp16 = einsum(equation = var_5510_equation_0, values = (var_5392_cast_fp16, var_5103_cast_fp16))[name = tensor("op_5510_cast_fp16")]; + tensor var_5511_to_fp16 = const()[name = tensor("op_5511_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_495_cast_fp16 = mul(x = var_5510_cast_fp16, y = var_5511_to_fp16)[name = tensor("aw_chunk_495_cast_fp16")]; + tensor var_5514_equation_0 = const()[name = tensor("op_5514_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5514_cast_fp16 = einsum(equation = var_5514_equation_0, values = (var_5396_cast_fp16, var_5110_cast_fp16))[name = tensor("op_5514_cast_fp16")]; + tensor var_5515_to_fp16 = const()[name = tensor("op_5515_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_497_cast_fp16 = mul(x = var_5514_cast_fp16, y = var_5515_to_fp16)[name = tensor("aw_chunk_497_cast_fp16")]; + tensor var_5518_equation_0 = const()[name = tensor("op_5518_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5518_cast_fp16 = einsum(equation = var_5518_equation_0, values = (var_5396_cast_fp16, var_5117_cast_fp16))[name = tensor("op_5518_cast_fp16")]; + tensor var_5519_to_fp16 = const()[name = tensor("op_5519_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_499_cast_fp16 = mul(x = var_5518_cast_fp16, y = var_5519_to_fp16)[name = tensor("aw_chunk_499_cast_fp16")]; + tensor var_5522_equation_0 = const()[name = tensor("op_5522_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5522_cast_fp16 = einsum(equation = var_5522_equation_0, values = (var_5396_cast_fp16, var_5124_cast_fp16))[name = tensor("op_5522_cast_fp16")]; + tensor var_5523_to_fp16 = const()[name = tensor("op_5523_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_501_cast_fp16 = mul(x = var_5522_cast_fp16, y = var_5523_to_fp16)[name = tensor("aw_chunk_501_cast_fp16")]; + tensor var_5526_equation_0 = const()[name = tensor("op_5526_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5526_cast_fp16 = einsum(equation = var_5526_equation_0, values = (var_5396_cast_fp16, var_5131_cast_fp16))[name = tensor("op_5526_cast_fp16")]; + tensor var_5527_to_fp16 = const()[name = tensor("op_5527_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_503_cast_fp16 = mul(x = var_5526_cast_fp16, y = var_5527_to_fp16)[name = tensor("aw_chunk_503_cast_fp16")]; + tensor var_5530_equation_0 = const()[name = tensor("op_5530_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5530_cast_fp16 = einsum(equation = var_5530_equation_0, values = (var_5400_cast_fp16, var_5138_cast_fp16))[name = tensor("op_5530_cast_fp16")]; + tensor var_5531_to_fp16 = const()[name = tensor("op_5531_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_505_cast_fp16 = mul(x = var_5530_cast_fp16, y = var_5531_to_fp16)[name = tensor("aw_chunk_505_cast_fp16")]; + tensor var_5534_equation_0 = const()[name = tensor("op_5534_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5534_cast_fp16 = einsum(equation = var_5534_equation_0, values = (var_5400_cast_fp16, var_5145_cast_fp16))[name = tensor("op_5534_cast_fp16")]; + tensor var_5535_to_fp16 = const()[name = tensor("op_5535_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_507_cast_fp16 = mul(x = var_5534_cast_fp16, y = var_5535_to_fp16)[name = tensor("aw_chunk_507_cast_fp16")]; + tensor var_5538_equation_0 = const()[name = tensor("op_5538_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5538_cast_fp16 = einsum(equation = var_5538_equation_0, values = (var_5400_cast_fp16, var_5152_cast_fp16))[name = tensor("op_5538_cast_fp16")]; + tensor var_5539_to_fp16 = const()[name = tensor("op_5539_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_509_cast_fp16 = mul(x = var_5538_cast_fp16, y = var_5539_to_fp16)[name = tensor("aw_chunk_509_cast_fp16")]; + tensor var_5542_equation_0 = const()[name = tensor("op_5542_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5542_cast_fp16 = einsum(equation = var_5542_equation_0, values = (var_5400_cast_fp16, var_5159_cast_fp16))[name = tensor("op_5542_cast_fp16")]; + tensor var_5543_to_fp16 = const()[name = tensor("op_5543_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_511_cast_fp16 = mul(x = var_5542_cast_fp16, y = var_5543_to_fp16)[name = tensor("aw_chunk_511_cast_fp16")]; + tensor var_5546_equation_0 = const()[name = tensor("op_5546_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5546_cast_fp16 = einsum(equation = var_5546_equation_0, values = (var_5404_cast_fp16, var_5166_cast_fp16))[name = tensor("op_5546_cast_fp16")]; + tensor var_5547_to_fp16 = const()[name = tensor("op_5547_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_513_cast_fp16 = mul(x = var_5546_cast_fp16, y = var_5547_to_fp16)[name = tensor("aw_chunk_513_cast_fp16")]; + tensor var_5550_equation_0 = const()[name = tensor("op_5550_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5550_cast_fp16 = einsum(equation = var_5550_equation_0, values = (var_5404_cast_fp16, var_5173_cast_fp16))[name = tensor("op_5550_cast_fp16")]; + tensor var_5551_to_fp16 = const()[name = tensor("op_5551_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_515_cast_fp16 = mul(x = var_5550_cast_fp16, y = var_5551_to_fp16)[name = tensor("aw_chunk_515_cast_fp16")]; + tensor var_5554_equation_0 = const()[name = tensor("op_5554_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5554_cast_fp16 = einsum(equation = var_5554_equation_0, values = (var_5404_cast_fp16, var_5180_cast_fp16))[name = tensor("op_5554_cast_fp16")]; + tensor var_5555_to_fp16 = const()[name = tensor("op_5555_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_517_cast_fp16 = mul(x = var_5554_cast_fp16, y = var_5555_to_fp16)[name = tensor("aw_chunk_517_cast_fp16")]; + tensor var_5558_equation_0 = const()[name = tensor("op_5558_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5558_cast_fp16 = einsum(equation = var_5558_equation_0, values = (var_5404_cast_fp16, var_5187_cast_fp16))[name = tensor("op_5558_cast_fp16")]; + tensor var_5559_to_fp16 = const()[name = tensor("op_5559_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_519_cast_fp16 = mul(x = var_5558_cast_fp16, y = var_5559_to_fp16)[name = tensor("aw_chunk_519_cast_fp16")]; + tensor var_5562_equation_0 = const()[name = tensor("op_5562_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5562_cast_fp16 = einsum(equation = var_5562_equation_0, values = (var_5408_cast_fp16, var_5194_cast_fp16))[name = tensor("op_5562_cast_fp16")]; + tensor var_5563_to_fp16 = const()[name = tensor("op_5563_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_521_cast_fp16 = mul(x = var_5562_cast_fp16, y = var_5563_to_fp16)[name = tensor("aw_chunk_521_cast_fp16")]; + tensor var_5566_equation_0 = const()[name = tensor("op_5566_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5566_cast_fp16 = einsum(equation = var_5566_equation_0, values = (var_5408_cast_fp16, var_5201_cast_fp16))[name = tensor("op_5566_cast_fp16")]; + tensor var_5567_to_fp16 = const()[name = tensor("op_5567_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_523_cast_fp16 = mul(x = var_5566_cast_fp16, y = var_5567_to_fp16)[name = tensor("aw_chunk_523_cast_fp16")]; + tensor var_5570_equation_0 = const()[name = tensor("op_5570_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5570_cast_fp16 = einsum(equation = var_5570_equation_0, values = (var_5408_cast_fp16, var_5208_cast_fp16))[name = tensor("op_5570_cast_fp16")]; + tensor var_5571_to_fp16 = const()[name = tensor("op_5571_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_525_cast_fp16 = mul(x = var_5570_cast_fp16, y = var_5571_to_fp16)[name = tensor("aw_chunk_525_cast_fp16")]; + tensor var_5574_equation_0 = const()[name = tensor("op_5574_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5574_cast_fp16 = einsum(equation = var_5574_equation_0, values = (var_5408_cast_fp16, var_5215_cast_fp16))[name = tensor("op_5574_cast_fp16")]; + tensor var_5575_to_fp16 = const()[name = tensor("op_5575_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_527_cast_fp16 = mul(x = var_5574_cast_fp16, y = var_5575_to_fp16)[name = tensor("aw_chunk_527_cast_fp16")]; + tensor var_5578_equation_0 = const()[name = tensor("op_5578_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5578_cast_fp16 = einsum(equation = var_5578_equation_0, values = (var_5412_cast_fp16, var_5222_cast_fp16))[name = tensor("op_5578_cast_fp16")]; + tensor var_5579_to_fp16 = const()[name = tensor("op_5579_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_529_cast_fp16 = mul(x = var_5578_cast_fp16, y = var_5579_to_fp16)[name = tensor("aw_chunk_529_cast_fp16")]; + tensor var_5582_equation_0 = const()[name = tensor("op_5582_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5582_cast_fp16 = einsum(equation = var_5582_equation_0, values = (var_5412_cast_fp16, var_5229_cast_fp16))[name = tensor("op_5582_cast_fp16")]; + tensor var_5583_to_fp16 = const()[name = tensor("op_5583_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_531_cast_fp16 = mul(x = var_5582_cast_fp16, y = var_5583_to_fp16)[name = tensor("aw_chunk_531_cast_fp16")]; + tensor var_5586_equation_0 = const()[name = tensor("op_5586_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5586_cast_fp16 = einsum(equation = var_5586_equation_0, values = (var_5412_cast_fp16, var_5236_cast_fp16))[name = tensor("op_5586_cast_fp16")]; + tensor var_5587_to_fp16 = const()[name = tensor("op_5587_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_533_cast_fp16 = mul(x = var_5586_cast_fp16, y = var_5587_to_fp16)[name = tensor("aw_chunk_533_cast_fp16")]; + tensor var_5590_equation_0 = const()[name = tensor("op_5590_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5590_cast_fp16 = einsum(equation = var_5590_equation_0, values = (var_5412_cast_fp16, var_5243_cast_fp16))[name = tensor("op_5590_cast_fp16")]; + tensor var_5591_to_fp16 = const()[name = tensor("op_5591_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_535_cast_fp16 = mul(x = var_5590_cast_fp16, y = var_5591_to_fp16)[name = tensor("aw_chunk_535_cast_fp16")]; + tensor var_5594_equation_0 = const()[name = tensor("op_5594_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5594_cast_fp16 = einsum(equation = var_5594_equation_0, values = (var_5416_cast_fp16, var_5250_cast_fp16))[name = tensor("op_5594_cast_fp16")]; + tensor var_5595_to_fp16 = const()[name = tensor("op_5595_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_537_cast_fp16 = mul(x = var_5594_cast_fp16, y = var_5595_to_fp16)[name = tensor("aw_chunk_537_cast_fp16")]; + tensor var_5598_equation_0 = const()[name = tensor("op_5598_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5598_cast_fp16 = einsum(equation = var_5598_equation_0, values = (var_5416_cast_fp16, var_5257_cast_fp16))[name = tensor("op_5598_cast_fp16")]; + tensor var_5599_to_fp16 = const()[name = tensor("op_5599_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_539_cast_fp16 = mul(x = var_5598_cast_fp16, y = var_5599_to_fp16)[name = tensor("aw_chunk_539_cast_fp16")]; + tensor var_5602_equation_0 = const()[name = tensor("op_5602_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5602_cast_fp16 = einsum(equation = var_5602_equation_0, values = (var_5416_cast_fp16, var_5264_cast_fp16))[name = tensor("op_5602_cast_fp16")]; + tensor var_5603_to_fp16 = const()[name = tensor("op_5603_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_541_cast_fp16 = mul(x = var_5602_cast_fp16, y = var_5603_to_fp16)[name = tensor("aw_chunk_541_cast_fp16")]; + tensor var_5606_equation_0 = const()[name = tensor("op_5606_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5606_cast_fp16 = einsum(equation = var_5606_equation_0, values = (var_5416_cast_fp16, var_5271_cast_fp16))[name = tensor("op_5606_cast_fp16")]; + tensor var_5607_to_fp16 = const()[name = tensor("op_5607_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_543_cast_fp16 = mul(x = var_5606_cast_fp16, y = var_5607_to_fp16)[name = tensor("aw_chunk_543_cast_fp16")]; + tensor var_5610_equation_0 = const()[name = tensor("op_5610_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5610_cast_fp16 = einsum(equation = var_5610_equation_0, values = (var_5420_cast_fp16, var_5278_cast_fp16))[name = tensor("op_5610_cast_fp16")]; + tensor var_5611_to_fp16 = const()[name = tensor("op_5611_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_545_cast_fp16 = mul(x = var_5610_cast_fp16, y = var_5611_to_fp16)[name = tensor("aw_chunk_545_cast_fp16")]; + tensor var_5614_equation_0 = const()[name = tensor("op_5614_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5614_cast_fp16 = einsum(equation = var_5614_equation_0, values = (var_5420_cast_fp16, var_5285_cast_fp16))[name = tensor("op_5614_cast_fp16")]; + tensor var_5615_to_fp16 = const()[name = tensor("op_5615_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_547_cast_fp16 = mul(x = var_5614_cast_fp16, y = var_5615_to_fp16)[name = tensor("aw_chunk_547_cast_fp16")]; + tensor var_5618_equation_0 = const()[name = tensor("op_5618_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5618_cast_fp16 = einsum(equation = var_5618_equation_0, values = (var_5420_cast_fp16, var_5292_cast_fp16))[name = tensor("op_5618_cast_fp16")]; + tensor var_5619_to_fp16 = const()[name = tensor("op_5619_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_549_cast_fp16 = mul(x = var_5618_cast_fp16, y = var_5619_to_fp16)[name = tensor("aw_chunk_549_cast_fp16")]; + tensor var_5622_equation_0 = const()[name = tensor("op_5622_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5622_cast_fp16 = einsum(equation = var_5622_equation_0, values = (var_5420_cast_fp16, var_5299_cast_fp16))[name = tensor("op_5622_cast_fp16")]; + tensor var_5623_to_fp16 = const()[name = tensor("op_5623_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_551_cast_fp16 = mul(x = var_5622_cast_fp16, y = var_5623_to_fp16)[name = tensor("aw_chunk_551_cast_fp16")]; + tensor var_5626_equation_0 = const()[name = tensor("op_5626_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5626_cast_fp16 = einsum(equation = var_5626_equation_0, values = (var_5424_cast_fp16, var_5306_cast_fp16))[name = tensor("op_5626_cast_fp16")]; + tensor var_5627_to_fp16 = const()[name = tensor("op_5627_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_553_cast_fp16 = mul(x = var_5626_cast_fp16, y = var_5627_to_fp16)[name = tensor("aw_chunk_553_cast_fp16")]; + tensor var_5630_equation_0 = const()[name = tensor("op_5630_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5630_cast_fp16 = einsum(equation = var_5630_equation_0, values = (var_5424_cast_fp16, var_5313_cast_fp16))[name = tensor("op_5630_cast_fp16")]; + tensor var_5631_to_fp16 = const()[name = tensor("op_5631_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_555_cast_fp16 = mul(x = var_5630_cast_fp16, y = var_5631_to_fp16)[name = tensor("aw_chunk_555_cast_fp16")]; + tensor var_5634_equation_0 = const()[name = tensor("op_5634_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5634_cast_fp16 = einsum(equation = var_5634_equation_0, values = (var_5424_cast_fp16, var_5320_cast_fp16))[name = tensor("op_5634_cast_fp16")]; + tensor var_5635_to_fp16 = const()[name = tensor("op_5635_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_557_cast_fp16 = mul(x = var_5634_cast_fp16, y = var_5635_to_fp16)[name = tensor("aw_chunk_557_cast_fp16")]; + tensor var_5638_equation_0 = const()[name = tensor("op_5638_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5638_cast_fp16 = einsum(equation = var_5638_equation_0, values = (var_5424_cast_fp16, var_5327_cast_fp16))[name = tensor("op_5638_cast_fp16")]; + tensor var_5639_to_fp16 = const()[name = tensor("op_5639_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_559_cast_fp16 = mul(x = var_5638_cast_fp16, y = var_5639_to_fp16)[name = tensor("aw_chunk_559_cast_fp16")]; + tensor var_5642_equation_0 = const()[name = tensor("op_5642_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5642_cast_fp16 = einsum(equation = var_5642_equation_0, values = (var_5428_cast_fp16, var_5334_cast_fp16))[name = tensor("op_5642_cast_fp16")]; + tensor var_5643_to_fp16 = const()[name = tensor("op_5643_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_561_cast_fp16 = mul(x = var_5642_cast_fp16, y = var_5643_to_fp16)[name = tensor("aw_chunk_561_cast_fp16")]; + tensor var_5646_equation_0 = const()[name = tensor("op_5646_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5646_cast_fp16 = einsum(equation = var_5646_equation_0, values = (var_5428_cast_fp16, var_5341_cast_fp16))[name = tensor("op_5646_cast_fp16")]; + tensor var_5647_to_fp16 = const()[name = tensor("op_5647_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_563_cast_fp16 = mul(x = var_5646_cast_fp16, y = var_5647_to_fp16)[name = tensor("aw_chunk_563_cast_fp16")]; + tensor var_5650_equation_0 = const()[name = tensor("op_5650_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5650_cast_fp16 = einsum(equation = var_5650_equation_0, values = (var_5428_cast_fp16, var_5348_cast_fp16))[name = tensor("op_5650_cast_fp16")]; + tensor var_5651_to_fp16 = const()[name = tensor("op_5651_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_565_cast_fp16 = mul(x = var_5650_cast_fp16, y = var_5651_to_fp16)[name = tensor("aw_chunk_565_cast_fp16")]; + tensor var_5654_equation_0 = const()[name = tensor("op_5654_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5654_cast_fp16 = einsum(equation = var_5654_equation_0, values = (var_5428_cast_fp16, var_5355_cast_fp16))[name = tensor("op_5654_cast_fp16")]; + tensor var_5655_to_fp16 = const()[name = tensor("op_5655_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_567_cast_fp16 = mul(x = var_5654_cast_fp16, y = var_5655_to_fp16)[name = tensor("aw_chunk_567_cast_fp16")]; + tensor var_5658_equation_0 = const()[name = tensor("op_5658_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5658_cast_fp16 = einsum(equation = var_5658_equation_0, values = (var_5432_cast_fp16, var_5362_cast_fp16))[name = tensor("op_5658_cast_fp16")]; + tensor var_5659_to_fp16 = const()[name = tensor("op_5659_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_569_cast_fp16 = mul(x = var_5658_cast_fp16, y = var_5659_to_fp16)[name = tensor("aw_chunk_569_cast_fp16")]; + tensor var_5662_equation_0 = const()[name = tensor("op_5662_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5662_cast_fp16 = einsum(equation = var_5662_equation_0, values = (var_5432_cast_fp16, var_5369_cast_fp16))[name = tensor("op_5662_cast_fp16")]; + tensor var_5663_to_fp16 = const()[name = tensor("op_5663_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_571_cast_fp16 = mul(x = var_5662_cast_fp16, y = var_5663_to_fp16)[name = tensor("aw_chunk_571_cast_fp16")]; + tensor var_5666_equation_0 = const()[name = tensor("op_5666_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5666_cast_fp16 = einsum(equation = var_5666_equation_0, values = (var_5432_cast_fp16, var_5376_cast_fp16))[name = tensor("op_5666_cast_fp16")]; + tensor var_5667_to_fp16 = const()[name = tensor("op_5667_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_573_cast_fp16 = mul(x = var_5666_cast_fp16, y = var_5667_to_fp16)[name = tensor("aw_chunk_573_cast_fp16")]; + tensor var_5670_equation_0 = const()[name = tensor("op_5670_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_5670_cast_fp16 = einsum(equation = var_5670_equation_0, values = (var_5432_cast_fp16, var_5383_cast_fp16))[name = tensor("op_5670_cast_fp16")]; + tensor var_5671_to_fp16 = const()[name = tensor("op_5671_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_575_cast_fp16 = mul(x = var_5670_cast_fp16, y = var_5671_to_fp16)[name = tensor("aw_chunk_575_cast_fp16")]; + tensor var_5673_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_481_cast_fp16)[name = tensor("op_5673_cast_fp16")]; + tensor var_5674_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_483_cast_fp16)[name = tensor("op_5674_cast_fp16")]; + tensor var_5675_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_485_cast_fp16)[name = tensor("op_5675_cast_fp16")]; + tensor var_5676_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_487_cast_fp16)[name = tensor("op_5676_cast_fp16")]; + tensor var_5677_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_489_cast_fp16)[name = tensor("op_5677_cast_fp16")]; + tensor var_5678_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_491_cast_fp16)[name = tensor("op_5678_cast_fp16")]; + tensor var_5679_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_493_cast_fp16)[name = tensor("op_5679_cast_fp16")]; + tensor var_5680_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_495_cast_fp16)[name = tensor("op_5680_cast_fp16")]; + tensor var_5681_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_497_cast_fp16)[name = tensor("op_5681_cast_fp16")]; + tensor var_5682_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_499_cast_fp16)[name = tensor("op_5682_cast_fp16")]; + tensor var_5683_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_501_cast_fp16)[name = tensor("op_5683_cast_fp16")]; + tensor var_5684_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_503_cast_fp16)[name = tensor("op_5684_cast_fp16")]; + tensor var_5685_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_505_cast_fp16)[name = tensor("op_5685_cast_fp16")]; + tensor var_5686_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_507_cast_fp16)[name = tensor("op_5686_cast_fp16")]; + tensor var_5687_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_509_cast_fp16)[name = tensor("op_5687_cast_fp16")]; + tensor var_5688_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_511_cast_fp16)[name = tensor("op_5688_cast_fp16")]; + tensor var_5689_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_513_cast_fp16)[name = tensor("op_5689_cast_fp16")]; + tensor var_5690_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_515_cast_fp16)[name = tensor("op_5690_cast_fp16")]; + tensor var_5691_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_517_cast_fp16)[name = tensor("op_5691_cast_fp16")]; + tensor var_5692_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_519_cast_fp16)[name = tensor("op_5692_cast_fp16")]; + tensor var_5693_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_521_cast_fp16)[name = tensor("op_5693_cast_fp16")]; + tensor var_5694_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_523_cast_fp16)[name = tensor("op_5694_cast_fp16")]; + tensor var_5695_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_525_cast_fp16)[name = tensor("op_5695_cast_fp16")]; + tensor var_5696_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_527_cast_fp16)[name = tensor("op_5696_cast_fp16")]; + tensor var_5697_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_529_cast_fp16)[name = tensor("op_5697_cast_fp16")]; + tensor var_5698_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_531_cast_fp16)[name = tensor("op_5698_cast_fp16")]; + tensor var_5699_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_533_cast_fp16)[name = tensor("op_5699_cast_fp16")]; + tensor var_5700_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_535_cast_fp16)[name = tensor("op_5700_cast_fp16")]; + tensor var_5701_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_537_cast_fp16)[name = tensor("op_5701_cast_fp16")]; + tensor var_5702_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_539_cast_fp16)[name = tensor("op_5702_cast_fp16")]; + tensor var_5703_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_541_cast_fp16)[name = tensor("op_5703_cast_fp16")]; + tensor var_5704_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_543_cast_fp16)[name = tensor("op_5704_cast_fp16")]; + tensor var_5705_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_545_cast_fp16)[name = tensor("op_5705_cast_fp16")]; + tensor var_5706_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_547_cast_fp16)[name = tensor("op_5706_cast_fp16")]; + tensor var_5707_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_549_cast_fp16)[name = tensor("op_5707_cast_fp16")]; + tensor var_5708_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_551_cast_fp16)[name = tensor("op_5708_cast_fp16")]; + tensor var_5709_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_553_cast_fp16)[name = tensor("op_5709_cast_fp16")]; + tensor var_5710_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_555_cast_fp16)[name = tensor("op_5710_cast_fp16")]; + tensor var_5711_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_557_cast_fp16)[name = tensor("op_5711_cast_fp16")]; + tensor var_5712_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_559_cast_fp16)[name = tensor("op_5712_cast_fp16")]; + tensor var_5713_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_561_cast_fp16)[name = tensor("op_5713_cast_fp16")]; + tensor var_5714_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_563_cast_fp16)[name = tensor("op_5714_cast_fp16")]; + tensor var_5715_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_565_cast_fp16)[name = tensor("op_5715_cast_fp16")]; + tensor var_5716_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_567_cast_fp16)[name = tensor("op_5716_cast_fp16")]; + tensor var_5717_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_569_cast_fp16)[name = tensor("op_5717_cast_fp16")]; + tensor var_5718_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_571_cast_fp16)[name = tensor("op_5718_cast_fp16")]; + tensor var_5719_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_573_cast_fp16)[name = tensor("op_5719_cast_fp16")]; + tensor var_5720_cast_fp16 = softmax(axis = var_4946, x = aw_chunk_575_cast_fp16)[name = tensor("op_5720_cast_fp16")]; + tensor var_5722_equation_0 = const()[name = tensor("op_5722_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5722_cast_fp16 = einsum(equation = var_5722_equation_0, values = (var_5434_cast_fp16, var_5673_cast_fp16))[name = tensor("op_5722_cast_fp16")]; + tensor var_5724_equation_0 = const()[name = tensor("op_5724_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5724_cast_fp16 = einsum(equation = var_5724_equation_0, values = (var_5434_cast_fp16, var_5674_cast_fp16))[name = tensor("op_5724_cast_fp16")]; + tensor var_5726_equation_0 = const()[name = tensor("op_5726_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5726_cast_fp16 = einsum(equation = var_5726_equation_0, values = (var_5434_cast_fp16, var_5675_cast_fp16))[name = tensor("op_5726_cast_fp16")]; + tensor var_5728_equation_0 = const()[name = tensor("op_5728_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5728_cast_fp16 = einsum(equation = var_5728_equation_0, values = (var_5434_cast_fp16, var_5676_cast_fp16))[name = tensor("op_5728_cast_fp16")]; + tensor var_5730_equation_0 = const()[name = tensor("op_5730_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5730_cast_fp16 = einsum(equation = var_5730_equation_0, values = (var_5438_cast_fp16, var_5677_cast_fp16))[name = tensor("op_5730_cast_fp16")]; + tensor var_5732_equation_0 = const()[name = tensor("op_5732_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5732_cast_fp16 = einsum(equation = var_5732_equation_0, values = (var_5438_cast_fp16, var_5678_cast_fp16))[name = tensor("op_5732_cast_fp16")]; + tensor var_5734_equation_0 = const()[name = tensor("op_5734_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5734_cast_fp16 = einsum(equation = var_5734_equation_0, values = (var_5438_cast_fp16, var_5679_cast_fp16))[name = tensor("op_5734_cast_fp16")]; + tensor var_5736_equation_0 = const()[name = tensor("op_5736_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5736_cast_fp16 = einsum(equation = var_5736_equation_0, values = (var_5438_cast_fp16, var_5680_cast_fp16))[name = tensor("op_5736_cast_fp16")]; + tensor var_5738_equation_0 = const()[name = tensor("op_5738_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5738_cast_fp16 = einsum(equation = var_5738_equation_0, values = (var_5442_cast_fp16, var_5681_cast_fp16))[name = tensor("op_5738_cast_fp16")]; + tensor var_5740_equation_0 = const()[name = tensor("op_5740_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5740_cast_fp16 = einsum(equation = var_5740_equation_0, values = (var_5442_cast_fp16, var_5682_cast_fp16))[name = tensor("op_5740_cast_fp16")]; + tensor var_5742_equation_0 = const()[name = tensor("op_5742_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5742_cast_fp16 = einsum(equation = var_5742_equation_0, values = (var_5442_cast_fp16, var_5683_cast_fp16))[name = tensor("op_5742_cast_fp16")]; + tensor var_5744_equation_0 = const()[name = tensor("op_5744_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5744_cast_fp16 = einsum(equation = var_5744_equation_0, values = (var_5442_cast_fp16, var_5684_cast_fp16))[name = tensor("op_5744_cast_fp16")]; + tensor var_5746_equation_0 = const()[name = tensor("op_5746_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5746_cast_fp16 = einsum(equation = var_5746_equation_0, values = (var_5446_cast_fp16, var_5685_cast_fp16))[name = tensor("op_5746_cast_fp16")]; + tensor var_5748_equation_0 = const()[name = tensor("op_5748_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5748_cast_fp16 = einsum(equation = var_5748_equation_0, values = (var_5446_cast_fp16, var_5686_cast_fp16))[name = tensor("op_5748_cast_fp16")]; + tensor var_5750_equation_0 = const()[name = tensor("op_5750_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5750_cast_fp16 = einsum(equation = var_5750_equation_0, values = (var_5446_cast_fp16, var_5687_cast_fp16))[name = tensor("op_5750_cast_fp16")]; + tensor var_5752_equation_0 = const()[name = tensor("op_5752_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5752_cast_fp16 = einsum(equation = var_5752_equation_0, values = (var_5446_cast_fp16, var_5688_cast_fp16))[name = tensor("op_5752_cast_fp16")]; + tensor var_5754_equation_0 = const()[name = tensor("op_5754_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5754_cast_fp16 = einsum(equation = var_5754_equation_0, values = (var_5450_cast_fp16, var_5689_cast_fp16))[name = tensor("op_5754_cast_fp16")]; + tensor var_5756_equation_0 = const()[name = tensor("op_5756_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5756_cast_fp16 = einsum(equation = var_5756_equation_0, values = (var_5450_cast_fp16, var_5690_cast_fp16))[name = tensor("op_5756_cast_fp16")]; + tensor var_5758_equation_0 = const()[name = tensor("op_5758_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5758_cast_fp16 = einsum(equation = var_5758_equation_0, values = (var_5450_cast_fp16, var_5691_cast_fp16))[name = tensor("op_5758_cast_fp16")]; + tensor var_5760_equation_0 = const()[name = tensor("op_5760_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5760_cast_fp16 = einsum(equation = var_5760_equation_0, values = (var_5450_cast_fp16, var_5692_cast_fp16))[name = tensor("op_5760_cast_fp16")]; + tensor var_5762_equation_0 = const()[name = tensor("op_5762_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5762_cast_fp16 = einsum(equation = var_5762_equation_0, values = (var_5454_cast_fp16, var_5693_cast_fp16))[name = tensor("op_5762_cast_fp16")]; + tensor var_5764_equation_0 = const()[name = tensor("op_5764_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5764_cast_fp16 = einsum(equation = var_5764_equation_0, values = (var_5454_cast_fp16, var_5694_cast_fp16))[name = tensor("op_5764_cast_fp16")]; + tensor var_5766_equation_0 = const()[name = tensor("op_5766_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5766_cast_fp16 = einsum(equation = var_5766_equation_0, values = (var_5454_cast_fp16, var_5695_cast_fp16))[name = tensor("op_5766_cast_fp16")]; + tensor var_5768_equation_0 = const()[name = tensor("op_5768_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5768_cast_fp16 = einsum(equation = var_5768_equation_0, values = (var_5454_cast_fp16, var_5696_cast_fp16))[name = tensor("op_5768_cast_fp16")]; + tensor var_5770_equation_0 = const()[name = tensor("op_5770_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5770_cast_fp16 = einsum(equation = var_5770_equation_0, values = (var_5458_cast_fp16, var_5697_cast_fp16))[name = tensor("op_5770_cast_fp16")]; + tensor var_5772_equation_0 = const()[name = tensor("op_5772_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5772_cast_fp16 = einsum(equation = var_5772_equation_0, values = (var_5458_cast_fp16, var_5698_cast_fp16))[name = tensor("op_5772_cast_fp16")]; + tensor var_5774_equation_0 = const()[name = tensor("op_5774_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5774_cast_fp16 = einsum(equation = var_5774_equation_0, values = (var_5458_cast_fp16, var_5699_cast_fp16))[name = tensor("op_5774_cast_fp16")]; + tensor var_5776_equation_0 = const()[name = tensor("op_5776_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5776_cast_fp16 = einsum(equation = var_5776_equation_0, values = (var_5458_cast_fp16, var_5700_cast_fp16))[name = tensor("op_5776_cast_fp16")]; + tensor var_5778_equation_0 = const()[name = tensor("op_5778_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5778_cast_fp16 = einsum(equation = var_5778_equation_0, values = (var_5462_cast_fp16, var_5701_cast_fp16))[name = tensor("op_5778_cast_fp16")]; + tensor var_5780_equation_0 = const()[name = tensor("op_5780_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5780_cast_fp16 = einsum(equation = var_5780_equation_0, values = (var_5462_cast_fp16, var_5702_cast_fp16))[name = tensor("op_5780_cast_fp16")]; + tensor var_5782_equation_0 = const()[name = tensor("op_5782_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5782_cast_fp16 = einsum(equation = var_5782_equation_0, values = (var_5462_cast_fp16, var_5703_cast_fp16))[name = tensor("op_5782_cast_fp16")]; + tensor var_5784_equation_0 = const()[name = tensor("op_5784_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5784_cast_fp16 = einsum(equation = var_5784_equation_0, values = (var_5462_cast_fp16, var_5704_cast_fp16))[name = tensor("op_5784_cast_fp16")]; + tensor var_5786_equation_0 = const()[name = tensor("op_5786_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5786_cast_fp16 = einsum(equation = var_5786_equation_0, values = (var_5466_cast_fp16, var_5705_cast_fp16))[name = tensor("op_5786_cast_fp16")]; + tensor var_5788_equation_0 = const()[name = tensor("op_5788_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5788_cast_fp16 = einsum(equation = var_5788_equation_0, values = (var_5466_cast_fp16, var_5706_cast_fp16))[name = tensor("op_5788_cast_fp16")]; + tensor var_5790_equation_0 = const()[name = tensor("op_5790_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5790_cast_fp16 = einsum(equation = var_5790_equation_0, values = (var_5466_cast_fp16, var_5707_cast_fp16))[name = tensor("op_5790_cast_fp16")]; + tensor var_5792_equation_0 = const()[name = tensor("op_5792_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5792_cast_fp16 = einsum(equation = var_5792_equation_0, values = (var_5466_cast_fp16, var_5708_cast_fp16))[name = tensor("op_5792_cast_fp16")]; + tensor var_5794_equation_0 = const()[name = tensor("op_5794_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5794_cast_fp16 = einsum(equation = var_5794_equation_0, values = (var_5470_cast_fp16, var_5709_cast_fp16))[name = tensor("op_5794_cast_fp16")]; + tensor var_5796_equation_0 = const()[name = tensor("op_5796_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5796_cast_fp16 = einsum(equation = var_5796_equation_0, values = (var_5470_cast_fp16, var_5710_cast_fp16))[name = tensor("op_5796_cast_fp16")]; + tensor var_5798_equation_0 = const()[name = tensor("op_5798_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5798_cast_fp16 = einsum(equation = var_5798_equation_0, values = (var_5470_cast_fp16, var_5711_cast_fp16))[name = tensor("op_5798_cast_fp16")]; + tensor var_5800_equation_0 = const()[name = tensor("op_5800_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5800_cast_fp16 = einsum(equation = var_5800_equation_0, values = (var_5470_cast_fp16, var_5712_cast_fp16))[name = tensor("op_5800_cast_fp16")]; + tensor var_5802_equation_0 = const()[name = tensor("op_5802_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5802_cast_fp16 = einsum(equation = var_5802_equation_0, values = (var_5474_cast_fp16, var_5713_cast_fp16))[name = tensor("op_5802_cast_fp16")]; + tensor var_5804_equation_0 = const()[name = tensor("op_5804_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5804_cast_fp16 = einsum(equation = var_5804_equation_0, values = (var_5474_cast_fp16, var_5714_cast_fp16))[name = tensor("op_5804_cast_fp16")]; + tensor var_5806_equation_0 = const()[name = tensor("op_5806_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5806_cast_fp16 = einsum(equation = var_5806_equation_0, values = (var_5474_cast_fp16, var_5715_cast_fp16))[name = tensor("op_5806_cast_fp16")]; + tensor var_5808_equation_0 = const()[name = tensor("op_5808_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5808_cast_fp16 = einsum(equation = var_5808_equation_0, values = (var_5474_cast_fp16, var_5716_cast_fp16))[name = tensor("op_5808_cast_fp16")]; + tensor var_5810_equation_0 = const()[name = tensor("op_5810_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5810_cast_fp16 = einsum(equation = var_5810_equation_0, values = (var_5478_cast_fp16, var_5717_cast_fp16))[name = tensor("op_5810_cast_fp16")]; + tensor var_5812_equation_0 = const()[name = tensor("op_5812_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5812_cast_fp16 = einsum(equation = var_5812_equation_0, values = (var_5478_cast_fp16, var_5718_cast_fp16))[name = tensor("op_5812_cast_fp16")]; + tensor var_5814_equation_0 = const()[name = tensor("op_5814_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5814_cast_fp16 = einsum(equation = var_5814_equation_0, values = (var_5478_cast_fp16, var_5719_cast_fp16))[name = tensor("op_5814_cast_fp16")]; + tensor var_5816_equation_0 = const()[name = tensor("op_5816_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_5816_cast_fp16 = einsum(equation = var_5816_equation_0, values = (var_5478_cast_fp16, var_5720_cast_fp16))[name = tensor("op_5816_cast_fp16")]; + tensor var_5818_interleave_0 = const()[name = tensor("op_5818_interleave_0"), val = tensor(false)]; + tensor var_5818_cast_fp16 = concat(axis = var_4929, interleave = var_5818_interleave_0, values = (var_5722_cast_fp16, var_5724_cast_fp16, var_5726_cast_fp16, var_5728_cast_fp16))[name = tensor("op_5818_cast_fp16")]; + tensor var_5820_interleave_0 = const()[name = tensor("op_5820_interleave_0"), val = tensor(false)]; + tensor var_5820_cast_fp16 = concat(axis = var_4929, interleave = var_5820_interleave_0, values = (var_5730_cast_fp16, var_5732_cast_fp16, var_5734_cast_fp16, var_5736_cast_fp16))[name = tensor("op_5820_cast_fp16")]; + tensor var_5822_interleave_0 = const()[name = tensor("op_5822_interleave_0"), val = tensor(false)]; + tensor var_5822_cast_fp16 = concat(axis = var_4929, interleave = var_5822_interleave_0, values = (var_5738_cast_fp16, var_5740_cast_fp16, var_5742_cast_fp16, var_5744_cast_fp16))[name = tensor("op_5822_cast_fp16")]; + tensor var_5824_interleave_0 = const()[name = tensor("op_5824_interleave_0"), val = tensor(false)]; + tensor var_5824_cast_fp16 = concat(axis = var_4929, interleave = var_5824_interleave_0, values = (var_5746_cast_fp16, var_5748_cast_fp16, var_5750_cast_fp16, var_5752_cast_fp16))[name = tensor("op_5824_cast_fp16")]; + tensor var_5826_interleave_0 = const()[name = tensor("op_5826_interleave_0"), val = tensor(false)]; + tensor var_5826_cast_fp16 = concat(axis = var_4929, interleave = var_5826_interleave_0, values = (var_5754_cast_fp16, var_5756_cast_fp16, var_5758_cast_fp16, var_5760_cast_fp16))[name = tensor("op_5826_cast_fp16")]; + tensor var_5828_interleave_0 = const()[name = tensor("op_5828_interleave_0"), val = tensor(false)]; + tensor var_5828_cast_fp16 = concat(axis = var_4929, interleave = var_5828_interleave_0, values = (var_5762_cast_fp16, var_5764_cast_fp16, var_5766_cast_fp16, var_5768_cast_fp16))[name = tensor("op_5828_cast_fp16")]; + tensor var_5830_interleave_0 = const()[name = tensor("op_5830_interleave_0"), val = tensor(false)]; + tensor var_5830_cast_fp16 = concat(axis = var_4929, interleave = var_5830_interleave_0, values = (var_5770_cast_fp16, var_5772_cast_fp16, var_5774_cast_fp16, var_5776_cast_fp16))[name = tensor("op_5830_cast_fp16")]; + tensor var_5832_interleave_0 = const()[name = tensor("op_5832_interleave_0"), val = tensor(false)]; + tensor var_5832_cast_fp16 = concat(axis = var_4929, interleave = var_5832_interleave_0, values = (var_5778_cast_fp16, var_5780_cast_fp16, var_5782_cast_fp16, var_5784_cast_fp16))[name = tensor("op_5832_cast_fp16")]; + tensor var_5834_interleave_0 = const()[name = tensor("op_5834_interleave_0"), val = tensor(false)]; + tensor var_5834_cast_fp16 = concat(axis = var_4929, interleave = var_5834_interleave_0, values = (var_5786_cast_fp16, var_5788_cast_fp16, var_5790_cast_fp16, var_5792_cast_fp16))[name = tensor("op_5834_cast_fp16")]; + tensor var_5836_interleave_0 = const()[name = tensor("op_5836_interleave_0"), val = tensor(false)]; + tensor var_5836_cast_fp16 = concat(axis = var_4929, interleave = var_5836_interleave_0, values = (var_5794_cast_fp16, var_5796_cast_fp16, var_5798_cast_fp16, var_5800_cast_fp16))[name = tensor("op_5836_cast_fp16")]; + tensor var_5838_interleave_0 = const()[name = tensor("op_5838_interleave_0"), val = tensor(false)]; + tensor var_5838_cast_fp16 = concat(axis = var_4929, interleave = var_5838_interleave_0, values = (var_5802_cast_fp16, var_5804_cast_fp16, var_5806_cast_fp16, var_5808_cast_fp16))[name = tensor("op_5838_cast_fp16")]; + tensor var_5840_interleave_0 = const()[name = tensor("op_5840_interleave_0"), val = tensor(false)]; + tensor var_5840_cast_fp16 = concat(axis = var_4929, interleave = var_5840_interleave_0, values = (var_5810_cast_fp16, var_5812_cast_fp16, var_5814_cast_fp16, var_5816_cast_fp16))[name = tensor("op_5840_cast_fp16")]; + tensor input_41_interleave_0 = const()[name = tensor("input_41_interleave_0"), val = tensor(false)]; + tensor input_41_cast_fp16 = concat(axis = var_4946, interleave = input_41_interleave_0, values = (var_5818_cast_fp16, var_5820_cast_fp16, var_5822_cast_fp16, var_5824_cast_fp16, var_5826_cast_fp16, var_5828_cast_fp16, var_5830_cast_fp16, var_5832_cast_fp16, var_5834_cast_fp16, var_5836_cast_fp16, var_5838_cast_fp16, var_5840_cast_fp16))[name = tensor("input_41_cast_fp16")]; + tensor var_5845 = const()[name = tensor("op_5845"), val = tensor([1, 1])]; + tensor var_5847 = const()[name = tensor("op_5847"), val = tensor([1, 1])]; + tensor obj_23_pad_type_0 = const()[name = tensor("obj_23_pad_type_0"), val = tensor("custom")]; + tensor obj_23_pad_0 = const()[name = tensor("obj_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80639616)))]; + tensor layers_5_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81819328)))]; + tensor obj_23_cast_fp16 = conv(bias = layers_5_self_attn_o_proj_bias_to_fp16, dilations = var_5847, groups = var_4946, pad = obj_23_pad_0, pad_type = obj_23_pad_type_0, strides = var_5845, weight = layers_5_self_attn_o_proj_weight_to_fp16, x = input_41_cast_fp16)[name = tensor("obj_23_cast_fp16")]; + tensor inputs_23_cast_fp16 = add(x = inputs_21_cast_fp16, y = obj_23_cast_fp16)[name = tensor("inputs_23_cast_fp16")]; + tensor var_5853 = const()[name = tensor("op_5853"), val = tensor([1])]; + tensor channels_mean_23_cast_fp16 = reduce_mean(axes = var_5853, keep_dims = var_4947, x = inputs_23_cast_fp16)[name = tensor("channels_mean_23_cast_fp16")]; + tensor zero_mean_23_cast_fp16 = sub(x = inputs_23_cast_fp16, y = channels_mean_23_cast_fp16)[name = tensor("zero_mean_23_cast_fp16")]; + tensor zero_mean_sq_23_cast_fp16 = mul(x = zero_mean_23_cast_fp16, y = zero_mean_23_cast_fp16)[name = tensor("zero_mean_sq_23_cast_fp16")]; + tensor var_5857 = const()[name = tensor("op_5857"), val = tensor([1])]; + tensor var_5858_cast_fp16 = reduce_mean(axes = var_5857, keep_dims = var_4947, x = zero_mean_sq_23_cast_fp16)[name = tensor("op_5858_cast_fp16")]; + tensor var_5859_to_fp16 = const()[name = tensor("op_5859_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_5860_cast_fp16 = add(x = var_5858_cast_fp16, y = var_5859_to_fp16)[name = tensor("op_5860_cast_fp16")]; + tensor denom_23_epsilon_0_to_fp16 = const()[name = tensor("denom_23_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_23_cast_fp16 = rsqrt(epsilon = denom_23_epsilon_0_to_fp16, x = var_5860_cast_fp16)[name = tensor("denom_23_cast_fp16")]; + tensor out_23_cast_fp16 = mul(x = zero_mean_23_cast_fp16, y = denom_23_cast_fp16)[name = tensor("out_23_cast_fp16")]; + tensor input_43_gamma_0_to_fp16 = const()[name = tensor("input_43_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81820928)))]; + tensor input_43_beta_0_to_fp16 = const()[name = tensor("input_43_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81822528)))]; + tensor input_43_epsilon_0_to_fp16 = const()[name = tensor("input_43_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_43_cast_fp16 = batch_norm(beta = input_43_beta_0_to_fp16, epsilon = input_43_epsilon_0_to_fp16, gamma = input_43_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_23_cast_fp16)[name = tensor("input_43_cast_fp16")]; + tensor var_5871 = const()[name = tensor("op_5871"), val = tensor([1, 1])]; + tensor var_5873 = const()[name = tensor("op_5873"), val = tensor([1, 1])]; + tensor input_45_pad_type_0 = const()[name = tensor("input_45_pad_type_0"), val = tensor("custom")]; + tensor input_45_pad_0 = const()[name = tensor("input_45_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_fc1_weight_to_fp16 = const()[name = tensor("layers_5_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81824128)))]; + tensor layers_5_fc1_bias_to_fp16 = const()[name = tensor("layers_5_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86542784)))]; + tensor input_45_cast_fp16 = conv(bias = layers_5_fc1_bias_to_fp16, dilations = var_5873, groups = var_4946, pad = input_45_pad_0, pad_type = input_45_pad_type_0, strides = var_5871, weight = layers_5_fc1_weight_to_fp16, x = input_43_cast_fp16)[name = tensor("input_45_cast_fp16")]; + tensor input_47_mode_0 = const()[name = tensor("input_47_mode_0"), val = tensor("EXACT")]; + tensor input_47_cast_fp16 = gelu(mode = input_47_mode_0, x = input_45_cast_fp16)[name = tensor("input_47_cast_fp16")]; + tensor var_5879 = const()[name = tensor("op_5879"), val = tensor([1, 1])]; + tensor var_5881 = const()[name = tensor("op_5881"), val = tensor([1, 1])]; + tensor hidden_states_15_pad_type_0 = const()[name = tensor("hidden_states_15_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_15_pad_0 = const()[name = tensor("hidden_states_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_fc2_weight_to_fp16 = const()[name = tensor("layers_5_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86548992)))]; + tensor layers_5_fc2_bias_to_fp16 = const()[name = tensor("layers_5_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91267648)))]; + tensor hidden_states_15_cast_fp16 = conv(bias = layers_5_fc2_bias_to_fp16, dilations = var_5881, groups = var_4946, pad = hidden_states_15_pad_0, pad_type = hidden_states_15_pad_type_0, strides = var_5879, weight = layers_5_fc2_weight_to_fp16, x = input_47_cast_fp16)[name = tensor("hidden_states_15_cast_fp16")]; + tensor inputs_25_cast_fp16 = add(x = inputs_23_cast_fp16, y = hidden_states_15_cast_fp16)[name = tensor("inputs_25_cast_fp16")]; + tensor var_5888 = const()[name = tensor("op_5888"), val = tensor(3)]; + tensor var_5905 = const()[name = tensor("op_5905"), val = tensor(1)]; + tensor var_5906 = const()[name = tensor("op_5906"), val = tensor(true)]; + tensor var_5916 = const()[name = tensor("op_5916"), val = tensor([1])]; + tensor channels_mean_25_cast_fp16 = reduce_mean(axes = var_5916, keep_dims = var_5906, x = inputs_25_cast_fp16)[name = tensor("channels_mean_25_cast_fp16")]; + tensor zero_mean_25_cast_fp16 = sub(x = inputs_25_cast_fp16, y = channels_mean_25_cast_fp16)[name = tensor("zero_mean_25_cast_fp16")]; + tensor zero_mean_sq_25_cast_fp16 = mul(x = zero_mean_25_cast_fp16, y = zero_mean_25_cast_fp16)[name = tensor("zero_mean_sq_25_cast_fp16")]; + tensor var_5920 = const()[name = tensor("op_5920"), val = tensor([1])]; + tensor var_5921_cast_fp16 = reduce_mean(axes = var_5920, keep_dims = var_5906, x = zero_mean_sq_25_cast_fp16)[name = tensor("op_5921_cast_fp16")]; + tensor var_5922_to_fp16 = const()[name = tensor("op_5922_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_5923_cast_fp16 = add(x = var_5921_cast_fp16, y = var_5922_to_fp16)[name = tensor("op_5923_cast_fp16")]; + tensor denom_25_epsilon_0_to_fp16 = const()[name = tensor("denom_25_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_25_cast_fp16 = rsqrt(epsilon = denom_25_epsilon_0_to_fp16, x = var_5923_cast_fp16)[name = tensor("denom_25_cast_fp16")]; + tensor out_25_cast_fp16 = mul(x = zero_mean_25_cast_fp16, y = denom_25_cast_fp16)[name = tensor("out_25_cast_fp16")]; + tensor obj_25_gamma_0_to_fp16 = const()[name = tensor("obj_25_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91269248)))]; + tensor obj_25_beta_0_to_fp16 = const()[name = tensor("obj_25_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91270848)))]; + tensor obj_25_epsilon_0_to_fp16 = const()[name = tensor("obj_25_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_25_cast_fp16 = batch_norm(beta = obj_25_beta_0_to_fp16, epsilon = obj_25_epsilon_0_to_fp16, gamma = obj_25_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_25_cast_fp16)[name = tensor("obj_25_cast_fp16")]; + tensor var_5938 = const()[name = tensor("op_5938"), val = tensor([1, 1])]; + tensor var_5940 = const()[name = tensor("op_5940"), val = tensor([1, 1])]; + tensor query_13_pad_type_0 = const()[name = tensor("query_13_pad_type_0"), val = tensor("custom")]; + tensor query_13_pad_0 = const()[name = tensor("query_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91272448)))]; + tensor layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92452160)))]; + tensor query_13_cast_fp16 = conv(bias = layers_6_self_attn_q_proj_bias_to_fp16, dilations = var_5940, groups = var_5905, pad = query_13_pad_0, pad_type = query_13_pad_type_0, strides = var_5938, weight = layers_6_self_attn_q_proj_weight_to_fp16, x = obj_25_cast_fp16)[name = tensor("query_13_cast_fp16")]; + tensor var_5944 = const()[name = tensor("op_5944"), val = tensor([1, 1])]; + tensor var_5946 = const()[name = tensor("op_5946"), val = tensor([1, 1])]; + tensor key_13_pad_type_0 = const()[name = tensor("key_13_pad_type_0"), val = tensor("custom")]; + tensor key_13_pad_0 = const()[name = tensor("key_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92453760)))]; + tensor key_13_cast_fp16 = conv(dilations = var_5946, groups = var_5905, pad = key_13_pad_0, pad_type = key_13_pad_type_0, strides = var_5944, weight = layers_6_self_attn_k_proj_weight_to_fp16, x = obj_25_cast_fp16)[name = tensor("key_13_cast_fp16")]; + tensor var_5951 = const()[name = tensor("op_5951"), val = tensor([1, 1])]; + tensor var_5953 = const()[name = tensor("op_5953"), val = tensor([1, 1])]; + tensor value_13_pad_type_0 = const()[name = tensor("value_13_pad_type_0"), val = tensor("custom")]; + tensor value_13_pad_0 = const()[name = tensor("value_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93633472)))]; + tensor layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94813184)))]; + tensor value_13_cast_fp16 = conv(bias = layers_6_self_attn_v_proj_bias_to_fp16, dilations = var_5953, groups = var_5905, pad = value_13_pad_0, pad_type = value_13_pad_type_0, strides = var_5951, weight = layers_6_self_attn_v_proj_weight_to_fp16, x = obj_25_cast_fp16)[name = tensor("value_13_cast_fp16")]; + tensor var_5960_begin_0 = const()[name = tensor("op_5960_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_5960_end_0 = const()[name = tensor("op_5960_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_5960_end_mask_0 = const()[name = tensor("op_5960_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5960_cast_fp16 = slice_by_index(begin = var_5960_begin_0, end = var_5960_end_0, end_mask = var_5960_end_mask_0, x = query_13_cast_fp16)[name = tensor("op_5960_cast_fp16")]; + tensor var_5964_begin_0 = const()[name = tensor("op_5964_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_5964_end_0 = const()[name = tensor("op_5964_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_5964_end_mask_0 = const()[name = tensor("op_5964_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5964_cast_fp16 = slice_by_index(begin = var_5964_begin_0, end = var_5964_end_0, end_mask = var_5964_end_mask_0, x = query_13_cast_fp16)[name = tensor("op_5964_cast_fp16")]; + tensor var_5968_begin_0 = const()[name = tensor("op_5968_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_5968_end_0 = const()[name = tensor("op_5968_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_5968_end_mask_0 = const()[name = tensor("op_5968_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5968_cast_fp16 = slice_by_index(begin = var_5968_begin_0, end = var_5968_end_0, end_mask = var_5968_end_mask_0, x = query_13_cast_fp16)[name = tensor("op_5968_cast_fp16")]; + tensor var_5972_begin_0 = const()[name = tensor("op_5972_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_5972_end_0 = const()[name = tensor("op_5972_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_5972_end_mask_0 = const()[name = tensor("op_5972_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5972_cast_fp16 = slice_by_index(begin = var_5972_begin_0, end = var_5972_end_0, end_mask = var_5972_end_mask_0, x = query_13_cast_fp16)[name = tensor("op_5972_cast_fp16")]; + tensor var_5976_begin_0 = const()[name = tensor("op_5976_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_5976_end_0 = const()[name = tensor("op_5976_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_5976_end_mask_0 = const()[name = tensor("op_5976_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5976_cast_fp16 = slice_by_index(begin = var_5976_begin_0, end = var_5976_end_0, end_mask = var_5976_end_mask_0, x = query_13_cast_fp16)[name = tensor("op_5976_cast_fp16")]; + tensor var_5980_begin_0 = const()[name = tensor("op_5980_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_5980_end_0 = const()[name = tensor("op_5980_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_5980_end_mask_0 = const()[name = tensor("op_5980_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5980_cast_fp16 = slice_by_index(begin = var_5980_begin_0, end = var_5980_end_0, end_mask = var_5980_end_mask_0, x = query_13_cast_fp16)[name = tensor("op_5980_cast_fp16")]; + tensor var_5984_begin_0 = const()[name = tensor("op_5984_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_5984_end_0 = const()[name = tensor("op_5984_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_5984_end_mask_0 = const()[name = tensor("op_5984_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5984_cast_fp16 = slice_by_index(begin = var_5984_begin_0, end = var_5984_end_0, end_mask = var_5984_end_mask_0, x = query_13_cast_fp16)[name = tensor("op_5984_cast_fp16")]; + tensor var_5988_begin_0 = const()[name = tensor("op_5988_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_5988_end_0 = const()[name = tensor("op_5988_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_5988_end_mask_0 = const()[name = tensor("op_5988_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5988_cast_fp16 = slice_by_index(begin = var_5988_begin_0, end = var_5988_end_0, end_mask = var_5988_end_mask_0, x = query_13_cast_fp16)[name = tensor("op_5988_cast_fp16")]; + tensor var_5992_begin_0 = const()[name = tensor("op_5992_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_5992_end_0 = const()[name = tensor("op_5992_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_5992_end_mask_0 = const()[name = tensor("op_5992_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5992_cast_fp16 = slice_by_index(begin = var_5992_begin_0, end = var_5992_end_0, end_mask = var_5992_end_mask_0, x = query_13_cast_fp16)[name = tensor("op_5992_cast_fp16")]; + tensor var_5996_begin_0 = const()[name = tensor("op_5996_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_5996_end_0 = const()[name = tensor("op_5996_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_5996_end_mask_0 = const()[name = tensor("op_5996_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_5996_cast_fp16 = slice_by_index(begin = var_5996_begin_0, end = var_5996_end_0, end_mask = var_5996_end_mask_0, x = query_13_cast_fp16)[name = tensor("op_5996_cast_fp16")]; + tensor var_6000_begin_0 = const()[name = tensor("op_6000_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_6000_end_0 = const()[name = tensor("op_6000_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_6000_end_mask_0 = const()[name = tensor("op_6000_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6000_cast_fp16 = slice_by_index(begin = var_6000_begin_0, end = var_6000_end_0, end_mask = var_6000_end_mask_0, x = query_13_cast_fp16)[name = tensor("op_6000_cast_fp16")]; + tensor var_6004_begin_0 = const()[name = tensor("op_6004_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_6004_end_0 = const()[name = tensor("op_6004_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_6004_end_mask_0 = const()[name = tensor("op_6004_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6004_cast_fp16 = slice_by_index(begin = var_6004_begin_0, end = var_6004_end_0, end_mask = var_6004_end_mask_0, x = query_13_cast_fp16)[name = tensor("op_6004_cast_fp16")]; + tensor var_6013_begin_0 = const()[name = tensor("op_6013_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6013_end_0 = const()[name = tensor("op_6013_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_6013_end_mask_0 = const()[name = tensor("op_6013_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6013_cast_fp16 = slice_by_index(begin = var_6013_begin_0, end = var_6013_end_0, end_mask = var_6013_end_mask_0, x = var_5960_cast_fp16)[name = tensor("op_6013_cast_fp16")]; + tensor var_6020_begin_0 = const()[name = tensor("op_6020_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_6020_end_0 = const()[name = tensor("op_6020_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_6020_end_mask_0 = const()[name = tensor("op_6020_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6020_cast_fp16 = slice_by_index(begin = var_6020_begin_0, end = var_6020_end_0, end_mask = var_6020_end_mask_0, x = var_5960_cast_fp16)[name = tensor("op_6020_cast_fp16")]; + tensor var_6027_begin_0 = const()[name = tensor("op_6027_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_6027_end_0 = const()[name = tensor("op_6027_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_6027_end_mask_0 = const()[name = tensor("op_6027_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6027_cast_fp16 = slice_by_index(begin = var_6027_begin_0, end = var_6027_end_0, end_mask = var_6027_end_mask_0, x = var_5960_cast_fp16)[name = tensor("op_6027_cast_fp16")]; + tensor var_6034_begin_0 = const()[name = tensor("op_6034_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_6034_end_0 = const()[name = tensor("op_6034_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6034_end_mask_0 = const()[name = tensor("op_6034_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6034_cast_fp16 = slice_by_index(begin = var_6034_begin_0, end = var_6034_end_0, end_mask = var_6034_end_mask_0, x = var_5960_cast_fp16)[name = tensor("op_6034_cast_fp16")]; + tensor var_6041_begin_0 = const()[name = tensor("op_6041_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6041_end_0 = const()[name = tensor("op_6041_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_6041_end_mask_0 = const()[name = tensor("op_6041_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6041_cast_fp16 = slice_by_index(begin = var_6041_begin_0, end = var_6041_end_0, end_mask = var_6041_end_mask_0, x = var_5964_cast_fp16)[name = tensor("op_6041_cast_fp16")]; + tensor var_6048_begin_0 = const()[name = tensor("op_6048_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_6048_end_0 = const()[name = tensor("op_6048_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_6048_end_mask_0 = const()[name = tensor("op_6048_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6048_cast_fp16 = slice_by_index(begin = var_6048_begin_0, end = var_6048_end_0, end_mask = var_6048_end_mask_0, x = var_5964_cast_fp16)[name = tensor("op_6048_cast_fp16")]; + tensor var_6055_begin_0 = const()[name = tensor("op_6055_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_6055_end_0 = const()[name = tensor("op_6055_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_6055_end_mask_0 = const()[name = tensor("op_6055_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6055_cast_fp16 = slice_by_index(begin = var_6055_begin_0, end = var_6055_end_0, end_mask = var_6055_end_mask_0, x = var_5964_cast_fp16)[name = tensor("op_6055_cast_fp16")]; + tensor var_6062_begin_0 = const()[name = tensor("op_6062_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_6062_end_0 = const()[name = tensor("op_6062_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6062_end_mask_0 = const()[name = tensor("op_6062_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6062_cast_fp16 = slice_by_index(begin = var_6062_begin_0, end = var_6062_end_0, end_mask = var_6062_end_mask_0, x = var_5964_cast_fp16)[name = tensor("op_6062_cast_fp16")]; + tensor var_6069_begin_0 = const()[name = tensor("op_6069_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6069_end_0 = const()[name = tensor("op_6069_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_6069_end_mask_0 = const()[name = tensor("op_6069_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6069_cast_fp16 = slice_by_index(begin = var_6069_begin_0, end = var_6069_end_0, end_mask = var_6069_end_mask_0, x = var_5968_cast_fp16)[name = tensor("op_6069_cast_fp16")]; + tensor var_6076_begin_0 = const()[name = tensor("op_6076_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_6076_end_0 = const()[name = tensor("op_6076_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_6076_end_mask_0 = const()[name = tensor("op_6076_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6076_cast_fp16 = slice_by_index(begin = var_6076_begin_0, end = var_6076_end_0, end_mask = var_6076_end_mask_0, x = var_5968_cast_fp16)[name = tensor("op_6076_cast_fp16")]; + tensor var_6083_begin_0 = const()[name = tensor("op_6083_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_6083_end_0 = const()[name = tensor("op_6083_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_6083_end_mask_0 = const()[name = tensor("op_6083_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6083_cast_fp16 = slice_by_index(begin = var_6083_begin_0, end = var_6083_end_0, end_mask = var_6083_end_mask_0, x = var_5968_cast_fp16)[name = tensor("op_6083_cast_fp16")]; + tensor var_6090_begin_0 = const()[name = tensor("op_6090_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_6090_end_0 = const()[name = tensor("op_6090_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6090_end_mask_0 = const()[name = tensor("op_6090_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6090_cast_fp16 = slice_by_index(begin = var_6090_begin_0, end = var_6090_end_0, end_mask = var_6090_end_mask_0, x = var_5968_cast_fp16)[name = tensor("op_6090_cast_fp16")]; + tensor var_6097_begin_0 = const()[name = tensor("op_6097_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6097_end_0 = const()[name = tensor("op_6097_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_6097_end_mask_0 = const()[name = tensor("op_6097_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6097_cast_fp16 = slice_by_index(begin = var_6097_begin_0, end = var_6097_end_0, end_mask = var_6097_end_mask_0, x = var_5972_cast_fp16)[name = tensor("op_6097_cast_fp16")]; + tensor var_6104_begin_0 = const()[name = tensor("op_6104_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_6104_end_0 = const()[name = tensor("op_6104_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_6104_end_mask_0 = const()[name = tensor("op_6104_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6104_cast_fp16 = slice_by_index(begin = var_6104_begin_0, end = var_6104_end_0, end_mask = var_6104_end_mask_0, x = var_5972_cast_fp16)[name = tensor("op_6104_cast_fp16")]; + tensor var_6111_begin_0 = const()[name = tensor("op_6111_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_6111_end_0 = const()[name = tensor("op_6111_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_6111_end_mask_0 = const()[name = tensor("op_6111_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6111_cast_fp16 = slice_by_index(begin = var_6111_begin_0, end = var_6111_end_0, end_mask = var_6111_end_mask_0, x = var_5972_cast_fp16)[name = tensor("op_6111_cast_fp16")]; + tensor var_6118_begin_0 = const()[name = tensor("op_6118_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_6118_end_0 = const()[name = tensor("op_6118_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6118_end_mask_0 = const()[name = tensor("op_6118_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6118_cast_fp16 = slice_by_index(begin = var_6118_begin_0, end = var_6118_end_0, end_mask = var_6118_end_mask_0, x = var_5972_cast_fp16)[name = tensor("op_6118_cast_fp16")]; + tensor var_6125_begin_0 = const()[name = tensor("op_6125_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6125_end_0 = const()[name = tensor("op_6125_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_6125_end_mask_0 = const()[name = tensor("op_6125_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6125_cast_fp16 = slice_by_index(begin = var_6125_begin_0, end = var_6125_end_0, end_mask = var_6125_end_mask_0, x = var_5976_cast_fp16)[name = tensor("op_6125_cast_fp16")]; + tensor var_6132_begin_0 = const()[name = tensor("op_6132_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_6132_end_0 = const()[name = tensor("op_6132_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_6132_end_mask_0 = const()[name = tensor("op_6132_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6132_cast_fp16 = slice_by_index(begin = var_6132_begin_0, end = var_6132_end_0, end_mask = var_6132_end_mask_0, x = var_5976_cast_fp16)[name = tensor("op_6132_cast_fp16")]; + tensor var_6139_begin_0 = const()[name = tensor("op_6139_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_6139_end_0 = const()[name = tensor("op_6139_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_6139_end_mask_0 = const()[name = tensor("op_6139_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6139_cast_fp16 = slice_by_index(begin = var_6139_begin_0, end = var_6139_end_0, end_mask = var_6139_end_mask_0, x = var_5976_cast_fp16)[name = tensor("op_6139_cast_fp16")]; + tensor var_6146_begin_0 = const()[name = tensor("op_6146_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_6146_end_0 = const()[name = tensor("op_6146_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6146_end_mask_0 = const()[name = tensor("op_6146_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6146_cast_fp16 = slice_by_index(begin = var_6146_begin_0, end = var_6146_end_0, end_mask = var_6146_end_mask_0, x = var_5976_cast_fp16)[name = tensor("op_6146_cast_fp16")]; + tensor var_6153_begin_0 = const()[name = tensor("op_6153_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6153_end_0 = const()[name = tensor("op_6153_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_6153_end_mask_0 = const()[name = tensor("op_6153_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6153_cast_fp16 = slice_by_index(begin = var_6153_begin_0, end = var_6153_end_0, end_mask = var_6153_end_mask_0, x = var_5980_cast_fp16)[name = tensor("op_6153_cast_fp16")]; + tensor var_6160_begin_0 = const()[name = tensor("op_6160_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_6160_end_0 = const()[name = tensor("op_6160_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_6160_end_mask_0 = const()[name = tensor("op_6160_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6160_cast_fp16 = slice_by_index(begin = var_6160_begin_0, end = var_6160_end_0, end_mask = var_6160_end_mask_0, x = var_5980_cast_fp16)[name = tensor("op_6160_cast_fp16")]; + tensor var_6167_begin_0 = const()[name = tensor("op_6167_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_6167_end_0 = const()[name = tensor("op_6167_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_6167_end_mask_0 = const()[name = tensor("op_6167_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6167_cast_fp16 = slice_by_index(begin = var_6167_begin_0, end = var_6167_end_0, end_mask = var_6167_end_mask_0, x = var_5980_cast_fp16)[name = tensor("op_6167_cast_fp16")]; + tensor var_6174_begin_0 = const()[name = tensor("op_6174_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_6174_end_0 = const()[name = tensor("op_6174_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6174_end_mask_0 = const()[name = tensor("op_6174_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6174_cast_fp16 = slice_by_index(begin = var_6174_begin_0, end = var_6174_end_0, end_mask = var_6174_end_mask_0, x = var_5980_cast_fp16)[name = tensor("op_6174_cast_fp16")]; + tensor var_6181_begin_0 = const()[name = tensor("op_6181_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6181_end_0 = const()[name = tensor("op_6181_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_6181_end_mask_0 = const()[name = tensor("op_6181_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6181_cast_fp16 = slice_by_index(begin = var_6181_begin_0, end = var_6181_end_0, end_mask = var_6181_end_mask_0, x = var_5984_cast_fp16)[name = tensor("op_6181_cast_fp16")]; + tensor var_6188_begin_0 = const()[name = tensor("op_6188_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_6188_end_0 = const()[name = tensor("op_6188_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_6188_end_mask_0 = const()[name = tensor("op_6188_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6188_cast_fp16 = slice_by_index(begin = var_6188_begin_0, end = var_6188_end_0, end_mask = var_6188_end_mask_0, x = var_5984_cast_fp16)[name = tensor("op_6188_cast_fp16")]; + tensor var_6195_begin_0 = const()[name = tensor("op_6195_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_6195_end_0 = const()[name = tensor("op_6195_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_6195_end_mask_0 = const()[name = tensor("op_6195_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6195_cast_fp16 = slice_by_index(begin = var_6195_begin_0, end = var_6195_end_0, end_mask = var_6195_end_mask_0, x = var_5984_cast_fp16)[name = tensor("op_6195_cast_fp16")]; + tensor var_6202_begin_0 = const()[name = tensor("op_6202_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_6202_end_0 = const()[name = tensor("op_6202_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6202_end_mask_0 = const()[name = tensor("op_6202_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6202_cast_fp16 = slice_by_index(begin = var_6202_begin_0, end = var_6202_end_0, end_mask = var_6202_end_mask_0, x = var_5984_cast_fp16)[name = tensor("op_6202_cast_fp16")]; + tensor var_6209_begin_0 = const()[name = tensor("op_6209_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6209_end_0 = const()[name = tensor("op_6209_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_6209_end_mask_0 = const()[name = tensor("op_6209_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6209_cast_fp16 = slice_by_index(begin = var_6209_begin_0, end = var_6209_end_0, end_mask = var_6209_end_mask_0, x = var_5988_cast_fp16)[name = tensor("op_6209_cast_fp16")]; + tensor var_6216_begin_0 = const()[name = tensor("op_6216_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_6216_end_0 = const()[name = tensor("op_6216_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_6216_end_mask_0 = const()[name = tensor("op_6216_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6216_cast_fp16 = slice_by_index(begin = var_6216_begin_0, end = var_6216_end_0, end_mask = var_6216_end_mask_0, x = var_5988_cast_fp16)[name = tensor("op_6216_cast_fp16")]; + tensor var_6223_begin_0 = const()[name = tensor("op_6223_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_6223_end_0 = const()[name = tensor("op_6223_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_6223_end_mask_0 = const()[name = tensor("op_6223_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6223_cast_fp16 = slice_by_index(begin = var_6223_begin_0, end = var_6223_end_0, end_mask = var_6223_end_mask_0, x = var_5988_cast_fp16)[name = tensor("op_6223_cast_fp16")]; + tensor var_6230_begin_0 = const()[name = tensor("op_6230_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_6230_end_0 = const()[name = tensor("op_6230_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6230_end_mask_0 = const()[name = tensor("op_6230_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6230_cast_fp16 = slice_by_index(begin = var_6230_begin_0, end = var_6230_end_0, end_mask = var_6230_end_mask_0, x = var_5988_cast_fp16)[name = tensor("op_6230_cast_fp16")]; + tensor var_6237_begin_0 = const()[name = tensor("op_6237_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6237_end_0 = const()[name = tensor("op_6237_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_6237_end_mask_0 = const()[name = tensor("op_6237_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6237_cast_fp16 = slice_by_index(begin = var_6237_begin_0, end = var_6237_end_0, end_mask = var_6237_end_mask_0, x = var_5992_cast_fp16)[name = tensor("op_6237_cast_fp16")]; + tensor var_6244_begin_0 = const()[name = tensor("op_6244_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_6244_end_0 = const()[name = tensor("op_6244_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_6244_end_mask_0 = const()[name = tensor("op_6244_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6244_cast_fp16 = slice_by_index(begin = var_6244_begin_0, end = var_6244_end_0, end_mask = var_6244_end_mask_0, x = var_5992_cast_fp16)[name = tensor("op_6244_cast_fp16")]; + tensor var_6251_begin_0 = const()[name = tensor("op_6251_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_6251_end_0 = const()[name = tensor("op_6251_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_6251_end_mask_0 = const()[name = tensor("op_6251_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6251_cast_fp16 = slice_by_index(begin = var_6251_begin_0, end = var_6251_end_0, end_mask = var_6251_end_mask_0, x = var_5992_cast_fp16)[name = tensor("op_6251_cast_fp16")]; + tensor var_6258_begin_0 = const()[name = tensor("op_6258_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_6258_end_0 = const()[name = tensor("op_6258_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6258_end_mask_0 = const()[name = tensor("op_6258_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6258_cast_fp16 = slice_by_index(begin = var_6258_begin_0, end = var_6258_end_0, end_mask = var_6258_end_mask_0, x = var_5992_cast_fp16)[name = tensor("op_6258_cast_fp16")]; + tensor var_6265_begin_0 = const()[name = tensor("op_6265_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6265_end_0 = const()[name = tensor("op_6265_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_6265_end_mask_0 = const()[name = tensor("op_6265_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6265_cast_fp16 = slice_by_index(begin = var_6265_begin_0, end = var_6265_end_0, end_mask = var_6265_end_mask_0, x = var_5996_cast_fp16)[name = tensor("op_6265_cast_fp16")]; + tensor var_6272_begin_0 = const()[name = tensor("op_6272_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_6272_end_0 = const()[name = tensor("op_6272_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_6272_end_mask_0 = const()[name = tensor("op_6272_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6272_cast_fp16 = slice_by_index(begin = var_6272_begin_0, end = var_6272_end_0, end_mask = var_6272_end_mask_0, x = var_5996_cast_fp16)[name = tensor("op_6272_cast_fp16")]; + tensor var_6279_begin_0 = const()[name = tensor("op_6279_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_6279_end_0 = const()[name = tensor("op_6279_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_6279_end_mask_0 = const()[name = tensor("op_6279_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6279_cast_fp16 = slice_by_index(begin = var_6279_begin_0, end = var_6279_end_0, end_mask = var_6279_end_mask_0, x = var_5996_cast_fp16)[name = tensor("op_6279_cast_fp16")]; + tensor var_6286_begin_0 = const()[name = tensor("op_6286_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_6286_end_0 = const()[name = tensor("op_6286_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6286_end_mask_0 = const()[name = tensor("op_6286_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6286_cast_fp16 = slice_by_index(begin = var_6286_begin_0, end = var_6286_end_0, end_mask = var_6286_end_mask_0, x = var_5996_cast_fp16)[name = tensor("op_6286_cast_fp16")]; + tensor var_6293_begin_0 = const()[name = tensor("op_6293_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6293_end_0 = const()[name = tensor("op_6293_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_6293_end_mask_0 = const()[name = tensor("op_6293_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6293_cast_fp16 = slice_by_index(begin = var_6293_begin_0, end = var_6293_end_0, end_mask = var_6293_end_mask_0, x = var_6000_cast_fp16)[name = tensor("op_6293_cast_fp16")]; + tensor var_6300_begin_0 = const()[name = tensor("op_6300_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_6300_end_0 = const()[name = tensor("op_6300_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_6300_end_mask_0 = const()[name = tensor("op_6300_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6300_cast_fp16 = slice_by_index(begin = var_6300_begin_0, end = var_6300_end_0, end_mask = var_6300_end_mask_0, x = var_6000_cast_fp16)[name = tensor("op_6300_cast_fp16")]; + tensor var_6307_begin_0 = const()[name = tensor("op_6307_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_6307_end_0 = const()[name = tensor("op_6307_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_6307_end_mask_0 = const()[name = tensor("op_6307_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6307_cast_fp16 = slice_by_index(begin = var_6307_begin_0, end = var_6307_end_0, end_mask = var_6307_end_mask_0, x = var_6000_cast_fp16)[name = tensor("op_6307_cast_fp16")]; + tensor var_6314_begin_0 = const()[name = tensor("op_6314_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_6314_end_0 = const()[name = tensor("op_6314_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6314_end_mask_0 = const()[name = tensor("op_6314_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6314_cast_fp16 = slice_by_index(begin = var_6314_begin_0, end = var_6314_end_0, end_mask = var_6314_end_mask_0, x = var_6000_cast_fp16)[name = tensor("op_6314_cast_fp16")]; + tensor var_6321_begin_0 = const()[name = tensor("op_6321_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6321_end_0 = const()[name = tensor("op_6321_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_6321_end_mask_0 = const()[name = tensor("op_6321_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6321_cast_fp16 = slice_by_index(begin = var_6321_begin_0, end = var_6321_end_0, end_mask = var_6321_end_mask_0, x = var_6004_cast_fp16)[name = tensor("op_6321_cast_fp16")]; + tensor var_6328_begin_0 = const()[name = tensor("op_6328_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_6328_end_0 = const()[name = tensor("op_6328_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_6328_end_mask_0 = const()[name = tensor("op_6328_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6328_cast_fp16 = slice_by_index(begin = var_6328_begin_0, end = var_6328_end_0, end_mask = var_6328_end_mask_0, x = var_6004_cast_fp16)[name = tensor("op_6328_cast_fp16")]; + tensor var_6335_begin_0 = const()[name = tensor("op_6335_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_6335_end_0 = const()[name = tensor("op_6335_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_6335_end_mask_0 = const()[name = tensor("op_6335_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6335_cast_fp16 = slice_by_index(begin = var_6335_begin_0, end = var_6335_end_0, end_mask = var_6335_end_mask_0, x = var_6004_cast_fp16)[name = tensor("op_6335_cast_fp16")]; + tensor var_6342_begin_0 = const()[name = tensor("op_6342_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_6342_end_0 = const()[name = tensor("op_6342_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6342_end_mask_0 = const()[name = tensor("op_6342_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6342_cast_fp16 = slice_by_index(begin = var_6342_begin_0, end = var_6342_end_0, end_mask = var_6342_end_mask_0, x = var_6004_cast_fp16)[name = tensor("op_6342_cast_fp16")]; + tensor k_13_perm_0 = const()[name = tensor("k_13_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_6347_begin_0 = const()[name = tensor("op_6347_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6347_end_0 = const()[name = tensor("op_6347_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_6347_end_mask_0 = const()[name = tensor("op_6347_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_5 = transpose(perm = k_13_perm_0, x = key_13_cast_fp16)[name = tensor("transpose_5")]; + tensor var_6347_cast_fp16 = slice_by_index(begin = var_6347_begin_0, end = var_6347_end_0, end_mask = var_6347_end_mask_0, x = transpose_5)[name = tensor("op_6347_cast_fp16")]; + tensor var_6351_begin_0 = const()[name = tensor("op_6351_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_6351_end_0 = const()[name = tensor("op_6351_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_6351_end_mask_0 = const()[name = tensor("op_6351_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6351_cast_fp16 = slice_by_index(begin = var_6351_begin_0, end = var_6351_end_0, end_mask = var_6351_end_mask_0, x = transpose_5)[name = tensor("op_6351_cast_fp16")]; + tensor var_6355_begin_0 = const()[name = tensor("op_6355_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_6355_end_0 = const()[name = tensor("op_6355_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_6355_end_mask_0 = const()[name = tensor("op_6355_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6355_cast_fp16 = slice_by_index(begin = var_6355_begin_0, end = var_6355_end_0, end_mask = var_6355_end_mask_0, x = transpose_5)[name = tensor("op_6355_cast_fp16")]; + tensor var_6359_begin_0 = const()[name = tensor("op_6359_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_6359_end_0 = const()[name = tensor("op_6359_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_6359_end_mask_0 = const()[name = tensor("op_6359_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6359_cast_fp16 = slice_by_index(begin = var_6359_begin_0, end = var_6359_end_0, end_mask = var_6359_end_mask_0, x = transpose_5)[name = tensor("op_6359_cast_fp16")]; + tensor var_6363_begin_0 = const()[name = tensor("op_6363_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_6363_end_0 = const()[name = tensor("op_6363_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_6363_end_mask_0 = const()[name = tensor("op_6363_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6363_cast_fp16 = slice_by_index(begin = var_6363_begin_0, end = var_6363_end_0, end_mask = var_6363_end_mask_0, x = transpose_5)[name = tensor("op_6363_cast_fp16")]; + tensor var_6367_begin_0 = const()[name = tensor("op_6367_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_6367_end_0 = const()[name = tensor("op_6367_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_6367_end_mask_0 = const()[name = tensor("op_6367_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6367_cast_fp16 = slice_by_index(begin = var_6367_begin_0, end = var_6367_end_0, end_mask = var_6367_end_mask_0, x = transpose_5)[name = tensor("op_6367_cast_fp16")]; + tensor var_6371_begin_0 = const()[name = tensor("op_6371_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_6371_end_0 = const()[name = tensor("op_6371_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_6371_end_mask_0 = const()[name = tensor("op_6371_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6371_cast_fp16 = slice_by_index(begin = var_6371_begin_0, end = var_6371_end_0, end_mask = var_6371_end_mask_0, x = transpose_5)[name = tensor("op_6371_cast_fp16")]; + tensor var_6375_begin_0 = const()[name = tensor("op_6375_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_6375_end_0 = const()[name = tensor("op_6375_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_6375_end_mask_0 = const()[name = tensor("op_6375_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6375_cast_fp16 = slice_by_index(begin = var_6375_begin_0, end = var_6375_end_0, end_mask = var_6375_end_mask_0, x = transpose_5)[name = tensor("op_6375_cast_fp16")]; + tensor var_6379_begin_0 = const()[name = tensor("op_6379_begin_0"), val = tensor([0, 0, 0, 512])]; + tensor var_6379_end_0 = const()[name = tensor("op_6379_end_0"), val = tensor([1, 1500, 1, 576])]; + tensor var_6379_end_mask_0 = const()[name = tensor("op_6379_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6379_cast_fp16 = slice_by_index(begin = var_6379_begin_0, end = var_6379_end_0, end_mask = var_6379_end_mask_0, x = transpose_5)[name = tensor("op_6379_cast_fp16")]; + tensor var_6383_begin_0 = const()[name = tensor("op_6383_begin_0"), val = tensor([0, 0, 0, 576])]; + tensor var_6383_end_0 = const()[name = tensor("op_6383_end_0"), val = tensor([1, 1500, 1, 640])]; + tensor var_6383_end_mask_0 = const()[name = tensor("op_6383_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6383_cast_fp16 = slice_by_index(begin = var_6383_begin_0, end = var_6383_end_0, end_mask = var_6383_end_mask_0, x = transpose_5)[name = tensor("op_6383_cast_fp16")]; + tensor var_6387_begin_0 = const()[name = tensor("op_6387_begin_0"), val = tensor([0, 0, 0, 640])]; + tensor var_6387_end_0 = const()[name = tensor("op_6387_end_0"), val = tensor([1, 1500, 1, 704])]; + tensor var_6387_end_mask_0 = const()[name = tensor("op_6387_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6387_cast_fp16 = slice_by_index(begin = var_6387_begin_0, end = var_6387_end_0, end_mask = var_6387_end_mask_0, x = transpose_5)[name = tensor("op_6387_cast_fp16")]; + tensor var_6391_begin_0 = const()[name = tensor("op_6391_begin_0"), val = tensor([0, 0, 0, 704])]; + tensor var_6391_end_0 = const()[name = tensor("op_6391_end_0"), val = tensor([1, 1500, 1, 768])]; + tensor var_6391_end_mask_0 = const()[name = tensor("op_6391_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6391_cast_fp16 = slice_by_index(begin = var_6391_begin_0, end = var_6391_end_0, end_mask = var_6391_end_mask_0, x = transpose_5)[name = tensor("op_6391_cast_fp16")]; + tensor var_6393_begin_0 = const()[name = tensor("op_6393_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6393_end_0 = const()[name = tensor("op_6393_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6393_end_mask_0 = const()[name = tensor("op_6393_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6393_cast_fp16 = slice_by_index(begin = var_6393_begin_0, end = var_6393_end_0, end_mask = var_6393_end_mask_0, x = value_13_cast_fp16)[name = tensor("op_6393_cast_fp16")]; + tensor var_6397_begin_0 = const()[name = tensor("op_6397_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_6397_end_0 = const()[name = tensor("op_6397_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_6397_end_mask_0 = const()[name = tensor("op_6397_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6397_cast_fp16 = slice_by_index(begin = var_6397_begin_0, end = var_6397_end_0, end_mask = var_6397_end_mask_0, x = value_13_cast_fp16)[name = tensor("op_6397_cast_fp16")]; + tensor var_6401_begin_0 = const()[name = tensor("op_6401_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_6401_end_0 = const()[name = tensor("op_6401_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_6401_end_mask_0 = const()[name = tensor("op_6401_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6401_cast_fp16 = slice_by_index(begin = var_6401_begin_0, end = var_6401_end_0, end_mask = var_6401_end_mask_0, x = value_13_cast_fp16)[name = tensor("op_6401_cast_fp16")]; + tensor var_6405_begin_0 = const()[name = tensor("op_6405_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_6405_end_0 = const()[name = tensor("op_6405_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_6405_end_mask_0 = const()[name = tensor("op_6405_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6405_cast_fp16 = slice_by_index(begin = var_6405_begin_0, end = var_6405_end_0, end_mask = var_6405_end_mask_0, x = value_13_cast_fp16)[name = tensor("op_6405_cast_fp16")]; + tensor var_6409_begin_0 = const()[name = tensor("op_6409_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_6409_end_0 = const()[name = tensor("op_6409_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_6409_end_mask_0 = const()[name = tensor("op_6409_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6409_cast_fp16 = slice_by_index(begin = var_6409_begin_0, end = var_6409_end_0, end_mask = var_6409_end_mask_0, x = value_13_cast_fp16)[name = tensor("op_6409_cast_fp16")]; + tensor var_6413_begin_0 = const()[name = tensor("op_6413_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_6413_end_0 = const()[name = tensor("op_6413_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_6413_end_mask_0 = const()[name = tensor("op_6413_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6413_cast_fp16 = slice_by_index(begin = var_6413_begin_0, end = var_6413_end_0, end_mask = var_6413_end_mask_0, x = value_13_cast_fp16)[name = tensor("op_6413_cast_fp16")]; + tensor var_6417_begin_0 = const()[name = tensor("op_6417_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_6417_end_0 = const()[name = tensor("op_6417_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_6417_end_mask_0 = const()[name = tensor("op_6417_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6417_cast_fp16 = slice_by_index(begin = var_6417_begin_0, end = var_6417_end_0, end_mask = var_6417_end_mask_0, x = value_13_cast_fp16)[name = tensor("op_6417_cast_fp16")]; + tensor var_6421_begin_0 = const()[name = tensor("op_6421_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_6421_end_0 = const()[name = tensor("op_6421_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_6421_end_mask_0 = const()[name = tensor("op_6421_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6421_cast_fp16 = slice_by_index(begin = var_6421_begin_0, end = var_6421_end_0, end_mask = var_6421_end_mask_0, x = value_13_cast_fp16)[name = tensor("op_6421_cast_fp16")]; + tensor var_6425_begin_0 = const()[name = tensor("op_6425_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_6425_end_0 = const()[name = tensor("op_6425_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_6425_end_mask_0 = const()[name = tensor("op_6425_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6425_cast_fp16 = slice_by_index(begin = var_6425_begin_0, end = var_6425_end_0, end_mask = var_6425_end_mask_0, x = value_13_cast_fp16)[name = tensor("op_6425_cast_fp16")]; + tensor var_6429_begin_0 = const()[name = tensor("op_6429_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_6429_end_0 = const()[name = tensor("op_6429_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_6429_end_mask_0 = const()[name = tensor("op_6429_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6429_cast_fp16 = slice_by_index(begin = var_6429_begin_0, end = var_6429_end_0, end_mask = var_6429_end_mask_0, x = value_13_cast_fp16)[name = tensor("op_6429_cast_fp16")]; + tensor var_6433_begin_0 = const()[name = tensor("op_6433_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_6433_end_0 = const()[name = tensor("op_6433_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_6433_end_mask_0 = const()[name = tensor("op_6433_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6433_cast_fp16 = slice_by_index(begin = var_6433_begin_0, end = var_6433_end_0, end_mask = var_6433_end_mask_0, x = value_13_cast_fp16)[name = tensor("op_6433_cast_fp16")]; + tensor var_6437_begin_0 = const()[name = tensor("op_6437_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_6437_end_0 = const()[name = tensor("op_6437_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_6437_end_mask_0 = const()[name = tensor("op_6437_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6437_cast_fp16 = slice_by_index(begin = var_6437_begin_0, end = var_6437_end_0, end_mask = var_6437_end_mask_0, x = value_13_cast_fp16)[name = tensor("op_6437_cast_fp16")]; + tensor var_6441_equation_0 = const()[name = tensor("op_6441_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6441_cast_fp16 = einsum(equation = var_6441_equation_0, values = (var_6347_cast_fp16, var_6013_cast_fp16))[name = tensor("op_6441_cast_fp16")]; + tensor var_6442_to_fp16 = const()[name = tensor("op_6442_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_577_cast_fp16 = mul(x = var_6441_cast_fp16, y = var_6442_to_fp16)[name = tensor("aw_chunk_577_cast_fp16")]; + tensor var_6445_equation_0 = const()[name = tensor("op_6445_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6445_cast_fp16 = einsum(equation = var_6445_equation_0, values = (var_6347_cast_fp16, var_6020_cast_fp16))[name = tensor("op_6445_cast_fp16")]; + tensor var_6446_to_fp16 = const()[name = tensor("op_6446_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_579_cast_fp16 = mul(x = var_6445_cast_fp16, y = var_6446_to_fp16)[name = tensor("aw_chunk_579_cast_fp16")]; + tensor var_6449_equation_0 = const()[name = tensor("op_6449_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6449_cast_fp16 = einsum(equation = var_6449_equation_0, values = (var_6347_cast_fp16, var_6027_cast_fp16))[name = tensor("op_6449_cast_fp16")]; + tensor var_6450_to_fp16 = const()[name = tensor("op_6450_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_581_cast_fp16 = mul(x = var_6449_cast_fp16, y = var_6450_to_fp16)[name = tensor("aw_chunk_581_cast_fp16")]; + tensor var_6453_equation_0 = const()[name = tensor("op_6453_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6453_cast_fp16 = einsum(equation = var_6453_equation_0, values = (var_6347_cast_fp16, var_6034_cast_fp16))[name = tensor("op_6453_cast_fp16")]; + tensor var_6454_to_fp16 = const()[name = tensor("op_6454_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_583_cast_fp16 = mul(x = var_6453_cast_fp16, y = var_6454_to_fp16)[name = tensor("aw_chunk_583_cast_fp16")]; + tensor var_6457_equation_0 = const()[name = tensor("op_6457_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6457_cast_fp16 = einsum(equation = var_6457_equation_0, values = (var_6351_cast_fp16, var_6041_cast_fp16))[name = tensor("op_6457_cast_fp16")]; + tensor var_6458_to_fp16 = const()[name = tensor("op_6458_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_585_cast_fp16 = mul(x = var_6457_cast_fp16, y = var_6458_to_fp16)[name = tensor("aw_chunk_585_cast_fp16")]; + tensor var_6461_equation_0 = const()[name = tensor("op_6461_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6461_cast_fp16 = einsum(equation = var_6461_equation_0, values = (var_6351_cast_fp16, var_6048_cast_fp16))[name = tensor("op_6461_cast_fp16")]; + tensor var_6462_to_fp16 = const()[name = tensor("op_6462_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_587_cast_fp16 = mul(x = var_6461_cast_fp16, y = var_6462_to_fp16)[name = tensor("aw_chunk_587_cast_fp16")]; + tensor var_6465_equation_0 = const()[name = tensor("op_6465_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6465_cast_fp16 = einsum(equation = var_6465_equation_0, values = (var_6351_cast_fp16, var_6055_cast_fp16))[name = tensor("op_6465_cast_fp16")]; + tensor var_6466_to_fp16 = const()[name = tensor("op_6466_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_589_cast_fp16 = mul(x = var_6465_cast_fp16, y = var_6466_to_fp16)[name = tensor("aw_chunk_589_cast_fp16")]; + tensor var_6469_equation_0 = const()[name = tensor("op_6469_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6469_cast_fp16 = einsum(equation = var_6469_equation_0, values = (var_6351_cast_fp16, var_6062_cast_fp16))[name = tensor("op_6469_cast_fp16")]; + tensor var_6470_to_fp16 = const()[name = tensor("op_6470_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_591_cast_fp16 = mul(x = var_6469_cast_fp16, y = var_6470_to_fp16)[name = tensor("aw_chunk_591_cast_fp16")]; + tensor var_6473_equation_0 = const()[name = tensor("op_6473_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6473_cast_fp16 = einsum(equation = var_6473_equation_0, values = (var_6355_cast_fp16, var_6069_cast_fp16))[name = tensor("op_6473_cast_fp16")]; + tensor var_6474_to_fp16 = const()[name = tensor("op_6474_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_593_cast_fp16 = mul(x = var_6473_cast_fp16, y = var_6474_to_fp16)[name = tensor("aw_chunk_593_cast_fp16")]; + tensor var_6477_equation_0 = const()[name = tensor("op_6477_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6477_cast_fp16 = einsum(equation = var_6477_equation_0, values = (var_6355_cast_fp16, var_6076_cast_fp16))[name = tensor("op_6477_cast_fp16")]; + tensor var_6478_to_fp16 = const()[name = tensor("op_6478_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_595_cast_fp16 = mul(x = var_6477_cast_fp16, y = var_6478_to_fp16)[name = tensor("aw_chunk_595_cast_fp16")]; + tensor var_6481_equation_0 = const()[name = tensor("op_6481_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6481_cast_fp16 = einsum(equation = var_6481_equation_0, values = (var_6355_cast_fp16, var_6083_cast_fp16))[name = tensor("op_6481_cast_fp16")]; + tensor var_6482_to_fp16 = const()[name = tensor("op_6482_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_597_cast_fp16 = mul(x = var_6481_cast_fp16, y = var_6482_to_fp16)[name = tensor("aw_chunk_597_cast_fp16")]; + tensor var_6485_equation_0 = const()[name = tensor("op_6485_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6485_cast_fp16 = einsum(equation = var_6485_equation_0, values = (var_6355_cast_fp16, var_6090_cast_fp16))[name = tensor("op_6485_cast_fp16")]; + tensor var_6486_to_fp16 = const()[name = tensor("op_6486_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_599_cast_fp16 = mul(x = var_6485_cast_fp16, y = var_6486_to_fp16)[name = tensor("aw_chunk_599_cast_fp16")]; + tensor var_6489_equation_0 = const()[name = tensor("op_6489_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6489_cast_fp16 = einsum(equation = var_6489_equation_0, values = (var_6359_cast_fp16, var_6097_cast_fp16))[name = tensor("op_6489_cast_fp16")]; + tensor var_6490_to_fp16 = const()[name = tensor("op_6490_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_601_cast_fp16 = mul(x = var_6489_cast_fp16, y = var_6490_to_fp16)[name = tensor("aw_chunk_601_cast_fp16")]; + tensor var_6493_equation_0 = const()[name = tensor("op_6493_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6493_cast_fp16 = einsum(equation = var_6493_equation_0, values = (var_6359_cast_fp16, var_6104_cast_fp16))[name = tensor("op_6493_cast_fp16")]; + tensor var_6494_to_fp16 = const()[name = tensor("op_6494_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_603_cast_fp16 = mul(x = var_6493_cast_fp16, y = var_6494_to_fp16)[name = tensor("aw_chunk_603_cast_fp16")]; + tensor var_6497_equation_0 = const()[name = tensor("op_6497_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6497_cast_fp16 = einsum(equation = var_6497_equation_0, values = (var_6359_cast_fp16, var_6111_cast_fp16))[name = tensor("op_6497_cast_fp16")]; + tensor var_6498_to_fp16 = const()[name = tensor("op_6498_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_605_cast_fp16 = mul(x = var_6497_cast_fp16, y = var_6498_to_fp16)[name = tensor("aw_chunk_605_cast_fp16")]; + tensor var_6501_equation_0 = const()[name = tensor("op_6501_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6501_cast_fp16 = einsum(equation = var_6501_equation_0, values = (var_6359_cast_fp16, var_6118_cast_fp16))[name = tensor("op_6501_cast_fp16")]; + tensor var_6502_to_fp16 = const()[name = tensor("op_6502_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_607_cast_fp16 = mul(x = var_6501_cast_fp16, y = var_6502_to_fp16)[name = tensor("aw_chunk_607_cast_fp16")]; + tensor var_6505_equation_0 = const()[name = tensor("op_6505_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6505_cast_fp16 = einsum(equation = var_6505_equation_0, values = (var_6363_cast_fp16, var_6125_cast_fp16))[name = tensor("op_6505_cast_fp16")]; + tensor var_6506_to_fp16 = const()[name = tensor("op_6506_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_609_cast_fp16 = mul(x = var_6505_cast_fp16, y = var_6506_to_fp16)[name = tensor("aw_chunk_609_cast_fp16")]; + tensor var_6509_equation_0 = const()[name = tensor("op_6509_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6509_cast_fp16 = einsum(equation = var_6509_equation_0, values = (var_6363_cast_fp16, var_6132_cast_fp16))[name = tensor("op_6509_cast_fp16")]; + tensor var_6510_to_fp16 = const()[name = tensor("op_6510_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_611_cast_fp16 = mul(x = var_6509_cast_fp16, y = var_6510_to_fp16)[name = tensor("aw_chunk_611_cast_fp16")]; + tensor var_6513_equation_0 = const()[name = tensor("op_6513_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6513_cast_fp16 = einsum(equation = var_6513_equation_0, values = (var_6363_cast_fp16, var_6139_cast_fp16))[name = tensor("op_6513_cast_fp16")]; + tensor var_6514_to_fp16 = const()[name = tensor("op_6514_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_613_cast_fp16 = mul(x = var_6513_cast_fp16, y = var_6514_to_fp16)[name = tensor("aw_chunk_613_cast_fp16")]; + tensor var_6517_equation_0 = const()[name = tensor("op_6517_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6517_cast_fp16 = einsum(equation = var_6517_equation_0, values = (var_6363_cast_fp16, var_6146_cast_fp16))[name = tensor("op_6517_cast_fp16")]; + tensor var_6518_to_fp16 = const()[name = tensor("op_6518_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_615_cast_fp16 = mul(x = var_6517_cast_fp16, y = var_6518_to_fp16)[name = tensor("aw_chunk_615_cast_fp16")]; + tensor var_6521_equation_0 = const()[name = tensor("op_6521_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6521_cast_fp16 = einsum(equation = var_6521_equation_0, values = (var_6367_cast_fp16, var_6153_cast_fp16))[name = tensor("op_6521_cast_fp16")]; + tensor var_6522_to_fp16 = const()[name = tensor("op_6522_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_617_cast_fp16 = mul(x = var_6521_cast_fp16, y = var_6522_to_fp16)[name = tensor("aw_chunk_617_cast_fp16")]; + tensor var_6525_equation_0 = const()[name = tensor("op_6525_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6525_cast_fp16 = einsum(equation = var_6525_equation_0, values = (var_6367_cast_fp16, var_6160_cast_fp16))[name = tensor("op_6525_cast_fp16")]; + tensor var_6526_to_fp16 = const()[name = tensor("op_6526_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_619_cast_fp16 = mul(x = var_6525_cast_fp16, y = var_6526_to_fp16)[name = tensor("aw_chunk_619_cast_fp16")]; + tensor var_6529_equation_0 = const()[name = tensor("op_6529_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6529_cast_fp16 = einsum(equation = var_6529_equation_0, values = (var_6367_cast_fp16, var_6167_cast_fp16))[name = tensor("op_6529_cast_fp16")]; + tensor var_6530_to_fp16 = const()[name = tensor("op_6530_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_621_cast_fp16 = mul(x = var_6529_cast_fp16, y = var_6530_to_fp16)[name = tensor("aw_chunk_621_cast_fp16")]; + tensor var_6533_equation_0 = const()[name = tensor("op_6533_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6533_cast_fp16 = einsum(equation = var_6533_equation_0, values = (var_6367_cast_fp16, var_6174_cast_fp16))[name = tensor("op_6533_cast_fp16")]; + tensor var_6534_to_fp16 = const()[name = tensor("op_6534_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_623_cast_fp16 = mul(x = var_6533_cast_fp16, y = var_6534_to_fp16)[name = tensor("aw_chunk_623_cast_fp16")]; + tensor var_6537_equation_0 = const()[name = tensor("op_6537_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6537_cast_fp16 = einsum(equation = var_6537_equation_0, values = (var_6371_cast_fp16, var_6181_cast_fp16))[name = tensor("op_6537_cast_fp16")]; + tensor var_6538_to_fp16 = const()[name = tensor("op_6538_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_625_cast_fp16 = mul(x = var_6537_cast_fp16, y = var_6538_to_fp16)[name = tensor("aw_chunk_625_cast_fp16")]; + tensor var_6541_equation_0 = const()[name = tensor("op_6541_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6541_cast_fp16 = einsum(equation = var_6541_equation_0, values = (var_6371_cast_fp16, var_6188_cast_fp16))[name = tensor("op_6541_cast_fp16")]; + tensor var_6542_to_fp16 = const()[name = tensor("op_6542_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_627_cast_fp16 = mul(x = var_6541_cast_fp16, y = var_6542_to_fp16)[name = tensor("aw_chunk_627_cast_fp16")]; + tensor var_6545_equation_0 = const()[name = tensor("op_6545_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6545_cast_fp16 = einsum(equation = var_6545_equation_0, values = (var_6371_cast_fp16, var_6195_cast_fp16))[name = tensor("op_6545_cast_fp16")]; + tensor var_6546_to_fp16 = const()[name = tensor("op_6546_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_629_cast_fp16 = mul(x = var_6545_cast_fp16, y = var_6546_to_fp16)[name = tensor("aw_chunk_629_cast_fp16")]; + tensor var_6549_equation_0 = const()[name = tensor("op_6549_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6549_cast_fp16 = einsum(equation = var_6549_equation_0, values = (var_6371_cast_fp16, var_6202_cast_fp16))[name = tensor("op_6549_cast_fp16")]; + tensor var_6550_to_fp16 = const()[name = tensor("op_6550_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_631_cast_fp16 = mul(x = var_6549_cast_fp16, y = var_6550_to_fp16)[name = tensor("aw_chunk_631_cast_fp16")]; + tensor var_6553_equation_0 = const()[name = tensor("op_6553_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6553_cast_fp16 = einsum(equation = var_6553_equation_0, values = (var_6375_cast_fp16, var_6209_cast_fp16))[name = tensor("op_6553_cast_fp16")]; + tensor var_6554_to_fp16 = const()[name = tensor("op_6554_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_633_cast_fp16 = mul(x = var_6553_cast_fp16, y = var_6554_to_fp16)[name = tensor("aw_chunk_633_cast_fp16")]; + tensor var_6557_equation_0 = const()[name = tensor("op_6557_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6557_cast_fp16 = einsum(equation = var_6557_equation_0, values = (var_6375_cast_fp16, var_6216_cast_fp16))[name = tensor("op_6557_cast_fp16")]; + tensor var_6558_to_fp16 = const()[name = tensor("op_6558_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_635_cast_fp16 = mul(x = var_6557_cast_fp16, y = var_6558_to_fp16)[name = tensor("aw_chunk_635_cast_fp16")]; + tensor var_6561_equation_0 = const()[name = tensor("op_6561_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6561_cast_fp16 = einsum(equation = var_6561_equation_0, values = (var_6375_cast_fp16, var_6223_cast_fp16))[name = tensor("op_6561_cast_fp16")]; + tensor var_6562_to_fp16 = const()[name = tensor("op_6562_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_637_cast_fp16 = mul(x = var_6561_cast_fp16, y = var_6562_to_fp16)[name = tensor("aw_chunk_637_cast_fp16")]; + tensor var_6565_equation_0 = const()[name = tensor("op_6565_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6565_cast_fp16 = einsum(equation = var_6565_equation_0, values = (var_6375_cast_fp16, var_6230_cast_fp16))[name = tensor("op_6565_cast_fp16")]; + tensor var_6566_to_fp16 = const()[name = tensor("op_6566_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_639_cast_fp16 = mul(x = var_6565_cast_fp16, y = var_6566_to_fp16)[name = tensor("aw_chunk_639_cast_fp16")]; + tensor var_6569_equation_0 = const()[name = tensor("op_6569_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6569_cast_fp16 = einsum(equation = var_6569_equation_0, values = (var_6379_cast_fp16, var_6237_cast_fp16))[name = tensor("op_6569_cast_fp16")]; + tensor var_6570_to_fp16 = const()[name = tensor("op_6570_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_641_cast_fp16 = mul(x = var_6569_cast_fp16, y = var_6570_to_fp16)[name = tensor("aw_chunk_641_cast_fp16")]; + tensor var_6573_equation_0 = const()[name = tensor("op_6573_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6573_cast_fp16 = einsum(equation = var_6573_equation_0, values = (var_6379_cast_fp16, var_6244_cast_fp16))[name = tensor("op_6573_cast_fp16")]; + tensor var_6574_to_fp16 = const()[name = tensor("op_6574_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_643_cast_fp16 = mul(x = var_6573_cast_fp16, y = var_6574_to_fp16)[name = tensor("aw_chunk_643_cast_fp16")]; + tensor var_6577_equation_0 = const()[name = tensor("op_6577_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6577_cast_fp16 = einsum(equation = var_6577_equation_0, values = (var_6379_cast_fp16, var_6251_cast_fp16))[name = tensor("op_6577_cast_fp16")]; + tensor var_6578_to_fp16 = const()[name = tensor("op_6578_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_645_cast_fp16 = mul(x = var_6577_cast_fp16, y = var_6578_to_fp16)[name = tensor("aw_chunk_645_cast_fp16")]; + tensor var_6581_equation_0 = const()[name = tensor("op_6581_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6581_cast_fp16 = einsum(equation = var_6581_equation_0, values = (var_6379_cast_fp16, var_6258_cast_fp16))[name = tensor("op_6581_cast_fp16")]; + tensor var_6582_to_fp16 = const()[name = tensor("op_6582_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_647_cast_fp16 = mul(x = var_6581_cast_fp16, y = var_6582_to_fp16)[name = tensor("aw_chunk_647_cast_fp16")]; + tensor var_6585_equation_0 = const()[name = tensor("op_6585_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6585_cast_fp16 = einsum(equation = var_6585_equation_0, values = (var_6383_cast_fp16, var_6265_cast_fp16))[name = tensor("op_6585_cast_fp16")]; + tensor var_6586_to_fp16 = const()[name = tensor("op_6586_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_649_cast_fp16 = mul(x = var_6585_cast_fp16, y = var_6586_to_fp16)[name = tensor("aw_chunk_649_cast_fp16")]; + tensor var_6589_equation_0 = const()[name = tensor("op_6589_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6589_cast_fp16 = einsum(equation = var_6589_equation_0, values = (var_6383_cast_fp16, var_6272_cast_fp16))[name = tensor("op_6589_cast_fp16")]; + tensor var_6590_to_fp16 = const()[name = tensor("op_6590_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_651_cast_fp16 = mul(x = var_6589_cast_fp16, y = var_6590_to_fp16)[name = tensor("aw_chunk_651_cast_fp16")]; + tensor var_6593_equation_0 = const()[name = tensor("op_6593_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6593_cast_fp16 = einsum(equation = var_6593_equation_0, values = (var_6383_cast_fp16, var_6279_cast_fp16))[name = tensor("op_6593_cast_fp16")]; + tensor var_6594_to_fp16 = const()[name = tensor("op_6594_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_653_cast_fp16 = mul(x = var_6593_cast_fp16, y = var_6594_to_fp16)[name = tensor("aw_chunk_653_cast_fp16")]; + tensor var_6597_equation_0 = const()[name = tensor("op_6597_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6597_cast_fp16 = einsum(equation = var_6597_equation_0, values = (var_6383_cast_fp16, var_6286_cast_fp16))[name = tensor("op_6597_cast_fp16")]; + tensor var_6598_to_fp16 = const()[name = tensor("op_6598_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_655_cast_fp16 = mul(x = var_6597_cast_fp16, y = var_6598_to_fp16)[name = tensor("aw_chunk_655_cast_fp16")]; + tensor var_6601_equation_0 = const()[name = tensor("op_6601_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6601_cast_fp16 = einsum(equation = var_6601_equation_0, values = (var_6387_cast_fp16, var_6293_cast_fp16))[name = tensor("op_6601_cast_fp16")]; + tensor var_6602_to_fp16 = const()[name = tensor("op_6602_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_657_cast_fp16 = mul(x = var_6601_cast_fp16, y = var_6602_to_fp16)[name = tensor("aw_chunk_657_cast_fp16")]; + tensor var_6605_equation_0 = const()[name = tensor("op_6605_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6605_cast_fp16 = einsum(equation = var_6605_equation_0, values = (var_6387_cast_fp16, var_6300_cast_fp16))[name = tensor("op_6605_cast_fp16")]; + tensor var_6606_to_fp16 = const()[name = tensor("op_6606_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_659_cast_fp16 = mul(x = var_6605_cast_fp16, y = var_6606_to_fp16)[name = tensor("aw_chunk_659_cast_fp16")]; + tensor var_6609_equation_0 = const()[name = tensor("op_6609_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6609_cast_fp16 = einsum(equation = var_6609_equation_0, values = (var_6387_cast_fp16, var_6307_cast_fp16))[name = tensor("op_6609_cast_fp16")]; + tensor var_6610_to_fp16 = const()[name = tensor("op_6610_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_661_cast_fp16 = mul(x = var_6609_cast_fp16, y = var_6610_to_fp16)[name = tensor("aw_chunk_661_cast_fp16")]; + tensor var_6613_equation_0 = const()[name = tensor("op_6613_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6613_cast_fp16 = einsum(equation = var_6613_equation_0, values = (var_6387_cast_fp16, var_6314_cast_fp16))[name = tensor("op_6613_cast_fp16")]; + tensor var_6614_to_fp16 = const()[name = tensor("op_6614_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_663_cast_fp16 = mul(x = var_6613_cast_fp16, y = var_6614_to_fp16)[name = tensor("aw_chunk_663_cast_fp16")]; + tensor var_6617_equation_0 = const()[name = tensor("op_6617_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6617_cast_fp16 = einsum(equation = var_6617_equation_0, values = (var_6391_cast_fp16, var_6321_cast_fp16))[name = tensor("op_6617_cast_fp16")]; + tensor var_6618_to_fp16 = const()[name = tensor("op_6618_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_665_cast_fp16 = mul(x = var_6617_cast_fp16, y = var_6618_to_fp16)[name = tensor("aw_chunk_665_cast_fp16")]; + tensor var_6621_equation_0 = const()[name = tensor("op_6621_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6621_cast_fp16 = einsum(equation = var_6621_equation_0, values = (var_6391_cast_fp16, var_6328_cast_fp16))[name = tensor("op_6621_cast_fp16")]; + tensor var_6622_to_fp16 = const()[name = tensor("op_6622_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_667_cast_fp16 = mul(x = var_6621_cast_fp16, y = var_6622_to_fp16)[name = tensor("aw_chunk_667_cast_fp16")]; + tensor var_6625_equation_0 = const()[name = tensor("op_6625_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6625_cast_fp16 = einsum(equation = var_6625_equation_0, values = (var_6391_cast_fp16, var_6335_cast_fp16))[name = tensor("op_6625_cast_fp16")]; + tensor var_6626_to_fp16 = const()[name = tensor("op_6626_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_669_cast_fp16 = mul(x = var_6625_cast_fp16, y = var_6626_to_fp16)[name = tensor("aw_chunk_669_cast_fp16")]; + tensor var_6629_equation_0 = const()[name = tensor("op_6629_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_6629_cast_fp16 = einsum(equation = var_6629_equation_0, values = (var_6391_cast_fp16, var_6342_cast_fp16))[name = tensor("op_6629_cast_fp16")]; + tensor var_6630_to_fp16 = const()[name = tensor("op_6630_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_671_cast_fp16 = mul(x = var_6629_cast_fp16, y = var_6630_to_fp16)[name = tensor("aw_chunk_671_cast_fp16")]; + tensor var_6632_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_577_cast_fp16)[name = tensor("op_6632_cast_fp16")]; + tensor var_6633_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_579_cast_fp16)[name = tensor("op_6633_cast_fp16")]; + tensor var_6634_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_581_cast_fp16)[name = tensor("op_6634_cast_fp16")]; + tensor var_6635_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_583_cast_fp16)[name = tensor("op_6635_cast_fp16")]; + tensor var_6636_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_585_cast_fp16)[name = tensor("op_6636_cast_fp16")]; + tensor var_6637_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_587_cast_fp16)[name = tensor("op_6637_cast_fp16")]; + tensor var_6638_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_589_cast_fp16)[name = tensor("op_6638_cast_fp16")]; + tensor var_6639_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_591_cast_fp16)[name = tensor("op_6639_cast_fp16")]; + tensor var_6640_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_593_cast_fp16)[name = tensor("op_6640_cast_fp16")]; + tensor var_6641_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_595_cast_fp16)[name = tensor("op_6641_cast_fp16")]; + tensor var_6642_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_597_cast_fp16)[name = tensor("op_6642_cast_fp16")]; + tensor var_6643_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_599_cast_fp16)[name = tensor("op_6643_cast_fp16")]; + tensor var_6644_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_601_cast_fp16)[name = tensor("op_6644_cast_fp16")]; + tensor var_6645_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_603_cast_fp16)[name = tensor("op_6645_cast_fp16")]; + tensor var_6646_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_605_cast_fp16)[name = tensor("op_6646_cast_fp16")]; + tensor var_6647_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_607_cast_fp16)[name = tensor("op_6647_cast_fp16")]; + tensor var_6648_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_609_cast_fp16)[name = tensor("op_6648_cast_fp16")]; + tensor var_6649_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_611_cast_fp16)[name = tensor("op_6649_cast_fp16")]; + tensor var_6650_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_613_cast_fp16)[name = tensor("op_6650_cast_fp16")]; + tensor var_6651_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_615_cast_fp16)[name = tensor("op_6651_cast_fp16")]; + tensor var_6652_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_617_cast_fp16)[name = tensor("op_6652_cast_fp16")]; + tensor var_6653_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_619_cast_fp16)[name = tensor("op_6653_cast_fp16")]; + tensor var_6654_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_621_cast_fp16)[name = tensor("op_6654_cast_fp16")]; + tensor var_6655_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_623_cast_fp16)[name = tensor("op_6655_cast_fp16")]; + tensor var_6656_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_625_cast_fp16)[name = tensor("op_6656_cast_fp16")]; + tensor var_6657_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_627_cast_fp16)[name = tensor("op_6657_cast_fp16")]; + tensor var_6658_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_629_cast_fp16)[name = tensor("op_6658_cast_fp16")]; + tensor var_6659_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_631_cast_fp16)[name = tensor("op_6659_cast_fp16")]; + tensor var_6660_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_633_cast_fp16)[name = tensor("op_6660_cast_fp16")]; + tensor var_6661_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_635_cast_fp16)[name = tensor("op_6661_cast_fp16")]; + tensor var_6662_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_637_cast_fp16)[name = tensor("op_6662_cast_fp16")]; + tensor var_6663_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_639_cast_fp16)[name = tensor("op_6663_cast_fp16")]; + tensor var_6664_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_641_cast_fp16)[name = tensor("op_6664_cast_fp16")]; + tensor var_6665_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_643_cast_fp16)[name = tensor("op_6665_cast_fp16")]; + tensor var_6666_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_645_cast_fp16)[name = tensor("op_6666_cast_fp16")]; + tensor var_6667_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_647_cast_fp16)[name = tensor("op_6667_cast_fp16")]; + tensor var_6668_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_649_cast_fp16)[name = tensor("op_6668_cast_fp16")]; + tensor var_6669_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_651_cast_fp16)[name = tensor("op_6669_cast_fp16")]; + tensor var_6670_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_653_cast_fp16)[name = tensor("op_6670_cast_fp16")]; + tensor var_6671_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_655_cast_fp16)[name = tensor("op_6671_cast_fp16")]; + tensor var_6672_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_657_cast_fp16)[name = tensor("op_6672_cast_fp16")]; + tensor var_6673_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_659_cast_fp16)[name = tensor("op_6673_cast_fp16")]; + tensor var_6674_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_661_cast_fp16)[name = tensor("op_6674_cast_fp16")]; + tensor var_6675_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_663_cast_fp16)[name = tensor("op_6675_cast_fp16")]; + tensor var_6676_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_665_cast_fp16)[name = tensor("op_6676_cast_fp16")]; + tensor var_6677_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_667_cast_fp16)[name = tensor("op_6677_cast_fp16")]; + tensor var_6678_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_669_cast_fp16)[name = tensor("op_6678_cast_fp16")]; + tensor var_6679_cast_fp16 = softmax(axis = var_5905, x = aw_chunk_671_cast_fp16)[name = tensor("op_6679_cast_fp16")]; + tensor var_6681_equation_0 = const()[name = tensor("op_6681_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6681_cast_fp16 = einsum(equation = var_6681_equation_0, values = (var_6393_cast_fp16, var_6632_cast_fp16))[name = tensor("op_6681_cast_fp16")]; + tensor var_6683_equation_0 = const()[name = tensor("op_6683_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6683_cast_fp16 = einsum(equation = var_6683_equation_0, values = (var_6393_cast_fp16, var_6633_cast_fp16))[name = tensor("op_6683_cast_fp16")]; + tensor var_6685_equation_0 = const()[name = tensor("op_6685_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6685_cast_fp16 = einsum(equation = var_6685_equation_0, values = (var_6393_cast_fp16, var_6634_cast_fp16))[name = tensor("op_6685_cast_fp16")]; + tensor var_6687_equation_0 = const()[name = tensor("op_6687_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6687_cast_fp16 = einsum(equation = var_6687_equation_0, values = (var_6393_cast_fp16, var_6635_cast_fp16))[name = tensor("op_6687_cast_fp16")]; + tensor var_6689_equation_0 = const()[name = tensor("op_6689_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6689_cast_fp16 = einsum(equation = var_6689_equation_0, values = (var_6397_cast_fp16, var_6636_cast_fp16))[name = tensor("op_6689_cast_fp16")]; + tensor var_6691_equation_0 = const()[name = tensor("op_6691_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6691_cast_fp16 = einsum(equation = var_6691_equation_0, values = (var_6397_cast_fp16, var_6637_cast_fp16))[name = tensor("op_6691_cast_fp16")]; + tensor var_6693_equation_0 = const()[name = tensor("op_6693_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6693_cast_fp16 = einsum(equation = var_6693_equation_0, values = (var_6397_cast_fp16, var_6638_cast_fp16))[name = tensor("op_6693_cast_fp16")]; + tensor var_6695_equation_0 = const()[name = tensor("op_6695_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6695_cast_fp16 = einsum(equation = var_6695_equation_0, values = (var_6397_cast_fp16, var_6639_cast_fp16))[name = tensor("op_6695_cast_fp16")]; + tensor var_6697_equation_0 = const()[name = tensor("op_6697_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6697_cast_fp16 = einsum(equation = var_6697_equation_0, values = (var_6401_cast_fp16, var_6640_cast_fp16))[name = tensor("op_6697_cast_fp16")]; + tensor var_6699_equation_0 = const()[name = tensor("op_6699_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6699_cast_fp16 = einsum(equation = var_6699_equation_0, values = (var_6401_cast_fp16, var_6641_cast_fp16))[name = tensor("op_6699_cast_fp16")]; + tensor var_6701_equation_0 = const()[name = tensor("op_6701_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6701_cast_fp16 = einsum(equation = var_6701_equation_0, values = (var_6401_cast_fp16, var_6642_cast_fp16))[name = tensor("op_6701_cast_fp16")]; + tensor var_6703_equation_0 = const()[name = tensor("op_6703_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6703_cast_fp16 = einsum(equation = var_6703_equation_0, values = (var_6401_cast_fp16, var_6643_cast_fp16))[name = tensor("op_6703_cast_fp16")]; + tensor var_6705_equation_0 = const()[name = tensor("op_6705_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6705_cast_fp16 = einsum(equation = var_6705_equation_0, values = (var_6405_cast_fp16, var_6644_cast_fp16))[name = tensor("op_6705_cast_fp16")]; + tensor var_6707_equation_0 = const()[name = tensor("op_6707_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6707_cast_fp16 = einsum(equation = var_6707_equation_0, values = (var_6405_cast_fp16, var_6645_cast_fp16))[name = tensor("op_6707_cast_fp16")]; + tensor var_6709_equation_0 = const()[name = tensor("op_6709_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6709_cast_fp16 = einsum(equation = var_6709_equation_0, values = (var_6405_cast_fp16, var_6646_cast_fp16))[name = tensor("op_6709_cast_fp16")]; + tensor var_6711_equation_0 = const()[name = tensor("op_6711_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6711_cast_fp16 = einsum(equation = var_6711_equation_0, values = (var_6405_cast_fp16, var_6647_cast_fp16))[name = tensor("op_6711_cast_fp16")]; + tensor var_6713_equation_0 = const()[name = tensor("op_6713_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6713_cast_fp16 = einsum(equation = var_6713_equation_0, values = (var_6409_cast_fp16, var_6648_cast_fp16))[name = tensor("op_6713_cast_fp16")]; + tensor var_6715_equation_0 = const()[name = tensor("op_6715_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6715_cast_fp16 = einsum(equation = var_6715_equation_0, values = (var_6409_cast_fp16, var_6649_cast_fp16))[name = tensor("op_6715_cast_fp16")]; + tensor var_6717_equation_0 = const()[name = tensor("op_6717_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6717_cast_fp16 = einsum(equation = var_6717_equation_0, values = (var_6409_cast_fp16, var_6650_cast_fp16))[name = tensor("op_6717_cast_fp16")]; + tensor var_6719_equation_0 = const()[name = tensor("op_6719_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6719_cast_fp16 = einsum(equation = var_6719_equation_0, values = (var_6409_cast_fp16, var_6651_cast_fp16))[name = tensor("op_6719_cast_fp16")]; + tensor var_6721_equation_0 = const()[name = tensor("op_6721_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6721_cast_fp16 = einsum(equation = var_6721_equation_0, values = (var_6413_cast_fp16, var_6652_cast_fp16))[name = tensor("op_6721_cast_fp16")]; + tensor var_6723_equation_0 = const()[name = tensor("op_6723_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6723_cast_fp16 = einsum(equation = var_6723_equation_0, values = (var_6413_cast_fp16, var_6653_cast_fp16))[name = tensor("op_6723_cast_fp16")]; + tensor var_6725_equation_0 = const()[name = tensor("op_6725_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6725_cast_fp16 = einsum(equation = var_6725_equation_0, values = (var_6413_cast_fp16, var_6654_cast_fp16))[name = tensor("op_6725_cast_fp16")]; + tensor var_6727_equation_0 = const()[name = tensor("op_6727_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6727_cast_fp16 = einsum(equation = var_6727_equation_0, values = (var_6413_cast_fp16, var_6655_cast_fp16))[name = tensor("op_6727_cast_fp16")]; + tensor var_6729_equation_0 = const()[name = tensor("op_6729_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6729_cast_fp16 = einsum(equation = var_6729_equation_0, values = (var_6417_cast_fp16, var_6656_cast_fp16))[name = tensor("op_6729_cast_fp16")]; + tensor var_6731_equation_0 = const()[name = tensor("op_6731_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6731_cast_fp16 = einsum(equation = var_6731_equation_0, values = (var_6417_cast_fp16, var_6657_cast_fp16))[name = tensor("op_6731_cast_fp16")]; + tensor var_6733_equation_0 = const()[name = tensor("op_6733_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6733_cast_fp16 = einsum(equation = var_6733_equation_0, values = (var_6417_cast_fp16, var_6658_cast_fp16))[name = tensor("op_6733_cast_fp16")]; + tensor var_6735_equation_0 = const()[name = tensor("op_6735_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6735_cast_fp16 = einsum(equation = var_6735_equation_0, values = (var_6417_cast_fp16, var_6659_cast_fp16))[name = tensor("op_6735_cast_fp16")]; + tensor var_6737_equation_0 = const()[name = tensor("op_6737_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6737_cast_fp16 = einsum(equation = var_6737_equation_0, values = (var_6421_cast_fp16, var_6660_cast_fp16))[name = tensor("op_6737_cast_fp16")]; + tensor var_6739_equation_0 = const()[name = tensor("op_6739_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6739_cast_fp16 = einsum(equation = var_6739_equation_0, values = (var_6421_cast_fp16, var_6661_cast_fp16))[name = tensor("op_6739_cast_fp16")]; + tensor var_6741_equation_0 = const()[name = tensor("op_6741_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6741_cast_fp16 = einsum(equation = var_6741_equation_0, values = (var_6421_cast_fp16, var_6662_cast_fp16))[name = tensor("op_6741_cast_fp16")]; + tensor var_6743_equation_0 = const()[name = tensor("op_6743_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6743_cast_fp16 = einsum(equation = var_6743_equation_0, values = (var_6421_cast_fp16, var_6663_cast_fp16))[name = tensor("op_6743_cast_fp16")]; + tensor var_6745_equation_0 = const()[name = tensor("op_6745_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6745_cast_fp16 = einsum(equation = var_6745_equation_0, values = (var_6425_cast_fp16, var_6664_cast_fp16))[name = tensor("op_6745_cast_fp16")]; + tensor var_6747_equation_0 = const()[name = tensor("op_6747_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6747_cast_fp16 = einsum(equation = var_6747_equation_0, values = (var_6425_cast_fp16, var_6665_cast_fp16))[name = tensor("op_6747_cast_fp16")]; + tensor var_6749_equation_0 = const()[name = tensor("op_6749_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6749_cast_fp16 = einsum(equation = var_6749_equation_0, values = (var_6425_cast_fp16, var_6666_cast_fp16))[name = tensor("op_6749_cast_fp16")]; + tensor var_6751_equation_0 = const()[name = tensor("op_6751_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6751_cast_fp16 = einsum(equation = var_6751_equation_0, values = (var_6425_cast_fp16, var_6667_cast_fp16))[name = tensor("op_6751_cast_fp16")]; + tensor var_6753_equation_0 = const()[name = tensor("op_6753_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6753_cast_fp16 = einsum(equation = var_6753_equation_0, values = (var_6429_cast_fp16, var_6668_cast_fp16))[name = tensor("op_6753_cast_fp16")]; + tensor var_6755_equation_0 = const()[name = tensor("op_6755_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6755_cast_fp16 = einsum(equation = var_6755_equation_0, values = (var_6429_cast_fp16, var_6669_cast_fp16))[name = tensor("op_6755_cast_fp16")]; + tensor var_6757_equation_0 = const()[name = tensor("op_6757_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6757_cast_fp16 = einsum(equation = var_6757_equation_0, values = (var_6429_cast_fp16, var_6670_cast_fp16))[name = tensor("op_6757_cast_fp16")]; + tensor var_6759_equation_0 = const()[name = tensor("op_6759_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6759_cast_fp16 = einsum(equation = var_6759_equation_0, values = (var_6429_cast_fp16, var_6671_cast_fp16))[name = tensor("op_6759_cast_fp16")]; + tensor var_6761_equation_0 = const()[name = tensor("op_6761_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6761_cast_fp16 = einsum(equation = var_6761_equation_0, values = (var_6433_cast_fp16, var_6672_cast_fp16))[name = tensor("op_6761_cast_fp16")]; + tensor var_6763_equation_0 = const()[name = tensor("op_6763_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6763_cast_fp16 = einsum(equation = var_6763_equation_0, values = (var_6433_cast_fp16, var_6673_cast_fp16))[name = tensor("op_6763_cast_fp16")]; + tensor var_6765_equation_0 = const()[name = tensor("op_6765_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6765_cast_fp16 = einsum(equation = var_6765_equation_0, values = (var_6433_cast_fp16, var_6674_cast_fp16))[name = tensor("op_6765_cast_fp16")]; + tensor var_6767_equation_0 = const()[name = tensor("op_6767_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6767_cast_fp16 = einsum(equation = var_6767_equation_0, values = (var_6433_cast_fp16, var_6675_cast_fp16))[name = tensor("op_6767_cast_fp16")]; + tensor var_6769_equation_0 = const()[name = tensor("op_6769_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6769_cast_fp16 = einsum(equation = var_6769_equation_0, values = (var_6437_cast_fp16, var_6676_cast_fp16))[name = tensor("op_6769_cast_fp16")]; + tensor var_6771_equation_0 = const()[name = tensor("op_6771_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6771_cast_fp16 = einsum(equation = var_6771_equation_0, values = (var_6437_cast_fp16, var_6677_cast_fp16))[name = tensor("op_6771_cast_fp16")]; + tensor var_6773_equation_0 = const()[name = tensor("op_6773_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6773_cast_fp16 = einsum(equation = var_6773_equation_0, values = (var_6437_cast_fp16, var_6678_cast_fp16))[name = tensor("op_6773_cast_fp16")]; + tensor var_6775_equation_0 = const()[name = tensor("op_6775_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_6775_cast_fp16 = einsum(equation = var_6775_equation_0, values = (var_6437_cast_fp16, var_6679_cast_fp16))[name = tensor("op_6775_cast_fp16")]; + tensor var_6777_interleave_0 = const()[name = tensor("op_6777_interleave_0"), val = tensor(false)]; + tensor var_6777_cast_fp16 = concat(axis = var_5888, interleave = var_6777_interleave_0, values = (var_6681_cast_fp16, var_6683_cast_fp16, var_6685_cast_fp16, var_6687_cast_fp16))[name = tensor("op_6777_cast_fp16")]; + tensor var_6779_interleave_0 = const()[name = tensor("op_6779_interleave_0"), val = tensor(false)]; + tensor var_6779_cast_fp16 = concat(axis = var_5888, interleave = var_6779_interleave_0, values = (var_6689_cast_fp16, var_6691_cast_fp16, var_6693_cast_fp16, var_6695_cast_fp16))[name = tensor("op_6779_cast_fp16")]; + tensor var_6781_interleave_0 = const()[name = tensor("op_6781_interleave_0"), val = tensor(false)]; + tensor var_6781_cast_fp16 = concat(axis = var_5888, interleave = var_6781_interleave_0, values = (var_6697_cast_fp16, var_6699_cast_fp16, var_6701_cast_fp16, var_6703_cast_fp16))[name = tensor("op_6781_cast_fp16")]; + tensor var_6783_interleave_0 = const()[name = tensor("op_6783_interleave_0"), val = tensor(false)]; + tensor var_6783_cast_fp16 = concat(axis = var_5888, interleave = var_6783_interleave_0, values = (var_6705_cast_fp16, var_6707_cast_fp16, var_6709_cast_fp16, var_6711_cast_fp16))[name = tensor("op_6783_cast_fp16")]; + tensor var_6785_interleave_0 = const()[name = tensor("op_6785_interleave_0"), val = tensor(false)]; + tensor var_6785_cast_fp16 = concat(axis = var_5888, interleave = var_6785_interleave_0, values = (var_6713_cast_fp16, var_6715_cast_fp16, var_6717_cast_fp16, var_6719_cast_fp16))[name = tensor("op_6785_cast_fp16")]; + tensor var_6787_interleave_0 = const()[name = tensor("op_6787_interleave_0"), val = tensor(false)]; + tensor var_6787_cast_fp16 = concat(axis = var_5888, interleave = var_6787_interleave_0, values = (var_6721_cast_fp16, var_6723_cast_fp16, var_6725_cast_fp16, var_6727_cast_fp16))[name = tensor("op_6787_cast_fp16")]; + tensor var_6789_interleave_0 = const()[name = tensor("op_6789_interleave_0"), val = tensor(false)]; + tensor var_6789_cast_fp16 = concat(axis = var_5888, interleave = var_6789_interleave_0, values = (var_6729_cast_fp16, var_6731_cast_fp16, var_6733_cast_fp16, var_6735_cast_fp16))[name = tensor("op_6789_cast_fp16")]; + tensor var_6791_interleave_0 = const()[name = tensor("op_6791_interleave_0"), val = tensor(false)]; + tensor var_6791_cast_fp16 = concat(axis = var_5888, interleave = var_6791_interleave_0, values = (var_6737_cast_fp16, var_6739_cast_fp16, var_6741_cast_fp16, var_6743_cast_fp16))[name = tensor("op_6791_cast_fp16")]; + tensor var_6793_interleave_0 = const()[name = tensor("op_6793_interleave_0"), val = tensor(false)]; + tensor var_6793_cast_fp16 = concat(axis = var_5888, interleave = var_6793_interleave_0, values = (var_6745_cast_fp16, var_6747_cast_fp16, var_6749_cast_fp16, var_6751_cast_fp16))[name = tensor("op_6793_cast_fp16")]; + tensor var_6795_interleave_0 = const()[name = tensor("op_6795_interleave_0"), val = tensor(false)]; + tensor var_6795_cast_fp16 = concat(axis = var_5888, interleave = var_6795_interleave_0, values = (var_6753_cast_fp16, var_6755_cast_fp16, var_6757_cast_fp16, var_6759_cast_fp16))[name = tensor("op_6795_cast_fp16")]; + tensor var_6797_interleave_0 = const()[name = tensor("op_6797_interleave_0"), val = tensor(false)]; + tensor var_6797_cast_fp16 = concat(axis = var_5888, interleave = var_6797_interleave_0, values = (var_6761_cast_fp16, var_6763_cast_fp16, var_6765_cast_fp16, var_6767_cast_fp16))[name = tensor("op_6797_cast_fp16")]; + tensor var_6799_interleave_0 = const()[name = tensor("op_6799_interleave_0"), val = tensor(false)]; + tensor var_6799_cast_fp16 = concat(axis = var_5888, interleave = var_6799_interleave_0, values = (var_6769_cast_fp16, var_6771_cast_fp16, var_6773_cast_fp16, var_6775_cast_fp16))[name = tensor("op_6799_cast_fp16")]; + tensor input_49_interleave_0 = const()[name = tensor("input_49_interleave_0"), val = tensor(false)]; + tensor input_49_cast_fp16 = concat(axis = var_5905, interleave = input_49_interleave_0, values = (var_6777_cast_fp16, var_6779_cast_fp16, var_6781_cast_fp16, var_6783_cast_fp16, var_6785_cast_fp16, var_6787_cast_fp16, var_6789_cast_fp16, var_6791_cast_fp16, var_6793_cast_fp16, var_6795_cast_fp16, var_6797_cast_fp16, var_6799_cast_fp16))[name = tensor("input_49_cast_fp16")]; + tensor var_6804 = const()[name = tensor("op_6804"), val = tensor([1, 1])]; + tensor var_6806 = const()[name = tensor("op_6806"), val = tensor([1, 1])]; + tensor obj_27_pad_type_0 = const()[name = tensor("obj_27_pad_type_0"), val = tensor("custom")]; + tensor obj_27_pad_0 = const()[name = tensor("obj_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94814784)))]; + tensor layers_6_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95994496)))]; + tensor obj_27_cast_fp16 = conv(bias = layers_6_self_attn_o_proj_bias_to_fp16, dilations = var_6806, groups = var_5905, pad = obj_27_pad_0, pad_type = obj_27_pad_type_0, strides = var_6804, weight = layers_6_self_attn_o_proj_weight_to_fp16, x = input_49_cast_fp16)[name = tensor("obj_27_cast_fp16")]; + tensor inputs_27_cast_fp16 = add(x = inputs_25_cast_fp16, y = obj_27_cast_fp16)[name = tensor("inputs_27_cast_fp16")]; + tensor var_6812 = const()[name = tensor("op_6812"), val = tensor([1])]; + tensor channels_mean_27_cast_fp16 = reduce_mean(axes = var_6812, keep_dims = var_5906, x = inputs_27_cast_fp16)[name = tensor("channels_mean_27_cast_fp16")]; + tensor zero_mean_27_cast_fp16 = sub(x = inputs_27_cast_fp16, y = channels_mean_27_cast_fp16)[name = tensor("zero_mean_27_cast_fp16")]; + tensor zero_mean_sq_27_cast_fp16 = mul(x = zero_mean_27_cast_fp16, y = zero_mean_27_cast_fp16)[name = tensor("zero_mean_sq_27_cast_fp16")]; + tensor var_6816 = const()[name = tensor("op_6816"), val = tensor([1])]; + tensor var_6817_cast_fp16 = reduce_mean(axes = var_6816, keep_dims = var_5906, x = zero_mean_sq_27_cast_fp16)[name = tensor("op_6817_cast_fp16")]; + tensor var_6818_to_fp16 = const()[name = tensor("op_6818_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_6819_cast_fp16 = add(x = var_6817_cast_fp16, y = var_6818_to_fp16)[name = tensor("op_6819_cast_fp16")]; + tensor denom_27_epsilon_0_to_fp16 = const()[name = tensor("denom_27_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_27_cast_fp16 = rsqrt(epsilon = denom_27_epsilon_0_to_fp16, x = var_6819_cast_fp16)[name = tensor("denom_27_cast_fp16")]; + tensor out_27_cast_fp16 = mul(x = zero_mean_27_cast_fp16, y = denom_27_cast_fp16)[name = tensor("out_27_cast_fp16")]; + tensor input_51_gamma_0_to_fp16 = const()[name = tensor("input_51_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95996096)))]; + tensor input_51_beta_0_to_fp16 = const()[name = tensor("input_51_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95997696)))]; + tensor input_51_epsilon_0_to_fp16 = const()[name = tensor("input_51_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_51_cast_fp16 = batch_norm(beta = input_51_beta_0_to_fp16, epsilon = input_51_epsilon_0_to_fp16, gamma = input_51_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_27_cast_fp16)[name = tensor("input_51_cast_fp16")]; + tensor var_6830 = const()[name = tensor("op_6830"), val = tensor([1, 1])]; + tensor var_6832 = const()[name = tensor("op_6832"), val = tensor([1, 1])]; + tensor input_53_pad_type_0 = const()[name = tensor("input_53_pad_type_0"), val = tensor("custom")]; + tensor input_53_pad_0 = const()[name = tensor("input_53_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_fc1_weight_to_fp16 = const()[name = tensor("layers_6_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95999296)))]; + tensor layers_6_fc1_bias_to_fp16 = const()[name = tensor("layers_6_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100717952)))]; + tensor input_53_cast_fp16 = conv(bias = layers_6_fc1_bias_to_fp16, dilations = var_6832, groups = var_5905, pad = input_53_pad_0, pad_type = input_53_pad_type_0, strides = var_6830, weight = layers_6_fc1_weight_to_fp16, x = input_51_cast_fp16)[name = tensor("input_53_cast_fp16")]; + tensor input_55_mode_0 = const()[name = tensor("input_55_mode_0"), val = tensor("EXACT")]; + tensor input_55_cast_fp16 = gelu(mode = input_55_mode_0, x = input_53_cast_fp16)[name = tensor("input_55_cast_fp16")]; + tensor var_6838 = const()[name = tensor("op_6838"), val = tensor([1, 1])]; + tensor var_6840 = const()[name = tensor("op_6840"), val = tensor([1, 1])]; + tensor hidden_states_17_pad_type_0 = const()[name = tensor("hidden_states_17_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_17_pad_0 = const()[name = tensor("hidden_states_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_fc2_weight_to_fp16 = const()[name = tensor("layers_6_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100724160)))]; + tensor layers_6_fc2_bias_to_fp16 = const()[name = tensor("layers_6_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(105442816)))]; + tensor hidden_states_17_cast_fp16 = conv(bias = layers_6_fc2_bias_to_fp16, dilations = var_6840, groups = var_5905, pad = hidden_states_17_pad_0, pad_type = hidden_states_17_pad_type_0, strides = var_6838, weight = layers_6_fc2_weight_to_fp16, x = input_55_cast_fp16)[name = tensor("hidden_states_17_cast_fp16")]; + tensor inputs_29_cast_fp16 = add(x = inputs_27_cast_fp16, y = hidden_states_17_cast_fp16)[name = tensor("inputs_29_cast_fp16")]; + tensor var_6847 = const()[name = tensor("op_6847"), val = tensor(3)]; + tensor var_6864 = const()[name = tensor("op_6864"), val = tensor(1)]; + tensor var_6865 = const()[name = tensor("op_6865"), val = tensor(true)]; + tensor var_6875 = const()[name = tensor("op_6875"), val = tensor([1])]; + tensor channels_mean_29_cast_fp16 = reduce_mean(axes = var_6875, keep_dims = var_6865, x = inputs_29_cast_fp16)[name = tensor("channels_mean_29_cast_fp16")]; + tensor zero_mean_29_cast_fp16 = sub(x = inputs_29_cast_fp16, y = channels_mean_29_cast_fp16)[name = tensor("zero_mean_29_cast_fp16")]; + tensor zero_mean_sq_29_cast_fp16 = mul(x = zero_mean_29_cast_fp16, y = zero_mean_29_cast_fp16)[name = tensor("zero_mean_sq_29_cast_fp16")]; + tensor var_6879 = const()[name = tensor("op_6879"), val = tensor([1])]; + tensor var_6880_cast_fp16 = reduce_mean(axes = var_6879, keep_dims = var_6865, x = zero_mean_sq_29_cast_fp16)[name = tensor("op_6880_cast_fp16")]; + tensor var_6881_to_fp16 = const()[name = tensor("op_6881_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_6882_cast_fp16 = add(x = var_6880_cast_fp16, y = var_6881_to_fp16)[name = tensor("op_6882_cast_fp16")]; + tensor denom_29_epsilon_0_to_fp16 = const()[name = tensor("denom_29_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_29_cast_fp16 = rsqrt(epsilon = denom_29_epsilon_0_to_fp16, x = var_6882_cast_fp16)[name = tensor("denom_29_cast_fp16")]; + tensor out_29_cast_fp16 = mul(x = zero_mean_29_cast_fp16, y = denom_29_cast_fp16)[name = tensor("out_29_cast_fp16")]; + tensor obj_29_gamma_0_to_fp16 = const()[name = tensor("obj_29_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(105444416)))]; + tensor obj_29_beta_0_to_fp16 = const()[name = tensor("obj_29_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(105446016)))]; + tensor obj_29_epsilon_0_to_fp16 = const()[name = tensor("obj_29_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_29_cast_fp16 = batch_norm(beta = obj_29_beta_0_to_fp16, epsilon = obj_29_epsilon_0_to_fp16, gamma = obj_29_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_29_cast_fp16)[name = tensor("obj_29_cast_fp16")]; + tensor var_6897 = const()[name = tensor("op_6897"), val = tensor([1, 1])]; + tensor var_6899 = const()[name = tensor("op_6899"), val = tensor([1, 1])]; + tensor query_15_pad_type_0 = const()[name = tensor("query_15_pad_type_0"), val = tensor("custom")]; + tensor query_15_pad_0 = const()[name = tensor("query_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(105447616)))]; + tensor layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106627328)))]; + tensor query_15_cast_fp16 = conv(bias = layers_7_self_attn_q_proj_bias_to_fp16, dilations = var_6899, groups = var_6864, pad = query_15_pad_0, pad_type = query_15_pad_type_0, strides = var_6897, weight = layers_7_self_attn_q_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("query_15_cast_fp16")]; + tensor var_6903 = const()[name = tensor("op_6903"), val = tensor([1, 1])]; + tensor var_6905 = const()[name = tensor("op_6905"), val = tensor([1, 1])]; + tensor key_15_pad_type_0 = const()[name = tensor("key_15_pad_type_0"), val = tensor("custom")]; + tensor key_15_pad_0 = const()[name = tensor("key_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106628928)))]; + tensor key_15_cast_fp16 = conv(dilations = var_6905, groups = var_6864, pad = key_15_pad_0, pad_type = key_15_pad_type_0, strides = var_6903, weight = layers_7_self_attn_k_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("key_15_cast_fp16")]; + tensor var_6910 = const()[name = tensor("op_6910"), val = tensor([1, 1])]; + tensor var_6912 = const()[name = tensor("op_6912"), val = tensor([1, 1])]; + tensor value_15_pad_type_0 = const()[name = tensor("value_15_pad_type_0"), val = tensor("custom")]; + tensor value_15_pad_0 = const()[name = tensor("value_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107808640)))]; + tensor layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108988352)))]; + tensor value_15_cast_fp16 = conv(bias = layers_7_self_attn_v_proj_bias_to_fp16, dilations = var_6912, groups = var_6864, pad = value_15_pad_0, pad_type = value_15_pad_type_0, strides = var_6910, weight = layers_7_self_attn_v_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("value_15_cast_fp16")]; + tensor var_6919_begin_0 = const()[name = tensor("op_6919_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6919_end_0 = const()[name = tensor("op_6919_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6919_end_mask_0 = const()[name = tensor("op_6919_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6919_cast_fp16 = slice_by_index(begin = var_6919_begin_0, end = var_6919_end_0, end_mask = var_6919_end_mask_0, x = query_15_cast_fp16)[name = tensor("op_6919_cast_fp16")]; + tensor var_6923_begin_0 = const()[name = tensor("op_6923_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_6923_end_0 = const()[name = tensor("op_6923_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_6923_end_mask_0 = const()[name = tensor("op_6923_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6923_cast_fp16 = slice_by_index(begin = var_6923_begin_0, end = var_6923_end_0, end_mask = var_6923_end_mask_0, x = query_15_cast_fp16)[name = tensor("op_6923_cast_fp16")]; + tensor var_6927_begin_0 = const()[name = tensor("op_6927_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_6927_end_0 = const()[name = tensor("op_6927_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_6927_end_mask_0 = const()[name = tensor("op_6927_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6927_cast_fp16 = slice_by_index(begin = var_6927_begin_0, end = var_6927_end_0, end_mask = var_6927_end_mask_0, x = query_15_cast_fp16)[name = tensor("op_6927_cast_fp16")]; + tensor var_6931_begin_0 = const()[name = tensor("op_6931_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_6931_end_0 = const()[name = tensor("op_6931_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_6931_end_mask_0 = const()[name = tensor("op_6931_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6931_cast_fp16 = slice_by_index(begin = var_6931_begin_0, end = var_6931_end_0, end_mask = var_6931_end_mask_0, x = query_15_cast_fp16)[name = tensor("op_6931_cast_fp16")]; + tensor var_6935_begin_0 = const()[name = tensor("op_6935_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_6935_end_0 = const()[name = tensor("op_6935_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_6935_end_mask_0 = const()[name = tensor("op_6935_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6935_cast_fp16 = slice_by_index(begin = var_6935_begin_0, end = var_6935_end_0, end_mask = var_6935_end_mask_0, x = query_15_cast_fp16)[name = tensor("op_6935_cast_fp16")]; + tensor var_6939_begin_0 = const()[name = tensor("op_6939_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_6939_end_0 = const()[name = tensor("op_6939_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_6939_end_mask_0 = const()[name = tensor("op_6939_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6939_cast_fp16 = slice_by_index(begin = var_6939_begin_0, end = var_6939_end_0, end_mask = var_6939_end_mask_0, x = query_15_cast_fp16)[name = tensor("op_6939_cast_fp16")]; + tensor var_6943_begin_0 = const()[name = tensor("op_6943_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_6943_end_0 = const()[name = tensor("op_6943_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_6943_end_mask_0 = const()[name = tensor("op_6943_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6943_cast_fp16 = slice_by_index(begin = var_6943_begin_0, end = var_6943_end_0, end_mask = var_6943_end_mask_0, x = query_15_cast_fp16)[name = tensor("op_6943_cast_fp16")]; + tensor var_6947_begin_0 = const()[name = tensor("op_6947_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_6947_end_0 = const()[name = tensor("op_6947_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_6947_end_mask_0 = const()[name = tensor("op_6947_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6947_cast_fp16 = slice_by_index(begin = var_6947_begin_0, end = var_6947_end_0, end_mask = var_6947_end_mask_0, x = query_15_cast_fp16)[name = tensor("op_6947_cast_fp16")]; + tensor var_6951_begin_0 = const()[name = tensor("op_6951_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_6951_end_0 = const()[name = tensor("op_6951_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_6951_end_mask_0 = const()[name = tensor("op_6951_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6951_cast_fp16 = slice_by_index(begin = var_6951_begin_0, end = var_6951_end_0, end_mask = var_6951_end_mask_0, x = query_15_cast_fp16)[name = tensor("op_6951_cast_fp16")]; + tensor var_6955_begin_0 = const()[name = tensor("op_6955_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_6955_end_0 = const()[name = tensor("op_6955_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_6955_end_mask_0 = const()[name = tensor("op_6955_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6955_cast_fp16 = slice_by_index(begin = var_6955_begin_0, end = var_6955_end_0, end_mask = var_6955_end_mask_0, x = query_15_cast_fp16)[name = tensor("op_6955_cast_fp16")]; + tensor var_6959_begin_0 = const()[name = tensor("op_6959_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_6959_end_0 = const()[name = tensor("op_6959_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_6959_end_mask_0 = const()[name = tensor("op_6959_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6959_cast_fp16 = slice_by_index(begin = var_6959_begin_0, end = var_6959_end_0, end_mask = var_6959_end_mask_0, x = query_15_cast_fp16)[name = tensor("op_6959_cast_fp16")]; + tensor var_6963_begin_0 = const()[name = tensor("op_6963_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_6963_end_0 = const()[name = tensor("op_6963_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_6963_end_mask_0 = const()[name = tensor("op_6963_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_6963_cast_fp16 = slice_by_index(begin = var_6963_begin_0, end = var_6963_end_0, end_mask = var_6963_end_mask_0, x = query_15_cast_fp16)[name = tensor("op_6963_cast_fp16")]; + tensor var_6972_begin_0 = const()[name = tensor("op_6972_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_6972_end_0 = const()[name = tensor("op_6972_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_6972_end_mask_0 = const()[name = tensor("op_6972_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6972_cast_fp16 = slice_by_index(begin = var_6972_begin_0, end = var_6972_end_0, end_mask = var_6972_end_mask_0, x = var_6919_cast_fp16)[name = tensor("op_6972_cast_fp16")]; + tensor var_6979_begin_0 = const()[name = tensor("op_6979_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_6979_end_0 = const()[name = tensor("op_6979_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_6979_end_mask_0 = const()[name = tensor("op_6979_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6979_cast_fp16 = slice_by_index(begin = var_6979_begin_0, end = var_6979_end_0, end_mask = var_6979_end_mask_0, x = var_6919_cast_fp16)[name = tensor("op_6979_cast_fp16")]; + tensor var_6986_begin_0 = const()[name = tensor("op_6986_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_6986_end_0 = const()[name = tensor("op_6986_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_6986_end_mask_0 = const()[name = tensor("op_6986_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6986_cast_fp16 = slice_by_index(begin = var_6986_begin_0, end = var_6986_end_0, end_mask = var_6986_end_mask_0, x = var_6919_cast_fp16)[name = tensor("op_6986_cast_fp16")]; + tensor var_6993_begin_0 = const()[name = tensor("op_6993_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_6993_end_0 = const()[name = tensor("op_6993_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_6993_end_mask_0 = const()[name = tensor("op_6993_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_6993_cast_fp16 = slice_by_index(begin = var_6993_begin_0, end = var_6993_end_0, end_mask = var_6993_end_mask_0, x = var_6919_cast_fp16)[name = tensor("op_6993_cast_fp16")]; + tensor var_7000_begin_0 = const()[name = tensor("op_7000_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7000_end_0 = const()[name = tensor("op_7000_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_7000_end_mask_0 = const()[name = tensor("op_7000_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7000_cast_fp16 = slice_by_index(begin = var_7000_begin_0, end = var_7000_end_0, end_mask = var_7000_end_mask_0, x = var_6923_cast_fp16)[name = tensor("op_7000_cast_fp16")]; + tensor var_7007_begin_0 = const()[name = tensor("op_7007_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_7007_end_0 = const()[name = tensor("op_7007_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_7007_end_mask_0 = const()[name = tensor("op_7007_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7007_cast_fp16 = slice_by_index(begin = var_7007_begin_0, end = var_7007_end_0, end_mask = var_7007_end_mask_0, x = var_6923_cast_fp16)[name = tensor("op_7007_cast_fp16")]; + tensor var_7014_begin_0 = const()[name = tensor("op_7014_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_7014_end_0 = const()[name = tensor("op_7014_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_7014_end_mask_0 = const()[name = tensor("op_7014_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7014_cast_fp16 = slice_by_index(begin = var_7014_begin_0, end = var_7014_end_0, end_mask = var_7014_end_mask_0, x = var_6923_cast_fp16)[name = tensor("op_7014_cast_fp16")]; + tensor var_7021_begin_0 = const()[name = tensor("op_7021_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_7021_end_0 = const()[name = tensor("op_7021_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7021_end_mask_0 = const()[name = tensor("op_7021_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7021_cast_fp16 = slice_by_index(begin = var_7021_begin_0, end = var_7021_end_0, end_mask = var_7021_end_mask_0, x = var_6923_cast_fp16)[name = tensor("op_7021_cast_fp16")]; + tensor var_7028_begin_0 = const()[name = tensor("op_7028_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7028_end_0 = const()[name = tensor("op_7028_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_7028_end_mask_0 = const()[name = tensor("op_7028_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7028_cast_fp16 = slice_by_index(begin = var_7028_begin_0, end = var_7028_end_0, end_mask = var_7028_end_mask_0, x = var_6927_cast_fp16)[name = tensor("op_7028_cast_fp16")]; + tensor var_7035_begin_0 = const()[name = tensor("op_7035_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_7035_end_0 = const()[name = tensor("op_7035_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_7035_end_mask_0 = const()[name = tensor("op_7035_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7035_cast_fp16 = slice_by_index(begin = var_7035_begin_0, end = var_7035_end_0, end_mask = var_7035_end_mask_0, x = var_6927_cast_fp16)[name = tensor("op_7035_cast_fp16")]; + tensor var_7042_begin_0 = const()[name = tensor("op_7042_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_7042_end_0 = const()[name = tensor("op_7042_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_7042_end_mask_0 = const()[name = tensor("op_7042_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7042_cast_fp16 = slice_by_index(begin = var_7042_begin_0, end = var_7042_end_0, end_mask = var_7042_end_mask_0, x = var_6927_cast_fp16)[name = tensor("op_7042_cast_fp16")]; + tensor var_7049_begin_0 = const()[name = tensor("op_7049_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_7049_end_0 = const()[name = tensor("op_7049_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7049_end_mask_0 = const()[name = tensor("op_7049_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7049_cast_fp16 = slice_by_index(begin = var_7049_begin_0, end = var_7049_end_0, end_mask = var_7049_end_mask_0, x = var_6927_cast_fp16)[name = tensor("op_7049_cast_fp16")]; + tensor var_7056_begin_0 = const()[name = tensor("op_7056_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7056_end_0 = const()[name = tensor("op_7056_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_7056_end_mask_0 = const()[name = tensor("op_7056_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7056_cast_fp16 = slice_by_index(begin = var_7056_begin_0, end = var_7056_end_0, end_mask = var_7056_end_mask_0, x = var_6931_cast_fp16)[name = tensor("op_7056_cast_fp16")]; + tensor var_7063_begin_0 = const()[name = tensor("op_7063_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_7063_end_0 = const()[name = tensor("op_7063_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_7063_end_mask_0 = const()[name = tensor("op_7063_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7063_cast_fp16 = slice_by_index(begin = var_7063_begin_0, end = var_7063_end_0, end_mask = var_7063_end_mask_0, x = var_6931_cast_fp16)[name = tensor("op_7063_cast_fp16")]; + tensor var_7070_begin_0 = const()[name = tensor("op_7070_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_7070_end_0 = const()[name = tensor("op_7070_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_7070_end_mask_0 = const()[name = tensor("op_7070_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7070_cast_fp16 = slice_by_index(begin = var_7070_begin_0, end = var_7070_end_0, end_mask = var_7070_end_mask_0, x = var_6931_cast_fp16)[name = tensor("op_7070_cast_fp16")]; + tensor var_7077_begin_0 = const()[name = tensor("op_7077_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_7077_end_0 = const()[name = tensor("op_7077_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7077_end_mask_0 = const()[name = tensor("op_7077_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7077_cast_fp16 = slice_by_index(begin = var_7077_begin_0, end = var_7077_end_0, end_mask = var_7077_end_mask_0, x = var_6931_cast_fp16)[name = tensor("op_7077_cast_fp16")]; + tensor var_7084_begin_0 = const()[name = tensor("op_7084_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7084_end_0 = const()[name = tensor("op_7084_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_7084_end_mask_0 = const()[name = tensor("op_7084_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7084_cast_fp16 = slice_by_index(begin = var_7084_begin_0, end = var_7084_end_0, end_mask = var_7084_end_mask_0, x = var_6935_cast_fp16)[name = tensor("op_7084_cast_fp16")]; + tensor var_7091_begin_0 = const()[name = tensor("op_7091_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_7091_end_0 = const()[name = tensor("op_7091_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_7091_end_mask_0 = const()[name = tensor("op_7091_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7091_cast_fp16 = slice_by_index(begin = var_7091_begin_0, end = var_7091_end_0, end_mask = var_7091_end_mask_0, x = var_6935_cast_fp16)[name = tensor("op_7091_cast_fp16")]; + tensor var_7098_begin_0 = const()[name = tensor("op_7098_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_7098_end_0 = const()[name = tensor("op_7098_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_7098_end_mask_0 = const()[name = tensor("op_7098_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7098_cast_fp16 = slice_by_index(begin = var_7098_begin_0, end = var_7098_end_0, end_mask = var_7098_end_mask_0, x = var_6935_cast_fp16)[name = tensor("op_7098_cast_fp16")]; + tensor var_7105_begin_0 = const()[name = tensor("op_7105_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_7105_end_0 = const()[name = tensor("op_7105_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7105_end_mask_0 = const()[name = tensor("op_7105_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7105_cast_fp16 = slice_by_index(begin = var_7105_begin_0, end = var_7105_end_0, end_mask = var_7105_end_mask_0, x = var_6935_cast_fp16)[name = tensor("op_7105_cast_fp16")]; + tensor var_7112_begin_0 = const()[name = tensor("op_7112_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7112_end_0 = const()[name = tensor("op_7112_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_7112_end_mask_0 = const()[name = tensor("op_7112_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7112_cast_fp16 = slice_by_index(begin = var_7112_begin_0, end = var_7112_end_0, end_mask = var_7112_end_mask_0, x = var_6939_cast_fp16)[name = tensor("op_7112_cast_fp16")]; + tensor var_7119_begin_0 = const()[name = tensor("op_7119_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_7119_end_0 = const()[name = tensor("op_7119_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_7119_end_mask_0 = const()[name = tensor("op_7119_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7119_cast_fp16 = slice_by_index(begin = var_7119_begin_0, end = var_7119_end_0, end_mask = var_7119_end_mask_0, x = var_6939_cast_fp16)[name = tensor("op_7119_cast_fp16")]; + tensor var_7126_begin_0 = const()[name = tensor("op_7126_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_7126_end_0 = const()[name = tensor("op_7126_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_7126_end_mask_0 = const()[name = tensor("op_7126_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7126_cast_fp16 = slice_by_index(begin = var_7126_begin_0, end = var_7126_end_0, end_mask = var_7126_end_mask_0, x = var_6939_cast_fp16)[name = tensor("op_7126_cast_fp16")]; + tensor var_7133_begin_0 = const()[name = tensor("op_7133_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_7133_end_0 = const()[name = tensor("op_7133_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7133_end_mask_0 = const()[name = tensor("op_7133_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7133_cast_fp16 = slice_by_index(begin = var_7133_begin_0, end = var_7133_end_0, end_mask = var_7133_end_mask_0, x = var_6939_cast_fp16)[name = tensor("op_7133_cast_fp16")]; + tensor var_7140_begin_0 = const()[name = tensor("op_7140_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7140_end_0 = const()[name = tensor("op_7140_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_7140_end_mask_0 = const()[name = tensor("op_7140_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7140_cast_fp16 = slice_by_index(begin = var_7140_begin_0, end = var_7140_end_0, end_mask = var_7140_end_mask_0, x = var_6943_cast_fp16)[name = tensor("op_7140_cast_fp16")]; + tensor var_7147_begin_0 = const()[name = tensor("op_7147_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_7147_end_0 = const()[name = tensor("op_7147_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_7147_end_mask_0 = const()[name = tensor("op_7147_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7147_cast_fp16 = slice_by_index(begin = var_7147_begin_0, end = var_7147_end_0, end_mask = var_7147_end_mask_0, x = var_6943_cast_fp16)[name = tensor("op_7147_cast_fp16")]; + tensor var_7154_begin_0 = const()[name = tensor("op_7154_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_7154_end_0 = const()[name = tensor("op_7154_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_7154_end_mask_0 = const()[name = tensor("op_7154_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7154_cast_fp16 = slice_by_index(begin = var_7154_begin_0, end = var_7154_end_0, end_mask = var_7154_end_mask_0, x = var_6943_cast_fp16)[name = tensor("op_7154_cast_fp16")]; + tensor var_7161_begin_0 = const()[name = tensor("op_7161_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_7161_end_0 = const()[name = tensor("op_7161_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7161_end_mask_0 = const()[name = tensor("op_7161_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7161_cast_fp16 = slice_by_index(begin = var_7161_begin_0, end = var_7161_end_0, end_mask = var_7161_end_mask_0, x = var_6943_cast_fp16)[name = tensor("op_7161_cast_fp16")]; + tensor var_7168_begin_0 = const()[name = tensor("op_7168_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7168_end_0 = const()[name = tensor("op_7168_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_7168_end_mask_0 = const()[name = tensor("op_7168_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7168_cast_fp16 = slice_by_index(begin = var_7168_begin_0, end = var_7168_end_0, end_mask = var_7168_end_mask_0, x = var_6947_cast_fp16)[name = tensor("op_7168_cast_fp16")]; + tensor var_7175_begin_0 = const()[name = tensor("op_7175_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_7175_end_0 = const()[name = tensor("op_7175_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_7175_end_mask_0 = const()[name = tensor("op_7175_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7175_cast_fp16 = slice_by_index(begin = var_7175_begin_0, end = var_7175_end_0, end_mask = var_7175_end_mask_0, x = var_6947_cast_fp16)[name = tensor("op_7175_cast_fp16")]; + tensor var_7182_begin_0 = const()[name = tensor("op_7182_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_7182_end_0 = const()[name = tensor("op_7182_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_7182_end_mask_0 = const()[name = tensor("op_7182_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7182_cast_fp16 = slice_by_index(begin = var_7182_begin_0, end = var_7182_end_0, end_mask = var_7182_end_mask_0, x = var_6947_cast_fp16)[name = tensor("op_7182_cast_fp16")]; + tensor var_7189_begin_0 = const()[name = tensor("op_7189_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_7189_end_0 = const()[name = tensor("op_7189_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7189_end_mask_0 = const()[name = tensor("op_7189_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7189_cast_fp16 = slice_by_index(begin = var_7189_begin_0, end = var_7189_end_0, end_mask = var_7189_end_mask_0, x = var_6947_cast_fp16)[name = tensor("op_7189_cast_fp16")]; + tensor var_7196_begin_0 = const()[name = tensor("op_7196_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7196_end_0 = const()[name = tensor("op_7196_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_7196_end_mask_0 = const()[name = tensor("op_7196_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7196_cast_fp16 = slice_by_index(begin = var_7196_begin_0, end = var_7196_end_0, end_mask = var_7196_end_mask_0, x = var_6951_cast_fp16)[name = tensor("op_7196_cast_fp16")]; + tensor var_7203_begin_0 = const()[name = tensor("op_7203_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_7203_end_0 = const()[name = tensor("op_7203_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_7203_end_mask_0 = const()[name = tensor("op_7203_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7203_cast_fp16 = slice_by_index(begin = var_7203_begin_0, end = var_7203_end_0, end_mask = var_7203_end_mask_0, x = var_6951_cast_fp16)[name = tensor("op_7203_cast_fp16")]; + tensor var_7210_begin_0 = const()[name = tensor("op_7210_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_7210_end_0 = const()[name = tensor("op_7210_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_7210_end_mask_0 = const()[name = tensor("op_7210_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7210_cast_fp16 = slice_by_index(begin = var_7210_begin_0, end = var_7210_end_0, end_mask = var_7210_end_mask_0, x = var_6951_cast_fp16)[name = tensor("op_7210_cast_fp16")]; + tensor var_7217_begin_0 = const()[name = tensor("op_7217_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_7217_end_0 = const()[name = tensor("op_7217_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7217_end_mask_0 = const()[name = tensor("op_7217_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7217_cast_fp16 = slice_by_index(begin = var_7217_begin_0, end = var_7217_end_0, end_mask = var_7217_end_mask_0, x = var_6951_cast_fp16)[name = tensor("op_7217_cast_fp16")]; + tensor var_7224_begin_0 = const()[name = tensor("op_7224_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7224_end_0 = const()[name = tensor("op_7224_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_7224_end_mask_0 = const()[name = tensor("op_7224_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7224_cast_fp16 = slice_by_index(begin = var_7224_begin_0, end = var_7224_end_0, end_mask = var_7224_end_mask_0, x = var_6955_cast_fp16)[name = tensor("op_7224_cast_fp16")]; + tensor var_7231_begin_0 = const()[name = tensor("op_7231_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_7231_end_0 = const()[name = tensor("op_7231_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_7231_end_mask_0 = const()[name = tensor("op_7231_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7231_cast_fp16 = slice_by_index(begin = var_7231_begin_0, end = var_7231_end_0, end_mask = var_7231_end_mask_0, x = var_6955_cast_fp16)[name = tensor("op_7231_cast_fp16")]; + tensor var_7238_begin_0 = const()[name = tensor("op_7238_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_7238_end_0 = const()[name = tensor("op_7238_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_7238_end_mask_0 = const()[name = tensor("op_7238_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7238_cast_fp16 = slice_by_index(begin = var_7238_begin_0, end = var_7238_end_0, end_mask = var_7238_end_mask_0, x = var_6955_cast_fp16)[name = tensor("op_7238_cast_fp16")]; + tensor var_7245_begin_0 = const()[name = tensor("op_7245_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_7245_end_0 = const()[name = tensor("op_7245_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7245_end_mask_0 = const()[name = tensor("op_7245_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7245_cast_fp16 = slice_by_index(begin = var_7245_begin_0, end = var_7245_end_0, end_mask = var_7245_end_mask_0, x = var_6955_cast_fp16)[name = tensor("op_7245_cast_fp16")]; + tensor var_7252_begin_0 = const()[name = tensor("op_7252_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7252_end_0 = const()[name = tensor("op_7252_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_7252_end_mask_0 = const()[name = tensor("op_7252_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7252_cast_fp16 = slice_by_index(begin = var_7252_begin_0, end = var_7252_end_0, end_mask = var_7252_end_mask_0, x = var_6959_cast_fp16)[name = tensor("op_7252_cast_fp16")]; + tensor var_7259_begin_0 = const()[name = tensor("op_7259_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_7259_end_0 = const()[name = tensor("op_7259_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_7259_end_mask_0 = const()[name = tensor("op_7259_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7259_cast_fp16 = slice_by_index(begin = var_7259_begin_0, end = var_7259_end_0, end_mask = var_7259_end_mask_0, x = var_6959_cast_fp16)[name = tensor("op_7259_cast_fp16")]; + tensor var_7266_begin_0 = const()[name = tensor("op_7266_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_7266_end_0 = const()[name = tensor("op_7266_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_7266_end_mask_0 = const()[name = tensor("op_7266_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7266_cast_fp16 = slice_by_index(begin = var_7266_begin_0, end = var_7266_end_0, end_mask = var_7266_end_mask_0, x = var_6959_cast_fp16)[name = tensor("op_7266_cast_fp16")]; + tensor var_7273_begin_0 = const()[name = tensor("op_7273_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_7273_end_0 = const()[name = tensor("op_7273_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7273_end_mask_0 = const()[name = tensor("op_7273_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7273_cast_fp16 = slice_by_index(begin = var_7273_begin_0, end = var_7273_end_0, end_mask = var_7273_end_mask_0, x = var_6959_cast_fp16)[name = tensor("op_7273_cast_fp16")]; + tensor var_7280_begin_0 = const()[name = tensor("op_7280_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7280_end_0 = const()[name = tensor("op_7280_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_7280_end_mask_0 = const()[name = tensor("op_7280_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7280_cast_fp16 = slice_by_index(begin = var_7280_begin_0, end = var_7280_end_0, end_mask = var_7280_end_mask_0, x = var_6963_cast_fp16)[name = tensor("op_7280_cast_fp16")]; + tensor var_7287_begin_0 = const()[name = tensor("op_7287_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_7287_end_0 = const()[name = tensor("op_7287_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_7287_end_mask_0 = const()[name = tensor("op_7287_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7287_cast_fp16 = slice_by_index(begin = var_7287_begin_0, end = var_7287_end_0, end_mask = var_7287_end_mask_0, x = var_6963_cast_fp16)[name = tensor("op_7287_cast_fp16")]; + tensor var_7294_begin_0 = const()[name = tensor("op_7294_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_7294_end_0 = const()[name = tensor("op_7294_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_7294_end_mask_0 = const()[name = tensor("op_7294_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7294_cast_fp16 = slice_by_index(begin = var_7294_begin_0, end = var_7294_end_0, end_mask = var_7294_end_mask_0, x = var_6963_cast_fp16)[name = tensor("op_7294_cast_fp16")]; + tensor var_7301_begin_0 = const()[name = tensor("op_7301_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_7301_end_0 = const()[name = tensor("op_7301_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7301_end_mask_0 = const()[name = tensor("op_7301_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7301_cast_fp16 = slice_by_index(begin = var_7301_begin_0, end = var_7301_end_0, end_mask = var_7301_end_mask_0, x = var_6963_cast_fp16)[name = tensor("op_7301_cast_fp16")]; + tensor k_15_perm_0 = const()[name = tensor("k_15_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_7306_begin_0 = const()[name = tensor("op_7306_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7306_end_0 = const()[name = tensor("op_7306_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_7306_end_mask_0 = const()[name = tensor("op_7306_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_4 = transpose(perm = k_15_perm_0, x = key_15_cast_fp16)[name = tensor("transpose_4")]; + tensor var_7306_cast_fp16 = slice_by_index(begin = var_7306_begin_0, end = var_7306_end_0, end_mask = var_7306_end_mask_0, x = transpose_4)[name = tensor("op_7306_cast_fp16")]; + tensor var_7310_begin_0 = const()[name = tensor("op_7310_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_7310_end_0 = const()[name = tensor("op_7310_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_7310_end_mask_0 = const()[name = tensor("op_7310_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7310_cast_fp16 = slice_by_index(begin = var_7310_begin_0, end = var_7310_end_0, end_mask = var_7310_end_mask_0, x = transpose_4)[name = tensor("op_7310_cast_fp16")]; + tensor var_7314_begin_0 = const()[name = tensor("op_7314_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_7314_end_0 = const()[name = tensor("op_7314_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_7314_end_mask_0 = const()[name = tensor("op_7314_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7314_cast_fp16 = slice_by_index(begin = var_7314_begin_0, end = var_7314_end_0, end_mask = var_7314_end_mask_0, x = transpose_4)[name = tensor("op_7314_cast_fp16")]; + tensor var_7318_begin_0 = const()[name = tensor("op_7318_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_7318_end_0 = const()[name = tensor("op_7318_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_7318_end_mask_0 = const()[name = tensor("op_7318_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7318_cast_fp16 = slice_by_index(begin = var_7318_begin_0, end = var_7318_end_0, end_mask = var_7318_end_mask_0, x = transpose_4)[name = tensor("op_7318_cast_fp16")]; + tensor var_7322_begin_0 = const()[name = tensor("op_7322_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_7322_end_0 = const()[name = tensor("op_7322_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_7322_end_mask_0 = const()[name = tensor("op_7322_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7322_cast_fp16 = slice_by_index(begin = var_7322_begin_0, end = var_7322_end_0, end_mask = var_7322_end_mask_0, x = transpose_4)[name = tensor("op_7322_cast_fp16")]; + tensor var_7326_begin_0 = const()[name = tensor("op_7326_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_7326_end_0 = const()[name = tensor("op_7326_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_7326_end_mask_0 = const()[name = tensor("op_7326_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7326_cast_fp16 = slice_by_index(begin = var_7326_begin_0, end = var_7326_end_0, end_mask = var_7326_end_mask_0, x = transpose_4)[name = tensor("op_7326_cast_fp16")]; + tensor var_7330_begin_0 = const()[name = tensor("op_7330_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_7330_end_0 = const()[name = tensor("op_7330_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_7330_end_mask_0 = const()[name = tensor("op_7330_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7330_cast_fp16 = slice_by_index(begin = var_7330_begin_0, end = var_7330_end_0, end_mask = var_7330_end_mask_0, x = transpose_4)[name = tensor("op_7330_cast_fp16")]; + tensor var_7334_begin_0 = const()[name = tensor("op_7334_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_7334_end_0 = const()[name = tensor("op_7334_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_7334_end_mask_0 = const()[name = tensor("op_7334_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7334_cast_fp16 = slice_by_index(begin = var_7334_begin_0, end = var_7334_end_0, end_mask = var_7334_end_mask_0, x = transpose_4)[name = tensor("op_7334_cast_fp16")]; + tensor var_7338_begin_0 = const()[name = tensor("op_7338_begin_0"), val = tensor([0, 0, 0, 512])]; + tensor var_7338_end_0 = const()[name = tensor("op_7338_end_0"), val = tensor([1, 1500, 1, 576])]; + tensor var_7338_end_mask_0 = const()[name = tensor("op_7338_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7338_cast_fp16 = slice_by_index(begin = var_7338_begin_0, end = var_7338_end_0, end_mask = var_7338_end_mask_0, x = transpose_4)[name = tensor("op_7338_cast_fp16")]; + tensor var_7342_begin_0 = const()[name = tensor("op_7342_begin_0"), val = tensor([0, 0, 0, 576])]; + tensor var_7342_end_0 = const()[name = tensor("op_7342_end_0"), val = tensor([1, 1500, 1, 640])]; + tensor var_7342_end_mask_0 = const()[name = tensor("op_7342_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7342_cast_fp16 = slice_by_index(begin = var_7342_begin_0, end = var_7342_end_0, end_mask = var_7342_end_mask_0, x = transpose_4)[name = tensor("op_7342_cast_fp16")]; + tensor var_7346_begin_0 = const()[name = tensor("op_7346_begin_0"), val = tensor([0, 0, 0, 640])]; + tensor var_7346_end_0 = const()[name = tensor("op_7346_end_0"), val = tensor([1, 1500, 1, 704])]; + tensor var_7346_end_mask_0 = const()[name = tensor("op_7346_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7346_cast_fp16 = slice_by_index(begin = var_7346_begin_0, end = var_7346_end_0, end_mask = var_7346_end_mask_0, x = transpose_4)[name = tensor("op_7346_cast_fp16")]; + tensor var_7350_begin_0 = const()[name = tensor("op_7350_begin_0"), val = tensor([0, 0, 0, 704])]; + tensor var_7350_end_0 = const()[name = tensor("op_7350_end_0"), val = tensor([1, 1500, 1, 768])]; + tensor var_7350_end_mask_0 = const()[name = tensor("op_7350_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7350_cast_fp16 = slice_by_index(begin = var_7350_begin_0, end = var_7350_end_0, end_mask = var_7350_end_mask_0, x = transpose_4)[name = tensor("op_7350_cast_fp16")]; + tensor var_7352_begin_0 = const()[name = tensor("op_7352_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7352_end_0 = const()[name = tensor("op_7352_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7352_end_mask_0 = const()[name = tensor("op_7352_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7352_cast_fp16 = slice_by_index(begin = var_7352_begin_0, end = var_7352_end_0, end_mask = var_7352_end_mask_0, x = value_15_cast_fp16)[name = tensor("op_7352_cast_fp16")]; + tensor var_7356_begin_0 = const()[name = tensor("op_7356_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_7356_end_0 = const()[name = tensor("op_7356_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_7356_end_mask_0 = const()[name = tensor("op_7356_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7356_cast_fp16 = slice_by_index(begin = var_7356_begin_0, end = var_7356_end_0, end_mask = var_7356_end_mask_0, x = value_15_cast_fp16)[name = tensor("op_7356_cast_fp16")]; + tensor var_7360_begin_0 = const()[name = tensor("op_7360_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_7360_end_0 = const()[name = tensor("op_7360_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_7360_end_mask_0 = const()[name = tensor("op_7360_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7360_cast_fp16 = slice_by_index(begin = var_7360_begin_0, end = var_7360_end_0, end_mask = var_7360_end_mask_0, x = value_15_cast_fp16)[name = tensor("op_7360_cast_fp16")]; + tensor var_7364_begin_0 = const()[name = tensor("op_7364_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_7364_end_0 = const()[name = tensor("op_7364_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_7364_end_mask_0 = const()[name = tensor("op_7364_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7364_cast_fp16 = slice_by_index(begin = var_7364_begin_0, end = var_7364_end_0, end_mask = var_7364_end_mask_0, x = value_15_cast_fp16)[name = tensor("op_7364_cast_fp16")]; + tensor var_7368_begin_0 = const()[name = tensor("op_7368_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_7368_end_0 = const()[name = tensor("op_7368_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_7368_end_mask_0 = const()[name = tensor("op_7368_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7368_cast_fp16 = slice_by_index(begin = var_7368_begin_0, end = var_7368_end_0, end_mask = var_7368_end_mask_0, x = value_15_cast_fp16)[name = tensor("op_7368_cast_fp16")]; + tensor var_7372_begin_0 = const()[name = tensor("op_7372_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_7372_end_0 = const()[name = tensor("op_7372_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_7372_end_mask_0 = const()[name = tensor("op_7372_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7372_cast_fp16 = slice_by_index(begin = var_7372_begin_0, end = var_7372_end_0, end_mask = var_7372_end_mask_0, x = value_15_cast_fp16)[name = tensor("op_7372_cast_fp16")]; + tensor var_7376_begin_0 = const()[name = tensor("op_7376_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_7376_end_0 = const()[name = tensor("op_7376_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_7376_end_mask_0 = const()[name = tensor("op_7376_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7376_cast_fp16 = slice_by_index(begin = var_7376_begin_0, end = var_7376_end_0, end_mask = var_7376_end_mask_0, x = value_15_cast_fp16)[name = tensor("op_7376_cast_fp16")]; + tensor var_7380_begin_0 = const()[name = tensor("op_7380_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_7380_end_0 = const()[name = tensor("op_7380_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_7380_end_mask_0 = const()[name = tensor("op_7380_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7380_cast_fp16 = slice_by_index(begin = var_7380_begin_0, end = var_7380_end_0, end_mask = var_7380_end_mask_0, x = value_15_cast_fp16)[name = tensor("op_7380_cast_fp16")]; + tensor var_7384_begin_0 = const()[name = tensor("op_7384_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_7384_end_0 = const()[name = tensor("op_7384_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_7384_end_mask_0 = const()[name = tensor("op_7384_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7384_cast_fp16 = slice_by_index(begin = var_7384_begin_0, end = var_7384_end_0, end_mask = var_7384_end_mask_0, x = value_15_cast_fp16)[name = tensor("op_7384_cast_fp16")]; + tensor var_7388_begin_0 = const()[name = tensor("op_7388_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_7388_end_0 = const()[name = tensor("op_7388_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_7388_end_mask_0 = const()[name = tensor("op_7388_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7388_cast_fp16 = slice_by_index(begin = var_7388_begin_0, end = var_7388_end_0, end_mask = var_7388_end_mask_0, x = value_15_cast_fp16)[name = tensor("op_7388_cast_fp16")]; + tensor var_7392_begin_0 = const()[name = tensor("op_7392_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_7392_end_0 = const()[name = tensor("op_7392_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_7392_end_mask_0 = const()[name = tensor("op_7392_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7392_cast_fp16 = slice_by_index(begin = var_7392_begin_0, end = var_7392_end_0, end_mask = var_7392_end_mask_0, x = value_15_cast_fp16)[name = tensor("op_7392_cast_fp16")]; + tensor var_7396_begin_0 = const()[name = tensor("op_7396_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_7396_end_0 = const()[name = tensor("op_7396_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_7396_end_mask_0 = const()[name = tensor("op_7396_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7396_cast_fp16 = slice_by_index(begin = var_7396_begin_0, end = var_7396_end_0, end_mask = var_7396_end_mask_0, x = value_15_cast_fp16)[name = tensor("op_7396_cast_fp16")]; + tensor var_7400_equation_0 = const()[name = tensor("op_7400_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7400_cast_fp16 = einsum(equation = var_7400_equation_0, values = (var_7306_cast_fp16, var_6972_cast_fp16))[name = tensor("op_7400_cast_fp16")]; + tensor var_7401_to_fp16 = const()[name = tensor("op_7401_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_673_cast_fp16 = mul(x = var_7400_cast_fp16, y = var_7401_to_fp16)[name = tensor("aw_chunk_673_cast_fp16")]; + tensor var_7404_equation_0 = const()[name = tensor("op_7404_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7404_cast_fp16 = einsum(equation = var_7404_equation_0, values = (var_7306_cast_fp16, var_6979_cast_fp16))[name = tensor("op_7404_cast_fp16")]; + tensor var_7405_to_fp16 = const()[name = tensor("op_7405_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_675_cast_fp16 = mul(x = var_7404_cast_fp16, y = var_7405_to_fp16)[name = tensor("aw_chunk_675_cast_fp16")]; + tensor var_7408_equation_0 = const()[name = tensor("op_7408_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7408_cast_fp16 = einsum(equation = var_7408_equation_0, values = (var_7306_cast_fp16, var_6986_cast_fp16))[name = tensor("op_7408_cast_fp16")]; + tensor var_7409_to_fp16 = const()[name = tensor("op_7409_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_677_cast_fp16 = mul(x = var_7408_cast_fp16, y = var_7409_to_fp16)[name = tensor("aw_chunk_677_cast_fp16")]; + tensor var_7412_equation_0 = const()[name = tensor("op_7412_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7412_cast_fp16 = einsum(equation = var_7412_equation_0, values = (var_7306_cast_fp16, var_6993_cast_fp16))[name = tensor("op_7412_cast_fp16")]; + tensor var_7413_to_fp16 = const()[name = tensor("op_7413_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_679_cast_fp16 = mul(x = var_7412_cast_fp16, y = var_7413_to_fp16)[name = tensor("aw_chunk_679_cast_fp16")]; + tensor var_7416_equation_0 = const()[name = tensor("op_7416_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7416_cast_fp16 = einsum(equation = var_7416_equation_0, values = (var_7310_cast_fp16, var_7000_cast_fp16))[name = tensor("op_7416_cast_fp16")]; + tensor var_7417_to_fp16 = const()[name = tensor("op_7417_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_681_cast_fp16 = mul(x = var_7416_cast_fp16, y = var_7417_to_fp16)[name = tensor("aw_chunk_681_cast_fp16")]; + tensor var_7420_equation_0 = const()[name = tensor("op_7420_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7420_cast_fp16 = einsum(equation = var_7420_equation_0, values = (var_7310_cast_fp16, var_7007_cast_fp16))[name = tensor("op_7420_cast_fp16")]; + tensor var_7421_to_fp16 = const()[name = tensor("op_7421_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_683_cast_fp16 = mul(x = var_7420_cast_fp16, y = var_7421_to_fp16)[name = tensor("aw_chunk_683_cast_fp16")]; + tensor var_7424_equation_0 = const()[name = tensor("op_7424_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7424_cast_fp16 = einsum(equation = var_7424_equation_0, values = (var_7310_cast_fp16, var_7014_cast_fp16))[name = tensor("op_7424_cast_fp16")]; + tensor var_7425_to_fp16 = const()[name = tensor("op_7425_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_685_cast_fp16 = mul(x = var_7424_cast_fp16, y = var_7425_to_fp16)[name = tensor("aw_chunk_685_cast_fp16")]; + tensor var_7428_equation_0 = const()[name = tensor("op_7428_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7428_cast_fp16 = einsum(equation = var_7428_equation_0, values = (var_7310_cast_fp16, var_7021_cast_fp16))[name = tensor("op_7428_cast_fp16")]; + tensor var_7429_to_fp16 = const()[name = tensor("op_7429_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_687_cast_fp16 = mul(x = var_7428_cast_fp16, y = var_7429_to_fp16)[name = tensor("aw_chunk_687_cast_fp16")]; + tensor var_7432_equation_0 = const()[name = tensor("op_7432_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7432_cast_fp16 = einsum(equation = var_7432_equation_0, values = (var_7314_cast_fp16, var_7028_cast_fp16))[name = tensor("op_7432_cast_fp16")]; + tensor var_7433_to_fp16 = const()[name = tensor("op_7433_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_689_cast_fp16 = mul(x = var_7432_cast_fp16, y = var_7433_to_fp16)[name = tensor("aw_chunk_689_cast_fp16")]; + tensor var_7436_equation_0 = const()[name = tensor("op_7436_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7436_cast_fp16 = einsum(equation = var_7436_equation_0, values = (var_7314_cast_fp16, var_7035_cast_fp16))[name = tensor("op_7436_cast_fp16")]; + tensor var_7437_to_fp16 = const()[name = tensor("op_7437_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_691_cast_fp16 = mul(x = var_7436_cast_fp16, y = var_7437_to_fp16)[name = tensor("aw_chunk_691_cast_fp16")]; + tensor var_7440_equation_0 = const()[name = tensor("op_7440_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7440_cast_fp16 = einsum(equation = var_7440_equation_0, values = (var_7314_cast_fp16, var_7042_cast_fp16))[name = tensor("op_7440_cast_fp16")]; + tensor var_7441_to_fp16 = const()[name = tensor("op_7441_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_693_cast_fp16 = mul(x = var_7440_cast_fp16, y = var_7441_to_fp16)[name = tensor("aw_chunk_693_cast_fp16")]; + tensor var_7444_equation_0 = const()[name = tensor("op_7444_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7444_cast_fp16 = einsum(equation = var_7444_equation_0, values = (var_7314_cast_fp16, var_7049_cast_fp16))[name = tensor("op_7444_cast_fp16")]; + tensor var_7445_to_fp16 = const()[name = tensor("op_7445_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_695_cast_fp16 = mul(x = var_7444_cast_fp16, y = var_7445_to_fp16)[name = tensor("aw_chunk_695_cast_fp16")]; + tensor var_7448_equation_0 = const()[name = tensor("op_7448_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7448_cast_fp16 = einsum(equation = var_7448_equation_0, values = (var_7318_cast_fp16, var_7056_cast_fp16))[name = tensor("op_7448_cast_fp16")]; + tensor var_7449_to_fp16 = const()[name = tensor("op_7449_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_697_cast_fp16 = mul(x = var_7448_cast_fp16, y = var_7449_to_fp16)[name = tensor("aw_chunk_697_cast_fp16")]; + tensor var_7452_equation_0 = const()[name = tensor("op_7452_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7452_cast_fp16 = einsum(equation = var_7452_equation_0, values = (var_7318_cast_fp16, var_7063_cast_fp16))[name = tensor("op_7452_cast_fp16")]; + tensor var_7453_to_fp16 = const()[name = tensor("op_7453_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_699_cast_fp16 = mul(x = var_7452_cast_fp16, y = var_7453_to_fp16)[name = tensor("aw_chunk_699_cast_fp16")]; + tensor var_7456_equation_0 = const()[name = tensor("op_7456_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7456_cast_fp16 = einsum(equation = var_7456_equation_0, values = (var_7318_cast_fp16, var_7070_cast_fp16))[name = tensor("op_7456_cast_fp16")]; + tensor var_7457_to_fp16 = const()[name = tensor("op_7457_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_701_cast_fp16 = mul(x = var_7456_cast_fp16, y = var_7457_to_fp16)[name = tensor("aw_chunk_701_cast_fp16")]; + tensor var_7460_equation_0 = const()[name = tensor("op_7460_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7460_cast_fp16 = einsum(equation = var_7460_equation_0, values = (var_7318_cast_fp16, var_7077_cast_fp16))[name = tensor("op_7460_cast_fp16")]; + tensor var_7461_to_fp16 = const()[name = tensor("op_7461_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_703_cast_fp16 = mul(x = var_7460_cast_fp16, y = var_7461_to_fp16)[name = tensor("aw_chunk_703_cast_fp16")]; + tensor var_7464_equation_0 = const()[name = tensor("op_7464_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7464_cast_fp16 = einsum(equation = var_7464_equation_0, values = (var_7322_cast_fp16, var_7084_cast_fp16))[name = tensor("op_7464_cast_fp16")]; + tensor var_7465_to_fp16 = const()[name = tensor("op_7465_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_705_cast_fp16 = mul(x = var_7464_cast_fp16, y = var_7465_to_fp16)[name = tensor("aw_chunk_705_cast_fp16")]; + tensor var_7468_equation_0 = const()[name = tensor("op_7468_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7468_cast_fp16 = einsum(equation = var_7468_equation_0, values = (var_7322_cast_fp16, var_7091_cast_fp16))[name = tensor("op_7468_cast_fp16")]; + tensor var_7469_to_fp16 = const()[name = tensor("op_7469_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_707_cast_fp16 = mul(x = var_7468_cast_fp16, y = var_7469_to_fp16)[name = tensor("aw_chunk_707_cast_fp16")]; + tensor var_7472_equation_0 = const()[name = tensor("op_7472_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7472_cast_fp16 = einsum(equation = var_7472_equation_0, values = (var_7322_cast_fp16, var_7098_cast_fp16))[name = tensor("op_7472_cast_fp16")]; + tensor var_7473_to_fp16 = const()[name = tensor("op_7473_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_709_cast_fp16 = mul(x = var_7472_cast_fp16, y = var_7473_to_fp16)[name = tensor("aw_chunk_709_cast_fp16")]; + tensor var_7476_equation_0 = const()[name = tensor("op_7476_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7476_cast_fp16 = einsum(equation = var_7476_equation_0, values = (var_7322_cast_fp16, var_7105_cast_fp16))[name = tensor("op_7476_cast_fp16")]; + tensor var_7477_to_fp16 = const()[name = tensor("op_7477_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_711_cast_fp16 = mul(x = var_7476_cast_fp16, y = var_7477_to_fp16)[name = tensor("aw_chunk_711_cast_fp16")]; + tensor var_7480_equation_0 = const()[name = tensor("op_7480_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7480_cast_fp16 = einsum(equation = var_7480_equation_0, values = (var_7326_cast_fp16, var_7112_cast_fp16))[name = tensor("op_7480_cast_fp16")]; + tensor var_7481_to_fp16 = const()[name = tensor("op_7481_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_713_cast_fp16 = mul(x = var_7480_cast_fp16, y = var_7481_to_fp16)[name = tensor("aw_chunk_713_cast_fp16")]; + tensor var_7484_equation_0 = const()[name = tensor("op_7484_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7484_cast_fp16 = einsum(equation = var_7484_equation_0, values = (var_7326_cast_fp16, var_7119_cast_fp16))[name = tensor("op_7484_cast_fp16")]; + tensor var_7485_to_fp16 = const()[name = tensor("op_7485_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_715_cast_fp16 = mul(x = var_7484_cast_fp16, y = var_7485_to_fp16)[name = tensor("aw_chunk_715_cast_fp16")]; + tensor var_7488_equation_0 = const()[name = tensor("op_7488_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7488_cast_fp16 = einsum(equation = var_7488_equation_0, values = (var_7326_cast_fp16, var_7126_cast_fp16))[name = tensor("op_7488_cast_fp16")]; + tensor var_7489_to_fp16 = const()[name = tensor("op_7489_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_717_cast_fp16 = mul(x = var_7488_cast_fp16, y = var_7489_to_fp16)[name = tensor("aw_chunk_717_cast_fp16")]; + tensor var_7492_equation_0 = const()[name = tensor("op_7492_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7492_cast_fp16 = einsum(equation = var_7492_equation_0, values = (var_7326_cast_fp16, var_7133_cast_fp16))[name = tensor("op_7492_cast_fp16")]; + tensor var_7493_to_fp16 = const()[name = tensor("op_7493_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_719_cast_fp16 = mul(x = var_7492_cast_fp16, y = var_7493_to_fp16)[name = tensor("aw_chunk_719_cast_fp16")]; + tensor var_7496_equation_0 = const()[name = tensor("op_7496_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7496_cast_fp16 = einsum(equation = var_7496_equation_0, values = (var_7330_cast_fp16, var_7140_cast_fp16))[name = tensor("op_7496_cast_fp16")]; + tensor var_7497_to_fp16 = const()[name = tensor("op_7497_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_721_cast_fp16 = mul(x = var_7496_cast_fp16, y = var_7497_to_fp16)[name = tensor("aw_chunk_721_cast_fp16")]; + tensor var_7500_equation_0 = const()[name = tensor("op_7500_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7500_cast_fp16 = einsum(equation = var_7500_equation_0, values = (var_7330_cast_fp16, var_7147_cast_fp16))[name = tensor("op_7500_cast_fp16")]; + tensor var_7501_to_fp16 = const()[name = tensor("op_7501_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_723_cast_fp16 = mul(x = var_7500_cast_fp16, y = var_7501_to_fp16)[name = tensor("aw_chunk_723_cast_fp16")]; + tensor var_7504_equation_0 = const()[name = tensor("op_7504_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7504_cast_fp16 = einsum(equation = var_7504_equation_0, values = (var_7330_cast_fp16, var_7154_cast_fp16))[name = tensor("op_7504_cast_fp16")]; + tensor var_7505_to_fp16 = const()[name = tensor("op_7505_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_725_cast_fp16 = mul(x = var_7504_cast_fp16, y = var_7505_to_fp16)[name = tensor("aw_chunk_725_cast_fp16")]; + tensor var_7508_equation_0 = const()[name = tensor("op_7508_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7508_cast_fp16 = einsum(equation = var_7508_equation_0, values = (var_7330_cast_fp16, var_7161_cast_fp16))[name = tensor("op_7508_cast_fp16")]; + tensor var_7509_to_fp16 = const()[name = tensor("op_7509_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_727_cast_fp16 = mul(x = var_7508_cast_fp16, y = var_7509_to_fp16)[name = tensor("aw_chunk_727_cast_fp16")]; + tensor var_7512_equation_0 = const()[name = tensor("op_7512_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7512_cast_fp16 = einsum(equation = var_7512_equation_0, values = (var_7334_cast_fp16, var_7168_cast_fp16))[name = tensor("op_7512_cast_fp16")]; + tensor var_7513_to_fp16 = const()[name = tensor("op_7513_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_729_cast_fp16 = mul(x = var_7512_cast_fp16, y = var_7513_to_fp16)[name = tensor("aw_chunk_729_cast_fp16")]; + tensor var_7516_equation_0 = const()[name = tensor("op_7516_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7516_cast_fp16 = einsum(equation = var_7516_equation_0, values = (var_7334_cast_fp16, var_7175_cast_fp16))[name = tensor("op_7516_cast_fp16")]; + tensor var_7517_to_fp16 = const()[name = tensor("op_7517_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_731_cast_fp16 = mul(x = var_7516_cast_fp16, y = var_7517_to_fp16)[name = tensor("aw_chunk_731_cast_fp16")]; + tensor var_7520_equation_0 = const()[name = tensor("op_7520_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7520_cast_fp16 = einsum(equation = var_7520_equation_0, values = (var_7334_cast_fp16, var_7182_cast_fp16))[name = tensor("op_7520_cast_fp16")]; + tensor var_7521_to_fp16 = const()[name = tensor("op_7521_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_733_cast_fp16 = mul(x = var_7520_cast_fp16, y = var_7521_to_fp16)[name = tensor("aw_chunk_733_cast_fp16")]; + tensor var_7524_equation_0 = const()[name = tensor("op_7524_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7524_cast_fp16 = einsum(equation = var_7524_equation_0, values = (var_7334_cast_fp16, var_7189_cast_fp16))[name = tensor("op_7524_cast_fp16")]; + tensor var_7525_to_fp16 = const()[name = tensor("op_7525_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_735_cast_fp16 = mul(x = var_7524_cast_fp16, y = var_7525_to_fp16)[name = tensor("aw_chunk_735_cast_fp16")]; + tensor var_7528_equation_0 = const()[name = tensor("op_7528_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7528_cast_fp16 = einsum(equation = var_7528_equation_0, values = (var_7338_cast_fp16, var_7196_cast_fp16))[name = tensor("op_7528_cast_fp16")]; + tensor var_7529_to_fp16 = const()[name = tensor("op_7529_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_737_cast_fp16 = mul(x = var_7528_cast_fp16, y = var_7529_to_fp16)[name = tensor("aw_chunk_737_cast_fp16")]; + tensor var_7532_equation_0 = const()[name = tensor("op_7532_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7532_cast_fp16 = einsum(equation = var_7532_equation_0, values = (var_7338_cast_fp16, var_7203_cast_fp16))[name = tensor("op_7532_cast_fp16")]; + tensor var_7533_to_fp16 = const()[name = tensor("op_7533_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_739_cast_fp16 = mul(x = var_7532_cast_fp16, y = var_7533_to_fp16)[name = tensor("aw_chunk_739_cast_fp16")]; + tensor var_7536_equation_0 = const()[name = tensor("op_7536_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7536_cast_fp16 = einsum(equation = var_7536_equation_0, values = (var_7338_cast_fp16, var_7210_cast_fp16))[name = tensor("op_7536_cast_fp16")]; + tensor var_7537_to_fp16 = const()[name = tensor("op_7537_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_741_cast_fp16 = mul(x = var_7536_cast_fp16, y = var_7537_to_fp16)[name = tensor("aw_chunk_741_cast_fp16")]; + tensor var_7540_equation_0 = const()[name = tensor("op_7540_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7540_cast_fp16 = einsum(equation = var_7540_equation_0, values = (var_7338_cast_fp16, var_7217_cast_fp16))[name = tensor("op_7540_cast_fp16")]; + tensor var_7541_to_fp16 = const()[name = tensor("op_7541_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_743_cast_fp16 = mul(x = var_7540_cast_fp16, y = var_7541_to_fp16)[name = tensor("aw_chunk_743_cast_fp16")]; + tensor var_7544_equation_0 = const()[name = tensor("op_7544_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7544_cast_fp16 = einsum(equation = var_7544_equation_0, values = (var_7342_cast_fp16, var_7224_cast_fp16))[name = tensor("op_7544_cast_fp16")]; + tensor var_7545_to_fp16 = const()[name = tensor("op_7545_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_745_cast_fp16 = mul(x = var_7544_cast_fp16, y = var_7545_to_fp16)[name = tensor("aw_chunk_745_cast_fp16")]; + tensor var_7548_equation_0 = const()[name = tensor("op_7548_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7548_cast_fp16 = einsum(equation = var_7548_equation_0, values = (var_7342_cast_fp16, var_7231_cast_fp16))[name = tensor("op_7548_cast_fp16")]; + tensor var_7549_to_fp16 = const()[name = tensor("op_7549_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_747_cast_fp16 = mul(x = var_7548_cast_fp16, y = var_7549_to_fp16)[name = tensor("aw_chunk_747_cast_fp16")]; + tensor var_7552_equation_0 = const()[name = tensor("op_7552_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7552_cast_fp16 = einsum(equation = var_7552_equation_0, values = (var_7342_cast_fp16, var_7238_cast_fp16))[name = tensor("op_7552_cast_fp16")]; + tensor var_7553_to_fp16 = const()[name = tensor("op_7553_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_749_cast_fp16 = mul(x = var_7552_cast_fp16, y = var_7553_to_fp16)[name = tensor("aw_chunk_749_cast_fp16")]; + tensor var_7556_equation_0 = const()[name = tensor("op_7556_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7556_cast_fp16 = einsum(equation = var_7556_equation_0, values = (var_7342_cast_fp16, var_7245_cast_fp16))[name = tensor("op_7556_cast_fp16")]; + tensor var_7557_to_fp16 = const()[name = tensor("op_7557_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_751_cast_fp16 = mul(x = var_7556_cast_fp16, y = var_7557_to_fp16)[name = tensor("aw_chunk_751_cast_fp16")]; + tensor var_7560_equation_0 = const()[name = tensor("op_7560_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7560_cast_fp16 = einsum(equation = var_7560_equation_0, values = (var_7346_cast_fp16, var_7252_cast_fp16))[name = tensor("op_7560_cast_fp16")]; + tensor var_7561_to_fp16 = const()[name = tensor("op_7561_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_753_cast_fp16 = mul(x = var_7560_cast_fp16, y = var_7561_to_fp16)[name = tensor("aw_chunk_753_cast_fp16")]; + tensor var_7564_equation_0 = const()[name = tensor("op_7564_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7564_cast_fp16 = einsum(equation = var_7564_equation_0, values = (var_7346_cast_fp16, var_7259_cast_fp16))[name = tensor("op_7564_cast_fp16")]; + tensor var_7565_to_fp16 = const()[name = tensor("op_7565_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_755_cast_fp16 = mul(x = var_7564_cast_fp16, y = var_7565_to_fp16)[name = tensor("aw_chunk_755_cast_fp16")]; + tensor var_7568_equation_0 = const()[name = tensor("op_7568_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7568_cast_fp16 = einsum(equation = var_7568_equation_0, values = (var_7346_cast_fp16, var_7266_cast_fp16))[name = tensor("op_7568_cast_fp16")]; + tensor var_7569_to_fp16 = const()[name = tensor("op_7569_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_757_cast_fp16 = mul(x = var_7568_cast_fp16, y = var_7569_to_fp16)[name = tensor("aw_chunk_757_cast_fp16")]; + tensor var_7572_equation_0 = const()[name = tensor("op_7572_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7572_cast_fp16 = einsum(equation = var_7572_equation_0, values = (var_7346_cast_fp16, var_7273_cast_fp16))[name = tensor("op_7572_cast_fp16")]; + tensor var_7573_to_fp16 = const()[name = tensor("op_7573_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_759_cast_fp16 = mul(x = var_7572_cast_fp16, y = var_7573_to_fp16)[name = tensor("aw_chunk_759_cast_fp16")]; + tensor var_7576_equation_0 = const()[name = tensor("op_7576_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7576_cast_fp16 = einsum(equation = var_7576_equation_0, values = (var_7350_cast_fp16, var_7280_cast_fp16))[name = tensor("op_7576_cast_fp16")]; + tensor var_7577_to_fp16 = const()[name = tensor("op_7577_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_761_cast_fp16 = mul(x = var_7576_cast_fp16, y = var_7577_to_fp16)[name = tensor("aw_chunk_761_cast_fp16")]; + tensor var_7580_equation_0 = const()[name = tensor("op_7580_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7580_cast_fp16 = einsum(equation = var_7580_equation_0, values = (var_7350_cast_fp16, var_7287_cast_fp16))[name = tensor("op_7580_cast_fp16")]; + tensor var_7581_to_fp16 = const()[name = tensor("op_7581_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_763_cast_fp16 = mul(x = var_7580_cast_fp16, y = var_7581_to_fp16)[name = tensor("aw_chunk_763_cast_fp16")]; + tensor var_7584_equation_0 = const()[name = tensor("op_7584_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7584_cast_fp16 = einsum(equation = var_7584_equation_0, values = (var_7350_cast_fp16, var_7294_cast_fp16))[name = tensor("op_7584_cast_fp16")]; + tensor var_7585_to_fp16 = const()[name = tensor("op_7585_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_765_cast_fp16 = mul(x = var_7584_cast_fp16, y = var_7585_to_fp16)[name = tensor("aw_chunk_765_cast_fp16")]; + tensor var_7588_equation_0 = const()[name = tensor("op_7588_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_7588_cast_fp16 = einsum(equation = var_7588_equation_0, values = (var_7350_cast_fp16, var_7301_cast_fp16))[name = tensor("op_7588_cast_fp16")]; + tensor var_7589_to_fp16 = const()[name = tensor("op_7589_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_767_cast_fp16 = mul(x = var_7588_cast_fp16, y = var_7589_to_fp16)[name = tensor("aw_chunk_767_cast_fp16")]; + tensor var_7591_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_673_cast_fp16)[name = tensor("op_7591_cast_fp16")]; + tensor var_7592_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_675_cast_fp16)[name = tensor("op_7592_cast_fp16")]; + tensor var_7593_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_677_cast_fp16)[name = tensor("op_7593_cast_fp16")]; + tensor var_7594_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_679_cast_fp16)[name = tensor("op_7594_cast_fp16")]; + tensor var_7595_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_681_cast_fp16)[name = tensor("op_7595_cast_fp16")]; + tensor var_7596_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_683_cast_fp16)[name = tensor("op_7596_cast_fp16")]; + tensor var_7597_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_685_cast_fp16)[name = tensor("op_7597_cast_fp16")]; + tensor var_7598_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_687_cast_fp16)[name = tensor("op_7598_cast_fp16")]; + tensor var_7599_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_689_cast_fp16)[name = tensor("op_7599_cast_fp16")]; + tensor var_7600_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_691_cast_fp16)[name = tensor("op_7600_cast_fp16")]; + tensor var_7601_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_693_cast_fp16)[name = tensor("op_7601_cast_fp16")]; + tensor var_7602_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_695_cast_fp16)[name = tensor("op_7602_cast_fp16")]; + tensor var_7603_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_697_cast_fp16)[name = tensor("op_7603_cast_fp16")]; + tensor var_7604_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_699_cast_fp16)[name = tensor("op_7604_cast_fp16")]; + tensor var_7605_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_701_cast_fp16)[name = tensor("op_7605_cast_fp16")]; + tensor var_7606_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_703_cast_fp16)[name = tensor("op_7606_cast_fp16")]; + tensor var_7607_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_705_cast_fp16)[name = tensor("op_7607_cast_fp16")]; + tensor var_7608_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_707_cast_fp16)[name = tensor("op_7608_cast_fp16")]; + tensor var_7609_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_709_cast_fp16)[name = tensor("op_7609_cast_fp16")]; + tensor var_7610_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_711_cast_fp16)[name = tensor("op_7610_cast_fp16")]; + tensor var_7611_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_713_cast_fp16)[name = tensor("op_7611_cast_fp16")]; + tensor var_7612_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_715_cast_fp16)[name = tensor("op_7612_cast_fp16")]; + tensor var_7613_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_717_cast_fp16)[name = tensor("op_7613_cast_fp16")]; + tensor var_7614_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_719_cast_fp16)[name = tensor("op_7614_cast_fp16")]; + tensor var_7615_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_721_cast_fp16)[name = tensor("op_7615_cast_fp16")]; + tensor var_7616_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_723_cast_fp16)[name = tensor("op_7616_cast_fp16")]; + tensor var_7617_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_725_cast_fp16)[name = tensor("op_7617_cast_fp16")]; + tensor var_7618_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_727_cast_fp16)[name = tensor("op_7618_cast_fp16")]; + tensor var_7619_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_729_cast_fp16)[name = tensor("op_7619_cast_fp16")]; + tensor var_7620_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_731_cast_fp16)[name = tensor("op_7620_cast_fp16")]; + tensor var_7621_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_733_cast_fp16)[name = tensor("op_7621_cast_fp16")]; + tensor var_7622_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_735_cast_fp16)[name = tensor("op_7622_cast_fp16")]; + tensor var_7623_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_737_cast_fp16)[name = tensor("op_7623_cast_fp16")]; + tensor var_7624_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_739_cast_fp16)[name = tensor("op_7624_cast_fp16")]; + tensor var_7625_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_741_cast_fp16)[name = tensor("op_7625_cast_fp16")]; + tensor var_7626_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_743_cast_fp16)[name = tensor("op_7626_cast_fp16")]; + tensor var_7627_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_745_cast_fp16)[name = tensor("op_7627_cast_fp16")]; + tensor var_7628_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_747_cast_fp16)[name = tensor("op_7628_cast_fp16")]; + tensor var_7629_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_749_cast_fp16)[name = tensor("op_7629_cast_fp16")]; + tensor var_7630_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_751_cast_fp16)[name = tensor("op_7630_cast_fp16")]; + tensor var_7631_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_753_cast_fp16)[name = tensor("op_7631_cast_fp16")]; + tensor var_7632_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_755_cast_fp16)[name = tensor("op_7632_cast_fp16")]; + tensor var_7633_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_757_cast_fp16)[name = tensor("op_7633_cast_fp16")]; + tensor var_7634_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_759_cast_fp16)[name = tensor("op_7634_cast_fp16")]; + tensor var_7635_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_761_cast_fp16)[name = tensor("op_7635_cast_fp16")]; + tensor var_7636_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_763_cast_fp16)[name = tensor("op_7636_cast_fp16")]; + tensor var_7637_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_765_cast_fp16)[name = tensor("op_7637_cast_fp16")]; + tensor var_7638_cast_fp16 = softmax(axis = var_6864, x = aw_chunk_767_cast_fp16)[name = tensor("op_7638_cast_fp16")]; + tensor var_7640_equation_0 = const()[name = tensor("op_7640_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7640_cast_fp16 = einsum(equation = var_7640_equation_0, values = (var_7352_cast_fp16, var_7591_cast_fp16))[name = tensor("op_7640_cast_fp16")]; + tensor var_7642_equation_0 = const()[name = tensor("op_7642_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7642_cast_fp16 = einsum(equation = var_7642_equation_0, values = (var_7352_cast_fp16, var_7592_cast_fp16))[name = tensor("op_7642_cast_fp16")]; + tensor var_7644_equation_0 = const()[name = tensor("op_7644_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7644_cast_fp16 = einsum(equation = var_7644_equation_0, values = (var_7352_cast_fp16, var_7593_cast_fp16))[name = tensor("op_7644_cast_fp16")]; + tensor var_7646_equation_0 = const()[name = tensor("op_7646_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7646_cast_fp16 = einsum(equation = var_7646_equation_0, values = (var_7352_cast_fp16, var_7594_cast_fp16))[name = tensor("op_7646_cast_fp16")]; + tensor var_7648_equation_0 = const()[name = tensor("op_7648_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7648_cast_fp16 = einsum(equation = var_7648_equation_0, values = (var_7356_cast_fp16, var_7595_cast_fp16))[name = tensor("op_7648_cast_fp16")]; + tensor var_7650_equation_0 = const()[name = tensor("op_7650_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7650_cast_fp16 = einsum(equation = var_7650_equation_0, values = (var_7356_cast_fp16, var_7596_cast_fp16))[name = tensor("op_7650_cast_fp16")]; + tensor var_7652_equation_0 = const()[name = tensor("op_7652_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7652_cast_fp16 = einsum(equation = var_7652_equation_0, values = (var_7356_cast_fp16, var_7597_cast_fp16))[name = tensor("op_7652_cast_fp16")]; + tensor var_7654_equation_0 = const()[name = tensor("op_7654_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7654_cast_fp16 = einsum(equation = var_7654_equation_0, values = (var_7356_cast_fp16, var_7598_cast_fp16))[name = tensor("op_7654_cast_fp16")]; + tensor var_7656_equation_0 = const()[name = tensor("op_7656_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7656_cast_fp16 = einsum(equation = var_7656_equation_0, values = (var_7360_cast_fp16, var_7599_cast_fp16))[name = tensor("op_7656_cast_fp16")]; + tensor var_7658_equation_0 = const()[name = tensor("op_7658_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7658_cast_fp16 = einsum(equation = var_7658_equation_0, values = (var_7360_cast_fp16, var_7600_cast_fp16))[name = tensor("op_7658_cast_fp16")]; + tensor var_7660_equation_0 = const()[name = tensor("op_7660_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7660_cast_fp16 = einsum(equation = var_7660_equation_0, values = (var_7360_cast_fp16, var_7601_cast_fp16))[name = tensor("op_7660_cast_fp16")]; + tensor var_7662_equation_0 = const()[name = tensor("op_7662_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7662_cast_fp16 = einsum(equation = var_7662_equation_0, values = (var_7360_cast_fp16, var_7602_cast_fp16))[name = tensor("op_7662_cast_fp16")]; + tensor var_7664_equation_0 = const()[name = tensor("op_7664_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7664_cast_fp16 = einsum(equation = var_7664_equation_0, values = (var_7364_cast_fp16, var_7603_cast_fp16))[name = tensor("op_7664_cast_fp16")]; + tensor var_7666_equation_0 = const()[name = tensor("op_7666_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7666_cast_fp16 = einsum(equation = var_7666_equation_0, values = (var_7364_cast_fp16, var_7604_cast_fp16))[name = tensor("op_7666_cast_fp16")]; + tensor var_7668_equation_0 = const()[name = tensor("op_7668_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7668_cast_fp16 = einsum(equation = var_7668_equation_0, values = (var_7364_cast_fp16, var_7605_cast_fp16))[name = tensor("op_7668_cast_fp16")]; + tensor var_7670_equation_0 = const()[name = tensor("op_7670_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7670_cast_fp16 = einsum(equation = var_7670_equation_0, values = (var_7364_cast_fp16, var_7606_cast_fp16))[name = tensor("op_7670_cast_fp16")]; + tensor var_7672_equation_0 = const()[name = tensor("op_7672_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7672_cast_fp16 = einsum(equation = var_7672_equation_0, values = (var_7368_cast_fp16, var_7607_cast_fp16))[name = tensor("op_7672_cast_fp16")]; + tensor var_7674_equation_0 = const()[name = tensor("op_7674_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7674_cast_fp16 = einsum(equation = var_7674_equation_0, values = (var_7368_cast_fp16, var_7608_cast_fp16))[name = tensor("op_7674_cast_fp16")]; + tensor var_7676_equation_0 = const()[name = tensor("op_7676_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7676_cast_fp16 = einsum(equation = var_7676_equation_0, values = (var_7368_cast_fp16, var_7609_cast_fp16))[name = tensor("op_7676_cast_fp16")]; + tensor var_7678_equation_0 = const()[name = tensor("op_7678_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7678_cast_fp16 = einsum(equation = var_7678_equation_0, values = (var_7368_cast_fp16, var_7610_cast_fp16))[name = tensor("op_7678_cast_fp16")]; + tensor var_7680_equation_0 = const()[name = tensor("op_7680_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7680_cast_fp16 = einsum(equation = var_7680_equation_0, values = (var_7372_cast_fp16, var_7611_cast_fp16))[name = tensor("op_7680_cast_fp16")]; + tensor var_7682_equation_0 = const()[name = tensor("op_7682_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7682_cast_fp16 = einsum(equation = var_7682_equation_0, values = (var_7372_cast_fp16, var_7612_cast_fp16))[name = tensor("op_7682_cast_fp16")]; + tensor var_7684_equation_0 = const()[name = tensor("op_7684_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7684_cast_fp16 = einsum(equation = var_7684_equation_0, values = (var_7372_cast_fp16, var_7613_cast_fp16))[name = tensor("op_7684_cast_fp16")]; + tensor var_7686_equation_0 = const()[name = tensor("op_7686_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7686_cast_fp16 = einsum(equation = var_7686_equation_0, values = (var_7372_cast_fp16, var_7614_cast_fp16))[name = tensor("op_7686_cast_fp16")]; + tensor var_7688_equation_0 = const()[name = tensor("op_7688_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7688_cast_fp16 = einsum(equation = var_7688_equation_0, values = (var_7376_cast_fp16, var_7615_cast_fp16))[name = tensor("op_7688_cast_fp16")]; + tensor var_7690_equation_0 = const()[name = tensor("op_7690_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7690_cast_fp16 = einsum(equation = var_7690_equation_0, values = (var_7376_cast_fp16, var_7616_cast_fp16))[name = tensor("op_7690_cast_fp16")]; + tensor var_7692_equation_0 = const()[name = tensor("op_7692_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7692_cast_fp16 = einsum(equation = var_7692_equation_0, values = (var_7376_cast_fp16, var_7617_cast_fp16))[name = tensor("op_7692_cast_fp16")]; + tensor var_7694_equation_0 = const()[name = tensor("op_7694_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7694_cast_fp16 = einsum(equation = var_7694_equation_0, values = (var_7376_cast_fp16, var_7618_cast_fp16))[name = tensor("op_7694_cast_fp16")]; + tensor var_7696_equation_0 = const()[name = tensor("op_7696_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7696_cast_fp16 = einsum(equation = var_7696_equation_0, values = (var_7380_cast_fp16, var_7619_cast_fp16))[name = tensor("op_7696_cast_fp16")]; + tensor var_7698_equation_0 = const()[name = tensor("op_7698_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7698_cast_fp16 = einsum(equation = var_7698_equation_0, values = (var_7380_cast_fp16, var_7620_cast_fp16))[name = tensor("op_7698_cast_fp16")]; + tensor var_7700_equation_0 = const()[name = tensor("op_7700_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7700_cast_fp16 = einsum(equation = var_7700_equation_0, values = (var_7380_cast_fp16, var_7621_cast_fp16))[name = tensor("op_7700_cast_fp16")]; + tensor var_7702_equation_0 = const()[name = tensor("op_7702_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7702_cast_fp16 = einsum(equation = var_7702_equation_0, values = (var_7380_cast_fp16, var_7622_cast_fp16))[name = tensor("op_7702_cast_fp16")]; + tensor var_7704_equation_0 = const()[name = tensor("op_7704_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7704_cast_fp16 = einsum(equation = var_7704_equation_0, values = (var_7384_cast_fp16, var_7623_cast_fp16))[name = tensor("op_7704_cast_fp16")]; + tensor var_7706_equation_0 = const()[name = tensor("op_7706_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7706_cast_fp16 = einsum(equation = var_7706_equation_0, values = (var_7384_cast_fp16, var_7624_cast_fp16))[name = tensor("op_7706_cast_fp16")]; + tensor var_7708_equation_0 = const()[name = tensor("op_7708_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7708_cast_fp16 = einsum(equation = var_7708_equation_0, values = (var_7384_cast_fp16, var_7625_cast_fp16))[name = tensor("op_7708_cast_fp16")]; + tensor var_7710_equation_0 = const()[name = tensor("op_7710_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7710_cast_fp16 = einsum(equation = var_7710_equation_0, values = (var_7384_cast_fp16, var_7626_cast_fp16))[name = tensor("op_7710_cast_fp16")]; + tensor var_7712_equation_0 = const()[name = tensor("op_7712_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7712_cast_fp16 = einsum(equation = var_7712_equation_0, values = (var_7388_cast_fp16, var_7627_cast_fp16))[name = tensor("op_7712_cast_fp16")]; + tensor var_7714_equation_0 = const()[name = tensor("op_7714_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7714_cast_fp16 = einsum(equation = var_7714_equation_0, values = (var_7388_cast_fp16, var_7628_cast_fp16))[name = tensor("op_7714_cast_fp16")]; + tensor var_7716_equation_0 = const()[name = tensor("op_7716_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7716_cast_fp16 = einsum(equation = var_7716_equation_0, values = (var_7388_cast_fp16, var_7629_cast_fp16))[name = tensor("op_7716_cast_fp16")]; + tensor var_7718_equation_0 = const()[name = tensor("op_7718_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7718_cast_fp16 = einsum(equation = var_7718_equation_0, values = (var_7388_cast_fp16, var_7630_cast_fp16))[name = tensor("op_7718_cast_fp16")]; + tensor var_7720_equation_0 = const()[name = tensor("op_7720_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7720_cast_fp16 = einsum(equation = var_7720_equation_0, values = (var_7392_cast_fp16, var_7631_cast_fp16))[name = tensor("op_7720_cast_fp16")]; + tensor var_7722_equation_0 = const()[name = tensor("op_7722_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7722_cast_fp16 = einsum(equation = var_7722_equation_0, values = (var_7392_cast_fp16, var_7632_cast_fp16))[name = tensor("op_7722_cast_fp16")]; + tensor var_7724_equation_0 = const()[name = tensor("op_7724_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7724_cast_fp16 = einsum(equation = var_7724_equation_0, values = (var_7392_cast_fp16, var_7633_cast_fp16))[name = tensor("op_7724_cast_fp16")]; + tensor var_7726_equation_0 = const()[name = tensor("op_7726_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7726_cast_fp16 = einsum(equation = var_7726_equation_0, values = (var_7392_cast_fp16, var_7634_cast_fp16))[name = tensor("op_7726_cast_fp16")]; + tensor var_7728_equation_0 = const()[name = tensor("op_7728_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7728_cast_fp16 = einsum(equation = var_7728_equation_0, values = (var_7396_cast_fp16, var_7635_cast_fp16))[name = tensor("op_7728_cast_fp16")]; + tensor var_7730_equation_0 = const()[name = tensor("op_7730_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7730_cast_fp16 = einsum(equation = var_7730_equation_0, values = (var_7396_cast_fp16, var_7636_cast_fp16))[name = tensor("op_7730_cast_fp16")]; + tensor var_7732_equation_0 = const()[name = tensor("op_7732_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7732_cast_fp16 = einsum(equation = var_7732_equation_0, values = (var_7396_cast_fp16, var_7637_cast_fp16))[name = tensor("op_7732_cast_fp16")]; + tensor var_7734_equation_0 = const()[name = tensor("op_7734_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_7734_cast_fp16 = einsum(equation = var_7734_equation_0, values = (var_7396_cast_fp16, var_7638_cast_fp16))[name = tensor("op_7734_cast_fp16")]; + tensor var_7736_interleave_0 = const()[name = tensor("op_7736_interleave_0"), val = tensor(false)]; + tensor var_7736_cast_fp16 = concat(axis = var_6847, interleave = var_7736_interleave_0, values = (var_7640_cast_fp16, var_7642_cast_fp16, var_7644_cast_fp16, var_7646_cast_fp16))[name = tensor("op_7736_cast_fp16")]; + tensor var_7738_interleave_0 = const()[name = tensor("op_7738_interleave_0"), val = tensor(false)]; + tensor var_7738_cast_fp16 = concat(axis = var_6847, interleave = var_7738_interleave_0, values = (var_7648_cast_fp16, var_7650_cast_fp16, var_7652_cast_fp16, var_7654_cast_fp16))[name = tensor("op_7738_cast_fp16")]; + tensor var_7740_interleave_0 = const()[name = tensor("op_7740_interleave_0"), val = tensor(false)]; + tensor var_7740_cast_fp16 = concat(axis = var_6847, interleave = var_7740_interleave_0, values = (var_7656_cast_fp16, var_7658_cast_fp16, var_7660_cast_fp16, var_7662_cast_fp16))[name = tensor("op_7740_cast_fp16")]; + tensor var_7742_interleave_0 = const()[name = tensor("op_7742_interleave_0"), val = tensor(false)]; + tensor var_7742_cast_fp16 = concat(axis = var_6847, interleave = var_7742_interleave_0, values = (var_7664_cast_fp16, var_7666_cast_fp16, var_7668_cast_fp16, var_7670_cast_fp16))[name = tensor("op_7742_cast_fp16")]; + tensor var_7744_interleave_0 = const()[name = tensor("op_7744_interleave_0"), val = tensor(false)]; + tensor var_7744_cast_fp16 = concat(axis = var_6847, interleave = var_7744_interleave_0, values = (var_7672_cast_fp16, var_7674_cast_fp16, var_7676_cast_fp16, var_7678_cast_fp16))[name = tensor("op_7744_cast_fp16")]; + tensor var_7746_interleave_0 = const()[name = tensor("op_7746_interleave_0"), val = tensor(false)]; + tensor var_7746_cast_fp16 = concat(axis = var_6847, interleave = var_7746_interleave_0, values = (var_7680_cast_fp16, var_7682_cast_fp16, var_7684_cast_fp16, var_7686_cast_fp16))[name = tensor("op_7746_cast_fp16")]; + tensor var_7748_interleave_0 = const()[name = tensor("op_7748_interleave_0"), val = tensor(false)]; + tensor var_7748_cast_fp16 = concat(axis = var_6847, interleave = var_7748_interleave_0, values = (var_7688_cast_fp16, var_7690_cast_fp16, var_7692_cast_fp16, var_7694_cast_fp16))[name = tensor("op_7748_cast_fp16")]; + tensor var_7750_interleave_0 = const()[name = tensor("op_7750_interleave_0"), val = tensor(false)]; + tensor var_7750_cast_fp16 = concat(axis = var_6847, interleave = var_7750_interleave_0, values = (var_7696_cast_fp16, var_7698_cast_fp16, var_7700_cast_fp16, var_7702_cast_fp16))[name = tensor("op_7750_cast_fp16")]; + tensor var_7752_interleave_0 = const()[name = tensor("op_7752_interleave_0"), val = tensor(false)]; + tensor var_7752_cast_fp16 = concat(axis = var_6847, interleave = var_7752_interleave_0, values = (var_7704_cast_fp16, var_7706_cast_fp16, var_7708_cast_fp16, var_7710_cast_fp16))[name = tensor("op_7752_cast_fp16")]; + tensor var_7754_interleave_0 = const()[name = tensor("op_7754_interleave_0"), val = tensor(false)]; + tensor var_7754_cast_fp16 = concat(axis = var_6847, interleave = var_7754_interleave_0, values = (var_7712_cast_fp16, var_7714_cast_fp16, var_7716_cast_fp16, var_7718_cast_fp16))[name = tensor("op_7754_cast_fp16")]; + tensor var_7756_interleave_0 = const()[name = tensor("op_7756_interleave_0"), val = tensor(false)]; + tensor var_7756_cast_fp16 = concat(axis = var_6847, interleave = var_7756_interleave_0, values = (var_7720_cast_fp16, var_7722_cast_fp16, var_7724_cast_fp16, var_7726_cast_fp16))[name = tensor("op_7756_cast_fp16")]; + tensor var_7758_interleave_0 = const()[name = tensor("op_7758_interleave_0"), val = tensor(false)]; + tensor var_7758_cast_fp16 = concat(axis = var_6847, interleave = var_7758_interleave_0, values = (var_7728_cast_fp16, var_7730_cast_fp16, var_7732_cast_fp16, var_7734_cast_fp16))[name = tensor("op_7758_cast_fp16")]; + tensor input_57_interleave_0 = const()[name = tensor("input_57_interleave_0"), val = tensor(false)]; + tensor input_57_cast_fp16 = concat(axis = var_6864, interleave = input_57_interleave_0, values = (var_7736_cast_fp16, var_7738_cast_fp16, var_7740_cast_fp16, var_7742_cast_fp16, var_7744_cast_fp16, var_7746_cast_fp16, var_7748_cast_fp16, var_7750_cast_fp16, var_7752_cast_fp16, var_7754_cast_fp16, var_7756_cast_fp16, var_7758_cast_fp16))[name = tensor("input_57_cast_fp16")]; + tensor var_7763 = const()[name = tensor("op_7763"), val = tensor([1, 1])]; + tensor var_7765 = const()[name = tensor("op_7765"), val = tensor([1, 1])]; + tensor obj_31_pad_type_0 = const()[name = tensor("obj_31_pad_type_0"), val = tensor("custom")]; + tensor obj_31_pad_0 = const()[name = tensor("obj_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108989952)))]; + tensor layers_7_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110169664)))]; + tensor obj_31_cast_fp16 = conv(bias = layers_7_self_attn_o_proj_bias_to_fp16, dilations = var_7765, groups = var_6864, pad = obj_31_pad_0, pad_type = obj_31_pad_type_0, strides = var_7763, weight = layers_7_self_attn_o_proj_weight_to_fp16, x = input_57_cast_fp16)[name = tensor("obj_31_cast_fp16")]; + tensor inputs_31_cast_fp16 = add(x = inputs_29_cast_fp16, y = obj_31_cast_fp16)[name = tensor("inputs_31_cast_fp16")]; + tensor var_7771 = const()[name = tensor("op_7771"), val = tensor([1])]; + tensor channels_mean_31_cast_fp16 = reduce_mean(axes = var_7771, keep_dims = var_6865, x = inputs_31_cast_fp16)[name = tensor("channels_mean_31_cast_fp16")]; + tensor zero_mean_31_cast_fp16 = sub(x = inputs_31_cast_fp16, y = channels_mean_31_cast_fp16)[name = tensor("zero_mean_31_cast_fp16")]; + tensor zero_mean_sq_31_cast_fp16 = mul(x = zero_mean_31_cast_fp16, y = zero_mean_31_cast_fp16)[name = tensor("zero_mean_sq_31_cast_fp16")]; + tensor var_7775 = const()[name = tensor("op_7775"), val = tensor([1])]; + tensor var_7776_cast_fp16 = reduce_mean(axes = var_7775, keep_dims = var_6865, x = zero_mean_sq_31_cast_fp16)[name = tensor("op_7776_cast_fp16")]; + tensor var_7777_to_fp16 = const()[name = tensor("op_7777_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_7778_cast_fp16 = add(x = var_7776_cast_fp16, y = var_7777_to_fp16)[name = tensor("op_7778_cast_fp16")]; + tensor denom_31_epsilon_0_to_fp16 = const()[name = tensor("denom_31_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_31_cast_fp16 = rsqrt(epsilon = denom_31_epsilon_0_to_fp16, x = var_7778_cast_fp16)[name = tensor("denom_31_cast_fp16")]; + tensor out_31_cast_fp16 = mul(x = zero_mean_31_cast_fp16, y = denom_31_cast_fp16)[name = tensor("out_31_cast_fp16")]; + tensor input_59_gamma_0_to_fp16 = const()[name = tensor("input_59_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110171264)))]; + tensor input_59_beta_0_to_fp16 = const()[name = tensor("input_59_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110172864)))]; + tensor input_59_epsilon_0_to_fp16 = const()[name = tensor("input_59_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_59_cast_fp16 = batch_norm(beta = input_59_beta_0_to_fp16, epsilon = input_59_epsilon_0_to_fp16, gamma = input_59_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_31_cast_fp16)[name = tensor("input_59_cast_fp16")]; + tensor var_7789 = const()[name = tensor("op_7789"), val = tensor([1, 1])]; + tensor var_7791 = const()[name = tensor("op_7791"), val = tensor([1, 1])]; + tensor input_61_pad_type_0 = const()[name = tensor("input_61_pad_type_0"), val = tensor("custom")]; + tensor input_61_pad_0 = const()[name = tensor("input_61_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_fc1_weight_to_fp16 = const()[name = tensor("layers_7_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110174464)))]; + tensor layers_7_fc1_bias_to_fp16 = const()[name = tensor("layers_7_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114893120)))]; + tensor input_61_cast_fp16 = conv(bias = layers_7_fc1_bias_to_fp16, dilations = var_7791, groups = var_6864, pad = input_61_pad_0, pad_type = input_61_pad_type_0, strides = var_7789, weight = layers_7_fc1_weight_to_fp16, x = input_59_cast_fp16)[name = tensor("input_61_cast_fp16")]; + tensor input_63_mode_0 = const()[name = tensor("input_63_mode_0"), val = tensor("EXACT")]; + tensor input_63_cast_fp16 = gelu(mode = input_63_mode_0, x = input_61_cast_fp16)[name = tensor("input_63_cast_fp16")]; + tensor var_7797 = const()[name = tensor("op_7797"), val = tensor([1, 1])]; + tensor var_7799 = const()[name = tensor("op_7799"), val = tensor([1, 1])]; + tensor hidden_states_19_pad_type_0 = const()[name = tensor("hidden_states_19_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_19_pad_0 = const()[name = tensor("hidden_states_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_fc2_weight_to_fp16 = const()[name = tensor("layers_7_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114899328)))]; + tensor layers_7_fc2_bias_to_fp16 = const()[name = tensor("layers_7_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119617984)))]; + tensor hidden_states_19_cast_fp16 = conv(bias = layers_7_fc2_bias_to_fp16, dilations = var_7799, groups = var_6864, pad = hidden_states_19_pad_0, pad_type = hidden_states_19_pad_type_0, strides = var_7797, weight = layers_7_fc2_weight_to_fp16, x = input_63_cast_fp16)[name = tensor("hidden_states_19_cast_fp16")]; + tensor inputs_33_cast_fp16 = add(x = inputs_31_cast_fp16, y = hidden_states_19_cast_fp16)[name = tensor("inputs_33_cast_fp16")]; + tensor var_7806 = const()[name = tensor("op_7806"), val = tensor(3)]; + tensor var_7823 = const()[name = tensor("op_7823"), val = tensor(1)]; + tensor var_7824 = const()[name = tensor("op_7824"), val = tensor(true)]; + tensor var_7834 = const()[name = tensor("op_7834"), val = tensor([1])]; + tensor channels_mean_33_cast_fp16 = reduce_mean(axes = var_7834, keep_dims = var_7824, x = inputs_33_cast_fp16)[name = tensor("channels_mean_33_cast_fp16")]; + tensor zero_mean_33_cast_fp16 = sub(x = inputs_33_cast_fp16, y = channels_mean_33_cast_fp16)[name = tensor("zero_mean_33_cast_fp16")]; + tensor zero_mean_sq_33_cast_fp16 = mul(x = zero_mean_33_cast_fp16, y = zero_mean_33_cast_fp16)[name = tensor("zero_mean_sq_33_cast_fp16")]; + tensor var_7838 = const()[name = tensor("op_7838"), val = tensor([1])]; + tensor var_7839_cast_fp16 = reduce_mean(axes = var_7838, keep_dims = var_7824, x = zero_mean_sq_33_cast_fp16)[name = tensor("op_7839_cast_fp16")]; + tensor var_7840_to_fp16 = const()[name = tensor("op_7840_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_7841_cast_fp16 = add(x = var_7839_cast_fp16, y = var_7840_to_fp16)[name = tensor("op_7841_cast_fp16")]; + tensor denom_33_epsilon_0_to_fp16 = const()[name = tensor("denom_33_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_33_cast_fp16 = rsqrt(epsilon = denom_33_epsilon_0_to_fp16, x = var_7841_cast_fp16)[name = tensor("denom_33_cast_fp16")]; + tensor out_33_cast_fp16 = mul(x = zero_mean_33_cast_fp16, y = denom_33_cast_fp16)[name = tensor("out_33_cast_fp16")]; + tensor obj_33_gamma_0_to_fp16 = const()[name = tensor("obj_33_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119619584)))]; + tensor obj_33_beta_0_to_fp16 = const()[name = tensor("obj_33_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119621184)))]; + tensor obj_33_epsilon_0_to_fp16 = const()[name = tensor("obj_33_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_33_cast_fp16 = batch_norm(beta = obj_33_beta_0_to_fp16, epsilon = obj_33_epsilon_0_to_fp16, gamma = obj_33_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_33_cast_fp16)[name = tensor("obj_33_cast_fp16")]; + tensor var_7856 = const()[name = tensor("op_7856"), val = tensor([1, 1])]; + tensor var_7858 = const()[name = tensor("op_7858"), val = tensor([1, 1])]; + tensor query_17_pad_type_0 = const()[name = tensor("query_17_pad_type_0"), val = tensor("custom")]; + tensor query_17_pad_0 = const()[name = tensor("query_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119622784)))]; + tensor layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120802496)))]; + tensor query_17_cast_fp16 = conv(bias = layers_8_self_attn_q_proj_bias_to_fp16, dilations = var_7858, groups = var_7823, pad = query_17_pad_0, pad_type = query_17_pad_type_0, strides = var_7856, weight = layers_8_self_attn_q_proj_weight_to_fp16, x = obj_33_cast_fp16)[name = tensor("query_17_cast_fp16")]; + tensor var_7862 = const()[name = tensor("op_7862"), val = tensor([1, 1])]; + tensor var_7864 = const()[name = tensor("op_7864"), val = tensor([1, 1])]; + tensor key_17_pad_type_0 = const()[name = tensor("key_17_pad_type_0"), val = tensor("custom")]; + tensor key_17_pad_0 = const()[name = tensor("key_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120804096)))]; + tensor key_17_cast_fp16 = conv(dilations = var_7864, groups = var_7823, pad = key_17_pad_0, pad_type = key_17_pad_type_0, strides = var_7862, weight = layers_8_self_attn_k_proj_weight_to_fp16, x = obj_33_cast_fp16)[name = tensor("key_17_cast_fp16")]; + tensor var_7869 = const()[name = tensor("op_7869"), val = tensor([1, 1])]; + tensor var_7871 = const()[name = tensor("op_7871"), val = tensor([1, 1])]; + tensor value_17_pad_type_0 = const()[name = tensor("value_17_pad_type_0"), val = tensor("custom")]; + tensor value_17_pad_0 = const()[name = tensor("value_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121983808)))]; + tensor layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123163520)))]; + tensor value_17_cast_fp16 = conv(bias = layers_8_self_attn_v_proj_bias_to_fp16, dilations = var_7871, groups = var_7823, pad = value_17_pad_0, pad_type = value_17_pad_type_0, strides = var_7869, weight = layers_8_self_attn_v_proj_weight_to_fp16, x = obj_33_cast_fp16)[name = tensor("value_17_cast_fp16")]; + tensor var_7878_begin_0 = const()[name = tensor("op_7878_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7878_end_0 = const()[name = tensor("op_7878_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7878_end_mask_0 = const()[name = tensor("op_7878_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7878_cast_fp16 = slice_by_index(begin = var_7878_begin_0, end = var_7878_end_0, end_mask = var_7878_end_mask_0, x = query_17_cast_fp16)[name = tensor("op_7878_cast_fp16")]; + tensor var_7882_begin_0 = const()[name = tensor("op_7882_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_7882_end_0 = const()[name = tensor("op_7882_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_7882_end_mask_0 = const()[name = tensor("op_7882_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7882_cast_fp16 = slice_by_index(begin = var_7882_begin_0, end = var_7882_end_0, end_mask = var_7882_end_mask_0, x = query_17_cast_fp16)[name = tensor("op_7882_cast_fp16")]; + tensor var_7886_begin_0 = const()[name = tensor("op_7886_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_7886_end_0 = const()[name = tensor("op_7886_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_7886_end_mask_0 = const()[name = tensor("op_7886_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7886_cast_fp16 = slice_by_index(begin = var_7886_begin_0, end = var_7886_end_0, end_mask = var_7886_end_mask_0, x = query_17_cast_fp16)[name = tensor("op_7886_cast_fp16")]; + tensor var_7890_begin_0 = const()[name = tensor("op_7890_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_7890_end_0 = const()[name = tensor("op_7890_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_7890_end_mask_0 = const()[name = tensor("op_7890_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7890_cast_fp16 = slice_by_index(begin = var_7890_begin_0, end = var_7890_end_0, end_mask = var_7890_end_mask_0, x = query_17_cast_fp16)[name = tensor("op_7890_cast_fp16")]; + tensor var_7894_begin_0 = const()[name = tensor("op_7894_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_7894_end_0 = const()[name = tensor("op_7894_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_7894_end_mask_0 = const()[name = tensor("op_7894_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7894_cast_fp16 = slice_by_index(begin = var_7894_begin_0, end = var_7894_end_0, end_mask = var_7894_end_mask_0, x = query_17_cast_fp16)[name = tensor("op_7894_cast_fp16")]; + tensor var_7898_begin_0 = const()[name = tensor("op_7898_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_7898_end_0 = const()[name = tensor("op_7898_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_7898_end_mask_0 = const()[name = tensor("op_7898_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7898_cast_fp16 = slice_by_index(begin = var_7898_begin_0, end = var_7898_end_0, end_mask = var_7898_end_mask_0, x = query_17_cast_fp16)[name = tensor("op_7898_cast_fp16")]; + tensor var_7902_begin_0 = const()[name = tensor("op_7902_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_7902_end_0 = const()[name = tensor("op_7902_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_7902_end_mask_0 = const()[name = tensor("op_7902_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7902_cast_fp16 = slice_by_index(begin = var_7902_begin_0, end = var_7902_end_0, end_mask = var_7902_end_mask_0, x = query_17_cast_fp16)[name = tensor("op_7902_cast_fp16")]; + tensor var_7906_begin_0 = const()[name = tensor("op_7906_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_7906_end_0 = const()[name = tensor("op_7906_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_7906_end_mask_0 = const()[name = tensor("op_7906_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7906_cast_fp16 = slice_by_index(begin = var_7906_begin_0, end = var_7906_end_0, end_mask = var_7906_end_mask_0, x = query_17_cast_fp16)[name = tensor("op_7906_cast_fp16")]; + tensor var_7910_begin_0 = const()[name = tensor("op_7910_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_7910_end_0 = const()[name = tensor("op_7910_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_7910_end_mask_0 = const()[name = tensor("op_7910_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7910_cast_fp16 = slice_by_index(begin = var_7910_begin_0, end = var_7910_end_0, end_mask = var_7910_end_mask_0, x = query_17_cast_fp16)[name = tensor("op_7910_cast_fp16")]; + tensor var_7914_begin_0 = const()[name = tensor("op_7914_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_7914_end_0 = const()[name = tensor("op_7914_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_7914_end_mask_0 = const()[name = tensor("op_7914_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7914_cast_fp16 = slice_by_index(begin = var_7914_begin_0, end = var_7914_end_0, end_mask = var_7914_end_mask_0, x = query_17_cast_fp16)[name = tensor("op_7914_cast_fp16")]; + tensor var_7918_begin_0 = const()[name = tensor("op_7918_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_7918_end_0 = const()[name = tensor("op_7918_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_7918_end_mask_0 = const()[name = tensor("op_7918_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7918_cast_fp16 = slice_by_index(begin = var_7918_begin_0, end = var_7918_end_0, end_mask = var_7918_end_mask_0, x = query_17_cast_fp16)[name = tensor("op_7918_cast_fp16")]; + tensor var_7922_begin_0 = const()[name = tensor("op_7922_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_7922_end_0 = const()[name = tensor("op_7922_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_7922_end_mask_0 = const()[name = tensor("op_7922_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_7922_cast_fp16 = slice_by_index(begin = var_7922_begin_0, end = var_7922_end_0, end_mask = var_7922_end_mask_0, x = query_17_cast_fp16)[name = tensor("op_7922_cast_fp16")]; + tensor var_7931_begin_0 = const()[name = tensor("op_7931_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7931_end_0 = const()[name = tensor("op_7931_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_7931_end_mask_0 = const()[name = tensor("op_7931_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7931_cast_fp16 = slice_by_index(begin = var_7931_begin_0, end = var_7931_end_0, end_mask = var_7931_end_mask_0, x = var_7878_cast_fp16)[name = tensor("op_7931_cast_fp16")]; + tensor var_7938_begin_0 = const()[name = tensor("op_7938_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_7938_end_0 = const()[name = tensor("op_7938_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_7938_end_mask_0 = const()[name = tensor("op_7938_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7938_cast_fp16 = slice_by_index(begin = var_7938_begin_0, end = var_7938_end_0, end_mask = var_7938_end_mask_0, x = var_7878_cast_fp16)[name = tensor("op_7938_cast_fp16")]; + tensor var_7945_begin_0 = const()[name = tensor("op_7945_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_7945_end_0 = const()[name = tensor("op_7945_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_7945_end_mask_0 = const()[name = tensor("op_7945_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7945_cast_fp16 = slice_by_index(begin = var_7945_begin_0, end = var_7945_end_0, end_mask = var_7945_end_mask_0, x = var_7878_cast_fp16)[name = tensor("op_7945_cast_fp16")]; + tensor var_7952_begin_0 = const()[name = tensor("op_7952_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_7952_end_0 = const()[name = tensor("op_7952_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7952_end_mask_0 = const()[name = tensor("op_7952_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7952_cast_fp16 = slice_by_index(begin = var_7952_begin_0, end = var_7952_end_0, end_mask = var_7952_end_mask_0, x = var_7878_cast_fp16)[name = tensor("op_7952_cast_fp16")]; + tensor var_7959_begin_0 = const()[name = tensor("op_7959_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7959_end_0 = const()[name = tensor("op_7959_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_7959_end_mask_0 = const()[name = tensor("op_7959_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7959_cast_fp16 = slice_by_index(begin = var_7959_begin_0, end = var_7959_end_0, end_mask = var_7959_end_mask_0, x = var_7882_cast_fp16)[name = tensor("op_7959_cast_fp16")]; + tensor var_7966_begin_0 = const()[name = tensor("op_7966_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_7966_end_0 = const()[name = tensor("op_7966_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_7966_end_mask_0 = const()[name = tensor("op_7966_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7966_cast_fp16 = slice_by_index(begin = var_7966_begin_0, end = var_7966_end_0, end_mask = var_7966_end_mask_0, x = var_7882_cast_fp16)[name = tensor("op_7966_cast_fp16")]; + tensor var_7973_begin_0 = const()[name = tensor("op_7973_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_7973_end_0 = const()[name = tensor("op_7973_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_7973_end_mask_0 = const()[name = tensor("op_7973_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7973_cast_fp16 = slice_by_index(begin = var_7973_begin_0, end = var_7973_end_0, end_mask = var_7973_end_mask_0, x = var_7882_cast_fp16)[name = tensor("op_7973_cast_fp16")]; + tensor var_7980_begin_0 = const()[name = tensor("op_7980_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_7980_end_0 = const()[name = tensor("op_7980_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_7980_end_mask_0 = const()[name = tensor("op_7980_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7980_cast_fp16 = slice_by_index(begin = var_7980_begin_0, end = var_7980_end_0, end_mask = var_7980_end_mask_0, x = var_7882_cast_fp16)[name = tensor("op_7980_cast_fp16")]; + tensor var_7987_begin_0 = const()[name = tensor("op_7987_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_7987_end_0 = const()[name = tensor("op_7987_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_7987_end_mask_0 = const()[name = tensor("op_7987_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7987_cast_fp16 = slice_by_index(begin = var_7987_begin_0, end = var_7987_end_0, end_mask = var_7987_end_mask_0, x = var_7886_cast_fp16)[name = tensor("op_7987_cast_fp16")]; + tensor var_7994_begin_0 = const()[name = tensor("op_7994_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_7994_end_0 = const()[name = tensor("op_7994_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_7994_end_mask_0 = const()[name = tensor("op_7994_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_7994_cast_fp16 = slice_by_index(begin = var_7994_begin_0, end = var_7994_end_0, end_mask = var_7994_end_mask_0, x = var_7886_cast_fp16)[name = tensor("op_7994_cast_fp16")]; + tensor var_8001_begin_0 = const()[name = tensor("op_8001_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_8001_end_0 = const()[name = tensor("op_8001_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_8001_end_mask_0 = const()[name = tensor("op_8001_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8001_cast_fp16 = slice_by_index(begin = var_8001_begin_0, end = var_8001_end_0, end_mask = var_8001_end_mask_0, x = var_7886_cast_fp16)[name = tensor("op_8001_cast_fp16")]; + tensor var_8008_begin_0 = const()[name = tensor("op_8008_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_8008_end_0 = const()[name = tensor("op_8008_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8008_end_mask_0 = const()[name = tensor("op_8008_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8008_cast_fp16 = slice_by_index(begin = var_8008_begin_0, end = var_8008_end_0, end_mask = var_8008_end_mask_0, x = var_7886_cast_fp16)[name = tensor("op_8008_cast_fp16")]; + tensor var_8015_begin_0 = const()[name = tensor("op_8015_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8015_end_0 = const()[name = tensor("op_8015_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_8015_end_mask_0 = const()[name = tensor("op_8015_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8015_cast_fp16 = slice_by_index(begin = var_8015_begin_0, end = var_8015_end_0, end_mask = var_8015_end_mask_0, x = var_7890_cast_fp16)[name = tensor("op_8015_cast_fp16")]; + tensor var_8022_begin_0 = const()[name = tensor("op_8022_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_8022_end_0 = const()[name = tensor("op_8022_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_8022_end_mask_0 = const()[name = tensor("op_8022_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8022_cast_fp16 = slice_by_index(begin = var_8022_begin_0, end = var_8022_end_0, end_mask = var_8022_end_mask_0, x = var_7890_cast_fp16)[name = tensor("op_8022_cast_fp16")]; + tensor var_8029_begin_0 = const()[name = tensor("op_8029_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_8029_end_0 = const()[name = tensor("op_8029_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_8029_end_mask_0 = const()[name = tensor("op_8029_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8029_cast_fp16 = slice_by_index(begin = var_8029_begin_0, end = var_8029_end_0, end_mask = var_8029_end_mask_0, x = var_7890_cast_fp16)[name = tensor("op_8029_cast_fp16")]; + tensor var_8036_begin_0 = const()[name = tensor("op_8036_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_8036_end_0 = const()[name = tensor("op_8036_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8036_end_mask_0 = const()[name = tensor("op_8036_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8036_cast_fp16 = slice_by_index(begin = var_8036_begin_0, end = var_8036_end_0, end_mask = var_8036_end_mask_0, x = var_7890_cast_fp16)[name = tensor("op_8036_cast_fp16")]; + tensor var_8043_begin_0 = const()[name = tensor("op_8043_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8043_end_0 = const()[name = tensor("op_8043_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_8043_end_mask_0 = const()[name = tensor("op_8043_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8043_cast_fp16 = slice_by_index(begin = var_8043_begin_0, end = var_8043_end_0, end_mask = var_8043_end_mask_0, x = var_7894_cast_fp16)[name = tensor("op_8043_cast_fp16")]; + tensor var_8050_begin_0 = const()[name = tensor("op_8050_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_8050_end_0 = const()[name = tensor("op_8050_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_8050_end_mask_0 = const()[name = tensor("op_8050_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8050_cast_fp16 = slice_by_index(begin = var_8050_begin_0, end = var_8050_end_0, end_mask = var_8050_end_mask_0, x = var_7894_cast_fp16)[name = tensor("op_8050_cast_fp16")]; + tensor var_8057_begin_0 = const()[name = tensor("op_8057_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_8057_end_0 = const()[name = tensor("op_8057_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_8057_end_mask_0 = const()[name = tensor("op_8057_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8057_cast_fp16 = slice_by_index(begin = var_8057_begin_0, end = var_8057_end_0, end_mask = var_8057_end_mask_0, x = var_7894_cast_fp16)[name = tensor("op_8057_cast_fp16")]; + tensor var_8064_begin_0 = const()[name = tensor("op_8064_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_8064_end_0 = const()[name = tensor("op_8064_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8064_end_mask_0 = const()[name = tensor("op_8064_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8064_cast_fp16 = slice_by_index(begin = var_8064_begin_0, end = var_8064_end_0, end_mask = var_8064_end_mask_0, x = var_7894_cast_fp16)[name = tensor("op_8064_cast_fp16")]; + tensor var_8071_begin_0 = const()[name = tensor("op_8071_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8071_end_0 = const()[name = tensor("op_8071_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_8071_end_mask_0 = const()[name = tensor("op_8071_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8071_cast_fp16 = slice_by_index(begin = var_8071_begin_0, end = var_8071_end_0, end_mask = var_8071_end_mask_0, x = var_7898_cast_fp16)[name = tensor("op_8071_cast_fp16")]; + tensor var_8078_begin_0 = const()[name = tensor("op_8078_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_8078_end_0 = const()[name = tensor("op_8078_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_8078_end_mask_0 = const()[name = tensor("op_8078_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8078_cast_fp16 = slice_by_index(begin = var_8078_begin_0, end = var_8078_end_0, end_mask = var_8078_end_mask_0, x = var_7898_cast_fp16)[name = tensor("op_8078_cast_fp16")]; + tensor var_8085_begin_0 = const()[name = tensor("op_8085_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_8085_end_0 = const()[name = tensor("op_8085_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_8085_end_mask_0 = const()[name = tensor("op_8085_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8085_cast_fp16 = slice_by_index(begin = var_8085_begin_0, end = var_8085_end_0, end_mask = var_8085_end_mask_0, x = var_7898_cast_fp16)[name = tensor("op_8085_cast_fp16")]; + tensor var_8092_begin_0 = const()[name = tensor("op_8092_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_8092_end_0 = const()[name = tensor("op_8092_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8092_end_mask_0 = const()[name = tensor("op_8092_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8092_cast_fp16 = slice_by_index(begin = var_8092_begin_0, end = var_8092_end_0, end_mask = var_8092_end_mask_0, x = var_7898_cast_fp16)[name = tensor("op_8092_cast_fp16")]; + tensor var_8099_begin_0 = const()[name = tensor("op_8099_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8099_end_0 = const()[name = tensor("op_8099_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_8099_end_mask_0 = const()[name = tensor("op_8099_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8099_cast_fp16 = slice_by_index(begin = var_8099_begin_0, end = var_8099_end_0, end_mask = var_8099_end_mask_0, x = var_7902_cast_fp16)[name = tensor("op_8099_cast_fp16")]; + tensor var_8106_begin_0 = const()[name = tensor("op_8106_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_8106_end_0 = const()[name = tensor("op_8106_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_8106_end_mask_0 = const()[name = tensor("op_8106_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8106_cast_fp16 = slice_by_index(begin = var_8106_begin_0, end = var_8106_end_0, end_mask = var_8106_end_mask_0, x = var_7902_cast_fp16)[name = tensor("op_8106_cast_fp16")]; + tensor var_8113_begin_0 = const()[name = tensor("op_8113_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_8113_end_0 = const()[name = tensor("op_8113_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_8113_end_mask_0 = const()[name = tensor("op_8113_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8113_cast_fp16 = slice_by_index(begin = var_8113_begin_0, end = var_8113_end_0, end_mask = var_8113_end_mask_0, x = var_7902_cast_fp16)[name = tensor("op_8113_cast_fp16")]; + tensor var_8120_begin_0 = const()[name = tensor("op_8120_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_8120_end_0 = const()[name = tensor("op_8120_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8120_end_mask_0 = const()[name = tensor("op_8120_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8120_cast_fp16 = slice_by_index(begin = var_8120_begin_0, end = var_8120_end_0, end_mask = var_8120_end_mask_0, x = var_7902_cast_fp16)[name = tensor("op_8120_cast_fp16")]; + tensor var_8127_begin_0 = const()[name = tensor("op_8127_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8127_end_0 = const()[name = tensor("op_8127_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_8127_end_mask_0 = const()[name = tensor("op_8127_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8127_cast_fp16 = slice_by_index(begin = var_8127_begin_0, end = var_8127_end_0, end_mask = var_8127_end_mask_0, x = var_7906_cast_fp16)[name = tensor("op_8127_cast_fp16")]; + tensor var_8134_begin_0 = const()[name = tensor("op_8134_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_8134_end_0 = const()[name = tensor("op_8134_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_8134_end_mask_0 = const()[name = tensor("op_8134_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8134_cast_fp16 = slice_by_index(begin = var_8134_begin_0, end = var_8134_end_0, end_mask = var_8134_end_mask_0, x = var_7906_cast_fp16)[name = tensor("op_8134_cast_fp16")]; + tensor var_8141_begin_0 = const()[name = tensor("op_8141_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_8141_end_0 = const()[name = tensor("op_8141_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_8141_end_mask_0 = const()[name = tensor("op_8141_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8141_cast_fp16 = slice_by_index(begin = var_8141_begin_0, end = var_8141_end_0, end_mask = var_8141_end_mask_0, x = var_7906_cast_fp16)[name = tensor("op_8141_cast_fp16")]; + tensor var_8148_begin_0 = const()[name = tensor("op_8148_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_8148_end_0 = const()[name = tensor("op_8148_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8148_end_mask_0 = const()[name = tensor("op_8148_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8148_cast_fp16 = slice_by_index(begin = var_8148_begin_0, end = var_8148_end_0, end_mask = var_8148_end_mask_0, x = var_7906_cast_fp16)[name = tensor("op_8148_cast_fp16")]; + tensor var_8155_begin_0 = const()[name = tensor("op_8155_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8155_end_0 = const()[name = tensor("op_8155_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_8155_end_mask_0 = const()[name = tensor("op_8155_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8155_cast_fp16 = slice_by_index(begin = var_8155_begin_0, end = var_8155_end_0, end_mask = var_8155_end_mask_0, x = var_7910_cast_fp16)[name = tensor("op_8155_cast_fp16")]; + tensor var_8162_begin_0 = const()[name = tensor("op_8162_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_8162_end_0 = const()[name = tensor("op_8162_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_8162_end_mask_0 = const()[name = tensor("op_8162_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8162_cast_fp16 = slice_by_index(begin = var_8162_begin_0, end = var_8162_end_0, end_mask = var_8162_end_mask_0, x = var_7910_cast_fp16)[name = tensor("op_8162_cast_fp16")]; + tensor var_8169_begin_0 = const()[name = tensor("op_8169_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_8169_end_0 = const()[name = tensor("op_8169_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_8169_end_mask_0 = const()[name = tensor("op_8169_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8169_cast_fp16 = slice_by_index(begin = var_8169_begin_0, end = var_8169_end_0, end_mask = var_8169_end_mask_0, x = var_7910_cast_fp16)[name = tensor("op_8169_cast_fp16")]; + tensor var_8176_begin_0 = const()[name = tensor("op_8176_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_8176_end_0 = const()[name = tensor("op_8176_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8176_end_mask_0 = const()[name = tensor("op_8176_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8176_cast_fp16 = slice_by_index(begin = var_8176_begin_0, end = var_8176_end_0, end_mask = var_8176_end_mask_0, x = var_7910_cast_fp16)[name = tensor("op_8176_cast_fp16")]; + tensor var_8183_begin_0 = const()[name = tensor("op_8183_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8183_end_0 = const()[name = tensor("op_8183_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_8183_end_mask_0 = const()[name = tensor("op_8183_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8183_cast_fp16 = slice_by_index(begin = var_8183_begin_0, end = var_8183_end_0, end_mask = var_8183_end_mask_0, x = var_7914_cast_fp16)[name = tensor("op_8183_cast_fp16")]; + tensor var_8190_begin_0 = const()[name = tensor("op_8190_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_8190_end_0 = const()[name = tensor("op_8190_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_8190_end_mask_0 = const()[name = tensor("op_8190_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8190_cast_fp16 = slice_by_index(begin = var_8190_begin_0, end = var_8190_end_0, end_mask = var_8190_end_mask_0, x = var_7914_cast_fp16)[name = tensor("op_8190_cast_fp16")]; + tensor var_8197_begin_0 = const()[name = tensor("op_8197_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_8197_end_0 = const()[name = tensor("op_8197_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_8197_end_mask_0 = const()[name = tensor("op_8197_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8197_cast_fp16 = slice_by_index(begin = var_8197_begin_0, end = var_8197_end_0, end_mask = var_8197_end_mask_0, x = var_7914_cast_fp16)[name = tensor("op_8197_cast_fp16")]; + tensor var_8204_begin_0 = const()[name = tensor("op_8204_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_8204_end_0 = const()[name = tensor("op_8204_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8204_end_mask_0 = const()[name = tensor("op_8204_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8204_cast_fp16 = slice_by_index(begin = var_8204_begin_0, end = var_8204_end_0, end_mask = var_8204_end_mask_0, x = var_7914_cast_fp16)[name = tensor("op_8204_cast_fp16")]; + tensor var_8211_begin_0 = const()[name = tensor("op_8211_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8211_end_0 = const()[name = tensor("op_8211_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_8211_end_mask_0 = const()[name = tensor("op_8211_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8211_cast_fp16 = slice_by_index(begin = var_8211_begin_0, end = var_8211_end_0, end_mask = var_8211_end_mask_0, x = var_7918_cast_fp16)[name = tensor("op_8211_cast_fp16")]; + tensor var_8218_begin_0 = const()[name = tensor("op_8218_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_8218_end_0 = const()[name = tensor("op_8218_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_8218_end_mask_0 = const()[name = tensor("op_8218_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8218_cast_fp16 = slice_by_index(begin = var_8218_begin_0, end = var_8218_end_0, end_mask = var_8218_end_mask_0, x = var_7918_cast_fp16)[name = tensor("op_8218_cast_fp16")]; + tensor var_8225_begin_0 = const()[name = tensor("op_8225_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_8225_end_0 = const()[name = tensor("op_8225_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_8225_end_mask_0 = const()[name = tensor("op_8225_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8225_cast_fp16 = slice_by_index(begin = var_8225_begin_0, end = var_8225_end_0, end_mask = var_8225_end_mask_0, x = var_7918_cast_fp16)[name = tensor("op_8225_cast_fp16")]; + tensor var_8232_begin_0 = const()[name = tensor("op_8232_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_8232_end_0 = const()[name = tensor("op_8232_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8232_end_mask_0 = const()[name = tensor("op_8232_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8232_cast_fp16 = slice_by_index(begin = var_8232_begin_0, end = var_8232_end_0, end_mask = var_8232_end_mask_0, x = var_7918_cast_fp16)[name = tensor("op_8232_cast_fp16")]; + tensor var_8239_begin_0 = const()[name = tensor("op_8239_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8239_end_0 = const()[name = tensor("op_8239_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_8239_end_mask_0 = const()[name = tensor("op_8239_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8239_cast_fp16 = slice_by_index(begin = var_8239_begin_0, end = var_8239_end_0, end_mask = var_8239_end_mask_0, x = var_7922_cast_fp16)[name = tensor("op_8239_cast_fp16")]; + tensor var_8246_begin_0 = const()[name = tensor("op_8246_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_8246_end_0 = const()[name = tensor("op_8246_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_8246_end_mask_0 = const()[name = tensor("op_8246_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8246_cast_fp16 = slice_by_index(begin = var_8246_begin_0, end = var_8246_end_0, end_mask = var_8246_end_mask_0, x = var_7922_cast_fp16)[name = tensor("op_8246_cast_fp16")]; + tensor var_8253_begin_0 = const()[name = tensor("op_8253_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_8253_end_0 = const()[name = tensor("op_8253_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_8253_end_mask_0 = const()[name = tensor("op_8253_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8253_cast_fp16 = slice_by_index(begin = var_8253_begin_0, end = var_8253_end_0, end_mask = var_8253_end_mask_0, x = var_7922_cast_fp16)[name = tensor("op_8253_cast_fp16")]; + tensor var_8260_begin_0 = const()[name = tensor("op_8260_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_8260_end_0 = const()[name = tensor("op_8260_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8260_end_mask_0 = const()[name = tensor("op_8260_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8260_cast_fp16 = slice_by_index(begin = var_8260_begin_0, end = var_8260_end_0, end_mask = var_8260_end_mask_0, x = var_7922_cast_fp16)[name = tensor("op_8260_cast_fp16")]; + tensor k_17_perm_0 = const()[name = tensor("k_17_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_8265_begin_0 = const()[name = tensor("op_8265_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8265_end_0 = const()[name = tensor("op_8265_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_8265_end_mask_0 = const()[name = tensor("op_8265_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_3 = transpose(perm = k_17_perm_0, x = key_17_cast_fp16)[name = tensor("transpose_3")]; + tensor var_8265_cast_fp16 = slice_by_index(begin = var_8265_begin_0, end = var_8265_end_0, end_mask = var_8265_end_mask_0, x = transpose_3)[name = tensor("op_8265_cast_fp16")]; + tensor var_8269_begin_0 = const()[name = tensor("op_8269_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_8269_end_0 = const()[name = tensor("op_8269_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_8269_end_mask_0 = const()[name = tensor("op_8269_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8269_cast_fp16 = slice_by_index(begin = var_8269_begin_0, end = var_8269_end_0, end_mask = var_8269_end_mask_0, x = transpose_3)[name = tensor("op_8269_cast_fp16")]; + tensor var_8273_begin_0 = const()[name = tensor("op_8273_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_8273_end_0 = const()[name = tensor("op_8273_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_8273_end_mask_0 = const()[name = tensor("op_8273_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8273_cast_fp16 = slice_by_index(begin = var_8273_begin_0, end = var_8273_end_0, end_mask = var_8273_end_mask_0, x = transpose_3)[name = tensor("op_8273_cast_fp16")]; + tensor var_8277_begin_0 = const()[name = tensor("op_8277_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_8277_end_0 = const()[name = tensor("op_8277_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_8277_end_mask_0 = const()[name = tensor("op_8277_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8277_cast_fp16 = slice_by_index(begin = var_8277_begin_0, end = var_8277_end_0, end_mask = var_8277_end_mask_0, x = transpose_3)[name = tensor("op_8277_cast_fp16")]; + tensor var_8281_begin_0 = const()[name = tensor("op_8281_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_8281_end_0 = const()[name = tensor("op_8281_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_8281_end_mask_0 = const()[name = tensor("op_8281_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8281_cast_fp16 = slice_by_index(begin = var_8281_begin_0, end = var_8281_end_0, end_mask = var_8281_end_mask_0, x = transpose_3)[name = tensor("op_8281_cast_fp16")]; + tensor var_8285_begin_0 = const()[name = tensor("op_8285_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_8285_end_0 = const()[name = tensor("op_8285_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_8285_end_mask_0 = const()[name = tensor("op_8285_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8285_cast_fp16 = slice_by_index(begin = var_8285_begin_0, end = var_8285_end_0, end_mask = var_8285_end_mask_0, x = transpose_3)[name = tensor("op_8285_cast_fp16")]; + tensor var_8289_begin_0 = const()[name = tensor("op_8289_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_8289_end_0 = const()[name = tensor("op_8289_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_8289_end_mask_0 = const()[name = tensor("op_8289_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8289_cast_fp16 = slice_by_index(begin = var_8289_begin_0, end = var_8289_end_0, end_mask = var_8289_end_mask_0, x = transpose_3)[name = tensor("op_8289_cast_fp16")]; + tensor var_8293_begin_0 = const()[name = tensor("op_8293_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_8293_end_0 = const()[name = tensor("op_8293_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_8293_end_mask_0 = const()[name = tensor("op_8293_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8293_cast_fp16 = slice_by_index(begin = var_8293_begin_0, end = var_8293_end_0, end_mask = var_8293_end_mask_0, x = transpose_3)[name = tensor("op_8293_cast_fp16")]; + tensor var_8297_begin_0 = const()[name = tensor("op_8297_begin_0"), val = tensor([0, 0, 0, 512])]; + tensor var_8297_end_0 = const()[name = tensor("op_8297_end_0"), val = tensor([1, 1500, 1, 576])]; + tensor var_8297_end_mask_0 = const()[name = tensor("op_8297_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8297_cast_fp16 = slice_by_index(begin = var_8297_begin_0, end = var_8297_end_0, end_mask = var_8297_end_mask_0, x = transpose_3)[name = tensor("op_8297_cast_fp16")]; + tensor var_8301_begin_0 = const()[name = tensor("op_8301_begin_0"), val = tensor([0, 0, 0, 576])]; + tensor var_8301_end_0 = const()[name = tensor("op_8301_end_0"), val = tensor([1, 1500, 1, 640])]; + tensor var_8301_end_mask_0 = const()[name = tensor("op_8301_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8301_cast_fp16 = slice_by_index(begin = var_8301_begin_0, end = var_8301_end_0, end_mask = var_8301_end_mask_0, x = transpose_3)[name = tensor("op_8301_cast_fp16")]; + tensor var_8305_begin_0 = const()[name = tensor("op_8305_begin_0"), val = tensor([0, 0, 0, 640])]; + tensor var_8305_end_0 = const()[name = tensor("op_8305_end_0"), val = tensor([1, 1500, 1, 704])]; + tensor var_8305_end_mask_0 = const()[name = tensor("op_8305_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8305_cast_fp16 = slice_by_index(begin = var_8305_begin_0, end = var_8305_end_0, end_mask = var_8305_end_mask_0, x = transpose_3)[name = tensor("op_8305_cast_fp16")]; + tensor var_8309_begin_0 = const()[name = tensor("op_8309_begin_0"), val = tensor([0, 0, 0, 704])]; + tensor var_8309_end_0 = const()[name = tensor("op_8309_end_0"), val = tensor([1, 1500, 1, 768])]; + tensor var_8309_end_mask_0 = const()[name = tensor("op_8309_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8309_cast_fp16 = slice_by_index(begin = var_8309_begin_0, end = var_8309_end_0, end_mask = var_8309_end_mask_0, x = transpose_3)[name = tensor("op_8309_cast_fp16")]; + tensor var_8311_begin_0 = const()[name = tensor("op_8311_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8311_end_0 = const()[name = tensor("op_8311_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8311_end_mask_0 = const()[name = tensor("op_8311_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8311_cast_fp16 = slice_by_index(begin = var_8311_begin_0, end = var_8311_end_0, end_mask = var_8311_end_mask_0, x = value_17_cast_fp16)[name = tensor("op_8311_cast_fp16")]; + tensor var_8315_begin_0 = const()[name = tensor("op_8315_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_8315_end_0 = const()[name = tensor("op_8315_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_8315_end_mask_0 = const()[name = tensor("op_8315_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8315_cast_fp16 = slice_by_index(begin = var_8315_begin_0, end = var_8315_end_0, end_mask = var_8315_end_mask_0, x = value_17_cast_fp16)[name = tensor("op_8315_cast_fp16")]; + tensor var_8319_begin_0 = const()[name = tensor("op_8319_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_8319_end_0 = const()[name = tensor("op_8319_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_8319_end_mask_0 = const()[name = tensor("op_8319_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8319_cast_fp16 = slice_by_index(begin = var_8319_begin_0, end = var_8319_end_0, end_mask = var_8319_end_mask_0, x = value_17_cast_fp16)[name = tensor("op_8319_cast_fp16")]; + tensor var_8323_begin_0 = const()[name = tensor("op_8323_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_8323_end_0 = const()[name = tensor("op_8323_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_8323_end_mask_0 = const()[name = tensor("op_8323_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8323_cast_fp16 = slice_by_index(begin = var_8323_begin_0, end = var_8323_end_0, end_mask = var_8323_end_mask_0, x = value_17_cast_fp16)[name = tensor("op_8323_cast_fp16")]; + tensor var_8327_begin_0 = const()[name = tensor("op_8327_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_8327_end_0 = const()[name = tensor("op_8327_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_8327_end_mask_0 = const()[name = tensor("op_8327_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8327_cast_fp16 = slice_by_index(begin = var_8327_begin_0, end = var_8327_end_0, end_mask = var_8327_end_mask_0, x = value_17_cast_fp16)[name = tensor("op_8327_cast_fp16")]; + tensor var_8331_begin_0 = const()[name = tensor("op_8331_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_8331_end_0 = const()[name = tensor("op_8331_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_8331_end_mask_0 = const()[name = tensor("op_8331_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8331_cast_fp16 = slice_by_index(begin = var_8331_begin_0, end = var_8331_end_0, end_mask = var_8331_end_mask_0, x = value_17_cast_fp16)[name = tensor("op_8331_cast_fp16")]; + tensor var_8335_begin_0 = const()[name = tensor("op_8335_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_8335_end_0 = const()[name = tensor("op_8335_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_8335_end_mask_0 = const()[name = tensor("op_8335_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8335_cast_fp16 = slice_by_index(begin = var_8335_begin_0, end = var_8335_end_0, end_mask = var_8335_end_mask_0, x = value_17_cast_fp16)[name = tensor("op_8335_cast_fp16")]; + tensor var_8339_begin_0 = const()[name = tensor("op_8339_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_8339_end_0 = const()[name = tensor("op_8339_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_8339_end_mask_0 = const()[name = tensor("op_8339_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8339_cast_fp16 = slice_by_index(begin = var_8339_begin_0, end = var_8339_end_0, end_mask = var_8339_end_mask_0, x = value_17_cast_fp16)[name = tensor("op_8339_cast_fp16")]; + tensor var_8343_begin_0 = const()[name = tensor("op_8343_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_8343_end_0 = const()[name = tensor("op_8343_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_8343_end_mask_0 = const()[name = tensor("op_8343_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8343_cast_fp16 = slice_by_index(begin = var_8343_begin_0, end = var_8343_end_0, end_mask = var_8343_end_mask_0, x = value_17_cast_fp16)[name = tensor("op_8343_cast_fp16")]; + tensor var_8347_begin_0 = const()[name = tensor("op_8347_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_8347_end_0 = const()[name = tensor("op_8347_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_8347_end_mask_0 = const()[name = tensor("op_8347_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8347_cast_fp16 = slice_by_index(begin = var_8347_begin_0, end = var_8347_end_0, end_mask = var_8347_end_mask_0, x = value_17_cast_fp16)[name = tensor("op_8347_cast_fp16")]; + tensor var_8351_begin_0 = const()[name = tensor("op_8351_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_8351_end_0 = const()[name = tensor("op_8351_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_8351_end_mask_0 = const()[name = tensor("op_8351_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8351_cast_fp16 = slice_by_index(begin = var_8351_begin_0, end = var_8351_end_0, end_mask = var_8351_end_mask_0, x = value_17_cast_fp16)[name = tensor("op_8351_cast_fp16")]; + tensor var_8355_begin_0 = const()[name = tensor("op_8355_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_8355_end_0 = const()[name = tensor("op_8355_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_8355_end_mask_0 = const()[name = tensor("op_8355_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8355_cast_fp16 = slice_by_index(begin = var_8355_begin_0, end = var_8355_end_0, end_mask = var_8355_end_mask_0, x = value_17_cast_fp16)[name = tensor("op_8355_cast_fp16")]; + tensor var_8359_equation_0 = const()[name = tensor("op_8359_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8359_cast_fp16 = einsum(equation = var_8359_equation_0, values = (var_8265_cast_fp16, var_7931_cast_fp16))[name = tensor("op_8359_cast_fp16")]; + tensor var_8360_to_fp16 = const()[name = tensor("op_8360_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_769_cast_fp16 = mul(x = var_8359_cast_fp16, y = var_8360_to_fp16)[name = tensor("aw_chunk_769_cast_fp16")]; + tensor var_8363_equation_0 = const()[name = tensor("op_8363_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8363_cast_fp16 = einsum(equation = var_8363_equation_0, values = (var_8265_cast_fp16, var_7938_cast_fp16))[name = tensor("op_8363_cast_fp16")]; + tensor var_8364_to_fp16 = const()[name = tensor("op_8364_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_771_cast_fp16 = mul(x = var_8363_cast_fp16, y = var_8364_to_fp16)[name = tensor("aw_chunk_771_cast_fp16")]; + tensor var_8367_equation_0 = const()[name = tensor("op_8367_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8367_cast_fp16 = einsum(equation = var_8367_equation_0, values = (var_8265_cast_fp16, var_7945_cast_fp16))[name = tensor("op_8367_cast_fp16")]; + tensor var_8368_to_fp16 = const()[name = tensor("op_8368_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_773_cast_fp16 = mul(x = var_8367_cast_fp16, y = var_8368_to_fp16)[name = tensor("aw_chunk_773_cast_fp16")]; + tensor var_8371_equation_0 = const()[name = tensor("op_8371_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8371_cast_fp16 = einsum(equation = var_8371_equation_0, values = (var_8265_cast_fp16, var_7952_cast_fp16))[name = tensor("op_8371_cast_fp16")]; + tensor var_8372_to_fp16 = const()[name = tensor("op_8372_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_775_cast_fp16 = mul(x = var_8371_cast_fp16, y = var_8372_to_fp16)[name = tensor("aw_chunk_775_cast_fp16")]; + tensor var_8375_equation_0 = const()[name = tensor("op_8375_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8375_cast_fp16 = einsum(equation = var_8375_equation_0, values = (var_8269_cast_fp16, var_7959_cast_fp16))[name = tensor("op_8375_cast_fp16")]; + tensor var_8376_to_fp16 = const()[name = tensor("op_8376_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_777_cast_fp16 = mul(x = var_8375_cast_fp16, y = var_8376_to_fp16)[name = tensor("aw_chunk_777_cast_fp16")]; + tensor var_8379_equation_0 = const()[name = tensor("op_8379_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8379_cast_fp16 = einsum(equation = var_8379_equation_0, values = (var_8269_cast_fp16, var_7966_cast_fp16))[name = tensor("op_8379_cast_fp16")]; + tensor var_8380_to_fp16 = const()[name = tensor("op_8380_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_779_cast_fp16 = mul(x = var_8379_cast_fp16, y = var_8380_to_fp16)[name = tensor("aw_chunk_779_cast_fp16")]; + tensor var_8383_equation_0 = const()[name = tensor("op_8383_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8383_cast_fp16 = einsum(equation = var_8383_equation_0, values = (var_8269_cast_fp16, var_7973_cast_fp16))[name = tensor("op_8383_cast_fp16")]; + tensor var_8384_to_fp16 = const()[name = tensor("op_8384_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_781_cast_fp16 = mul(x = var_8383_cast_fp16, y = var_8384_to_fp16)[name = tensor("aw_chunk_781_cast_fp16")]; + tensor var_8387_equation_0 = const()[name = tensor("op_8387_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8387_cast_fp16 = einsum(equation = var_8387_equation_0, values = (var_8269_cast_fp16, var_7980_cast_fp16))[name = tensor("op_8387_cast_fp16")]; + tensor var_8388_to_fp16 = const()[name = tensor("op_8388_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_783_cast_fp16 = mul(x = var_8387_cast_fp16, y = var_8388_to_fp16)[name = tensor("aw_chunk_783_cast_fp16")]; + tensor var_8391_equation_0 = const()[name = tensor("op_8391_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8391_cast_fp16 = einsum(equation = var_8391_equation_0, values = (var_8273_cast_fp16, var_7987_cast_fp16))[name = tensor("op_8391_cast_fp16")]; + tensor var_8392_to_fp16 = const()[name = tensor("op_8392_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_785_cast_fp16 = mul(x = var_8391_cast_fp16, y = var_8392_to_fp16)[name = tensor("aw_chunk_785_cast_fp16")]; + tensor var_8395_equation_0 = const()[name = tensor("op_8395_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8395_cast_fp16 = einsum(equation = var_8395_equation_0, values = (var_8273_cast_fp16, var_7994_cast_fp16))[name = tensor("op_8395_cast_fp16")]; + tensor var_8396_to_fp16 = const()[name = tensor("op_8396_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_787_cast_fp16 = mul(x = var_8395_cast_fp16, y = var_8396_to_fp16)[name = tensor("aw_chunk_787_cast_fp16")]; + tensor var_8399_equation_0 = const()[name = tensor("op_8399_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8399_cast_fp16 = einsum(equation = var_8399_equation_0, values = (var_8273_cast_fp16, var_8001_cast_fp16))[name = tensor("op_8399_cast_fp16")]; + tensor var_8400_to_fp16 = const()[name = tensor("op_8400_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_789_cast_fp16 = mul(x = var_8399_cast_fp16, y = var_8400_to_fp16)[name = tensor("aw_chunk_789_cast_fp16")]; + tensor var_8403_equation_0 = const()[name = tensor("op_8403_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8403_cast_fp16 = einsum(equation = var_8403_equation_0, values = (var_8273_cast_fp16, var_8008_cast_fp16))[name = tensor("op_8403_cast_fp16")]; + tensor var_8404_to_fp16 = const()[name = tensor("op_8404_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_791_cast_fp16 = mul(x = var_8403_cast_fp16, y = var_8404_to_fp16)[name = tensor("aw_chunk_791_cast_fp16")]; + tensor var_8407_equation_0 = const()[name = tensor("op_8407_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8407_cast_fp16 = einsum(equation = var_8407_equation_0, values = (var_8277_cast_fp16, var_8015_cast_fp16))[name = tensor("op_8407_cast_fp16")]; + tensor var_8408_to_fp16 = const()[name = tensor("op_8408_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_793_cast_fp16 = mul(x = var_8407_cast_fp16, y = var_8408_to_fp16)[name = tensor("aw_chunk_793_cast_fp16")]; + tensor var_8411_equation_0 = const()[name = tensor("op_8411_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8411_cast_fp16 = einsum(equation = var_8411_equation_0, values = (var_8277_cast_fp16, var_8022_cast_fp16))[name = tensor("op_8411_cast_fp16")]; + tensor var_8412_to_fp16 = const()[name = tensor("op_8412_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_795_cast_fp16 = mul(x = var_8411_cast_fp16, y = var_8412_to_fp16)[name = tensor("aw_chunk_795_cast_fp16")]; + tensor var_8415_equation_0 = const()[name = tensor("op_8415_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8415_cast_fp16 = einsum(equation = var_8415_equation_0, values = (var_8277_cast_fp16, var_8029_cast_fp16))[name = tensor("op_8415_cast_fp16")]; + tensor var_8416_to_fp16 = const()[name = tensor("op_8416_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_797_cast_fp16 = mul(x = var_8415_cast_fp16, y = var_8416_to_fp16)[name = tensor("aw_chunk_797_cast_fp16")]; + tensor var_8419_equation_0 = const()[name = tensor("op_8419_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8419_cast_fp16 = einsum(equation = var_8419_equation_0, values = (var_8277_cast_fp16, var_8036_cast_fp16))[name = tensor("op_8419_cast_fp16")]; + tensor var_8420_to_fp16 = const()[name = tensor("op_8420_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_799_cast_fp16 = mul(x = var_8419_cast_fp16, y = var_8420_to_fp16)[name = tensor("aw_chunk_799_cast_fp16")]; + tensor var_8423_equation_0 = const()[name = tensor("op_8423_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8423_cast_fp16 = einsum(equation = var_8423_equation_0, values = (var_8281_cast_fp16, var_8043_cast_fp16))[name = tensor("op_8423_cast_fp16")]; + tensor var_8424_to_fp16 = const()[name = tensor("op_8424_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_801_cast_fp16 = mul(x = var_8423_cast_fp16, y = var_8424_to_fp16)[name = tensor("aw_chunk_801_cast_fp16")]; + tensor var_8427_equation_0 = const()[name = tensor("op_8427_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8427_cast_fp16 = einsum(equation = var_8427_equation_0, values = (var_8281_cast_fp16, var_8050_cast_fp16))[name = tensor("op_8427_cast_fp16")]; + tensor var_8428_to_fp16 = const()[name = tensor("op_8428_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_803_cast_fp16 = mul(x = var_8427_cast_fp16, y = var_8428_to_fp16)[name = tensor("aw_chunk_803_cast_fp16")]; + tensor var_8431_equation_0 = const()[name = tensor("op_8431_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8431_cast_fp16 = einsum(equation = var_8431_equation_0, values = (var_8281_cast_fp16, var_8057_cast_fp16))[name = tensor("op_8431_cast_fp16")]; + tensor var_8432_to_fp16 = const()[name = tensor("op_8432_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_805_cast_fp16 = mul(x = var_8431_cast_fp16, y = var_8432_to_fp16)[name = tensor("aw_chunk_805_cast_fp16")]; + tensor var_8435_equation_0 = const()[name = tensor("op_8435_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8435_cast_fp16 = einsum(equation = var_8435_equation_0, values = (var_8281_cast_fp16, var_8064_cast_fp16))[name = tensor("op_8435_cast_fp16")]; + tensor var_8436_to_fp16 = const()[name = tensor("op_8436_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_807_cast_fp16 = mul(x = var_8435_cast_fp16, y = var_8436_to_fp16)[name = tensor("aw_chunk_807_cast_fp16")]; + tensor var_8439_equation_0 = const()[name = tensor("op_8439_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8439_cast_fp16 = einsum(equation = var_8439_equation_0, values = (var_8285_cast_fp16, var_8071_cast_fp16))[name = tensor("op_8439_cast_fp16")]; + tensor var_8440_to_fp16 = const()[name = tensor("op_8440_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_809_cast_fp16 = mul(x = var_8439_cast_fp16, y = var_8440_to_fp16)[name = tensor("aw_chunk_809_cast_fp16")]; + tensor var_8443_equation_0 = const()[name = tensor("op_8443_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8443_cast_fp16 = einsum(equation = var_8443_equation_0, values = (var_8285_cast_fp16, var_8078_cast_fp16))[name = tensor("op_8443_cast_fp16")]; + tensor var_8444_to_fp16 = const()[name = tensor("op_8444_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_811_cast_fp16 = mul(x = var_8443_cast_fp16, y = var_8444_to_fp16)[name = tensor("aw_chunk_811_cast_fp16")]; + tensor var_8447_equation_0 = const()[name = tensor("op_8447_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8447_cast_fp16 = einsum(equation = var_8447_equation_0, values = (var_8285_cast_fp16, var_8085_cast_fp16))[name = tensor("op_8447_cast_fp16")]; + tensor var_8448_to_fp16 = const()[name = tensor("op_8448_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_813_cast_fp16 = mul(x = var_8447_cast_fp16, y = var_8448_to_fp16)[name = tensor("aw_chunk_813_cast_fp16")]; + tensor var_8451_equation_0 = const()[name = tensor("op_8451_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8451_cast_fp16 = einsum(equation = var_8451_equation_0, values = (var_8285_cast_fp16, var_8092_cast_fp16))[name = tensor("op_8451_cast_fp16")]; + tensor var_8452_to_fp16 = const()[name = tensor("op_8452_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_815_cast_fp16 = mul(x = var_8451_cast_fp16, y = var_8452_to_fp16)[name = tensor("aw_chunk_815_cast_fp16")]; + tensor var_8455_equation_0 = const()[name = tensor("op_8455_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8455_cast_fp16 = einsum(equation = var_8455_equation_0, values = (var_8289_cast_fp16, var_8099_cast_fp16))[name = tensor("op_8455_cast_fp16")]; + tensor var_8456_to_fp16 = const()[name = tensor("op_8456_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_817_cast_fp16 = mul(x = var_8455_cast_fp16, y = var_8456_to_fp16)[name = tensor("aw_chunk_817_cast_fp16")]; + tensor var_8459_equation_0 = const()[name = tensor("op_8459_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8459_cast_fp16 = einsum(equation = var_8459_equation_0, values = (var_8289_cast_fp16, var_8106_cast_fp16))[name = tensor("op_8459_cast_fp16")]; + tensor var_8460_to_fp16 = const()[name = tensor("op_8460_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_819_cast_fp16 = mul(x = var_8459_cast_fp16, y = var_8460_to_fp16)[name = tensor("aw_chunk_819_cast_fp16")]; + tensor var_8463_equation_0 = const()[name = tensor("op_8463_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8463_cast_fp16 = einsum(equation = var_8463_equation_0, values = (var_8289_cast_fp16, var_8113_cast_fp16))[name = tensor("op_8463_cast_fp16")]; + tensor var_8464_to_fp16 = const()[name = tensor("op_8464_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_821_cast_fp16 = mul(x = var_8463_cast_fp16, y = var_8464_to_fp16)[name = tensor("aw_chunk_821_cast_fp16")]; + tensor var_8467_equation_0 = const()[name = tensor("op_8467_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8467_cast_fp16 = einsum(equation = var_8467_equation_0, values = (var_8289_cast_fp16, var_8120_cast_fp16))[name = tensor("op_8467_cast_fp16")]; + tensor var_8468_to_fp16 = const()[name = tensor("op_8468_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_823_cast_fp16 = mul(x = var_8467_cast_fp16, y = var_8468_to_fp16)[name = tensor("aw_chunk_823_cast_fp16")]; + tensor var_8471_equation_0 = const()[name = tensor("op_8471_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8471_cast_fp16 = einsum(equation = var_8471_equation_0, values = (var_8293_cast_fp16, var_8127_cast_fp16))[name = tensor("op_8471_cast_fp16")]; + tensor var_8472_to_fp16 = const()[name = tensor("op_8472_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_825_cast_fp16 = mul(x = var_8471_cast_fp16, y = var_8472_to_fp16)[name = tensor("aw_chunk_825_cast_fp16")]; + tensor var_8475_equation_0 = const()[name = tensor("op_8475_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8475_cast_fp16 = einsum(equation = var_8475_equation_0, values = (var_8293_cast_fp16, var_8134_cast_fp16))[name = tensor("op_8475_cast_fp16")]; + tensor var_8476_to_fp16 = const()[name = tensor("op_8476_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_827_cast_fp16 = mul(x = var_8475_cast_fp16, y = var_8476_to_fp16)[name = tensor("aw_chunk_827_cast_fp16")]; + tensor var_8479_equation_0 = const()[name = tensor("op_8479_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8479_cast_fp16 = einsum(equation = var_8479_equation_0, values = (var_8293_cast_fp16, var_8141_cast_fp16))[name = tensor("op_8479_cast_fp16")]; + tensor var_8480_to_fp16 = const()[name = tensor("op_8480_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_829_cast_fp16 = mul(x = var_8479_cast_fp16, y = var_8480_to_fp16)[name = tensor("aw_chunk_829_cast_fp16")]; + tensor var_8483_equation_0 = const()[name = tensor("op_8483_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8483_cast_fp16 = einsum(equation = var_8483_equation_0, values = (var_8293_cast_fp16, var_8148_cast_fp16))[name = tensor("op_8483_cast_fp16")]; + tensor var_8484_to_fp16 = const()[name = tensor("op_8484_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_831_cast_fp16 = mul(x = var_8483_cast_fp16, y = var_8484_to_fp16)[name = tensor("aw_chunk_831_cast_fp16")]; + tensor var_8487_equation_0 = const()[name = tensor("op_8487_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8487_cast_fp16 = einsum(equation = var_8487_equation_0, values = (var_8297_cast_fp16, var_8155_cast_fp16))[name = tensor("op_8487_cast_fp16")]; + tensor var_8488_to_fp16 = const()[name = tensor("op_8488_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_833_cast_fp16 = mul(x = var_8487_cast_fp16, y = var_8488_to_fp16)[name = tensor("aw_chunk_833_cast_fp16")]; + tensor var_8491_equation_0 = const()[name = tensor("op_8491_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8491_cast_fp16 = einsum(equation = var_8491_equation_0, values = (var_8297_cast_fp16, var_8162_cast_fp16))[name = tensor("op_8491_cast_fp16")]; + tensor var_8492_to_fp16 = const()[name = tensor("op_8492_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_835_cast_fp16 = mul(x = var_8491_cast_fp16, y = var_8492_to_fp16)[name = tensor("aw_chunk_835_cast_fp16")]; + tensor var_8495_equation_0 = const()[name = tensor("op_8495_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8495_cast_fp16 = einsum(equation = var_8495_equation_0, values = (var_8297_cast_fp16, var_8169_cast_fp16))[name = tensor("op_8495_cast_fp16")]; + tensor var_8496_to_fp16 = const()[name = tensor("op_8496_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_837_cast_fp16 = mul(x = var_8495_cast_fp16, y = var_8496_to_fp16)[name = tensor("aw_chunk_837_cast_fp16")]; + tensor var_8499_equation_0 = const()[name = tensor("op_8499_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8499_cast_fp16 = einsum(equation = var_8499_equation_0, values = (var_8297_cast_fp16, var_8176_cast_fp16))[name = tensor("op_8499_cast_fp16")]; + tensor var_8500_to_fp16 = const()[name = tensor("op_8500_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_839_cast_fp16 = mul(x = var_8499_cast_fp16, y = var_8500_to_fp16)[name = tensor("aw_chunk_839_cast_fp16")]; + tensor var_8503_equation_0 = const()[name = tensor("op_8503_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8503_cast_fp16 = einsum(equation = var_8503_equation_0, values = (var_8301_cast_fp16, var_8183_cast_fp16))[name = tensor("op_8503_cast_fp16")]; + tensor var_8504_to_fp16 = const()[name = tensor("op_8504_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_841_cast_fp16 = mul(x = var_8503_cast_fp16, y = var_8504_to_fp16)[name = tensor("aw_chunk_841_cast_fp16")]; + tensor var_8507_equation_0 = const()[name = tensor("op_8507_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8507_cast_fp16 = einsum(equation = var_8507_equation_0, values = (var_8301_cast_fp16, var_8190_cast_fp16))[name = tensor("op_8507_cast_fp16")]; + tensor var_8508_to_fp16 = const()[name = tensor("op_8508_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_843_cast_fp16 = mul(x = var_8507_cast_fp16, y = var_8508_to_fp16)[name = tensor("aw_chunk_843_cast_fp16")]; + tensor var_8511_equation_0 = const()[name = tensor("op_8511_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8511_cast_fp16 = einsum(equation = var_8511_equation_0, values = (var_8301_cast_fp16, var_8197_cast_fp16))[name = tensor("op_8511_cast_fp16")]; + tensor var_8512_to_fp16 = const()[name = tensor("op_8512_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_845_cast_fp16 = mul(x = var_8511_cast_fp16, y = var_8512_to_fp16)[name = tensor("aw_chunk_845_cast_fp16")]; + tensor var_8515_equation_0 = const()[name = tensor("op_8515_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8515_cast_fp16 = einsum(equation = var_8515_equation_0, values = (var_8301_cast_fp16, var_8204_cast_fp16))[name = tensor("op_8515_cast_fp16")]; + tensor var_8516_to_fp16 = const()[name = tensor("op_8516_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_847_cast_fp16 = mul(x = var_8515_cast_fp16, y = var_8516_to_fp16)[name = tensor("aw_chunk_847_cast_fp16")]; + tensor var_8519_equation_0 = const()[name = tensor("op_8519_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8519_cast_fp16 = einsum(equation = var_8519_equation_0, values = (var_8305_cast_fp16, var_8211_cast_fp16))[name = tensor("op_8519_cast_fp16")]; + tensor var_8520_to_fp16 = const()[name = tensor("op_8520_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_849_cast_fp16 = mul(x = var_8519_cast_fp16, y = var_8520_to_fp16)[name = tensor("aw_chunk_849_cast_fp16")]; + tensor var_8523_equation_0 = const()[name = tensor("op_8523_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8523_cast_fp16 = einsum(equation = var_8523_equation_0, values = (var_8305_cast_fp16, var_8218_cast_fp16))[name = tensor("op_8523_cast_fp16")]; + tensor var_8524_to_fp16 = const()[name = tensor("op_8524_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_851_cast_fp16 = mul(x = var_8523_cast_fp16, y = var_8524_to_fp16)[name = tensor("aw_chunk_851_cast_fp16")]; + tensor var_8527_equation_0 = const()[name = tensor("op_8527_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8527_cast_fp16 = einsum(equation = var_8527_equation_0, values = (var_8305_cast_fp16, var_8225_cast_fp16))[name = tensor("op_8527_cast_fp16")]; + tensor var_8528_to_fp16 = const()[name = tensor("op_8528_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_853_cast_fp16 = mul(x = var_8527_cast_fp16, y = var_8528_to_fp16)[name = tensor("aw_chunk_853_cast_fp16")]; + tensor var_8531_equation_0 = const()[name = tensor("op_8531_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8531_cast_fp16 = einsum(equation = var_8531_equation_0, values = (var_8305_cast_fp16, var_8232_cast_fp16))[name = tensor("op_8531_cast_fp16")]; + tensor var_8532_to_fp16 = const()[name = tensor("op_8532_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_855_cast_fp16 = mul(x = var_8531_cast_fp16, y = var_8532_to_fp16)[name = tensor("aw_chunk_855_cast_fp16")]; + tensor var_8535_equation_0 = const()[name = tensor("op_8535_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8535_cast_fp16 = einsum(equation = var_8535_equation_0, values = (var_8309_cast_fp16, var_8239_cast_fp16))[name = tensor("op_8535_cast_fp16")]; + tensor var_8536_to_fp16 = const()[name = tensor("op_8536_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_857_cast_fp16 = mul(x = var_8535_cast_fp16, y = var_8536_to_fp16)[name = tensor("aw_chunk_857_cast_fp16")]; + tensor var_8539_equation_0 = const()[name = tensor("op_8539_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8539_cast_fp16 = einsum(equation = var_8539_equation_0, values = (var_8309_cast_fp16, var_8246_cast_fp16))[name = tensor("op_8539_cast_fp16")]; + tensor var_8540_to_fp16 = const()[name = tensor("op_8540_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_859_cast_fp16 = mul(x = var_8539_cast_fp16, y = var_8540_to_fp16)[name = tensor("aw_chunk_859_cast_fp16")]; + tensor var_8543_equation_0 = const()[name = tensor("op_8543_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8543_cast_fp16 = einsum(equation = var_8543_equation_0, values = (var_8309_cast_fp16, var_8253_cast_fp16))[name = tensor("op_8543_cast_fp16")]; + tensor var_8544_to_fp16 = const()[name = tensor("op_8544_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_861_cast_fp16 = mul(x = var_8543_cast_fp16, y = var_8544_to_fp16)[name = tensor("aw_chunk_861_cast_fp16")]; + tensor var_8547_equation_0 = const()[name = tensor("op_8547_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_8547_cast_fp16 = einsum(equation = var_8547_equation_0, values = (var_8309_cast_fp16, var_8260_cast_fp16))[name = tensor("op_8547_cast_fp16")]; + tensor var_8548_to_fp16 = const()[name = tensor("op_8548_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_863_cast_fp16 = mul(x = var_8547_cast_fp16, y = var_8548_to_fp16)[name = tensor("aw_chunk_863_cast_fp16")]; + tensor var_8550_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_769_cast_fp16)[name = tensor("op_8550_cast_fp16")]; + tensor var_8551_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_771_cast_fp16)[name = tensor("op_8551_cast_fp16")]; + tensor var_8552_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_773_cast_fp16)[name = tensor("op_8552_cast_fp16")]; + tensor var_8553_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_775_cast_fp16)[name = tensor("op_8553_cast_fp16")]; + tensor var_8554_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_777_cast_fp16)[name = tensor("op_8554_cast_fp16")]; + tensor var_8555_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_779_cast_fp16)[name = tensor("op_8555_cast_fp16")]; + tensor var_8556_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_781_cast_fp16)[name = tensor("op_8556_cast_fp16")]; + tensor var_8557_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_783_cast_fp16)[name = tensor("op_8557_cast_fp16")]; + tensor var_8558_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_785_cast_fp16)[name = tensor("op_8558_cast_fp16")]; + tensor var_8559_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_787_cast_fp16)[name = tensor("op_8559_cast_fp16")]; + tensor var_8560_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_789_cast_fp16)[name = tensor("op_8560_cast_fp16")]; + tensor var_8561_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_791_cast_fp16)[name = tensor("op_8561_cast_fp16")]; + tensor var_8562_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_793_cast_fp16)[name = tensor("op_8562_cast_fp16")]; + tensor var_8563_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_795_cast_fp16)[name = tensor("op_8563_cast_fp16")]; + tensor var_8564_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_797_cast_fp16)[name = tensor("op_8564_cast_fp16")]; + tensor var_8565_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_799_cast_fp16)[name = tensor("op_8565_cast_fp16")]; + tensor var_8566_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_801_cast_fp16)[name = tensor("op_8566_cast_fp16")]; + tensor var_8567_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_803_cast_fp16)[name = tensor("op_8567_cast_fp16")]; + tensor var_8568_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_805_cast_fp16)[name = tensor("op_8568_cast_fp16")]; + tensor var_8569_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_807_cast_fp16)[name = tensor("op_8569_cast_fp16")]; + tensor var_8570_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_809_cast_fp16)[name = tensor("op_8570_cast_fp16")]; + tensor var_8571_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_811_cast_fp16)[name = tensor("op_8571_cast_fp16")]; + tensor var_8572_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_813_cast_fp16)[name = tensor("op_8572_cast_fp16")]; + tensor var_8573_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_815_cast_fp16)[name = tensor("op_8573_cast_fp16")]; + tensor var_8574_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_817_cast_fp16)[name = tensor("op_8574_cast_fp16")]; + tensor var_8575_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_819_cast_fp16)[name = tensor("op_8575_cast_fp16")]; + tensor var_8576_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_821_cast_fp16)[name = tensor("op_8576_cast_fp16")]; + tensor var_8577_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_823_cast_fp16)[name = tensor("op_8577_cast_fp16")]; + tensor var_8578_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_825_cast_fp16)[name = tensor("op_8578_cast_fp16")]; + tensor var_8579_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_827_cast_fp16)[name = tensor("op_8579_cast_fp16")]; + tensor var_8580_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_829_cast_fp16)[name = tensor("op_8580_cast_fp16")]; + tensor var_8581_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_831_cast_fp16)[name = tensor("op_8581_cast_fp16")]; + tensor var_8582_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_833_cast_fp16)[name = tensor("op_8582_cast_fp16")]; + tensor var_8583_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_835_cast_fp16)[name = tensor("op_8583_cast_fp16")]; + tensor var_8584_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_837_cast_fp16)[name = tensor("op_8584_cast_fp16")]; + tensor var_8585_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_839_cast_fp16)[name = tensor("op_8585_cast_fp16")]; + tensor var_8586_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_841_cast_fp16)[name = tensor("op_8586_cast_fp16")]; + tensor var_8587_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_843_cast_fp16)[name = tensor("op_8587_cast_fp16")]; + tensor var_8588_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_845_cast_fp16)[name = tensor("op_8588_cast_fp16")]; + tensor var_8589_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_847_cast_fp16)[name = tensor("op_8589_cast_fp16")]; + tensor var_8590_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_849_cast_fp16)[name = tensor("op_8590_cast_fp16")]; + tensor var_8591_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_851_cast_fp16)[name = tensor("op_8591_cast_fp16")]; + tensor var_8592_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_853_cast_fp16)[name = tensor("op_8592_cast_fp16")]; + tensor var_8593_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_855_cast_fp16)[name = tensor("op_8593_cast_fp16")]; + tensor var_8594_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_857_cast_fp16)[name = tensor("op_8594_cast_fp16")]; + tensor var_8595_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_859_cast_fp16)[name = tensor("op_8595_cast_fp16")]; + tensor var_8596_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_861_cast_fp16)[name = tensor("op_8596_cast_fp16")]; + tensor var_8597_cast_fp16 = softmax(axis = var_7823, x = aw_chunk_863_cast_fp16)[name = tensor("op_8597_cast_fp16")]; + tensor var_8599_equation_0 = const()[name = tensor("op_8599_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8599_cast_fp16 = einsum(equation = var_8599_equation_0, values = (var_8311_cast_fp16, var_8550_cast_fp16))[name = tensor("op_8599_cast_fp16")]; + tensor var_8601_equation_0 = const()[name = tensor("op_8601_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8601_cast_fp16 = einsum(equation = var_8601_equation_0, values = (var_8311_cast_fp16, var_8551_cast_fp16))[name = tensor("op_8601_cast_fp16")]; + tensor var_8603_equation_0 = const()[name = tensor("op_8603_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8603_cast_fp16 = einsum(equation = var_8603_equation_0, values = (var_8311_cast_fp16, var_8552_cast_fp16))[name = tensor("op_8603_cast_fp16")]; + tensor var_8605_equation_0 = const()[name = tensor("op_8605_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8605_cast_fp16 = einsum(equation = var_8605_equation_0, values = (var_8311_cast_fp16, var_8553_cast_fp16))[name = tensor("op_8605_cast_fp16")]; + tensor var_8607_equation_0 = const()[name = tensor("op_8607_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8607_cast_fp16 = einsum(equation = var_8607_equation_0, values = (var_8315_cast_fp16, var_8554_cast_fp16))[name = tensor("op_8607_cast_fp16")]; + tensor var_8609_equation_0 = const()[name = tensor("op_8609_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8609_cast_fp16 = einsum(equation = var_8609_equation_0, values = (var_8315_cast_fp16, var_8555_cast_fp16))[name = tensor("op_8609_cast_fp16")]; + tensor var_8611_equation_0 = const()[name = tensor("op_8611_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8611_cast_fp16 = einsum(equation = var_8611_equation_0, values = (var_8315_cast_fp16, var_8556_cast_fp16))[name = tensor("op_8611_cast_fp16")]; + tensor var_8613_equation_0 = const()[name = tensor("op_8613_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8613_cast_fp16 = einsum(equation = var_8613_equation_0, values = (var_8315_cast_fp16, var_8557_cast_fp16))[name = tensor("op_8613_cast_fp16")]; + tensor var_8615_equation_0 = const()[name = tensor("op_8615_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8615_cast_fp16 = einsum(equation = var_8615_equation_0, values = (var_8319_cast_fp16, var_8558_cast_fp16))[name = tensor("op_8615_cast_fp16")]; + tensor var_8617_equation_0 = const()[name = tensor("op_8617_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8617_cast_fp16 = einsum(equation = var_8617_equation_0, values = (var_8319_cast_fp16, var_8559_cast_fp16))[name = tensor("op_8617_cast_fp16")]; + tensor var_8619_equation_0 = const()[name = tensor("op_8619_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8619_cast_fp16 = einsum(equation = var_8619_equation_0, values = (var_8319_cast_fp16, var_8560_cast_fp16))[name = tensor("op_8619_cast_fp16")]; + tensor var_8621_equation_0 = const()[name = tensor("op_8621_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8621_cast_fp16 = einsum(equation = var_8621_equation_0, values = (var_8319_cast_fp16, var_8561_cast_fp16))[name = tensor("op_8621_cast_fp16")]; + tensor var_8623_equation_0 = const()[name = tensor("op_8623_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8623_cast_fp16 = einsum(equation = var_8623_equation_0, values = (var_8323_cast_fp16, var_8562_cast_fp16))[name = tensor("op_8623_cast_fp16")]; + tensor var_8625_equation_0 = const()[name = tensor("op_8625_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8625_cast_fp16 = einsum(equation = var_8625_equation_0, values = (var_8323_cast_fp16, var_8563_cast_fp16))[name = tensor("op_8625_cast_fp16")]; + tensor var_8627_equation_0 = const()[name = tensor("op_8627_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8627_cast_fp16 = einsum(equation = var_8627_equation_0, values = (var_8323_cast_fp16, var_8564_cast_fp16))[name = tensor("op_8627_cast_fp16")]; + tensor var_8629_equation_0 = const()[name = tensor("op_8629_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8629_cast_fp16 = einsum(equation = var_8629_equation_0, values = (var_8323_cast_fp16, var_8565_cast_fp16))[name = tensor("op_8629_cast_fp16")]; + tensor var_8631_equation_0 = const()[name = tensor("op_8631_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8631_cast_fp16 = einsum(equation = var_8631_equation_0, values = (var_8327_cast_fp16, var_8566_cast_fp16))[name = tensor("op_8631_cast_fp16")]; + tensor var_8633_equation_0 = const()[name = tensor("op_8633_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8633_cast_fp16 = einsum(equation = var_8633_equation_0, values = (var_8327_cast_fp16, var_8567_cast_fp16))[name = tensor("op_8633_cast_fp16")]; + tensor var_8635_equation_0 = const()[name = tensor("op_8635_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8635_cast_fp16 = einsum(equation = var_8635_equation_0, values = (var_8327_cast_fp16, var_8568_cast_fp16))[name = tensor("op_8635_cast_fp16")]; + tensor var_8637_equation_0 = const()[name = tensor("op_8637_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8637_cast_fp16 = einsum(equation = var_8637_equation_0, values = (var_8327_cast_fp16, var_8569_cast_fp16))[name = tensor("op_8637_cast_fp16")]; + tensor var_8639_equation_0 = const()[name = tensor("op_8639_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8639_cast_fp16 = einsum(equation = var_8639_equation_0, values = (var_8331_cast_fp16, var_8570_cast_fp16))[name = tensor("op_8639_cast_fp16")]; + tensor var_8641_equation_0 = const()[name = tensor("op_8641_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8641_cast_fp16 = einsum(equation = var_8641_equation_0, values = (var_8331_cast_fp16, var_8571_cast_fp16))[name = tensor("op_8641_cast_fp16")]; + tensor var_8643_equation_0 = const()[name = tensor("op_8643_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8643_cast_fp16 = einsum(equation = var_8643_equation_0, values = (var_8331_cast_fp16, var_8572_cast_fp16))[name = tensor("op_8643_cast_fp16")]; + tensor var_8645_equation_0 = const()[name = tensor("op_8645_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8645_cast_fp16 = einsum(equation = var_8645_equation_0, values = (var_8331_cast_fp16, var_8573_cast_fp16))[name = tensor("op_8645_cast_fp16")]; + tensor var_8647_equation_0 = const()[name = tensor("op_8647_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8647_cast_fp16 = einsum(equation = var_8647_equation_0, values = (var_8335_cast_fp16, var_8574_cast_fp16))[name = tensor("op_8647_cast_fp16")]; + tensor var_8649_equation_0 = const()[name = tensor("op_8649_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8649_cast_fp16 = einsum(equation = var_8649_equation_0, values = (var_8335_cast_fp16, var_8575_cast_fp16))[name = tensor("op_8649_cast_fp16")]; + tensor var_8651_equation_0 = const()[name = tensor("op_8651_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8651_cast_fp16 = einsum(equation = var_8651_equation_0, values = (var_8335_cast_fp16, var_8576_cast_fp16))[name = tensor("op_8651_cast_fp16")]; + tensor var_8653_equation_0 = const()[name = tensor("op_8653_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8653_cast_fp16 = einsum(equation = var_8653_equation_0, values = (var_8335_cast_fp16, var_8577_cast_fp16))[name = tensor("op_8653_cast_fp16")]; + tensor var_8655_equation_0 = const()[name = tensor("op_8655_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8655_cast_fp16 = einsum(equation = var_8655_equation_0, values = (var_8339_cast_fp16, var_8578_cast_fp16))[name = tensor("op_8655_cast_fp16")]; + tensor var_8657_equation_0 = const()[name = tensor("op_8657_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8657_cast_fp16 = einsum(equation = var_8657_equation_0, values = (var_8339_cast_fp16, var_8579_cast_fp16))[name = tensor("op_8657_cast_fp16")]; + tensor var_8659_equation_0 = const()[name = tensor("op_8659_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8659_cast_fp16 = einsum(equation = var_8659_equation_0, values = (var_8339_cast_fp16, var_8580_cast_fp16))[name = tensor("op_8659_cast_fp16")]; + tensor var_8661_equation_0 = const()[name = tensor("op_8661_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8661_cast_fp16 = einsum(equation = var_8661_equation_0, values = (var_8339_cast_fp16, var_8581_cast_fp16))[name = tensor("op_8661_cast_fp16")]; + tensor var_8663_equation_0 = const()[name = tensor("op_8663_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8663_cast_fp16 = einsum(equation = var_8663_equation_0, values = (var_8343_cast_fp16, var_8582_cast_fp16))[name = tensor("op_8663_cast_fp16")]; + tensor var_8665_equation_0 = const()[name = tensor("op_8665_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8665_cast_fp16 = einsum(equation = var_8665_equation_0, values = (var_8343_cast_fp16, var_8583_cast_fp16))[name = tensor("op_8665_cast_fp16")]; + tensor var_8667_equation_0 = const()[name = tensor("op_8667_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8667_cast_fp16 = einsum(equation = var_8667_equation_0, values = (var_8343_cast_fp16, var_8584_cast_fp16))[name = tensor("op_8667_cast_fp16")]; + tensor var_8669_equation_0 = const()[name = tensor("op_8669_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8669_cast_fp16 = einsum(equation = var_8669_equation_0, values = (var_8343_cast_fp16, var_8585_cast_fp16))[name = tensor("op_8669_cast_fp16")]; + tensor var_8671_equation_0 = const()[name = tensor("op_8671_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8671_cast_fp16 = einsum(equation = var_8671_equation_0, values = (var_8347_cast_fp16, var_8586_cast_fp16))[name = tensor("op_8671_cast_fp16")]; + tensor var_8673_equation_0 = const()[name = tensor("op_8673_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8673_cast_fp16 = einsum(equation = var_8673_equation_0, values = (var_8347_cast_fp16, var_8587_cast_fp16))[name = tensor("op_8673_cast_fp16")]; + tensor var_8675_equation_0 = const()[name = tensor("op_8675_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8675_cast_fp16 = einsum(equation = var_8675_equation_0, values = (var_8347_cast_fp16, var_8588_cast_fp16))[name = tensor("op_8675_cast_fp16")]; + tensor var_8677_equation_0 = const()[name = tensor("op_8677_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8677_cast_fp16 = einsum(equation = var_8677_equation_0, values = (var_8347_cast_fp16, var_8589_cast_fp16))[name = tensor("op_8677_cast_fp16")]; + tensor var_8679_equation_0 = const()[name = tensor("op_8679_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8679_cast_fp16 = einsum(equation = var_8679_equation_0, values = (var_8351_cast_fp16, var_8590_cast_fp16))[name = tensor("op_8679_cast_fp16")]; + tensor var_8681_equation_0 = const()[name = tensor("op_8681_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8681_cast_fp16 = einsum(equation = var_8681_equation_0, values = (var_8351_cast_fp16, var_8591_cast_fp16))[name = tensor("op_8681_cast_fp16")]; + tensor var_8683_equation_0 = const()[name = tensor("op_8683_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8683_cast_fp16 = einsum(equation = var_8683_equation_0, values = (var_8351_cast_fp16, var_8592_cast_fp16))[name = tensor("op_8683_cast_fp16")]; + tensor var_8685_equation_0 = const()[name = tensor("op_8685_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8685_cast_fp16 = einsum(equation = var_8685_equation_0, values = (var_8351_cast_fp16, var_8593_cast_fp16))[name = tensor("op_8685_cast_fp16")]; + tensor var_8687_equation_0 = const()[name = tensor("op_8687_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8687_cast_fp16 = einsum(equation = var_8687_equation_0, values = (var_8355_cast_fp16, var_8594_cast_fp16))[name = tensor("op_8687_cast_fp16")]; + tensor var_8689_equation_0 = const()[name = tensor("op_8689_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8689_cast_fp16 = einsum(equation = var_8689_equation_0, values = (var_8355_cast_fp16, var_8595_cast_fp16))[name = tensor("op_8689_cast_fp16")]; + tensor var_8691_equation_0 = const()[name = tensor("op_8691_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8691_cast_fp16 = einsum(equation = var_8691_equation_0, values = (var_8355_cast_fp16, var_8596_cast_fp16))[name = tensor("op_8691_cast_fp16")]; + tensor var_8693_equation_0 = const()[name = tensor("op_8693_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_8693_cast_fp16 = einsum(equation = var_8693_equation_0, values = (var_8355_cast_fp16, var_8597_cast_fp16))[name = tensor("op_8693_cast_fp16")]; + tensor var_8695_interleave_0 = const()[name = tensor("op_8695_interleave_0"), val = tensor(false)]; + tensor var_8695_cast_fp16 = concat(axis = var_7806, interleave = var_8695_interleave_0, values = (var_8599_cast_fp16, var_8601_cast_fp16, var_8603_cast_fp16, var_8605_cast_fp16))[name = tensor("op_8695_cast_fp16")]; + tensor var_8697_interleave_0 = const()[name = tensor("op_8697_interleave_0"), val = tensor(false)]; + tensor var_8697_cast_fp16 = concat(axis = var_7806, interleave = var_8697_interleave_0, values = (var_8607_cast_fp16, var_8609_cast_fp16, var_8611_cast_fp16, var_8613_cast_fp16))[name = tensor("op_8697_cast_fp16")]; + tensor var_8699_interleave_0 = const()[name = tensor("op_8699_interleave_0"), val = tensor(false)]; + tensor var_8699_cast_fp16 = concat(axis = var_7806, interleave = var_8699_interleave_0, values = (var_8615_cast_fp16, var_8617_cast_fp16, var_8619_cast_fp16, var_8621_cast_fp16))[name = tensor("op_8699_cast_fp16")]; + tensor var_8701_interleave_0 = const()[name = tensor("op_8701_interleave_0"), val = tensor(false)]; + tensor var_8701_cast_fp16 = concat(axis = var_7806, interleave = var_8701_interleave_0, values = (var_8623_cast_fp16, var_8625_cast_fp16, var_8627_cast_fp16, var_8629_cast_fp16))[name = tensor("op_8701_cast_fp16")]; + tensor var_8703_interleave_0 = const()[name = tensor("op_8703_interleave_0"), val = tensor(false)]; + tensor var_8703_cast_fp16 = concat(axis = var_7806, interleave = var_8703_interleave_0, values = (var_8631_cast_fp16, var_8633_cast_fp16, var_8635_cast_fp16, var_8637_cast_fp16))[name = tensor("op_8703_cast_fp16")]; + tensor var_8705_interleave_0 = const()[name = tensor("op_8705_interleave_0"), val = tensor(false)]; + tensor var_8705_cast_fp16 = concat(axis = var_7806, interleave = var_8705_interleave_0, values = (var_8639_cast_fp16, var_8641_cast_fp16, var_8643_cast_fp16, var_8645_cast_fp16))[name = tensor("op_8705_cast_fp16")]; + tensor var_8707_interleave_0 = const()[name = tensor("op_8707_interleave_0"), val = tensor(false)]; + tensor var_8707_cast_fp16 = concat(axis = var_7806, interleave = var_8707_interleave_0, values = (var_8647_cast_fp16, var_8649_cast_fp16, var_8651_cast_fp16, var_8653_cast_fp16))[name = tensor("op_8707_cast_fp16")]; + tensor var_8709_interleave_0 = const()[name = tensor("op_8709_interleave_0"), val = tensor(false)]; + tensor var_8709_cast_fp16 = concat(axis = var_7806, interleave = var_8709_interleave_0, values = (var_8655_cast_fp16, var_8657_cast_fp16, var_8659_cast_fp16, var_8661_cast_fp16))[name = tensor("op_8709_cast_fp16")]; + tensor var_8711_interleave_0 = const()[name = tensor("op_8711_interleave_0"), val = tensor(false)]; + tensor var_8711_cast_fp16 = concat(axis = var_7806, interleave = var_8711_interleave_0, values = (var_8663_cast_fp16, var_8665_cast_fp16, var_8667_cast_fp16, var_8669_cast_fp16))[name = tensor("op_8711_cast_fp16")]; + tensor var_8713_interleave_0 = const()[name = tensor("op_8713_interleave_0"), val = tensor(false)]; + tensor var_8713_cast_fp16 = concat(axis = var_7806, interleave = var_8713_interleave_0, values = (var_8671_cast_fp16, var_8673_cast_fp16, var_8675_cast_fp16, var_8677_cast_fp16))[name = tensor("op_8713_cast_fp16")]; + tensor var_8715_interleave_0 = const()[name = tensor("op_8715_interleave_0"), val = tensor(false)]; + tensor var_8715_cast_fp16 = concat(axis = var_7806, interleave = var_8715_interleave_0, values = (var_8679_cast_fp16, var_8681_cast_fp16, var_8683_cast_fp16, var_8685_cast_fp16))[name = tensor("op_8715_cast_fp16")]; + tensor var_8717_interleave_0 = const()[name = tensor("op_8717_interleave_0"), val = tensor(false)]; + tensor var_8717_cast_fp16 = concat(axis = var_7806, interleave = var_8717_interleave_0, values = (var_8687_cast_fp16, var_8689_cast_fp16, var_8691_cast_fp16, var_8693_cast_fp16))[name = tensor("op_8717_cast_fp16")]; + tensor input_65_interleave_0 = const()[name = tensor("input_65_interleave_0"), val = tensor(false)]; + tensor input_65_cast_fp16 = concat(axis = var_7823, interleave = input_65_interleave_0, values = (var_8695_cast_fp16, var_8697_cast_fp16, var_8699_cast_fp16, var_8701_cast_fp16, var_8703_cast_fp16, var_8705_cast_fp16, var_8707_cast_fp16, var_8709_cast_fp16, var_8711_cast_fp16, var_8713_cast_fp16, var_8715_cast_fp16, var_8717_cast_fp16))[name = tensor("input_65_cast_fp16")]; + tensor var_8722 = const()[name = tensor("op_8722"), val = tensor([1, 1])]; + tensor var_8724 = const()[name = tensor("op_8724"), val = tensor([1, 1])]; + tensor obj_35_pad_type_0 = const()[name = tensor("obj_35_pad_type_0"), val = tensor("custom")]; + tensor obj_35_pad_0 = const()[name = tensor("obj_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123165120)))]; + tensor layers_8_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124344832)))]; + tensor obj_35_cast_fp16 = conv(bias = layers_8_self_attn_o_proj_bias_to_fp16, dilations = var_8724, groups = var_7823, pad = obj_35_pad_0, pad_type = obj_35_pad_type_0, strides = var_8722, weight = layers_8_self_attn_o_proj_weight_to_fp16, x = input_65_cast_fp16)[name = tensor("obj_35_cast_fp16")]; + tensor inputs_35_cast_fp16 = add(x = inputs_33_cast_fp16, y = obj_35_cast_fp16)[name = tensor("inputs_35_cast_fp16")]; + tensor var_8730 = const()[name = tensor("op_8730"), val = tensor([1])]; + tensor channels_mean_35_cast_fp16 = reduce_mean(axes = var_8730, keep_dims = var_7824, x = inputs_35_cast_fp16)[name = tensor("channels_mean_35_cast_fp16")]; + tensor zero_mean_35_cast_fp16 = sub(x = inputs_35_cast_fp16, y = channels_mean_35_cast_fp16)[name = tensor("zero_mean_35_cast_fp16")]; + tensor zero_mean_sq_35_cast_fp16 = mul(x = zero_mean_35_cast_fp16, y = zero_mean_35_cast_fp16)[name = tensor("zero_mean_sq_35_cast_fp16")]; + tensor var_8734 = const()[name = tensor("op_8734"), val = tensor([1])]; + tensor var_8735_cast_fp16 = reduce_mean(axes = var_8734, keep_dims = var_7824, x = zero_mean_sq_35_cast_fp16)[name = tensor("op_8735_cast_fp16")]; + tensor var_8736_to_fp16 = const()[name = tensor("op_8736_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_8737_cast_fp16 = add(x = var_8735_cast_fp16, y = var_8736_to_fp16)[name = tensor("op_8737_cast_fp16")]; + tensor denom_35_epsilon_0_to_fp16 = const()[name = tensor("denom_35_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_35_cast_fp16 = rsqrt(epsilon = denom_35_epsilon_0_to_fp16, x = var_8737_cast_fp16)[name = tensor("denom_35_cast_fp16")]; + tensor out_35_cast_fp16 = mul(x = zero_mean_35_cast_fp16, y = denom_35_cast_fp16)[name = tensor("out_35_cast_fp16")]; + tensor input_67_gamma_0_to_fp16 = const()[name = tensor("input_67_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124346432)))]; + tensor input_67_beta_0_to_fp16 = const()[name = tensor("input_67_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124348032)))]; + tensor input_67_epsilon_0_to_fp16 = const()[name = tensor("input_67_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_67_cast_fp16 = batch_norm(beta = input_67_beta_0_to_fp16, epsilon = input_67_epsilon_0_to_fp16, gamma = input_67_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_35_cast_fp16)[name = tensor("input_67_cast_fp16")]; + tensor var_8748 = const()[name = tensor("op_8748"), val = tensor([1, 1])]; + tensor var_8750 = const()[name = tensor("op_8750"), val = tensor([1, 1])]; + tensor input_69_pad_type_0 = const()[name = tensor("input_69_pad_type_0"), val = tensor("custom")]; + tensor input_69_pad_0 = const()[name = tensor("input_69_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_fc1_weight_to_fp16 = const()[name = tensor("layers_8_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124349632)))]; + tensor layers_8_fc1_bias_to_fp16 = const()[name = tensor("layers_8_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129068288)))]; + tensor input_69_cast_fp16 = conv(bias = layers_8_fc1_bias_to_fp16, dilations = var_8750, groups = var_7823, pad = input_69_pad_0, pad_type = input_69_pad_type_0, strides = var_8748, weight = layers_8_fc1_weight_to_fp16, x = input_67_cast_fp16)[name = tensor("input_69_cast_fp16")]; + tensor input_71_mode_0 = const()[name = tensor("input_71_mode_0"), val = tensor("EXACT")]; + tensor input_71_cast_fp16 = gelu(mode = input_71_mode_0, x = input_69_cast_fp16)[name = tensor("input_71_cast_fp16")]; + tensor var_8756 = const()[name = tensor("op_8756"), val = tensor([1, 1])]; + tensor var_8758 = const()[name = tensor("op_8758"), val = tensor([1, 1])]; + tensor hidden_states_21_pad_type_0 = const()[name = tensor("hidden_states_21_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_21_pad_0 = const()[name = tensor("hidden_states_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_fc2_weight_to_fp16 = const()[name = tensor("layers_8_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129074496)))]; + tensor layers_8_fc2_bias_to_fp16 = const()[name = tensor("layers_8_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(133793152)))]; + tensor hidden_states_21_cast_fp16 = conv(bias = layers_8_fc2_bias_to_fp16, dilations = var_8758, groups = var_7823, pad = hidden_states_21_pad_0, pad_type = hidden_states_21_pad_type_0, strides = var_8756, weight = layers_8_fc2_weight_to_fp16, x = input_71_cast_fp16)[name = tensor("hidden_states_21_cast_fp16")]; + tensor inputs_37_cast_fp16 = add(x = inputs_35_cast_fp16, y = hidden_states_21_cast_fp16)[name = tensor("inputs_37_cast_fp16")]; + tensor var_8765 = const()[name = tensor("op_8765"), val = tensor(3)]; + tensor var_8782 = const()[name = tensor("op_8782"), val = tensor(1)]; + tensor var_8783 = const()[name = tensor("op_8783"), val = tensor(true)]; + tensor var_8793 = const()[name = tensor("op_8793"), val = tensor([1])]; + tensor channels_mean_37_cast_fp16 = reduce_mean(axes = var_8793, keep_dims = var_8783, x = inputs_37_cast_fp16)[name = tensor("channels_mean_37_cast_fp16")]; + tensor zero_mean_37_cast_fp16 = sub(x = inputs_37_cast_fp16, y = channels_mean_37_cast_fp16)[name = tensor("zero_mean_37_cast_fp16")]; + tensor zero_mean_sq_37_cast_fp16 = mul(x = zero_mean_37_cast_fp16, y = zero_mean_37_cast_fp16)[name = tensor("zero_mean_sq_37_cast_fp16")]; + tensor var_8797 = const()[name = tensor("op_8797"), val = tensor([1])]; + tensor var_8798_cast_fp16 = reduce_mean(axes = var_8797, keep_dims = var_8783, x = zero_mean_sq_37_cast_fp16)[name = tensor("op_8798_cast_fp16")]; + tensor var_8799_to_fp16 = const()[name = tensor("op_8799_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_8800_cast_fp16 = add(x = var_8798_cast_fp16, y = var_8799_to_fp16)[name = tensor("op_8800_cast_fp16")]; + tensor denom_37_epsilon_0_to_fp16 = const()[name = tensor("denom_37_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_37_cast_fp16 = rsqrt(epsilon = denom_37_epsilon_0_to_fp16, x = var_8800_cast_fp16)[name = tensor("denom_37_cast_fp16")]; + tensor out_37_cast_fp16 = mul(x = zero_mean_37_cast_fp16, y = denom_37_cast_fp16)[name = tensor("out_37_cast_fp16")]; + tensor obj_37_gamma_0_to_fp16 = const()[name = tensor("obj_37_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(133794752)))]; + tensor obj_37_beta_0_to_fp16 = const()[name = tensor("obj_37_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(133796352)))]; + tensor obj_37_epsilon_0_to_fp16 = const()[name = tensor("obj_37_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_37_cast_fp16 = batch_norm(beta = obj_37_beta_0_to_fp16, epsilon = obj_37_epsilon_0_to_fp16, gamma = obj_37_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_37_cast_fp16)[name = tensor("obj_37_cast_fp16")]; + tensor var_8815 = const()[name = tensor("op_8815"), val = tensor([1, 1])]; + tensor var_8817 = const()[name = tensor("op_8817"), val = tensor([1, 1])]; + tensor query_19_pad_type_0 = const()[name = tensor("query_19_pad_type_0"), val = tensor("custom")]; + tensor query_19_pad_0 = const()[name = tensor("query_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(133797952)))]; + tensor layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134977664)))]; + tensor query_19_cast_fp16 = conv(bias = layers_9_self_attn_q_proj_bias_to_fp16, dilations = var_8817, groups = var_8782, pad = query_19_pad_0, pad_type = query_19_pad_type_0, strides = var_8815, weight = layers_9_self_attn_q_proj_weight_to_fp16, x = obj_37_cast_fp16)[name = tensor("query_19_cast_fp16")]; + tensor var_8821 = const()[name = tensor("op_8821"), val = tensor([1, 1])]; + tensor var_8823 = const()[name = tensor("op_8823"), val = tensor([1, 1])]; + tensor key_19_pad_type_0 = const()[name = tensor("key_19_pad_type_0"), val = tensor("custom")]; + tensor key_19_pad_0 = const()[name = tensor("key_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134979264)))]; + tensor key_19_cast_fp16 = conv(dilations = var_8823, groups = var_8782, pad = key_19_pad_0, pad_type = key_19_pad_type_0, strides = var_8821, weight = layers_9_self_attn_k_proj_weight_to_fp16, x = obj_37_cast_fp16)[name = tensor("key_19_cast_fp16")]; + tensor var_8828 = const()[name = tensor("op_8828"), val = tensor([1, 1])]; + tensor var_8830 = const()[name = tensor("op_8830"), val = tensor([1, 1])]; + tensor value_19_pad_type_0 = const()[name = tensor("value_19_pad_type_0"), val = tensor("custom")]; + tensor value_19_pad_0 = const()[name = tensor("value_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136158976)))]; + tensor layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137338688)))]; + tensor value_19_cast_fp16 = conv(bias = layers_9_self_attn_v_proj_bias_to_fp16, dilations = var_8830, groups = var_8782, pad = value_19_pad_0, pad_type = value_19_pad_type_0, strides = var_8828, weight = layers_9_self_attn_v_proj_weight_to_fp16, x = obj_37_cast_fp16)[name = tensor("value_19_cast_fp16")]; + tensor var_8837_begin_0 = const()[name = tensor("op_8837_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8837_end_0 = const()[name = tensor("op_8837_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8837_end_mask_0 = const()[name = tensor("op_8837_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8837_cast_fp16 = slice_by_index(begin = var_8837_begin_0, end = var_8837_end_0, end_mask = var_8837_end_mask_0, x = query_19_cast_fp16)[name = tensor("op_8837_cast_fp16")]; + tensor var_8841_begin_0 = const()[name = tensor("op_8841_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_8841_end_0 = const()[name = tensor("op_8841_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_8841_end_mask_0 = const()[name = tensor("op_8841_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8841_cast_fp16 = slice_by_index(begin = var_8841_begin_0, end = var_8841_end_0, end_mask = var_8841_end_mask_0, x = query_19_cast_fp16)[name = tensor("op_8841_cast_fp16")]; + tensor var_8845_begin_0 = const()[name = tensor("op_8845_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_8845_end_0 = const()[name = tensor("op_8845_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_8845_end_mask_0 = const()[name = tensor("op_8845_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8845_cast_fp16 = slice_by_index(begin = var_8845_begin_0, end = var_8845_end_0, end_mask = var_8845_end_mask_0, x = query_19_cast_fp16)[name = tensor("op_8845_cast_fp16")]; + tensor var_8849_begin_0 = const()[name = tensor("op_8849_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_8849_end_0 = const()[name = tensor("op_8849_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_8849_end_mask_0 = const()[name = tensor("op_8849_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8849_cast_fp16 = slice_by_index(begin = var_8849_begin_0, end = var_8849_end_0, end_mask = var_8849_end_mask_0, x = query_19_cast_fp16)[name = tensor("op_8849_cast_fp16")]; + tensor var_8853_begin_0 = const()[name = tensor("op_8853_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_8853_end_0 = const()[name = tensor("op_8853_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_8853_end_mask_0 = const()[name = tensor("op_8853_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8853_cast_fp16 = slice_by_index(begin = var_8853_begin_0, end = var_8853_end_0, end_mask = var_8853_end_mask_0, x = query_19_cast_fp16)[name = tensor("op_8853_cast_fp16")]; + tensor var_8857_begin_0 = const()[name = tensor("op_8857_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_8857_end_0 = const()[name = tensor("op_8857_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_8857_end_mask_0 = const()[name = tensor("op_8857_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8857_cast_fp16 = slice_by_index(begin = var_8857_begin_0, end = var_8857_end_0, end_mask = var_8857_end_mask_0, x = query_19_cast_fp16)[name = tensor("op_8857_cast_fp16")]; + tensor var_8861_begin_0 = const()[name = tensor("op_8861_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_8861_end_0 = const()[name = tensor("op_8861_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_8861_end_mask_0 = const()[name = tensor("op_8861_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8861_cast_fp16 = slice_by_index(begin = var_8861_begin_0, end = var_8861_end_0, end_mask = var_8861_end_mask_0, x = query_19_cast_fp16)[name = tensor("op_8861_cast_fp16")]; + tensor var_8865_begin_0 = const()[name = tensor("op_8865_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_8865_end_0 = const()[name = tensor("op_8865_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_8865_end_mask_0 = const()[name = tensor("op_8865_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8865_cast_fp16 = slice_by_index(begin = var_8865_begin_0, end = var_8865_end_0, end_mask = var_8865_end_mask_0, x = query_19_cast_fp16)[name = tensor("op_8865_cast_fp16")]; + tensor var_8869_begin_0 = const()[name = tensor("op_8869_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_8869_end_0 = const()[name = tensor("op_8869_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_8869_end_mask_0 = const()[name = tensor("op_8869_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8869_cast_fp16 = slice_by_index(begin = var_8869_begin_0, end = var_8869_end_0, end_mask = var_8869_end_mask_0, x = query_19_cast_fp16)[name = tensor("op_8869_cast_fp16")]; + tensor var_8873_begin_0 = const()[name = tensor("op_8873_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_8873_end_0 = const()[name = tensor("op_8873_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_8873_end_mask_0 = const()[name = tensor("op_8873_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8873_cast_fp16 = slice_by_index(begin = var_8873_begin_0, end = var_8873_end_0, end_mask = var_8873_end_mask_0, x = query_19_cast_fp16)[name = tensor("op_8873_cast_fp16")]; + tensor var_8877_begin_0 = const()[name = tensor("op_8877_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_8877_end_0 = const()[name = tensor("op_8877_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_8877_end_mask_0 = const()[name = tensor("op_8877_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8877_cast_fp16 = slice_by_index(begin = var_8877_begin_0, end = var_8877_end_0, end_mask = var_8877_end_mask_0, x = query_19_cast_fp16)[name = tensor("op_8877_cast_fp16")]; + tensor var_8881_begin_0 = const()[name = tensor("op_8881_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_8881_end_0 = const()[name = tensor("op_8881_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_8881_end_mask_0 = const()[name = tensor("op_8881_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_8881_cast_fp16 = slice_by_index(begin = var_8881_begin_0, end = var_8881_end_0, end_mask = var_8881_end_mask_0, x = query_19_cast_fp16)[name = tensor("op_8881_cast_fp16")]; + tensor var_8890_begin_0 = const()[name = tensor("op_8890_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8890_end_0 = const()[name = tensor("op_8890_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_8890_end_mask_0 = const()[name = tensor("op_8890_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8890_cast_fp16 = slice_by_index(begin = var_8890_begin_0, end = var_8890_end_0, end_mask = var_8890_end_mask_0, x = var_8837_cast_fp16)[name = tensor("op_8890_cast_fp16")]; + tensor var_8897_begin_0 = const()[name = tensor("op_8897_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_8897_end_0 = const()[name = tensor("op_8897_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_8897_end_mask_0 = const()[name = tensor("op_8897_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8897_cast_fp16 = slice_by_index(begin = var_8897_begin_0, end = var_8897_end_0, end_mask = var_8897_end_mask_0, x = var_8837_cast_fp16)[name = tensor("op_8897_cast_fp16")]; + tensor var_8904_begin_0 = const()[name = tensor("op_8904_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_8904_end_0 = const()[name = tensor("op_8904_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_8904_end_mask_0 = const()[name = tensor("op_8904_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8904_cast_fp16 = slice_by_index(begin = var_8904_begin_0, end = var_8904_end_0, end_mask = var_8904_end_mask_0, x = var_8837_cast_fp16)[name = tensor("op_8904_cast_fp16")]; + tensor var_8911_begin_0 = const()[name = tensor("op_8911_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_8911_end_0 = const()[name = tensor("op_8911_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8911_end_mask_0 = const()[name = tensor("op_8911_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8911_cast_fp16 = slice_by_index(begin = var_8911_begin_0, end = var_8911_end_0, end_mask = var_8911_end_mask_0, x = var_8837_cast_fp16)[name = tensor("op_8911_cast_fp16")]; + tensor var_8918_begin_0 = const()[name = tensor("op_8918_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8918_end_0 = const()[name = tensor("op_8918_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_8918_end_mask_0 = const()[name = tensor("op_8918_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8918_cast_fp16 = slice_by_index(begin = var_8918_begin_0, end = var_8918_end_0, end_mask = var_8918_end_mask_0, x = var_8841_cast_fp16)[name = tensor("op_8918_cast_fp16")]; + tensor var_8925_begin_0 = const()[name = tensor("op_8925_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_8925_end_0 = const()[name = tensor("op_8925_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_8925_end_mask_0 = const()[name = tensor("op_8925_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8925_cast_fp16 = slice_by_index(begin = var_8925_begin_0, end = var_8925_end_0, end_mask = var_8925_end_mask_0, x = var_8841_cast_fp16)[name = tensor("op_8925_cast_fp16")]; + tensor var_8932_begin_0 = const()[name = tensor("op_8932_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_8932_end_0 = const()[name = tensor("op_8932_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_8932_end_mask_0 = const()[name = tensor("op_8932_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8932_cast_fp16 = slice_by_index(begin = var_8932_begin_0, end = var_8932_end_0, end_mask = var_8932_end_mask_0, x = var_8841_cast_fp16)[name = tensor("op_8932_cast_fp16")]; + tensor var_8939_begin_0 = const()[name = tensor("op_8939_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_8939_end_0 = const()[name = tensor("op_8939_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8939_end_mask_0 = const()[name = tensor("op_8939_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8939_cast_fp16 = slice_by_index(begin = var_8939_begin_0, end = var_8939_end_0, end_mask = var_8939_end_mask_0, x = var_8841_cast_fp16)[name = tensor("op_8939_cast_fp16")]; + tensor var_8946_begin_0 = const()[name = tensor("op_8946_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8946_end_0 = const()[name = tensor("op_8946_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_8946_end_mask_0 = const()[name = tensor("op_8946_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8946_cast_fp16 = slice_by_index(begin = var_8946_begin_0, end = var_8946_end_0, end_mask = var_8946_end_mask_0, x = var_8845_cast_fp16)[name = tensor("op_8946_cast_fp16")]; + tensor var_8953_begin_0 = const()[name = tensor("op_8953_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_8953_end_0 = const()[name = tensor("op_8953_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_8953_end_mask_0 = const()[name = tensor("op_8953_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8953_cast_fp16 = slice_by_index(begin = var_8953_begin_0, end = var_8953_end_0, end_mask = var_8953_end_mask_0, x = var_8845_cast_fp16)[name = tensor("op_8953_cast_fp16")]; + tensor var_8960_begin_0 = const()[name = tensor("op_8960_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_8960_end_0 = const()[name = tensor("op_8960_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_8960_end_mask_0 = const()[name = tensor("op_8960_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8960_cast_fp16 = slice_by_index(begin = var_8960_begin_0, end = var_8960_end_0, end_mask = var_8960_end_mask_0, x = var_8845_cast_fp16)[name = tensor("op_8960_cast_fp16")]; + tensor var_8967_begin_0 = const()[name = tensor("op_8967_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_8967_end_0 = const()[name = tensor("op_8967_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8967_end_mask_0 = const()[name = tensor("op_8967_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8967_cast_fp16 = slice_by_index(begin = var_8967_begin_0, end = var_8967_end_0, end_mask = var_8967_end_mask_0, x = var_8845_cast_fp16)[name = tensor("op_8967_cast_fp16")]; + tensor var_8974_begin_0 = const()[name = tensor("op_8974_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_8974_end_0 = const()[name = tensor("op_8974_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_8974_end_mask_0 = const()[name = tensor("op_8974_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8974_cast_fp16 = slice_by_index(begin = var_8974_begin_0, end = var_8974_end_0, end_mask = var_8974_end_mask_0, x = var_8849_cast_fp16)[name = tensor("op_8974_cast_fp16")]; + tensor var_8981_begin_0 = const()[name = tensor("op_8981_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_8981_end_0 = const()[name = tensor("op_8981_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_8981_end_mask_0 = const()[name = tensor("op_8981_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8981_cast_fp16 = slice_by_index(begin = var_8981_begin_0, end = var_8981_end_0, end_mask = var_8981_end_mask_0, x = var_8849_cast_fp16)[name = tensor("op_8981_cast_fp16")]; + tensor var_8988_begin_0 = const()[name = tensor("op_8988_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_8988_end_0 = const()[name = tensor("op_8988_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_8988_end_mask_0 = const()[name = tensor("op_8988_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8988_cast_fp16 = slice_by_index(begin = var_8988_begin_0, end = var_8988_end_0, end_mask = var_8988_end_mask_0, x = var_8849_cast_fp16)[name = tensor("op_8988_cast_fp16")]; + tensor var_8995_begin_0 = const()[name = tensor("op_8995_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_8995_end_0 = const()[name = tensor("op_8995_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_8995_end_mask_0 = const()[name = tensor("op_8995_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_8995_cast_fp16 = slice_by_index(begin = var_8995_begin_0, end = var_8995_end_0, end_mask = var_8995_end_mask_0, x = var_8849_cast_fp16)[name = tensor("op_8995_cast_fp16")]; + tensor var_9002_begin_0 = const()[name = tensor("op_9002_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9002_end_0 = const()[name = tensor("op_9002_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_9002_end_mask_0 = const()[name = tensor("op_9002_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9002_cast_fp16 = slice_by_index(begin = var_9002_begin_0, end = var_9002_end_0, end_mask = var_9002_end_mask_0, x = var_8853_cast_fp16)[name = tensor("op_9002_cast_fp16")]; + tensor var_9009_begin_0 = const()[name = tensor("op_9009_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_9009_end_0 = const()[name = tensor("op_9009_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_9009_end_mask_0 = const()[name = tensor("op_9009_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9009_cast_fp16 = slice_by_index(begin = var_9009_begin_0, end = var_9009_end_0, end_mask = var_9009_end_mask_0, x = var_8853_cast_fp16)[name = tensor("op_9009_cast_fp16")]; + tensor var_9016_begin_0 = const()[name = tensor("op_9016_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_9016_end_0 = const()[name = tensor("op_9016_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_9016_end_mask_0 = const()[name = tensor("op_9016_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9016_cast_fp16 = slice_by_index(begin = var_9016_begin_0, end = var_9016_end_0, end_mask = var_9016_end_mask_0, x = var_8853_cast_fp16)[name = tensor("op_9016_cast_fp16")]; + tensor var_9023_begin_0 = const()[name = tensor("op_9023_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_9023_end_0 = const()[name = tensor("op_9023_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9023_end_mask_0 = const()[name = tensor("op_9023_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9023_cast_fp16 = slice_by_index(begin = var_9023_begin_0, end = var_9023_end_0, end_mask = var_9023_end_mask_0, x = var_8853_cast_fp16)[name = tensor("op_9023_cast_fp16")]; + tensor var_9030_begin_0 = const()[name = tensor("op_9030_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9030_end_0 = const()[name = tensor("op_9030_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_9030_end_mask_0 = const()[name = tensor("op_9030_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9030_cast_fp16 = slice_by_index(begin = var_9030_begin_0, end = var_9030_end_0, end_mask = var_9030_end_mask_0, x = var_8857_cast_fp16)[name = tensor("op_9030_cast_fp16")]; + tensor var_9037_begin_0 = const()[name = tensor("op_9037_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_9037_end_0 = const()[name = tensor("op_9037_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_9037_end_mask_0 = const()[name = tensor("op_9037_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9037_cast_fp16 = slice_by_index(begin = var_9037_begin_0, end = var_9037_end_0, end_mask = var_9037_end_mask_0, x = var_8857_cast_fp16)[name = tensor("op_9037_cast_fp16")]; + tensor var_9044_begin_0 = const()[name = tensor("op_9044_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_9044_end_0 = const()[name = tensor("op_9044_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_9044_end_mask_0 = const()[name = tensor("op_9044_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9044_cast_fp16 = slice_by_index(begin = var_9044_begin_0, end = var_9044_end_0, end_mask = var_9044_end_mask_0, x = var_8857_cast_fp16)[name = tensor("op_9044_cast_fp16")]; + tensor var_9051_begin_0 = const()[name = tensor("op_9051_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_9051_end_0 = const()[name = tensor("op_9051_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9051_end_mask_0 = const()[name = tensor("op_9051_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9051_cast_fp16 = slice_by_index(begin = var_9051_begin_0, end = var_9051_end_0, end_mask = var_9051_end_mask_0, x = var_8857_cast_fp16)[name = tensor("op_9051_cast_fp16")]; + tensor var_9058_begin_0 = const()[name = tensor("op_9058_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9058_end_0 = const()[name = tensor("op_9058_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_9058_end_mask_0 = const()[name = tensor("op_9058_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9058_cast_fp16 = slice_by_index(begin = var_9058_begin_0, end = var_9058_end_0, end_mask = var_9058_end_mask_0, x = var_8861_cast_fp16)[name = tensor("op_9058_cast_fp16")]; + tensor var_9065_begin_0 = const()[name = tensor("op_9065_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_9065_end_0 = const()[name = tensor("op_9065_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_9065_end_mask_0 = const()[name = tensor("op_9065_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9065_cast_fp16 = slice_by_index(begin = var_9065_begin_0, end = var_9065_end_0, end_mask = var_9065_end_mask_0, x = var_8861_cast_fp16)[name = tensor("op_9065_cast_fp16")]; + tensor var_9072_begin_0 = const()[name = tensor("op_9072_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_9072_end_0 = const()[name = tensor("op_9072_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_9072_end_mask_0 = const()[name = tensor("op_9072_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9072_cast_fp16 = slice_by_index(begin = var_9072_begin_0, end = var_9072_end_0, end_mask = var_9072_end_mask_0, x = var_8861_cast_fp16)[name = tensor("op_9072_cast_fp16")]; + tensor var_9079_begin_0 = const()[name = tensor("op_9079_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_9079_end_0 = const()[name = tensor("op_9079_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9079_end_mask_0 = const()[name = tensor("op_9079_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9079_cast_fp16 = slice_by_index(begin = var_9079_begin_0, end = var_9079_end_0, end_mask = var_9079_end_mask_0, x = var_8861_cast_fp16)[name = tensor("op_9079_cast_fp16")]; + tensor var_9086_begin_0 = const()[name = tensor("op_9086_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9086_end_0 = const()[name = tensor("op_9086_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_9086_end_mask_0 = const()[name = tensor("op_9086_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9086_cast_fp16 = slice_by_index(begin = var_9086_begin_0, end = var_9086_end_0, end_mask = var_9086_end_mask_0, x = var_8865_cast_fp16)[name = tensor("op_9086_cast_fp16")]; + tensor var_9093_begin_0 = const()[name = tensor("op_9093_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_9093_end_0 = const()[name = tensor("op_9093_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_9093_end_mask_0 = const()[name = tensor("op_9093_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9093_cast_fp16 = slice_by_index(begin = var_9093_begin_0, end = var_9093_end_0, end_mask = var_9093_end_mask_0, x = var_8865_cast_fp16)[name = tensor("op_9093_cast_fp16")]; + tensor var_9100_begin_0 = const()[name = tensor("op_9100_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_9100_end_0 = const()[name = tensor("op_9100_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_9100_end_mask_0 = const()[name = tensor("op_9100_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9100_cast_fp16 = slice_by_index(begin = var_9100_begin_0, end = var_9100_end_0, end_mask = var_9100_end_mask_0, x = var_8865_cast_fp16)[name = tensor("op_9100_cast_fp16")]; + tensor var_9107_begin_0 = const()[name = tensor("op_9107_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_9107_end_0 = const()[name = tensor("op_9107_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9107_end_mask_0 = const()[name = tensor("op_9107_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9107_cast_fp16 = slice_by_index(begin = var_9107_begin_0, end = var_9107_end_0, end_mask = var_9107_end_mask_0, x = var_8865_cast_fp16)[name = tensor("op_9107_cast_fp16")]; + tensor var_9114_begin_0 = const()[name = tensor("op_9114_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9114_end_0 = const()[name = tensor("op_9114_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_9114_end_mask_0 = const()[name = tensor("op_9114_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9114_cast_fp16 = slice_by_index(begin = var_9114_begin_0, end = var_9114_end_0, end_mask = var_9114_end_mask_0, x = var_8869_cast_fp16)[name = tensor("op_9114_cast_fp16")]; + tensor var_9121_begin_0 = const()[name = tensor("op_9121_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_9121_end_0 = const()[name = tensor("op_9121_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_9121_end_mask_0 = const()[name = tensor("op_9121_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9121_cast_fp16 = slice_by_index(begin = var_9121_begin_0, end = var_9121_end_0, end_mask = var_9121_end_mask_0, x = var_8869_cast_fp16)[name = tensor("op_9121_cast_fp16")]; + tensor var_9128_begin_0 = const()[name = tensor("op_9128_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_9128_end_0 = const()[name = tensor("op_9128_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_9128_end_mask_0 = const()[name = tensor("op_9128_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9128_cast_fp16 = slice_by_index(begin = var_9128_begin_0, end = var_9128_end_0, end_mask = var_9128_end_mask_0, x = var_8869_cast_fp16)[name = tensor("op_9128_cast_fp16")]; + tensor var_9135_begin_0 = const()[name = tensor("op_9135_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_9135_end_0 = const()[name = tensor("op_9135_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9135_end_mask_0 = const()[name = tensor("op_9135_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9135_cast_fp16 = slice_by_index(begin = var_9135_begin_0, end = var_9135_end_0, end_mask = var_9135_end_mask_0, x = var_8869_cast_fp16)[name = tensor("op_9135_cast_fp16")]; + tensor var_9142_begin_0 = const()[name = tensor("op_9142_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9142_end_0 = const()[name = tensor("op_9142_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_9142_end_mask_0 = const()[name = tensor("op_9142_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9142_cast_fp16 = slice_by_index(begin = var_9142_begin_0, end = var_9142_end_0, end_mask = var_9142_end_mask_0, x = var_8873_cast_fp16)[name = tensor("op_9142_cast_fp16")]; + tensor var_9149_begin_0 = const()[name = tensor("op_9149_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_9149_end_0 = const()[name = tensor("op_9149_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_9149_end_mask_0 = const()[name = tensor("op_9149_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9149_cast_fp16 = slice_by_index(begin = var_9149_begin_0, end = var_9149_end_0, end_mask = var_9149_end_mask_0, x = var_8873_cast_fp16)[name = tensor("op_9149_cast_fp16")]; + tensor var_9156_begin_0 = const()[name = tensor("op_9156_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_9156_end_0 = const()[name = tensor("op_9156_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_9156_end_mask_0 = const()[name = tensor("op_9156_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9156_cast_fp16 = slice_by_index(begin = var_9156_begin_0, end = var_9156_end_0, end_mask = var_9156_end_mask_0, x = var_8873_cast_fp16)[name = tensor("op_9156_cast_fp16")]; + tensor var_9163_begin_0 = const()[name = tensor("op_9163_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_9163_end_0 = const()[name = tensor("op_9163_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9163_end_mask_0 = const()[name = tensor("op_9163_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9163_cast_fp16 = slice_by_index(begin = var_9163_begin_0, end = var_9163_end_0, end_mask = var_9163_end_mask_0, x = var_8873_cast_fp16)[name = tensor("op_9163_cast_fp16")]; + tensor var_9170_begin_0 = const()[name = tensor("op_9170_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9170_end_0 = const()[name = tensor("op_9170_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_9170_end_mask_0 = const()[name = tensor("op_9170_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9170_cast_fp16 = slice_by_index(begin = var_9170_begin_0, end = var_9170_end_0, end_mask = var_9170_end_mask_0, x = var_8877_cast_fp16)[name = tensor("op_9170_cast_fp16")]; + tensor var_9177_begin_0 = const()[name = tensor("op_9177_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_9177_end_0 = const()[name = tensor("op_9177_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_9177_end_mask_0 = const()[name = tensor("op_9177_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9177_cast_fp16 = slice_by_index(begin = var_9177_begin_0, end = var_9177_end_0, end_mask = var_9177_end_mask_0, x = var_8877_cast_fp16)[name = tensor("op_9177_cast_fp16")]; + tensor var_9184_begin_0 = const()[name = tensor("op_9184_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_9184_end_0 = const()[name = tensor("op_9184_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_9184_end_mask_0 = const()[name = tensor("op_9184_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9184_cast_fp16 = slice_by_index(begin = var_9184_begin_0, end = var_9184_end_0, end_mask = var_9184_end_mask_0, x = var_8877_cast_fp16)[name = tensor("op_9184_cast_fp16")]; + tensor var_9191_begin_0 = const()[name = tensor("op_9191_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_9191_end_0 = const()[name = tensor("op_9191_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9191_end_mask_0 = const()[name = tensor("op_9191_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9191_cast_fp16 = slice_by_index(begin = var_9191_begin_0, end = var_9191_end_0, end_mask = var_9191_end_mask_0, x = var_8877_cast_fp16)[name = tensor("op_9191_cast_fp16")]; + tensor var_9198_begin_0 = const()[name = tensor("op_9198_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9198_end_0 = const()[name = tensor("op_9198_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_9198_end_mask_0 = const()[name = tensor("op_9198_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9198_cast_fp16 = slice_by_index(begin = var_9198_begin_0, end = var_9198_end_0, end_mask = var_9198_end_mask_0, x = var_8881_cast_fp16)[name = tensor("op_9198_cast_fp16")]; + tensor var_9205_begin_0 = const()[name = tensor("op_9205_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_9205_end_0 = const()[name = tensor("op_9205_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_9205_end_mask_0 = const()[name = tensor("op_9205_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9205_cast_fp16 = slice_by_index(begin = var_9205_begin_0, end = var_9205_end_0, end_mask = var_9205_end_mask_0, x = var_8881_cast_fp16)[name = tensor("op_9205_cast_fp16")]; + tensor var_9212_begin_0 = const()[name = tensor("op_9212_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_9212_end_0 = const()[name = tensor("op_9212_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_9212_end_mask_0 = const()[name = tensor("op_9212_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9212_cast_fp16 = slice_by_index(begin = var_9212_begin_0, end = var_9212_end_0, end_mask = var_9212_end_mask_0, x = var_8881_cast_fp16)[name = tensor("op_9212_cast_fp16")]; + tensor var_9219_begin_0 = const()[name = tensor("op_9219_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_9219_end_0 = const()[name = tensor("op_9219_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9219_end_mask_0 = const()[name = tensor("op_9219_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9219_cast_fp16 = slice_by_index(begin = var_9219_begin_0, end = var_9219_end_0, end_mask = var_9219_end_mask_0, x = var_8881_cast_fp16)[name = tensor("op_9219_cast_fp16")]; + tensor k_19_perm_0 = const()[name = tensor("k_19_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_9224_begin_0 = const()[name = tensor("op_9224_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9224_end_0 = const()[name = tensor("op_9224_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_9224_end_mask_0 = const()[name = tensor("op_9224_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_2 = transpose(perm = k_19_perm_0, x = key_19_cast_fp16)[name = tensor("transpose_2")]; + tensor var_9224_cast_fp16 = slice_by_index(begin = var_9224_begin_0, end = var_9224_end_0, end_mask = var_9224_end_mask_0, x = transpose_2)[name = tensor("op_9224_cast_fp16")]; + tensor var_9228_begin_0 = const()[name = tensor("op_9228_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_9228_end_0 = const()[name = tensor("op_9228_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_9228_end_mask_0 = const()[name = tensor("op_9228_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9228_cast_fp16 = slice_by_index(begin = var_9228_begin_0, end = var_9228_end_0, end_mask = var_9228_end_mask_0, x = transpose_2)[name = tensor("op_9228_cast_fp16")]; + tensor var_9232_begin_0 = const()[name = tensor("op_9232_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_9232_end_0 = const()[name = tensor("op_9232_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_9232_end_mask_0 = const()[name = tensor("op_9232_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9232_cast_fp16 = slice_by_index(begin = var_9232_begin_0, end = var_9232_end_0, end_mask = var_9232_end_mask_0, x = transpose_2)[name = tensor("op_9232_cast_fp16")]; + tensor var_9236_begin_0 = const()[name = tensor("op_9236_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_9236_end_0 = const()[name = tensor("op_9236_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_9236_end_mask_0 = const()[name = tensor("op_9236_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9236_cast_fp16 = slice_by_index(begin = var_9236_begin_0, end = var_9236_end_0, end_mask = var_9236_end_mask_0, x = transpose_2)[name = tensor("op_9236_cast_fp16")]; + tensor var_9240_begin_0 = const()[name = tensor("op_9240_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_9240_end_0 = const()[name = tensor("op_9240_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_9240_end_mask_0 = const()[name = tensor("op_9240_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9240_cast_fp16 = slice_by_index(begin = var_9240_begin_0, end = var_9240_end_0, end_mask = var_9240_end_mask_0, x = transpose_2)[name = tensor("op_9240_cast_fp16")]; + tensor var_9244_begin_0 = const()[name = tensor("op_9244_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_9244_end_0 = const()[name = tensor("op_9244_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_9244_end_mask_0 = const()[name = tensor("op_9244_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9244_cast_fp16 = slice_by_index(begin = var_9244_begin_0, end = var_9244_end_0, end_mask = var_9244_end_mask_0, x = transpose_2)[name = tensor("op_9244_cast_fp16")]; + tensor var_9248_begin_0 = const()[name = tensor("op_9248_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_9248_end_0 = const()[name = tensor("op_9248_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_9248_end_mask_0 = const()[name = tensor("op_9248_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9248_cast_fp16 = slice_by_index(begin = var_9248_begin_0, end = var_9248_end_0, end_mask = var_9248_end_mask_0, x = transpose_2)[name = tensor("op_9248_cast_fp16")]; + tensor var_9252_begin_0 = const()[name = tensor("op_9252_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_9252_end_0 = const()[name = tensor("op_9252_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_9252_end_mask_0 = const()[name = tensor("op_9252_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9252_cast_fp16 = slice_by_index(begin = var_9252_begin_0, end = var_9252_end_0, end_mask = var_9252_end_mask_0, x = transpose_2)[name = tensor("op_9252_cast_fp16")]; + tensor var_9256_begin_0 = const()[name = tensor("op_9256_begin_0"), val = tensor([0, 0, 0, 512])]; + tensor var_9256_end_0 = const()[name = tensor("op_9256_end_0"), val = tensor([1, 1500, 1, 576])]; + tensor var_9256_end_mask_0 = const()[name = tensor("op_9256_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9256_cast_fp16 = slice_by_index(begin = var_9256_begin_0, end = var_9256_end_0, end_mask = var_9256_end_mask_0, x = transpose_2)[name = tensor("op_9256_cast_fp16")]; + tensor var_9260_begin_0 = const()[name = tensor("op_9260_begin_0"), val = tensor([0, 0, 0, 576])]; + tensor var_9260_end_0 = const()[name = tensor("op_9260_end_0"), val = tensor([1, 1500, 1, 640])]; + tensor var_9260_end_mask_0 = const()[name = tensor("op_9260_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9260_cast_fp16 = slice_by_index(begin = var_9260_begin_0, end = var_9260_end_0, end_mask = var_9260_end_mask_0, x = transpose_2)[name = tensor("op_9260_cast_fp16")]; + tensor var_9264_begin_0 = const()[name = tensor("op_9264_begin_0"), val = tensor([0, 0, 0, 640])]; + tensor var_9264_end_0 = const()[name = tensor("op_9264_end_0"), val = tensor([1, 1500, 1, 704])]; + tensor var_9264_end_mask_0 = const()[name = tensor("op_9264_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9264_cast_fp16 = slice_by_index(begin = var_9264_begin_0, end = var_9264_end_0, end_mask = var_9264_end_mask_0, x = transpose_2)[name = tensor("op_9264_cast_fp16")]; + tensor var_9268_begin_0 = const()[name = tensor("op_9268_begin_0"), val = tensor([0, 0, 0, 704])]; + tensor var_9268_end_0 = const()[name = tensor("op_9268_end_0"), val = tensor([1, 1500, 1, 768])]; + tensor var_9268_end_mask_0 = const()[name = tensor("op_9268_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9268_cast_fp16 = slice_by_index(begin = var_9268_begin_0, end = var_9268_end_0, end_mask = var_9268_end_mask_0, x = transpose_2)[name = tensor("op_9268_cast_fp16")]; + tensor var_9270_begin_0 = const()[name = tensor("op_9270_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9270_end_0 = const()[name = tensor("op_9270_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9270_end_mask_0 = const()[name = tensor("op_9270_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9270_cast_fp16 = slice_by_index(begin = var_9270_begin_0, end = var_9270_end_0, end_mask = var_9270_end_mask_0, x = value_19_cast_fp16)[name = tensor("op_9270_cast_fp16")]; + tensor var_9274_begin_0 = const()[name = tensor("op_9274_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_9274_end_0 = const()[name = tensor("op_9274_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_9274_end_mask_0 = const()[name = tensor("op_9274_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9274_cast_fp16 = slice_by_index(begin = var_9274_begin_0, end = var_9274_end_0, end_mask = var_9274_end_mask_0, x = value_19_cast_fp16)[name = tensor("op_9274_cast_fp16")]; + tensor var_9278_begin_0 = const()[name = tensor("op_9278_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_9278_end_0 = const()[name = tensor("op_9278_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_9278_end_mask_0 = const()[name = tensor("op_9278_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9278_cast_fp16 = slice_by_index(begin = var_9278_begin_0, end = var_9278_end_0, end_mask = var_9278_end_mask_0, x = value_19_cast_fp16)[name = tensor("op_9278_cast_fp16")]; + tensor var_9282_begin_0 = const()[name = tensor("op_9282_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_9282_end_0 = const()[name = tensor("op_9282_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_9282_end_mask_0 = const()[name = tensor("op_9282_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9282_cast_fp16 = slice_by_index(begin = var_9282_begin_0, end = var_9282_end_0, end_mask = var_9282_end_mask_0, x = value_19_cast_fp16)[name = tensor("op_9282_cast_fp16")]; + tensor var_9286_begin_0 = const()[name = tensor("op_9286_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_9286_end_0 = const()[name = tensor("op_9286_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_9286_end_mask_0 = const()[name = tensor("op_9286_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9286_cast_fp16 = slice_by_index(begin = var_9286_begin_0, end = var_9286_end_0, end_mask = var_9286_end_mask_0, x = value_19_cast_fp16)[name = tensor("op_9286_cast_fp16")]; + tensor var_9290_begin_0 = const()[name = tensor("op_9290_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_9290_end_0 = const()[name = tensor("op_9290_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_9290_end_mask_0 = const()[name = tensor("op_9290_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9290_cast_fp16 = slice_by_index(begin = var_9290_begin_0, end = var_9290_end_0, end_mask = var_9290_end_mask_0, x = value_19_cast_fp16)[name = tensor("op_9290_cast_fp16")]; + tensor var_9294_begin_0 = const()[name = tensor("op_9294_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_9294_end_0 = const()[name = tensor("op_9294_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_9294_end_mask_0 = const()[name = tensor("op_9294_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9294_cast_fp16 = slice_by_index(begin = var_9294_begin_0, end = var_9294_end_0, end_mask = var_9294_end_mask_0, x = value_19_cast_fp16)[name = tensor("op_9294_cast_fp16")]; + tensor var_9298_begin_0 = const()[name = tensor("op_9298_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_9298_end_0 = const()[name = tensor("op_9298_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_9298_end_mask_0 = const()[name = tensor("op_9298_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9298_cast_fp16 = slice_by_index(begin = var_9298_begin_0, end = var_9298_end_0, end_mask = var_9298_end_mask_0, x = value_19_cast_fp16)[name = tensor("op_9298_cast_fp16")]; + tensor var_9302_begin_0 = const()[name = tensor("op_9302_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_9302_end_0 = const()[name = tensor("op_9302_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_9302_end_mask_0 = const()[name = tensor("op_9302_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9302_cast_fp16 = slice_by_index(begin = var_9302_begin_0, end = var_9302_end_0, end_mask = var_9302_end_mask_0, x = value_19_cast_fp16)[name = tensor("op_9302_cast_fp16")]; + tensor var_9306_begin_0 = const()[name = tensor("op_9306_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_9306_end_0 = const()[name = tensor("op_9306_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_9306_end_mask_0 = const()[name = tensor("op_9306_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9306_cast_fp16 = slice_by_index(begin = var_9306_begin_0, end = var_9306_end_0, end_mask = var_9306_end_mask_0, x = value_19_cast_fp16)[name = tensor("op_9306_cast_fp16")]; + tensor var_9310_begin_0 = const()[name = tensor("op_9310_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_9310_end_0 = const()[name = tensor("op_9310_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_9310_end_mask_0 = const()[name = tensor("op_9310_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9310_cast_fp16 = slice_by_index(begin = var_9310_begin_0, end = var_9310_end_0, end_mask = var_9310_end_mask_0, x = value_19_cast_fp16)[name = tensor("op_9310_cast_fp16")]; + tensor var_9314_begin_0 = const()[name = tensor("op_9314_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_9314_end_0 = const()[name = tensor("op_9314_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_9314_end_mask_0 = const()[name = tensor("op_9314_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9314_cast_fp16 = slice_by_index(begin = var_9314_begin_0, end = var_9314_end_0, end_mask = var_9314_end_mask_0, x = value_19_cast_fp16)[name = tensor("op_9314_cast_fp16")]; + tensor var_9318_equation_0 = const()[name = tensor("op_9318_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9318_cast_fp16 = einsum(equation = var_9318_equation_0, values = (var_9224_cast_fp16, var_8890_cast_fp16))[name = tensor("op_9318_cast_fp16")]; + tensor var_9319_to_fp16 = const()[name = tensor("op_9319_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_865_cast_fp16 = mul(x = var_9318_cast_fp16, y = var_9319_to_fp16)[name = tensor("aw_chunk_865_cast_fp16")]; + tensor var_9322_equation_0 = const()[name = tensor("op_9322_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9322_cast_fp16 = einsum(equation = var_9322_equation_0, values = (var_9224_cast_fp16, var_8897_cast_fp16))[name = tensor("op_9322_cast_fp16")]; + tensor var_9323_to_fp16 = const()[name = tensor("op_9323_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_867_cast_fp16 = mul(x = var_9322_cast_fp16, y = var_9323_to_fp16)[name = tensor("aw_chunk_867_cast_fp16")]; + tensor var_9326_equation_0 = const()[name = tensor("op_9326_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9326_cast_fp16 = einsum(equation = var_9326_equation_0, values = (var_9224_cast_fp16, var_8904_cast_fp16))[name = tensor("op_9326_cast_fp16")]; + tensor var_9327_to_fp16 = const()[name = tensor("op_9327_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_869_cast_fp16 = mul(x = var_9326_cast_fp16, y = var_9327_to_fp16)[name = tensor("aw_chunk_869_cast_fp16")]; + tensor var_9330_equation_0 = const()[name = tensor("op_9330_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9330_cast_fp16 = einsum(equation = var_9330_equation_0, values = (var_9224_cast_fp16, var_8911_cast_fp16))[name = tensor("op_9330_cast_fp16")]; + tensor var_9331_to_fp16 = const()[name = tensor("op_9331_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_871_cast_fp16 = mul(x = var_9330_cast_fp16, y = var_9331_to_fp16)[name = tensor("aw_chunk_871_cast_fp16")]; + tensor var_9334_equation_0 = const()[name = tensor("op_9334_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9334_cast_fp16 = einsum(equation = var_9334_equation_0, values = (var_9228_cast_fp16, var_8918_cast_fp16))[name = tensor("op_9334_cast_fp16")]; + tensor var_9335_to_fp16 = const()[name = tensor("op_9335_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_873_cast_fp16 = mul(x = var_9334_cast_fp16, y = var_9335_to_fp16)[name = tensor("aw_chunk_873_cast_fp16")]; + tensor var_9338_equation_0 = const()[name = tensor("op_9338_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9338_cast_fp16 = einsum(equation = var_9338_equation_0, values = (var_9228_cast_fp16, var_8925_cast_fp16))[name = tensor("op_9338_cast_fp16")]; + tensor var_9339_to_fp16 = const()[name = tensor("op_9339_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_875_cast_fp16 = mul(x = var_9338_cast_fp16, y = var_9339_to_fp16)[name = tensor("aw_chunk_875_cast_fp16")]; + tensor var_9342_equation_0 = const()[name = tensor("op_9342_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9342_cast_fp16 = einsum(equation = var_9342_equation_0, values = (var_9228_cast_fp16, var_8932_cast_fp16))[name = tensor("op_9342_cast_fp16")]; + tensor var_9343_to_fp16 = const()[name = tensor("op_9343_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_877_cast_fp16 = mul(x = var_9342_cast_fp16, y = var_9343_to_fp16)[name = tensor("aw_chunk_877_cast_fp16")]; + tensor var_9346_equation_0 = const()[name = tensor("op_9346_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9346_cast_fp16 = einsum(equation = var_9346_equation_0, values = (var_9228_cast_fp16, var_8939_cast_fp16))[name = tensor("op_9346_cast_fp16")]; + tensor var_9347_to_fp16 = const()[name = tensor("op_9347_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_879_cast_fp16 = mul(x = var_9346_cast_fp16, y = var_9347_to_fp16)[name = tensor("aw_chunk_879_cast_fp16")]; + tensor var_9350_equation_0 = const()[name = tensor("op_9350_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9350_cast_fp16 = einsum(equation = var_9350_equation_0, values = (var_9232_cast_fp16, var_8946_cast_fp16))[name = tensor("op_9350_cast_fp16")]; + tensor var_9351_to_fp16 = const()[name = tensor("op_9351_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_881_cast_fp16 = mul(x = var_9350_cast_fp16, y = var_9351_to_fp16)[name = tensor("aw_chunk_881_cast_fp16")]; + tensor var_9354_equation_0 = const()[name = tensor("op_9354_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9354_cast_fp16 = einsum(equation = var_9354_equation_0, values = (var_9232_cast_fp16, var_8953_cast_fp16))[name = tensor("op_9354_cast_fp16")]; + tensor var_9355_to_fp16 = const()[name = tensor("op_9355_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_883_cast_fp16 = mul(x = var_9354_cast_fp16, y = var_9355_to_fp16)[name = tensor("aw_chunk_883_cast_fp16")]; + tensor var_9358_equation_0 = const()[name = tensor("op_9358_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9358_cast_fp16 = einsum(equation = var_9358_equation_0, values = (var_9232_cast_fp16, var_8960_cast_fp16))[name = tensor("op_9358_cast_fp16")]; + tensor var_9359_to_fp16 = const()[name = tensor("op_9359_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_885_cast_fp16 = mul(x = var_9358_cast_fp16, y = var_9359_to_fp16)[name = tensor("aw_chunk_885_cast_fp16")]; + tensor var_9362_equation_0 = const()[name = tensor("op_9362_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9362_cast_fp16 = einsum(equation = var_9362_equation_0, values = (var_9232_cast_fp16, var_8967_cast_fp16))[name = tensor("op_9362_cast_fp16")]; + tensor var_9363_to_fp16 = const()[name = tensor("op_9363_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_887_cast_fp16 = mul(x = var_9362_cast_fp16, y = var_9363_to_fp16)[name = tensor("aw_chunk_887_cast_fp16")]; + tensor var_9366_equation_0 = const()[name = tensor("op_9366_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9366_cast_fp16 = einsum(equation = var_9366_equation_0, values = (var_9236_cast_fp16, var_8974_cast_fp16))[name = tensor("op_9366_cast_fp16")]; + tensor var_9367_to_fp16 = const()[name = tensor("op_9367_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_889_cast_fp16 = mul(x = var_9366_cast_fp16, y = var_9367_to_fp16)[name = tensor("aw_chunk_889_cast_fp16")]; + tensor var_9370_equation_0 = const()[name = tensor("op_9370_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9370_cast_fp16 = einsum(equation = var_9370_equation_0, values = (var_9236_cast_fp16, var_8981_cast_fp16))[name = tensor("op_9370_cast_fp16")]; + tensor var_9371_to_fp16 = const()[name = tensor("op_9371_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_891_cast_fp16 = mul(x = var_9370_cast_fp16, y = var_9371_to_fp16)[name = tensor("aw_chunk_891_cast_fp16")]; + tensor var_9374_equation_0 = const()[name = tensor("op_9374_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9374_cast_fp16 = einsum(equation = var_9374_equation_0, values = (var_9236_cast_fp16, var_8988_cast_fp16))[name = tensor("op_9374_cast_fp16")]; + tensor var_9375_to_fp16 = const()[name = tensor("op_9375_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_893_cast_fp16 = mul(x = var_9374_cast_fp16, y = var_9375_to_fp16)[name = tensor("aw_chunk_893_cast_fp16")]; + tensor var_9378_equation_0 = const()[name = tensor("op_9378_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9378_cast_fp16 = einsum(equation = var_9378_equation_0, values = (var_9236_cast_fp16, var_8995_cast_fp16))[name = tensor("op_9378_cast_fp16")]; + tensor var_9379_to_fp16 = const()[name = tensor("op_9379_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_895_cast_fp16 = mul(x = var_9378_cast_fp16, y = var_9379_to_fp16)[name = tensor("aw_chunk_895_cast_fp16")]; + tensor var_9382_equation_0 = const()[name = tensor("op_9382_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9382_cast_fp16 = einsum(equation = var_9382_equation_0, values = (var_9240_cast_fp16, var_9002_cast_fp16))[name = tensor("op_9382_cast_fp16")]; + tensor var_9383_to_fp16 = const()[name = tensor("op_9383_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_897_cast_fp16 = mul(x = var_9382_cast_fp16, y = var_9383_to_fp16)[name = tensor("aw_chunk_897_cast_fp16")]; + tensor var_9386_equation_0 = const()[name = tensor("op_9386_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9386_cast_fp16 = einsum(equation = var_9386_equation_0, values = (var_9240_cast_fp16, var_9009_cast_fp16))[name = tensor("op_9386_cast_fp16")]; + tensor var_9387_to_fp16 = const()[name = tensor("op_9387_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_899_cast_fp16 = mul(x = var_9386_cast_fp16, y = var_9387_to_fp16)[name = tensor("aw_chunk_899_cast_fp16")]; + tensor var_9390_equation_0 = const()[name = tensor("op_9390_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9390_cast_fp16 = einsum(equation = var_9390_equation_0, values = (var_9240_cast_fp16, var_9016_cast_fp16))[name = tensor("op_9390_cast_fp16")]; + tensor var_9391_to_fp16 = const()[name = tensor("op_9391_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_901_cast_fp16 = mul(x = var_9390_cast_fp16, y = var_9391_to_fp16)[name = tensor("aw_chunk_901_cast_fp16")]; + tensor var_9394_equation_0 = const()[name = tensor("op_9394_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9394_cast_fp16 = einsum(equation = var_9394_equation_0, values = (var_9240_cast_fp16, var_9023_cast_fp16))[name = tensor("op_9394_cast_fp16")]; + tensor var_9395_to_fp16 = const()[name = tensor("op_9395_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_903_cast_fp16 = mul(x = var_9394_cast_fp16, y = var_9395_to_fp16)[name = tensor("aw_chunk_903_cast_fp16")]; + tensor var_9398_equation_0 = const()[name = tensor("op_9398_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9398_cast_fp16 = einsum(equation = var_9398_equation_0, values = (var_9244_cast_fp16, var_9030_cast_fp16))[name = tensor("op_9398_cast_fp16")]; + tensor var_9399_to_fp16 = const()[name = tensor("op_9399_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_905_cast_fp16 = mul(x = var_9398_cast_fp16, y = var_9399_to_fp16)[name = tensor("aw_chunk_905_cast_fp16")]; + tensor var_9402_equation_0 = const()[name = tensor("op_9402_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9402_cast_fp16 = einsum(equation = var_9402_equation_0, values = (var_9244_cast_fp16, var_9037_cast_fp16))[name = tensor("op_9402_cast_fp16")]; + tensor var_9403_to_fp16 = const()[name = tensor("op_9403_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_907_cast_fp16 = mul(x = var_9402_cast_fp16, y = var_9403_to_fp16)[name = tensor("aw_chunk_907_cast_fp16")]; + tensor var_9406_equation_0 = const()[name = tensor("op_9406_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9406_cast_fp16 = einsum(equation = var_9406_equation_0, values = (var_9244_cast_fp16, var_9044_cast_fp16))[name = tensor("op_9406_cast_fp16")]; + tensor var_9407_to_fp16 = const()[name = tensor("op_9407_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_909_cast_fp16 = mul(x = var_9406_cast_fp16, y = var_9407_to_fp16)[name = tensor("aw_chunk_909_cast_fp16")]; + tensor var_9410_equation_0 = const()[name = tensor("op_9410_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9410_cast_fp16 = einsum(equation = var_9410_equation_0, values = (var_9244_cast_fp16, var_9051_cast_fp16))[name = tensor("op_9410_cast_fp16")]; + tensor var_9411_to_fp16 = const()[name = tensor("op_9411_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_911_cast_fp16 = mul(x = var_9410_cast_fp16, y = var_9411_to_fp16)[name = tensor("aw_chunk_911_cast_fp16")]; + tensor var_9414_equation_0 = const()[name = tensor("op_9414_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9414_cast_fp16 = einsum(equation = var_9414_equation_0, values = (var_9248_cast_fp16, var_9058_cast_fp16))[name = tensor("op_9414_cast_fp16")]; + tensor var_9415_to_fp16 = const()[name = tensor("op_9415_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_913_cast_fp16 = mul(x = var_9414_cast_fp16, y = var_9415_to_fp16)[name = tensor("aw_chunk_913_cast_fp16")]; + tensor var_9418_equation_0 = const()[name = tensor("op_9418_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9418_cast_fp16 = einsum(equation = var_9418_equation_0, values = (var_9248_cast_fp16, var_9065_cast_fp16))[name = tensor("op_9418_cast_fp16")]; + tensor var_9419_to_fp16 = const()[name = tensor("op_9419_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_915_cast_fp16 = mul(x = var_9418_cast_fp16, y = var_9419_to_fp16)[name = tensor("aw_chunk_915_cast_fp16")]; + tensor var_9422_equation_0 = const()[name = tensor("op_9422_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9422_cast_fp16 = einsum(equation = var_9422_equation_0, values = (var_9248_cast_fp16, var_9072_cast_fp16))[name = tensor("op_9422_cast_fp16")]; + tensor var_9423_to_fp16 = const()[name = tensor("op_9423_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_917_cast_fp16 = mul(x = var_9422_cast_fp16, y = var_9423_to_fp16)[name = tensor("aw_chunk_917_cast_fp16")]; + tensor var_9426_equation_0 = const()[name = tensor("op_9426_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9426_cast_fp16 = einsum(equation = var_9426_equation_0, values = (var_9248_cast_fp16, var_9079_cast_fp16))[name = tensor("op_9426_cast_fp16")]; + tensor var_9427_to_fp16 = const()[name = tensor("op_9427_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_919_cast_fp16 = mul(x = var_9426_cast_fp16, y = var_9427_to_fp16)[name = tensor("aw_chunk_919_cast_fp16")]; + tensor var_9430_equation_0 = const()[name = tensor("op_9430_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9430_cast_fp16 = einsum(equation = var_9430_equation_0, values = (var_9252_cast_fp16, var_9086_cast_fp16))[name = tensor("op_9430_cast_fp16")]; + tensor var_9431_to_fp16 = const()[name = tensor("op_9431_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_921_cast_fp16 = mul(x = var_9430_cast_fp16, y = var_9431_to_fp16)[name = tensor("aw_chunk_921_cast_fp16")]; + tensor var_9434_equation_0 = const()[name = tensor("op_9434_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9434_cast_fp16 = einsum(equation = var_9434_equation_0, values = (var_9252_cast_fp16, var_9093_cast_fp16))[name = tensor("op_9434_cast_fp16")]; + tensor var_9435_to_fp16 = const()[name = tensor("op_9435_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_923_cast_fp16 = mul(x = var_9434_cast_fp16, y = var_9435_to_fp16)[name = tensor("aw_chunk_923_cast_fp16")]; + tensor var_9438_equation_0 = const()[name = tensor("op_9438_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9438_cast_fp16 = einsum(equation = var_9438_equation_0, values = (var_9252_cast_fp16, var_9100_cast_fp16))[name = tensor("op_9438_cast_fp16")]; + tensor var_9439_to_fp16 = const()[name = tensor("op_9439_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_925_cast_fp16 = mul(x = var_9438_cast_fp16, y = var_9439_to_fp16)[name = tensor("aw_chunk_925_cast_fp16")]; + tensor var_9442_equation_0 = const()[name = tensor("op_9442_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9442_cast_fp16 = einsum(equation = var_9442_equation_0, values = (var_9252_cast_fp16, var_9107_cast_fp16))[name = tensor("op_9442_cast_fp16")]; + tensor var_9443_to_fp16 = const()[name = tensor("op_9443_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_927_cast_fp16 = mul(x = var_9442_cast_fp16, y = var_9443_to_fp16)[name = tensor("aw_chunk_927_cast_fp16")]; + tensor var_9446_equation_0 = const()[name = tensor("op_9446_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9446_cast_fp16 = einsum(equation = var_9446_equation_0, values = (var_9256_cast_fp16, var_9114_cast_fp16))[name = tensor("op_9446_cast_fp16")]; + tensor var_9447_to_fp16 = const()[name = tensor("op_9447_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_929_cast_fp16 = mul(x = var_9446_cast_fp16, y = var_9447_to_fp16)[name = tensor("aw_chunk_929_cast_fp16")]; + tensor var_9450_equation_0 = const()[name = tensor("op_9450_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9450_cast_fp16 = einsum(equation = var_9450_equation_0, values = (var_9256_cast_fp16, var_9121_cast_fp16))[name = tensor("op_9450_cast_fp16")]; + tensor var_9451_to_fp16 = const()[name = tensor("op_9451_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_931_cast_fp16 = mul(x = var_9450_cast_fp16, y = var_9451_to_fp16)[name = tensor("aw_chunk_931_cast_fp16")]; + tensor var_9454_equation_0 = const()[name = tensor("op_9454_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9454_cast_fp16 = einsum(equation = var_9454_equation_0, values = (var_9256_cast_fp16, var_9128_cast_fp16))[name = tensor("op_9454_cast_fp16")]; + tensor var_9455_to_fp16 = const()[name = tensor("op_9455_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_933_cast_fp16 = mul(x = var_9454_cast_fp16, y = var_9455_to_fp16)[name = tensor("aw_chunk_933_cast_fp16")]; + tensor var_9458_equation_0 = const()[name = tensor("op_9458_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9458_cast_fp16 = einsum(equation = var_9458_equation_0, values = (var_9256_cast_fp16, var_9135_cast_fp16))[name = tensor("op_9458_cast_fp16")]; + tensor var_9459_to_fp16 = const()[name = tensor("op_9459_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_935_cast_fp16 = mul(x = var_9458_cast_fp16, y = var_9459_to_fp16)[name = tensor("aw_chunk_935_cast_fp16")]; + tensor var_9462_equation_0 = const()[name = tensor("op_9462_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9462_cast_fp16 = einsum(equation = var_9462_equation_0, values = (var_9260_cast_fp16, var_9142_cast_fp16))[name = tensor("op_9462_cast_fp16")]; + tensor var_9463_to_fp16 = const()[name = tensor("op_9463_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_937_cast_fp16 = mul(x = var_9462_cast_fp16, y = var_9463_to_fp16)[name = tensor("aw_chunk_937_cast_fp16")]; + tensor var_9466_equation_0 = const()[name = tensor("op_9466_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9466_cast_fp16 = einsum(equation = var_9466_equation_0, values = (var_9260_cast_fp16, var_9149_cast_fp16))[name = tensor("op_9466_cast_fp16")]; + tensor var_9467_to_fp16 = const()[name = tensor("op_9467_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_939_cast_fp16 = mul(x = var_9466_cast_fp16, y = var_9467_to_fp16)[name = tensor("aw_chunk_939_cast_fp16")]; + tensor var_9470_equation_0 = const()[name = tensor("op_9470_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9470_cast_fp16 = einsum(equation = var_9470_equation_0, values = (var_9260_cast_fp16, var_9156_cast_fp16))[name = tensor("op_9470_cast_fp16")]; + tensor var_9471_to_fp16 = const()[name = tensor("op_9471_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_941_cast_fp16 = mul(x = var_9470_cast_fp16, y = var_9471_to_fp16)[name = tensor("aw_chunk_941_cast_fp16")]; + tensor var_9474_equation_0 = const()[name = tensor("op_9474_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9474_cast_fp16 = einsum(equation = var_9474_equation_0, values = (var_9260_cast_fp16, var_9163_cast_fp16))[name = tensor("op_9474_cast_fp16")]; + tensor var_9475_to_fp16 = const()[name = tensor("op_9475_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_943_cast_fp16 = mul(x = var_9474_cast_fp16, y = var_9475_to_fp16)[name = tensor("aw_chunk_943_cast_fp16")]; + tensor var_9478_equation_0 = const()[name = tensor("op_9478_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9478_cast_fp16 = einsum(equation = var_9478_equation_0, values = (var_9264_cast_fp16, var_9170_cast_fp16))[name = tensor("op_9478_cast_fp16")]; + tensor var_9479_to_fp16 = const()[name = tensor("op_9479_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_945_cast_fp16 = mul(x = var_9478_cast_fp16, y = var_9479_to_fp16)[name = tensor("aw_chunk_945_cast_fp16")]; + tensor var_9482_equation_0 = const()[name = tensor("op_9482_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9482_cast_fp16 = einsum(equation = var_9482_equation_0, values = (var_9264_cast_fp16, var_9177_cast_fp16))[name = tensor("op_9482_cast_fp16")]; + tensor var_9483_to_fp16 = const()[name = tensor("op_9483_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_947_cast_fp16 = mul(x = var_9482_cast_fp16, y = var_9483_to_fp16)[name = tensor("aw_chunk_947_cast_fp16")]; + tensor var_9486_equation_0 = const()[name = tensor("op_9486_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9486_cast_fp16 = einsum(equation = var_9486_equation_0, values = (var_9264_cast_fp16, var_9184_cast_fp16))[name = tensor("op_9486_cast_fp16")]; + tensor var_9487_to_fp16 = const()[name = tensor("op_9487_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_949_cast_fp16 = mul(x = var_9486_cast_fp16, y = var_9487_to_fp16)[name = tensor("aw_chunk_949_cast_fp16")]; + tensor var_9490_equation_0 = const()[name = tensor("op_9490_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9490_cast_fp16 = einsum(equation = var_9490_equation_0, values = (var_9264_cast_fp16, var_9191_cast_fp16))[name = tensor("op_9490_cast_fp16")]; + tensor var_9491_to_fp16 = const()[name = tensor("op_9491_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_951_cast_fp16 = mul(x = var_9490_cast_fp16, y = var_9491_to_fp16)[name = tensor("aw_chunk_951_cast_fp16")]; + tensor var_9494_equation_0 = const()[name = tensor("op_9494_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9494_cast_fp16 = einsum(equation = var_9494_equation_0, values = (var_9268_cast_fp16, var_9198_cast_fp16))[name = tensor("op_9494_cast_fp16")]; + tensor var_9495_to_fp16 = const()[name = tensor("op_9495_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_953_cast_fp16 = mul(x = var_9494_cast_fp16, y = var_9495_to_fp16)[name = tensor("aw_chunk_953_cast_fp16")]; + tensor var_9498_equation_0 = const()[name = tensor("op_9498_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9498_cast_fp16 = einsum(equation = var_9498_equation_0, values = (var_9268_cast_fp16, var_9205_cast_fp16))[name = tensor("op_9498_cast_fp16")]; + tensor var_9499_to_fp16 = const()[name = tensor("op_9499_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_955_cast_fp16 = mul(x = var_9498_cast_fp16, y = var_9499_to_fp16)[name = tensor("aw_chunk_955_cast_fp16")]; + tensor var_9502_equation_0 = const()[name = tensor("op_9502_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9502_cast_fp16 = einsum(equation = var_9502_equation_0, values = (var_9268_cast_fp16, var_9212_cast_fp16))[name = tensor("op_9502_cast_fp16")]; + tensor var_9503_to_fp16 = const()[name = tensor("op_9503_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_957_cast_fp16 = mul(x = var_9502_cast_fp16, y = var_9503_to_fp16)[name = tensor("aw_chunk_957_cast_fp16")]; + tensor var_9506_equation_0 = const()[name = tensor("op_9506_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_9506_cast_fp16 = einsum(equation = var_9506_equation_0, values = (var_9268_cast_fp16, var_9219_cast_fp16))[name = tensor("op_9506_cast_fp16")]; + tensor var_9507_to_fp16 = const()[name = tensor("op_9507_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_959_cast_fp16 = mul(x = var_9506_cast_fp16, y = var_9507_to_fp16)[name = tensor("aw_chunk_959_cast_fp16")]; + tensor var_9509_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_865_cast_fp16)[name = tensor("op_9509_cast_fp16")]; + tensor var_9510_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_867_cast_fp16)[name = tensor("op_9510_cast_fp16")]; + tensor var_9511_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_869_cast_fp16)[name = tensor("op_9511_cast_fp16")]; + tensor var_9512_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_871_cast_fp16)[name = tensor("op_9512_cast_fp16")]; + tensor var_9513_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_873_cast_fp16)[name = tensor("op_9513_cast_fp16")]; + tensor var_9514_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_875_cast_fp16)[name = tensor("op_9514_cast_fp16")]; + tensor var_9515_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_877_cast_fp16)[name = tensor("op_9515_cast_fp16")]; + tensor var_9516_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_879_cast_fp16)[name = tensor("op_9516_cast_fp16")]; + tensor var_9517_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_881_cast_fp16)[name = tensor("op_9517_cast_fp16")]; + tensor var_9518_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_883_cast_fp16)[name = tensor("op_9518_cast_fp16")]; + tensor var_9519_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_885_cast_fp16)[name = tensor("op_9519_cast_fp16")]; + tensor var_9520_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_887_cast_fp16)[name = tensor("op_9520_cast_fp16")]; + tensor var_9521_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_889_cast_fp16)[name = tensor("op_9521_cast_fp16")]; + tensor var_9522_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_891_cast_fp16)[name = tensor("op_9522_cast_fp16")]; + tensor var_9523_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_893_cast_fp16)[name = tensor("op_9523_cast_fp16")]; + tensor var_9524_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_895_cast_fp16)[name = tensor("op_9524_cast_fp16")]; + tensor var_9525_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_897_cast_fp16)[name = tensor("op_9525_cast_fp16")]; + tensor var_9526_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_899_cast_fp16)[name = tensor("op_9526_cast_fp16")]; + tensor var_9527_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_901_cast_fp16)[name = tensor("op_9527_cast_fp16")]; + tensor var_9528_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_903_cast_fp16)[name = tensor("op_9528_cast_fp16")]; + tensor var_9529_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_905_cast_fp16)[name = tensor("op_9529_cast_fp16")]; + tensor var_9530_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_907_cast_fp16)[name = tensor("op_9530_cast_fp16")]; + tensor var_9531_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_909_cast_fp16)[name = tensor("op_9531_cast_fp16")]; + tensor var_9532_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_911_cast_fp16)[name = tensor("op_9532_cast_fp16")]; + tensor var_9533_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_913_cast_fp16)[name = tensor("op_9533_cast_fp16")]; + tensor var_9534_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_915_cast_fp16)[name = tensor("op_9534_cast_fp16")]; + tensor var_9535_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_917_cast_fp16)[name = tensor("op_9535_cast_fp16")]; + tensor var_9536_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_919_cast_fp16)[name = tensor("op_9536_cast_fp16")]; + tensor var_9537_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_921_cast_fp16)[name = tensor("op_9537_cast_fp16")]; + tensor var_9538_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_923_cast_fp16)[name = tensor("op_9538_cast_fp16")]; + tensor var_9539_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_925_cast_fp16)[name = tensor("op_9539_cast_fp16")]; + tensor var_9540_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_927_cast_fp16)[name = tensor("op_9540_cast_fp16")]; + tensor var_9541_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_929_cast_fp16)[name = tensor("op_9541_cast_fp16")]; + tensor var_9542_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_931_cast_fp16)[name = tensor("op_9542_cast_fp16")]; + tensor var_9543_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_933_cast_fp16)[name = tensor("op_9543_cast_fp16")]; + tensor var_9544_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_935_cast_fp16)[name = tensor("op_9544_cast_fp16")]; + tensor var_9545_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_937_cast_fp16)[name = tensor("op_9545_cast_fp16")]; + tensor var_9546_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_939_cast_fp16)[name = tensor("op_9546_cast_fp16")]; + tensor var_9547_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_941_cast_fp16)[name = tensor("op_9547_cast_fp16")]; + tensor var_9548_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_943_cast_fp16)[name = tensor("op_9548_cast_fp16")]; + tensor var_9549_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_945_cast_fp16)[name = tensor("op_9549_cast_fp16")]; + tensor var_9550_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_947_cast_fp16)[name = tensor("op_9550_cast_fp16")]; + tensor var_9551_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_949_cast_fp16)[name = tensor("op_9551_cast_fp16")]; + tensor var_9552_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_951_cast_fp16)[name = tensor("op_9552_cast_fp16")]; + tensor var_9553_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_953_cast_fp16)[name = tensor("op_9553_cast_fp16")]; + tensor var_9554_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_955_cast_fp16)[name = tensor("op_9554_cast_fp16")]; + tensor var_9555_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_957_cast_fp16)[name = tensor("op_9555_cast_fp16")]; + tensor var_9556_cast_fp16 = softmax(axis = var_8782, x = aw_chunk_959_cast_fp16)[name = tensor("op_9556_cast_fp16")]; + tensor var_9558_equation_0 = const()[name = tensor("op_9558_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9558_cast_fp16 = einsum(equation = var_9558_equation_0, values = (var_9270_cast_fp16, var_9509_cast_fp16))[name = tensor("op_9558_cast_fp16")]; + tensor var_9560_equation_0 = const()[name = tensor("op_9560_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9560_cast_fp16 = einsum(equation = var_9560_equation_0, values = (var_9270_cast_fp16, var_9510_cast_fp16))[name = tensor("op_9560_cast_fp16")]; + tensor var_9562_equation_0 = const()[name = tensor("op_9562_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9562_cast_fp16 = einsum(equation = var_9562_equation_0, values = (var_9270_cast_fp16, var_9511_cast_fp16))[name = tensor("op_9562_cast_fp16")]; + tensor var_9564_equation_0 = const()[name = tensor("op_9564_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9564_cast_fp16 = einsum(equation = var_9564_equation_0, values = (var_9270_cast_fp16, var_9512_cast_fp16))[name = tensor("op_9564_cast_fp16")]; + tensor var_9566_equation_0 = const()[name = tensor("op_9566_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9566_cast_fp16 = einsum(equation = var_9566_equation_0, values = (var_9274_cast_fp16, var_9513_cast_fp16))[name = tensor("op_9566_cast_fp16")]; + tensor var_9568_equation_0 = const()[name = tensor("op_9568_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9568_cast_fp16 = einsum(equation = var_9568_equation_0, values = (var_9274_cast_fp16, var_9514_cast_fp16))[name = tensor("op_9568_cast_fp16")]; + tensor var_9570_equation_0 = const()[name = tensor("op_9570_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9570_cast_fp16 = einsum(equation = var_9570_equation_0, values = (var_9274_cast_fp16, var_9515_cast_fp16))[name = tensor("op_9570_cast_fp16")]; + tensor var_9572_equation_0 = const()[name = tensor("op_9572_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9572_cast_fp16 = einsum(equation = var_9572_equation_0, values = (var_9274_cast_fp16, var_9516_cast_fp16))[name = tensor("op_9572_cast_fp16")]; + tensor var_9574_equation_0 = const()[name = tensor("op_9574_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9574_cast_fp16 = einsum(equation = var_9574_equation_0, values = (var_9278_cast_fp16, var_9517_cast_fp16))[name = tensor("op_9574_cast_fp16")]; + tensor var_9576_equation_0 = const()[name = tensor("op_9576_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9576_cast_fp16 = einsum(equation = var_9576_equation_0, values = (var_9278_cast_fp16, var_9518_cast_fp16))[name = tensor("op_9576_cast_fp16")]; + tensor var_9578_equation_0 = const()[name = tensor("op_9578_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9578_cast_fp16 = einsum(equation = var_9578_equation_0, values = (var_9278_cast_fp16, var_9519_cast_fp16))[name = tensor("op_9578_cast_fp16")]; + tensor var_9580_equation_0 = const()[name = tensor("op_9580_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9580_cast_fp16 = einsum(equation = var_9580_equation_0, values = (var_9278_cast_fp16, var_9520_cast_fp16))[name = tensor("op_9580_cast_fp16")]; + tensor var_9582_equation_0 = const()[name = tensor("op_9582_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9582_cast_fp16 = einsum(equation = var_9582_equation_0, values = (var_9282_cast_fp16, var_9521_cast_fp16))[name = tensor("op_9582_cast_fp16")]; + tensor var_9584_equation_0 = const()[name = tensor("op_9584_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9584_cast_fp16 = einsum(equation = var_9584_equation_0, values = (var_9282_cast_fp16, var_9522_cast_fp16))[name = tensor("op_9584_cast_fp16")]; + tensor var_9586_equation_0 = const()[name = tensor("op_9586_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9586_cast_fp16 = einsum(equation = var_9586_equation_0, values = (var_9282_cast_fp16, var_9523_cast_fp16))[name = tensor("op_9586_cast_fp16")]; + tensor var_9588_equation_0 = const()[name = tensor("op_9588_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9588_cast_fp16 = einsum(equation = var_9588_equation_0, values = (var_9282_cast_fp16, var_9524_cast_fp16))[name = tensor("op_9588_cast_fp16")]; + tensor var_9590_equation_0 = const()[name = tensor("op_9590_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9590_cast_fp16 = einsum(equation = var_9590_equation_0, values = (var_9286_cast_fp16, var_9525_cast_fp16))[name = tensor("op_9590_cast_fp16")]; + tensor var_9592_equation_0 = const()[name = tensor("op_9592_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9592_cast_fp16 = einsum(equation = var_9592_equation_0, values = (var_9286_cast_fp16, var_9526_cast_fp16))[name = tensor("op_9592_cast_fp16")]; + tensor var_9594_equation_0 = const()[name = tensor("op_9594_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9594_cast_fp16 = einsum(equation = var_9594_equation_0, values = (var_9286_cast_fp16, var_9527_cast_fp16))[name = tensor("op_9594_cast_fp16")]; + tensor var_9596_equation_0 = const()[name = tensor("op_9596_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9596_cast_fp16 = einsum(equation = var_9596_equation_0, values = (var_9286_cast_fp16, var_9528_cast_fp16))[name = tensor("op_9596_cast_fp16")]; + tensor var_9598_equation_0 = const()[name = tensor("op_9598_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9598_cast_fp16 = einsum(equation = var_9598_equation_0, values = (var_9290_cast_fp16, var_9529_cast_fp16))[name = tensor("op_9598_cast_fp16")]; + tensor var_9600_equation_0 = const()[name = tensor("op_9600_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9600_cast_fp16 = einsum(equation = var_9600_equation_0, values = (var_9290_cast_fp16, var_9530_cast_fp16))[name = tensor("op_9600_cast_fp16")]; + tensor var_9602_equation_0 = const()[name = tensor("op_9602_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9602_cast_fp16 = einsum(equation = var_9602_equation_0, values = (var_9290_cast_fp16, var_9531_cast_fp16))[name = tensor("op_9602_cast_fp16")]; + tensor var_9604_equation_0 = const()[name = tensor("op_9604_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9604_cast_fp16 = einsum(equation = var_9604_equation_0, values = (var_9290_cast_fp16, var_9532_cast_fp16))[name = tensor("op_9604_cast_fp16")]; + tensor var_9606_equation_0 = const()[name = tensor("op_9606_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9606_cast_fp16 = einsum(equation = var_9606_equation_0, values = (var_9294_cast_fp16, var_9533_cast_fp16))[name = tensor("op_9606_cast_fp16")]; + tensor var_9608_equation_0 = const()[name = tensor("op_9608_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9608_cast_fp16 = einsum(equation = var_9608_equation_0, values = (var_9294_cast_fp16, var_9534_cast_fp16))[name = tensor("op_9608_cast_fp16")]; + tensor var_9610_equation_0 = const()[name = tensor("op_9610_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9610_cast_fp16 = einsum(equation = var_9610_equation_0, values = (var_9294_cast_fp16, var_9535_cast_fp16))[name = tensor("op_9610_cast_fp16")]; + tensor var_9612_equation_0 = const()[name = tensor("op_9612_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9612_cast_fp16 = einsum(equation = var_9612_equation_0, values = (var_9294_cast_fp16, var_9536_cast_fp16))[name = tensor("op_9612_cast_fp16")]; + tensor var_9614_equation_0 = const()[name = tensor("op_9614_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9614_cast_fp16 = einsum(equation = var_9614_equation_0, values = (var_9298_cast_fp16, var_9537_cast_fp16))[name = tensor("op_9614_cast_fp16")]; + tensor var_9616_equation_0 = const()[name = tensor("op_9616_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9616_cast_fp16 = einsum(equation = var_9616_equation_0, values = (var_9298_cast_fp16, var_9538_cast_fp16))[name = tensor("op_9616_cast_fp16")]; + tensor var_9618_equation_0 = const()[name = tensor("op_9618_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9618_cast_fp16 = einsum(equation = var_9618_equation_0, values = (var_9298_cast_fp16, var_9539_cast_fp16))[name = tensor("op_9618_cast_fp16")]; + tensor var_9620_equation_0 = const()[name = tensor("op_9620_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9620_cast_fp16 = einsum(equation = var_9620_equation_0, values = (var_9298_cast_fp16, var_9540_cast_fp16))[name = tensor("op_9620_cast_fp16")]; + tensor var_9622_equation_0 = const()[name = tensor("op_9622_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9622_cast_fp16 = einsum(equation = var_9622_equation_0, values = (var_9302_cast_fp16, var_9541_cast_fp16))[name = tensor("op_9622_cast_fp16")]; + tensor var_9624_equation_0 = const()[name = tensor("op_9624_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9624_cast_fp16 = einsum(equation = var_9624_equation_0, values = (var_9302_cast_fp16, var_9542_cast_fp16))[name = tensor("op_9624_cast_fp16")]; + tensor var_9626_equation_0 = const()[name = tensor("op_9626_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9626_cast_fp16 = einsum(equation = var_9626_equation_0, values = (var_9302_cast_fp16, var_9543_cast_fp16))[name = tensor("op_9626_cast_fp16")]; + tensor var_9628_equation_0 = const()[name = tensor("op_9628_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9628_cast_fp16 = einsum(equation = var_9628_equation_0, values = (var_9302_cast_fp16, var_9544_cast_fp16))[name = tensor("op_9628_cast_fp16")]; + tensor var_9630_equation_0 = const()[name = tensor("op_9630_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9630_cast_fp16 = einsum(equation = var_9630_equation_0, values = (var_9306_cast_fp16, var_9545_cast_fp16))[name = tensor("op_9630_cast_fp16")]; + tensor var_9632_equation_0 = const()[name = tensor("op_9632_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9632_cast_fp16 = einsum(equation = var_9632_equation_0, values = (var_9306_cast_fp16, var_9546_cast_fp16))[name = tensor("op_9632_cast_fp16")]; + tensor var_9634_equation_0 = const()[name = tensor("op_9634_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9634_cast_fp16 = einsum(equation = var_9634_equation_0, values = (var_9306_cast_fp16, var_9547_cast_fp16))[name = tensor("op_9634_cast_fp16")]; + tensor var_9636_equation_0 = const()[name = tensor("op_9636_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9636_cast_fp16 = einsum(equation = var_9636_equation_0, values = (var_9306_cast_fp16, var_9548_cast_fp16))[name = tensor("op_9636_cast_fp16")]; + tensor var_9638_equation_0 = const()[name = tensor("op_9638_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9638_cast_fp16 = einsum(equation = var_9638_equation_0, values = (var_9310_cast_fp16, var_9549_cast_fp16))[name = tensor("op_9638_cast_fp16")]; + tensor var_9640_equation_0 = const()[name = tensor("op_9640_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9640_cast_fp16 = einsum(equation = var_9640_equation_0, values = (var_9310_cast_fp16, var_9550_cast_fp16))[name = tensor("op_9640_cast_fp16")]; + tensor var_9642_equation_0 = const()[name = tensor("op_9642_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9642_cast_fp16 = einsum(equation = var_9642_equation_0, values = (var_9310_cast_fp16, var_9551_cast_fp16))[name = tensor("op_9642_cast_fp16")]; + tensor var_9644_equation_0 = const()[name = tensor("op_9644_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9644_cast_fp16 = einsum(equation = var_9644_equation_0, values = (var_9310_cast_fp16, var_9552_cast_fp16))[name = tensor("op_9644_cast_fp16")]; + tensor var_9646_equation_0 = const()[name = tensor("op_9646_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9646_cast_fp16 = einsum(equation = var_9646_equation_0, values = (var_9314_cast_fp16, var_9553_cast_fp16))[name = tensor("op_9646_cast_fp16")]; + tensor var_9648_equation_0 = const()[name = tensor("op_9648_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9648_cast_fp16 = einsum(equation = var_9648_equation_0, values = (var_9314_cast_fp16, var_9554_cast_fp16))[name = tensor("op_9648_cast_fp16")]; + tensor var_9650_equation_0 = const()[name = tensor("op_9650_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9650_cast_fp16 = einsum(equation = var_9650_equation_0, values = (var_9314_cast_fp16, var_9555_cast_fp16))[name = tensor("op_9650_cast_fp16")]; + tensor var_9652_equation_0 = const()[name = tensor("op_9652_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_9652_cast_fp16 = einsum(equation = var_9652_equation_0, values = (var_9314_cast_fp16, var_9556_cast_fp16))[name = tensor("op_9652_cast_fp16")]; + tensor var_9654_interleave_0 = const()[name = tensor("op_9654_interleave_0"), val = tensor(false)]; + tensor var_9654_cast_fp16 = concat(axis = var_8765, interleave = var_9654_interleave_0, values = (var_9558_cast_fp16, var_9560_cast_fp16, var_9562_cast_fp16, var_9564_cast_fp16))[name = tensor("op_9654_cast_fp16")]; + tensor var_9656_interleave_0 = const()[name = tensor("op_9656_interleave_0"), val = tensor(false)]; + tensor var_9656_cast_fp16 = concat(axis = var_8765, interleave = var_9656_interleave_0, values = (var_9566_cast_fp16, var_9568_cast_fp16, var_9570_cast_fp16, var_9572_cast_fp16))[name = tensor("op_9656_cast_fp16")]; + tensor var_9658_interleave_0 = const()[name = tensor("op_9658_interleave_0"), val = tensor(false)]; + tensor var_9658_cast_fp16 = concat(axis = var_8765, interleave = var_9658_interleave_0, values = (var_9574_cast_fp16, var_9576_cast_fp16, var_9578_cast_fp16, var_9580_cast_fp16))[name = tensor("op_9658_cast_fp16")]; + tensor var_9660_interleave_0 = const()[name = tensor("op_9660_interleave_0"), val = tensor(false)]; + tensor var_9660_cast_fp16 = concat(axis = var_8765, interleave = var_9660_interleave_0, values = (var_9582_cast_fp16, var_9584_cast_fp16, var_9586_cast_fp16, var_9588_cast_fp16))[name = tensor("op_9660_cast_fp16")]; + tensor var_9662_interleave_0 = const()[name = tensor("op_9662_interleave_0"), val = tensor(false)]; + tensor var_9662_cast_fp16 = concat(axis = var_8765, interleave = var_9662_interleave_0, values = (var_9590_cast_fp16, var_9592_cast_fp16, var_9594_cast_fp16, var_9596_cast_fp16))[name = tensor("op_9662_cast_fp16")]; + tensor var_9664_interleave_0 = const()[name = tensor("op_9664_interleave_0"), val = tensor(false)]; + tensor var_9664_cast_fp16 = concat(axis = var_8765, interleave = var_9664_interleave_0, values = (var_9598_cast_fp16, var_9600_cast_fp16, var_9602_cast_fp16, var_9604_cast_fp16))[name = tensor("op_9664_cast_fp16")]; + tensor var_9666_interleave_0 = const()[name = tensor("op_9666_interleave_0"), val = tensor(false)]; + tensor var_9666_cast_fp16 = concat(axis = var_8765, interleave = var_9666_interleave_0, values = (var_9606_cast_fp16, var_9608_cast_fp16, var_9610_cast_fp16, var_9612_cast_fp16))[name = tensor("op_9666_cast_fp16")]; + tensor var_9668_interleave_0 = const()[name = tensor("op_9668_interleave_0"), val = tensor(false)]; + tensor var_9668_cast_fp16 = concat(axis = var_8765, interleave = var_9668_interleave_0, values = (var_9614_cast_fp16, var_9616_cast_fp16, var_9618_cast_fp16, var_9620_cast_fp16))[name = tensor("op_9668_cast_fp16")]; + tensor var_9670_interleave_0 = const()[name = tensor("op_9670_interleave_0"), val = tensor(false)]; + tensor var_9670_cast_fp16 = concat(axis = var_8765, interleave = var_9670_interleave_0, values = (var_9622_cast_fp16, var_9624_cast_fp16, var_9626_cast_fp16, var_9628_cast_fp16))[name = tensor("op_9670_cast_fp16")]; + tensor var_9672_interleave_0 = const()[name = tensor("op_9672_interleave_0"), val = tensor(false)]; + tensor var_9672_cast_fp16 = concat(axis = var_8765, interleave = var_9672_interleave_0, values = (var_9630_cast_fp16, var_9632_cast_fp16, var_9634_cast_fp16, var_9636_cast_fp16))[name = tensor("op_9672_cast_fp16")]; + tensor var_9674_interleave_0 = const()[name = tensor("op_9674_interleave_0"), val = tensor(false)]; + tensor var_9674_cast_fp16 = concat(axis = var_8765, interleave = var_9674_interleave_0, values = (var_9638_cast_fp16, var_9640_cast_fp16, var_9642_cast_fp16, var_9644_cast_fp16))[name = tensor("op_9674_cast_fp16")]; + tensor var_9676_interleave_0 = const()[name = tensor("op_9676_interleave_0"), val = tensor(false)]; + tensor var_9676_cast_fp16 = concat(axis = var_8765, interleave = var_9676_interleave_0, values = (var_9646_cast_fp16, var_9648_cast_fp16, var_9650_cast_fp16, var_9652_cast_fp16))[name = tensor("op_9676_cast_fp16")]; + tensor input_73_interleave_0 = const()[name = tensor("input_73_interleave_0"), val = tensor(false)]; + tensor input_73_cast_fp16 = concat(axis = var_8782, interleave = input_73_interleave_0, values = (var_9654_cast_fp16, var_9656_cast_fp16, var_9658_cast_fp16, var_9660_cast_fp16, var_9662_cast_fp16, var_9664_cast_fp16, var_9666_cast_fp16, var_9668_cast_fp16, var_9670_cast_fp16, var_9672_cast_fp16, var_9674_cast_fp16, var_9676_cast_fp16))[name = tensor("input_73_cast_fp16")]; + tensor var_9681 = const()[name = tensor("op_9681"), val = tensor([1, 1])]; + tensor var_9683 = const()[name = tensor("op_9683"), val = tensor([1, 1])]; + tensor obj_39_pad_type_0 = const()[name = tensor("obj_39_pad_type_0"), val = tensor("custom")]; + tensor obj_39_pad_0 = const()[name = tensor("obj_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137340288)))]; + tensor layers_9_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138520000)))]; + tensor obj_39_cast_fp16 = conv(bias = layers_9_self_attn_o_proj_bias_to_fp16, dilations = var_9683, groups = var_8782, pad = obj_39_pad_0, pad_type = obj_39_pad_type_0, strides = var_9681, weight = layers_9_self_attn_o_proj_weight_to_fp16, x = input_73_cast_fp16)[name = tensor("obj_39_cast_fp16")]; + tensor inputs_39_cast_fp16 = add(x = inputs_37_cast_fp16, y = obj_39_cast_fp16)[name = tensor("inputs_39_cast_fp16")]; + tensor var_9689 = const()[name = tensor("op_9689"), val = tensor([1])]; + tensor channels_mean_39_cast_fp16 = reduce_mean(axes = var_9689, keep_dims = var_8783, x = inputs_39_cast_fp16)[name = tensor("channels_mean_39_cast_fp16")]; + tensor zero_mean_39_cast_fp16 = sub(x = inputs_39_cast_fp16, y = channels_mean_39_cast_fp16)[name = tensor("zero_mean_39_cast_fp16")]; + tensor zero_mean_sq_39_cast_fp16 = mul(x = zero_mean_39_cast_fp16, y = zero_mean_39_cast_fp16)[name = tensor("zero_mean_sq_39_cast_fp16")]; + tensor var_9693 = const()[name = tensor("op_9693"), val = tensor([1])]; + tensor var_9694_cast_fp16 = reduce_mean(axes = var_9693, keep_dims = var_8783, x = zero_mean_sq_39_cast_fp16)[name = tensor("op_9694_cast_fp16")]; + tensor var_9695_to_fp16 = const()[name = tensor("op_9695_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_9696_cast_fp16 = add(x = var_9694_cast_fp16, y = var_9695_to_fp16)[name = tensor("op_9696_cast_fp16")]; + tensor denom_39_epsilon_0_to_fp16 = const()[name = tensor("denom_39_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_39_cast_fp16 = rsqrt(epsilon = denom_39_epsilon_0_to_fp16, x = var_9696_cast_fp16)[name = tensor("denom_39_cast_fp16")]; + tensor out_39_cast_fp16 = mul(x = zero_mean_39_cast_fp16, y = denom_39_cast_fp16)[name = tensor("out_39_cast_fp16")]; + tensor input_75_gamma_0_to_fp16 = const()[name = tensor("input_75_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138521600)))]; + tensor input_75_beta_0_to_fp16 = const()[name = tensor("input_75_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138523200)))]; + tensor input_75_epsilon_0_to_fp16 = const()[name = tensor("input_75_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_75_cast_fp16 = batch_norm(beta = input_75_beta_0_to_fp16, epsilon = input_75_epsilon_0_to_fp16, gamma = input_75_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_39_cast_fp16)[name = tensor("input_75_cast_fp16")]; + tensor var_9707 = const()[name = tensor("op_9707"), val = tensor([1, 1])]; + tensor var_9709 = const()[name = tensor("op_9709"), val = tensor([1, 1])]; + tensor input_77_pad_type_0 = const()[name = tensor("input_77_pad_type_0"), val = tensor("custom")]; + tensor input_77_pad_0 = const()[name = tensor("input_77_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_fc1_weight_to_fp16 = const()[name = tensor("layers_9_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138524800)))]; + tensor layers_9_fc1_bias_to_fp16 = const()[name = tensor("layers_9_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(143243456)))]; + tensor input_77_cast_fp16 = conv(bias = layers_9_fc1_bias_to_fp16, dilations = var_9709, groups = var_8782, pad = input_77_pad_0, pad_type = input_77_pad_type_0, strides = var_9707, weight = layers_9_fc1_weight_to_fp16, x = input_75_cast_fp16)[name = tensor("input_77_cast_fp16")]; + tensor input_79_mode_0 = const()[name = tensor("input_79_mode_0"), val = tensor("EXACT")]; + tensor input_79_cast_fp16 = gelu(mode = input_79_mode_0, x = input_77_cast_fp16)[name = tensor("input_79_cast_fp16")]; + tensor var_9715 = const()[name = tensor("op_9715"), val = tensor([1, 1])]; + tensor var_9717 = const()[name = tensor("op_9717"), val = tensor([1, 1])]; + tensor hidden_states_23_pad_type_0 = const()[name = tensor("hidden_states_23_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_23_pad_0 = const()[name = tensor("hidden_states_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_fc2_weight_to_fp16 = const()[name = tensor("layers_9_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(143249664)))]; + tensor layers_9_fc2_bias_to_fp16 = const()[name = tensor("layers_9_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147968320)))]; + tensor hidden_states_23_cast_fp16 = conv(bias = layers_9_fc2_bias_to_fp16, dilations = var_9717, groups = var_8782, pad = hidden_states_23_pad_0, pad_type = hidden_states_23_pad_type_0, strides = var_9715, weight = layers_9_fc2_weight_to_fp16, x = input_79_cast_fp16)[name = tensor("hidden_states_23_cast_fp16")]; + tensor inputs_41_cast_fp16 = add(x = inputs_39_cast_fp16, y = hidden_states_23_cast_fp16)[name = tensor("inputs_41_cast_fp16")]; + tensor var_9724 = const()[name = tensor("op_9724"), val = tensor(3)]; + tensor var_9741 = const()[name = tensor("op_9741"), val = tensor(1)]; + tensor var_9742 = const()[name = tensor("op_9742"), val = tensor(true)]; + tensor var_9752 = const()[name = tensor("op_9752"), val = tensor([1])]; + tensor channels_mean_41_cast_fp16 = reduce_mean(axes = var_9752, keep_dims = var_9742, x = inputs_41_cast_fp16)[name = tensor("channels_mean_41_cast_fp16")]; + tensor zero_mean_41_cast_fp16 = sub(x = inputs_41_cast_fp16, y = channels_mean_41_cast_fp16)[name = tensor("zero_mean_41_cast_fp16")]; + tensor zero_mean_sq_41_cast_fp16 = mul(x = zero_mean_41_cast_fp16, y = zero_mean_41_cast_fp16)[name = tensor("zero_mean_sq_41_cast_fp16")]; + tensor var_9756 = const()[name = tensor("op_9756"), val = tensor([1])]; + tensor var_9757_cast_fp16 = reduce_mean(axes = var_9756, keep_dims = var_9742, x = zero_mean_sq_41_cast_fp16)[name = tensor("op_9757_cast_fp16")]; + tensor var_9758_to_fp16 = const()[name = tensor("op_9758_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_9759_cast_fp16 = add(x = var_9757_cast_fp16, y = var_9758_to_fp16)[name = tensor("op_9759_cast_fp16")]; + tensor denom_41_epsilon_0_to_fp16 = const()[name = tensor("denom_41_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_41_cast_fp16 = rsqrt(epsilon = denom_41_epsilon_0_to_fp16, x = var_9759_cast_fp16)[name = tensor("denom_41_cast_fp16")]; + tensor out_41_cast_fp16 = mul(x = zero_mean_41_cast_fp16, y = denom_41_cast_fp16)[name = tensor("out_41_cast_fp16")]; + tensor obj_41_gamma_0_to_fp16 = const()[name = tensor("obj_41_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147969920)))]; + tensor obj_41_beta_0_to_fp16 = const()[name = tensor("obj_41_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147971520)))]; + tensor obj_41_epsilon_0_to_fp16 = const()[name = tensor("obj_41_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_41_cast_fp16 = batch_norm(beta = obj_41_beta_0_to_fp16, epsilon = obj_41_epsilon_0_to_fp16, gamma = obj_41_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_41_cast_fp16)[name = tensor("obj_41_cast_fp16")]; + tensor var_9774 = const()[name = tensor("op_9774"), val = tensor([1, 1])]; + tensor var_9776 = const()[name = tensor("op_9776"), val = tensor([1, 1])]; + tensor query_21_pad_type_0 = const()[name = tensor("query_21_pad_type_0"), val = tensor("custom")]; + tensor query_21_pad_0 = const()[name = tensor("query_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147973120)))]; + tensor layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149152832)))]; + tensor query_21_cast_fp16 = conv(bias = layers_10_self_attn_q_proj_bias_to_fp16, dilations = var_9776, groups = var_9741, pad = query_21_pad_0, pad_type = query_21_pad_type_0, strides = var_9774, weight = layers_10_self_attn_q_proj_weight_to_fp16, x = obj_41_cast_fp16)[name = tensor("query_21_cast_fp16")]; + tensor var_9780 = const()[name = tensor("op_9780"), val = tensor([1, 1])]; + tensor var_9782 = const()[name = tensor("op_9782"), val = tensor([1, 1])]; + tensor key_21_pad_type_0 = const()[name = tensor("key_21_pad_type_0"), val = tensor("custom")]; + tensor key_21_pad_0 = const()[name = tensor("key_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149154432)))]; + tensor key_21_cast_fp16 = conv(dilations = var_9782, groups = var_9741, pad = key_21_pad_0, pad_type = key_21_pad_type_0, strides = var_9780, weight = layers_10_self_attn_k_proj_weight_to_fp16, x = obj_41_cast_fp16)[name = tensor("key_21_cast_fp16")]; + tensor var_9787 = const()[name = tensor("op_9787"), val = tensor([1, 1])]; + tensor var_9789 = const()[name = tensor("op_9789"), val = tensor([1, 1])]; + tensor value_21_pad_type_0 = const()[name = tensor("value_21_pad_type_0"), val = tensor("custom")]; + tensor value_21_pad_0 = const()[name = tensor("value_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(150334144)))]; + tensor layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151513856)))]; + tensor value_21_cast_fp16 = conv(bias = layers_10_self_attn_v_proj_bias_to_fp16, dilations = var_9789, groups = var_9741, pad = value_21_pad_0, pad_type = value_21_pad_type_0, strides = var_9787, weight = layers_10_self_attn_v_proj_weight_to_fp16, x = obj_41_cast_fp16)[name = tensor("value_21_cast_fp16")]; + tensor var_9796_begin_0 = const()[name = tensor("op_9796_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9796_end_0 = const()[name = tensor("op_9796_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9796_end_mask_0 = const()[name = tensor("op_9796_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9796_cast_fp16 = slice_by_index(begin = var_9796_begin_0, end = var_9796_end_0, end_mask = var_9796_end_mask_0, x = query_21_cast_fp16)[name = tensor("op_9796_cast_fp16")]; + tensor var_9800_begin_0 = const()[name = tensor("op_9800_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_9800_end_0 = const()[name = tensor("op_9800_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_9800_end_mask_0 = const()[name = tensor("op_9800_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9800_cast_fp16 = slice_by_index(begin = var_9800_begin_0, end = var_9800_end_0, end_mask = var_9800_end_mask_0, x = query_21_cast_fp16)[name = tensor("op_9800_cast_fp16")]; + tensor var_9804_begin_0 = const()[name = tensor("op_9804_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_9804_end_0 = const()[name = tensor("op_9804_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_9804_end_mask_0 = const()[name = tensor("op_9804_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9804_cast_fp16 = slice_by_index(begin = var_9804_begin_0, end = var_9804_end_0, end_mask = var_9804_end_mask_0, x = query_21_cast_fp16)[name = tensor("op_9804_cast_fp16")]; + tensor var_9808_begin_0 = const()[name = tensor("op_9808_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_9808_end_0 = const()[name = tensor("op_9808_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_9808_end_mask_0 = const()[name = tensor("op_9808_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9808_cast_fp16 = slice_by_index(begin = var_9808_begin_0, end = var_9808_end_0, end_mask = var_9808_end_mask_0, x = query_21_cast_fp16)[name = tensor("op_9808_cast_fp16")]; + tensor var_9812_begin_0 = const()[name = tensor("op_9812_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_9812_end_0 = const()[name = tensor("op_9812_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_9812_end_mask_0 = const()[name = tensor("op_9812_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9812_cast_fp16 = slice_by_index(begin = var_9812_begin_0, end = var_9812_end_0, end_mask = var_9812_end_mask_0, x = query_21_cast_fp16)[name = tensor("op_9812_cast_fp16")]; + tensor var_9816_begin_0 = const()[name = tensor("op_9816_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_9816_end_0 = const()[name = tensor("op_9816_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_9816_end_mask_0 = const()[name = tensor("op_9816_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9816_cast_fp16 = slice_by_index(begin = var_9816_begin_0, end = var_9816_end_0, end_mask = var_9816_end_mask_0, x = query_21_cast_fp16)[name = tensor("op_9816_cast_fp16")]; + tensor var_9820_begin_0 = const()[name = tensor("op_9820_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_9820_end_0 = const()[name = tensor("op_9820_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_9820_end_mask_0 = const()[name = tensor("op_9820_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9820_cast_fp16 = slice_by_index(begin = var_9820_begin_0, end = var_9820_end_0, end_mask = var_9820_end_mask_0, x = query_21_cast_fp16)[name = tensor("op_9820_cast_fp16")]; + tensor var_9824_begin_0 = const()[name = tensor("op_9824_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_9824_end_0 = const()[name = tensor("op_9824_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_9824_end_mask_0 = const()[name = tensor("op_9824_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9824_cast_fp16 = slice_by_index(begin = var_9824_begin_0, end = var_9824_end_0, end_mask = var_9824_end_mask_0, x = query_21_cast_fp16)[name = tensor("op_9824_cast_fp16")]; + tensor var_9828_begin_0 = const()[name = tensor("op_9828_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_9828_end_0 = const()[name = tensor("op_9828_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_9828_end_mask_0 = const()[name = tensor("op_9828_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9828_cast_fp16 = slice_by_index(begin = var_9828_begin_0, end = var_9828_end_0, end_mask = var_9828_end_mask_0, x = query_21_cast_fp16)[name = tensor("op_9828_cast_fp16")]; + tensor var_9832_begin_0 = const()[name = tensor("op_9832_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_9832_end_0 = const()[name = tensor("op_9832_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_9832_end_mask_0 = const()[name = tensor("op_9832_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9832_cast_fp16 = slice_by_index(begin = var_9832_begin_0, end = var_9832_end_0, end_mask = var_9832_end_mask_0, x = query_21_cast_fp16)[name = tensor("op_9832_cast_fp16")]; + tensor var_9836_begin_0 = const()[name = tensor("op_9836_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_9836_end_0 = const()[name = tensor("op_9836_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_9836_end_mask_0 = const()[name = tensor("op_9836_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9836_cast_fp16 = slice_by_index(begin = var_9836_begin_0, end = var_9836_end_0, end_mask = var_9836_end_mask_0, x = query_21_cast_fp16)[name = tensor("op_9836_cast_fp16")]; + tensor var_9840_begin_0 = const()[name = tensor("op_9840_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_9840_end_0 = const()[name = tensor("op_9840_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_9840_end_mask_0 = const()[name = tensor("op_9840_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_9840_cast_fp16 = slice_by_index(begin = var_9840_begin_0, end = var_9840_end_0, end_mask = var_9840_end_mask_0, x = query_21_cast_fp16)[name = tensor("op_9840_cast_fp16")]; + tensor var_9849_begin_0 = const()[name = tensor("op_9849_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9849_end_0 = const()[name = tensor("op_9849_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_9849_end_mask_0 = const()[name = tensor("op_9849_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9849_cast_fp16 = slice_by_index(begin = var_9849_begin_0, end = var_9849_end_0, end_mask = var_9849_end_mask_0, x = var_9796_cast_fp16)[name = tensor("op_9849_cast_fp16")]; + tensor var_9856_begin_0 = const()[name = tensor("op_9856_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_9856_end_0 = const()[name = tensor("op_9856_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_9856_end_mask_0 = const()[name = tensor("op_9856_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9856_cast_fp16 = slice_by_index(begin = var_9856_begin_0, end = var_9856_end_0, end_mask = var_9856_end_mask_0, x = var_9796_cast_fp16)[name = tensor("op_9856_cast_fp16")]; + tensor var_9863_begin_0 = const()[name = tensor("op_9863_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_9863_end_0 = const()[name = tensor("op_9863_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_9863_end_mask_0 = const()[name = tensor("op_9863_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9863_cast_fp16 = slice_by_index(begin = var_9863_begin_0, end = var_9863_end_0, end_mask = var_9863_end_mask_0, x = var_9796_cast_fp16)[name = tensor("op_9863_cast_fp16")]; + tensor var_9870_begin_0 = const()[name = tensor("op_9870_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_9870_end_0 = const()[name = tensor("op_9870_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9870_end_mask_0 = const()[name = tensor("op_9870_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9870_cast_fp16 = slice_by_index(begin = var_9870_begin_0, end = var_9870_end_0, end_mask = var_9870_end_mask_0, x = var_9796_cast_fp16)[name = tensor("op_9870_cast_fp16")]; + tensor var_9877_begin_0 = const()[name = tensor("op_9877_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9877_end_0 = const()[name = tensor("op_9877_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_9877_end_mask_0 = const()[name = tensor("op_9877_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9877_cast_fp16 = slice_by_index(begin = var_9877_begin_0, end = var_9877_end_0, end_mask = var_9877_end_mask_0, x = var_9800_cast_fp16)[name = tensor("op_9877_cast_fp16")]; + tensor var_9884_begin_0 = const()[name = tensor("op_9884_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_9884_end_0 = const()[name = tensor("op_9884_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_9884_end_mask_0 = const()[name = tensor("op_9884_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9884_cast_fp16 = slice_by_index(begin = var_9884_begin_0, end = var_9884_end_0, end_mask = var_9884_end_mask_0, x = var_9800_cast_fp16)[name = tensor("op_9884_cast_fp16")]; + tensor var_9891_begin_0 = const()[name = tensor("op_9891_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_9891_end_0 = const()[name = tensor("op_9891_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_9891_end_mask_0 = const()[name = tensor("op_9891_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9891_cast_fp16 = slice_by_index(begin = var_9891_begin_0, end = var_9891_end_0, end_mask = var_9891_end_mask_0, x = var_9800_cast_fp16)[name = tensor("op_9891_cast_fp16")]; + tensor var_9898_begin_0 = const()[name = tensor("op_9898_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_9898_end_0 = const()[name = tensor("op_9898_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9898_end_mask_0 = const()[name = tensor("op_9898_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9898_cast_fp16 = slice_by_index(begin = var_9898_begin_0, end = var_9898_end_0, end_mask = var_9898_end_mask_0, x = var_9800_cast_fp16)[name = tensor("op_9898_cast_fp16")]; + tensor var_9905_begin_0 = const()[name = tensor("op_9905_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9905_end_0 = const()[name = tensor("op_9905_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_9905_end_mask_0 = const()[name = tensor("op_9905_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9905_cast_fp16 = slice_by_index(begin = var_9905_begin_0, end = var_9905_end_0, end_mask = var_9905_end_mask_0, x = var_9804_cast_fp16)[name = tensor("op_9905_cast_fp16")]; + tensor var_9912_begin_0 = const()[name = tensor("op_9912_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_9912_end_0 = const()[name = tensor("op_9912_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_9912_end_mask_0 = const()[name = tensor("op_9912_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9912_cast_fp16 = slice_by_index(begin = var_9912_begin_0, end = var_9912_end_0, end_mask = var_9912_end_mask_0, x = var_9804_cast_fp16)[name = tensor("op_9912_cast_fp16")]; + tensor var_9919_begin_0 = const()[name = tensor("op_9919_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_9919_end_0 = const()[name = tensor("op_9919_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_9919_end_mask_0 = const()[name = tensor("op_9919_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9919_cast_fp16 = slice_by_index(begin = var_9919_begin_0, end = var_9919_end_0, end_mask = var_9919_end_mask_0, x = var_9804_cast_fp16)[name = tensor("op_9919_cast_fp16")]; + tensor var_9926_begin_0 = const()[name = tensor("op_9926_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_9926_end_0 = const()[name = tensor("op_9926_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9926_end_mask_0 = const()[name = tensor("op_9926_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9926_cast_fp16 = slice_by_index(begin = var_9926_begin_0, end = var_9926_end_0, end_mask = var_9926_end_mask_0, x = var_9804_cast_fp16)[name = tensor("op_9926_cast_fp16")]; + tensor var_9933_begin_0 = const()[name = tensor("op_9933_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9933_end_0 = const()[name = tensor("op_9933_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_9933_end_mask_0 = const()[name = tensor("op_9933_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9933_cast_fp16 = slice_by_index(begin = var_9933_begin_0, end = var_9933_end_0, end_mask = var_9933_end_mask_0, x = var_9808_cast_fp16)[name = tensor("op_9933_cast_fp16")]; + tensor var_9940_begin_0 = const()[name = tensor("op_9940_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_9940_end_0 = const()[name = tensor("op_9940_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_9940_end_mask_0 = const()[name = tensor("op_9940_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9940_cast_fp16 = slice_by_index(begin = var_9940_begin_0, end = var_9940_end_0, end_mask = var_9940_end_mask_0, x = var_9808_cast_fp16)[name = tensor("op_9940_cast_fp16")]; + tensor var_9947_begin_0 = const()[name = tensor("op_9947_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_9947_end_0 = const()[name = tensor("op_9947_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_9947_end_mask_0 = const()[name = tensor("op_9947_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9947_cast_fp16 = slice_by_index(begin = var_9947_begin_0, end = var_9947_end_0, end_mask = var_9947_end_mask_0, x = var_9808_cast_fp16)[name = tensor("op_9947_cast_fp16")]; + tensor var_9954_begin_0 = const()[name = tensor("op_9954_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_9954_end_0 = const()[name = tensor("op_9954_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9954_end_mask_0 = const()[name = tensor("op_9954_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9954_cast_fp16 = slice_by_index(begin = var_9954_begin_0, end = var_9954_end_0, end_mask = var_9954_end_mask_0, x = var_9808_cast_fp16)[name = tensor("op_9954_cast_fp16")]; + tensor var_9961_begin_0 = const()[name = tensor("op_9961_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9961_end_0 = const()[name = tensor("op_9961_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_9961_end_mask_0 = const()[name = tensor("op_9961_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9961_cast_fp16 = slice_by_index(begin = var_9961_begin_0, end = var_9961_end_0, end_mask = var_9961_end_mask_0, x = var_9812_cast_fp16)[name = tensor("op_9961_cast_fp16")]; + tensor var_9968_begin_0 = const()[name = tensor("op_9968_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_9968_end_0 = const()[name = tensor("op_9968_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_9968_end_mask_0 = const()[name = tensor("op_9968_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9968_cast_fp16 = slice_by_index(begin = var_9968_begin_0, end = var_9968_end_0, end_mask = var_9968_end_mask_0, x = var_9812_cast_fp16)[name = tensor("op_9968_cast_fp16")]; + tensor var_9975_begin_0 = const()[name = tensor("op_9975_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_9975_end_0 = const()[name = tensor("op_9975_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_9975_end_mask_0 = const()[name = tensor("op_9975_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9975_cast_fp16 = slice_by_index(begin = var_9975_begin_0, end = var_9975_end_0, end_mask = var_9975_end_mask_0, x = var_9812_cast_fp16)[name = tensor("op_9975_cast_fp16")]; + tensor var_9982_begin_0 = const()[name = tensor("op_9982_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_9982_end_0 = const()[name = tensor("op_9982_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_9982_end_mask_0 = const()[name = tensor("op_9982_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9982_cast_fp16 = slice_by_index(begin = var_9982_begin_0, end = var_9982_end_0, end_mask = var_9982_end_mask_0, x = var_9812_cast_fp16)[name = tensor("op_9982_cast_fp16")]; + tensor var_9989_begin_0 = const()[name = tensor("op_9989_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_9989_end_0 = const()[name = tensor("op_9989_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_9989_end_mask_0 = const()[name = tensor("op_9989_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9989_cast_fp16 = slice_by_index(begin = var_9989_begin_0, end = var_9989_end_0, end_mask = var_9989_end_mask_0, x = var_9816_cast_fp16)[name = tensor("op_9989_cast_fp16")]; + tensor var_9996_begin_0 = const()[name = tensor("op_9996_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_9996_end_0 = const()[name = tensor("op_9996_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_9996_end_mask_0 = const()[name = tensor("op_9996_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_9996_cast_fp16 = slice_by_index(begin = var_9996_begin_0, end = var_9996_end_0, end_mask = var_9996_end_mask_0, x = var_9816_cast_fp16)[name = tensor("op_9996_cast_fp16")]; + tensor var_10003_begin_0 = const()[name = tensor("op_10003_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_10003_end_0 = const()[name = tensor("op_10003_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_10003_end_mask_0 = const()[name = tensor("op_10003_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10003_cast_fp16 = slice_by_index(begin = var_10003_begin_0, end = var_10003_end_0, end_mask = var_10003_end_mask_0, x = var_9816_cast_fp16)[name = tensor("op_10003_cast_fp16")]; + tensor var_10010_begin_0 = const()[name = tensor("op_10010_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_10010_end_0 = const()[name = tensor("op_10010_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10010_end_mask_0 = const()[name = tensor("op_10010_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10010_cast_fp16 = slice_by_index(begin = var_10010_begin_0, end = var_10010_end_0, end_mask = var_10010_end_mask_0, x = var_9816_cast_fp16)[name = tensor("op_10010_cast_fp16")]; + tensor var_10017_begin_0 = const()[name = tensor("op_10017_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10017_end_0 = const()[name = tensor("op_10017_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_10017_end_mask_0 = const()[name = tensor("op_10017_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10017_cast_fp16 = slice_by_index(begin = var_10017_begin_0, end = var_10017_end_0, end_mask = var_10017_end_mask_0, x = var_9820_cast_fp16)[name = tensor("op_10017_cast_fp16")]; + tensor var_10024_begin_0 = const()[name = tensor("op_10024_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_10024_end_0 = const()[name = tensor("op_10024_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_10024_end_mask_0 = const()[name = tensor("op_10024_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10024_cast_fp16 = slice_by_index(begin = var_10024_begin_0, end = var_10024_end_0, end_mask = var_10024_end_mask_0, x = var_9820_cast_fp16)[name = tensor("op_10024_cast_fp16")]; + tensor var_10031_begin_0 = const()[name = tensor("op_10031_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_10031_end_0 = const()[name = tensor("op_10031_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_10031_end_mask_0 = const()[name = tensor("op_10031_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10031_cast_fp16 = slice_by_index(begin = var_10031_begin_0, end = var_10031_end_0, end_mask = var_10031_end_mask_0, x = var_9820_cast_fp16)[name = tensor("op_10031_cast_fp16")]; + tensor var_10038_begin_0 = const()[name = tensor("op_10038_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_10038_end_0 = const()[name = tensor("op_10038_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10038_end_mask_0 = const()[name = tensor("op_10038_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10038_cast_fp16 = slice_by_index(begin = var_10038_begin_0, end = var_10038_end_0, end_mask = var_10038_end_mask_0, x = var_9820_cast_fp16)[name = tensor("op_10038_cast_fp16")]; + tensor var_10045_begin_0 = const()[name = tensor("op_10045_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10045_end_0 = const()[name = tensor("op_10045_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_10045_end_mask_0 = const()[name = tensor("op_10045_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10045_cast_fp16 = slice_by_index(begin = var_10045_begin_0, end = var_10045_end_0, end_mask = var_10045_end_mask_0, x = var_9824_cast_fp16)[name = tensor("op_10045_cast_fp16")]; + tensor var_10052_begin_0 = const()[name = tensor("op_10052_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_10052_end_0 = const()[name = tensor("op_10052_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_10052_end_mask_0 = const()[name = tensor("op_10052_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10052_cast_fp16 = slice_by_index(begin = var_10052_begin_0, end = var_10052_end_0, end_mask = var_10052_end_mask_0, x = var_9824_cast_fp16)[name = tensor("op_10052_cast_fp16")]; + tensor var_10059_begin_0 = const()[name = tensor("op_10059_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_10059_end_0 = const()[name = tensor("op_10059_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_10059_end_mask_0 = const()[name = tensor("op_10059_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10059_cast_fp16 = slice_by_index(begin = var_10059_begin_0, end = var_10059_end_0, end_mask = var_10059_end_mask_0, x = var_9824_cast_fp16)[name = tensor("op_10059_cast_fp16")]; + tensor var_10066_begin_0 = const()[name = tensor("op_10066_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_10066_end_0 = const()[name = tensor("op_10066_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10066_end_mask_0 = const()[name = tensor("op_10066_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10066_cast_fp16 = slice_by_index(begin = var_10066_begin_0, end = var_10066_end_0, end_mask = var_10066_end_mask_0, x = var_9824_cast_fp16)[name = tensor("op_10066_cast_fp16")]; + tensor var_10073_begin_0 = const()[name = tensor("op_10073_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10073_end_0 = const()[name = tensor("op_10073_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_10073_end_mask_0 = const()[name = tensor("op_10073_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10073_cast_fp16 = slice_by_index(begin = var_10073_begin_0, end = var_10073_end_0, end_mask = var_10073_end_mask_0, x = var_9828_cast_fp16)[name = tensor("op_10073_cast_fp16")]; + tensor var_10080_begin_0 = const()[name = tensor("op_10080_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_10080_end_0 = const()[name = tensor("op_10080_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_10080_end_mask_0 = const()[name = tensor("op_10080_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10080_cast_fp16 = slice_by_index(begin = var_10080_begin_0, end = var_10080_end_0, end_mask = var_10080_end_mask_0, x = var_9828_cast_fp16)[name = tensor("op_10080_cast_fp16")]; + tensor var_10087_begin_0 = const()[name = tensor("op_10087_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_10087_end_0 = const()[name = tensor("op_10087_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_10087_end_mask_0 = const()[name = tensor("op_10087_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10087_cast_fp16 = slice_by_index(begin = var_10087_begin_0, end = var_10087_end_0, end_mask = var_10087_end_mask_0, x = var_9828_cast_fp16)[name = tensor("op_10087_cast_fp16")]; + tensor var_10094_begin_0 = const()[name = tensor("op_10094_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_10094_end_0 = const()[name = tensor("op_10094_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10094_end_mask_0 = const()[name = tensor("op_10094_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10094_cast_fp16 = slice_by_index(begin = var_10094_begin_0, end = var_10094_end_0, end_mask = var_10094_end_mask_0, x = var_9828_cast_fp16)[name = tensor("op_10094_cast_fp16")]; + tensor var_10101_begin_0 = const()[name = tensor("op_10101_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10101_end_0 = const()[name = tensor("op_10101_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_10101_end_mask_0 = const()[name = tensor("op_10101_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10101_cast_fp16 = slice_by_index(begin = var_10101_begin_0, end = var_10101_end_0, end_mask = var_10101_end_mask_0, x = var_9832_cast_fp16)[name = tensor("op_10101_cast_fp16")]; + tensor var_10108_begin_0 = const()[name = tensor("op_10108_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_10108_end_0 = const()[name = tensor("op_10108_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_10108_end_mask_0 = const()[name = tensor("op_10108_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10108_cast_fp16 = slice_by_index(begin = var_10108_begin_0, end = var_10108_end_0, end_mask = var_10108_end_mask_0, x = var_9832_cast_fp16)[name = tensor("op_10108_cast_fp16")]; + tensor var_10115_begin_0 = const()[name = tensor("op_10115_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_10115_end_0 = const()[name = tensor("op_10115_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_10115_end_mask_0 = const()[name = tensor("op_10115_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10115_cast_fp16 = slice_by_index(begin = var_10115_begin_0, end = var_10115_end_0, end_mask = var_10115_end_mask_0, x = var_9832_cast_fp16)[name = tensor("op_10115_cast_fp16")]; + tensor var_10122_begin_0 = const()[name = tensor("op_10122_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_10122_end_0 = const()[name = tensor("op_10122_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10122_end_mask_0 = const()[name = tensor("op_10122_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10122_cast_fp16 = slice_by_index(begin = var_10122_begin_0, end = var_10122_end_0, end_mask = var_10122_end_mask_0, x = var_9832_cast_fp16)[name = tensor("op_10122_cast_fp16")]; + tensor var_10129_begin_0 = const()[name = tensor("op_10129_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10129_end_0 = const()[name = tensor("op_10129_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_10129_end_mask_0 = const()[name = tensor("op_10129_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10129_cast_fp16 = slice_by_index(begin = var_10129_begin_0, end = var_10129_end_0, end_mask = var_10129_end_mask_0, x = var_9836_cast_fp16)[name = tensor("op_10129_cast_fp16")]; + tensor var_10136_begin_0 = const()[name = tensor("op_10136_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_10136_end_0 = const()[name = tensor("op_10136_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_10136_end_mask_0 = const()[name = tensor("op_10136_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10136_cast_fp16 = slice_by_index(begin = var_10136_begin_0, end = var_10136_end_0, end_mask = var_10136_end_mask_0, x = var_9836_cast_fp16)[name = tensor("op_10136_cast_fp16")]; + tensor var_10143_begin_0 = const()[name = tensor("op_10143_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_10143_end_0 = const()[name = tensor("op_10143_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_10143_end_mask_0 = const()[name = tensor("op_10143_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10143_cast_fp16 = slice_by_index(begin = var_10143_begin_0, end = var_10143_end_0, end_mask = var_10143_end_mask_0, x = var_9836_cast_fp16)[name = tensor("op_10143_cast_fp16")]; + tensor var_10150_begin_0 = const()[name = tensor("op_10150_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_10150_end_0 = const()[name = tensor("op_10150_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10150_end_mask_0 = const()[name = tensor("op_10150_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10150_cast_fp16 = slice_by_index(begin = var_10150_begin_0, end = var_10150_end_0, end_mask = var_10150_end_mask_0, x = var_9836_cast_fp16)[name = tensor("op_10150_cast_fp16")]; + tensor var_10157_begin_0 = const()[name = tensor("op_10157_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10157_end_0 = const()[name = tensor("op_10157_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_10157_end_mask_0 = const()[name = tensor("op_10157_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10157_cast_fp16 = slice_by_index(begin = var_10157_begin_0, end = var_10157_end_0, end_mask = var_10157_end_mask_0, x = var_9840_cast_fp16)[name = tensor("op_10157_cast_fp16")]; + tensor var_10164_begin_0 = const()[name = tensor("op_10164_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_10164_end_0 = const()[name = tensor("op_10164_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_10164_end_mask_0 = const()[name = tensor("op_10164_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10164_cast_fp16 = slice_by_index(begin = var_10164_begin_0, end = var_10164_end_0, end_mask = var_10164_end_mask_0, x = var_9840_cast_fp16)[name = tensor("op_10164_cast_fp16")]; + tensor var_10171_begin_0 = const()[name = tensor("op_10171_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_10171_end_0 = const()[name = tensor("op_10171_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_10171_end_mask_0 = const()[name = tensor("op_10171_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10171_cast_fp16 = slice_by_index(begin = var_10171_begin_0, end = var_10171_end_0, end_mask = var_10171_end_mask_0, x = var_9840_cast_fp16)[name = tensor("op_10171_cast_fp16")]; + tensor var_10178_begin_0 = const()[name = tensor("op_10178_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_10178_end_0 = const()[name = tensor("op_10178_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10178_end_mask_0 = const()[name = tensor("op_10178_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10178_cast_fp16 = slice_by_index(begin = var_10178_begin_0, end = var_10178_end_0, end_mask = var_10178_end_mask_0, x = var_9840_cast_fp16)[name = tensor("op_10178_cast_fp16")]; + tensor k_21_perm_0 = const()[name = tensor("k_21_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_10183_begin_0 = const()[name = tensor("op_10183_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10183_end_0 = const()[name = tensor("op_10183_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_10183_end_mask_0 = const()[name = tensor("op_10183_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_1 = transpose(perm = k_21_perm_0, x = key_21_cast_fp16)[name = tensor("transpose_1")]; + tensor var_10183_cast_fp16 = slice_by_index(begin = var_10183_begin_0, end = var_10183_end_0, end_mask = var_10183_end_mask_0, x = transpose_1)[name = tensor("op_10183_cast_fp16")]; + tensor var_10187_begin_0 = const()[name = tensor("op_10187_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_10187_end_0 = const()[name = tensor("op_10187_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_10187_end_mask_0 = const()[name = tensor("op_10187_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10187_cast_fp16 = slice_by_index(begin = var_10187_begin_0, end = var_10187_end_0, end_mask = var_10187_end_mask_0, x = transpose_1)[name = tensor("op_10187_cast_fp16")]; + tensor var_10191_begin_0 = const()[name = tensor("op_10191_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_10191_end_0 = const()[name = tensor("op_10191_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_10191_end_mask_0 = const()[name = tensor("op_10191_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10191_cast_fp16 = slice_by_index(begin = var_10191_begin_0, end = var_10191_end_0, end_mask = var_10191_end_mask_0, x = transpose_1)[name = tensor("op_10191_cast_fp16")]; + tensor var_10195_begin_0 = const()[name = tensor("op_10195_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_10195_end_0 = const()[name = tensor("op_10195_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_10195_end_mask_0 = const()[name = tensor("op_10195_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10195_cast_fp16 = slice_by_index(begin = var_10195_begin_0, end = var_10195_end_0, end_mask = var_10195_end_mask_0, x = transpose_1)[name = tensor("op_10195_cast_fp16")]; + tensor var_10199_begin_0 = const()[name = tensor("op_10199_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_10199_end_0 = const()[name = tensor("op_10199_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_10199_end_mask_0 = const()[name = tensor("op_10199_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10199_cast_fp16 = slice_by_index(begin = var_10199_begin_0, end = var_10199_end_0, end_mask = var_10199_end_mask_0, x = transpose_1)[name = tensor("op_10199_cast_fp16")]; + tensor var_10203_begin_0 = const()[name = tensor("op_10203_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_10203_end_0 = const()[name = tensor("op_10203_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_10203_end_mask_0 = const()[name = tensor("op_10203_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10203_cast_fp16 = slice_by_index(begin = var_10203_begin_0, end = var_10203_end_0, end_mask = var_10203_end_mask_0, x = transpose_1)[name = tensor("op_10203_cast_fp16")]; + tensor var_10207_begin_0 = const()[name = tensor("op_10207_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_10207_end_0 = const()[name = tensor("op_10207_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_10207_end_mask_0 = const()[name = tensor("op_10207_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10207_cast_fp16 = slice_by_index(begin = var_10207_begin_0, end = var_10207_end_0, end_mask = var_10207_end_mask_0, x = transpose_1)[name = tensor("op_10207_cast_fp16")]; + tensor var_10211_begin_0 = const()[name = tensor("op_10211_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_10211_end_0 = const()[name = tensor("op_10211_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_10211_end_mask_0 = const()[name = tensor("op_10211_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10211_cast_fp16 = slice_by_index(begin = var_10211_begin_0, end = var_10211_end_0, end_mask = var_10211_end_mask_0, x = transpose_1)[name = tensor("op_10211_cast_fp16")]; + tensor var_10215_begin_0 = const()[name = tensor("op_10215_begin_0"), val = tensor([0, 0, 0, 512])]; + tensor var_10215_end_0 = const()[name = tensor("op_10215_end_0"), val = tensor([1, 1500, 1, 576])]; + tensor var_10215_end_mask_0 = const()[name = tensor("op_10215_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10215_cast_fp16 = slice_by_index(begin = var_10215_begin_0, end = var_10215_end_0, end_mask = var_10215_end_mask_0, x = transpose_1)[name = tensor("op_10215_cast_fp16")]; + tensor var_10219_begin_0 = const()[name = tensor("op_10219_begin_0"), val = tensor([0, 0, 0, 576])]; + tensor var_10219_end_0 = const()[name = tensor("op_10219_end_0"), val = tensor([1, 1500, 1, 640])]; + tensor var_10219_end_mask_0 = const()[name = tensor("op_10219_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10219_cast_fp16 = slice_by_index(begin = var_10219_begin_0, end = var_10219_end_0, end_mask = var_10219_end_mask_0, x = transpose_1)[name = tensor("op_10219_cast_fp16")]; + tensor var_10223_begin_0 = const()[name = tensor("op_10223_begin_0"), val = tensor([0, 0, 0, 640])]; + tensor var_10223_end_0 = const()[name = tensor("op_10223_end_0"), val = tensor([1, 1500, 1, 704])]; + tensor var_10223_end_mask_0 = const()[name = tensor("op_10223_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10223_cast_fp16 = slice_by_index(begin = var_10223_begin_0, end = var_10223_end_0, end_mask = var_10223_end_mask_0, x = transpose_1)[name = tensor("op_10223_cast_fp16")]; + tensor var_10227_begin_0 = const()[name = tensor("op_10227_begin_0"), val = tensor([0, 0, 0, 704])]; + tensor var_10227_end_0 = const()[name = tensor("op_10227_end_0"), val = tensor([1, 1500, 1, 768])]; + tensor var_10227_end_mask_0 = const()[name = tensor("op_10227_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10227_cast_fp16 = slice_by_index(begin = var_10227_begin_0, end = var_10227_end_0, end_mask = var_10227_end_mask_0, x = transpose_1)[name = tensor("op_10227_cast_fp16")]; + tensor var_10229_begin_0 = const()[name = tensor("op_10229_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10229_end_0 = const()[name = tensor("op_10229_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10229_end_mask_0 = const()[name = tensor("op_10229_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10229_cast_fp16 = slice_by_index(begin = var_10229_begin_0, end = var_10229_end_0, end_mask = var_10229_end_mask_0, x = value_21_cast_fp16)[name = tensor("op_10229_cast_fp16")]; + tensor var_10233_begin_0 = const()[name = tensor("op_10233_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_10233_end_0 = const()[name = tensor("op_10233_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_10233_end_mask_0 = const()[name = tensor("op_10233_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10233_cast_fp16 = slice_by_index(begin = var_10233_begin_0, end = var_10233_end_0, end_mask = var_10233_end_mask_0, x = value_21_cast_fp16)[name = tensor("op_10233_cast_fp16")]; + tensor var_10237_begin_0 = const()[name = tensor("op_10237_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_10237_end_0 = const()[name = tensor("op_10237_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_10237_end_mask_0 = const()[name = tensor("op_10237_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10237_cast_fp16 = slice_by_index(begin = var_10237_begin_0, end = var_10237_end_0, end_mask = var_10237_end_mask_0, x = value_21_cast_fp16)[name = tensor("op_10237_cast_fp16")]; + tensor var_10241_begin_0 = const()[name = tensor("op_10241_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_10241_end_0 = const()[name = tensor("op_10241_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_10241_end_mask_0 = const()[name = tensor("op_10241_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10241_cast_fp16 = slice_by_index(begin = var_10241_begin_0, end = var_10241_end_0, end_mask = var_10241_end_mask_0, x = value_21_cast_fp16)[name = tensor("op_10241_cast_fp16")]; + tensor var_10245_begin_0 = const()[name = tensor("op_10245_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_10245_end_0 = const()[name = tensor("op_10245_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_10245_end_mask_0 = const()[name = tensor("op_10245_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10245_cast_fp16 = slice_by_index(begin = var_10245_begin_0, end = var_10245_end_0, end_mask = var_10245_end_mask_0, x = value_21_cast_fp16)[name = tensor("op_10245_cast_fp16")]; + tensor var_10249_begin_0 = const()[name = tensor("op_10249_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_10249_end_0 = const()[name = tensor("op_10249_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_10249_end_mask_0 = const()[name = tensor("op_10249_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10249_cast_fp16 = slice_by_index(begin = var_10249_begin_0, end = var_10249_end_0, end_mask = var_10249_end_mask_0, x = value_21_cast_fp16)[name = tensor("op_10249_cast_fp16")]; + tensor var_10253_begin_0 = const()[name = tensor("op_10253_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_10253_end_0 = const()[name = tensor("op_10253_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_10253_end_mask_0 = const()[name = tensor("op_10253_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10253_cast_fp16 = slice_by_index(begin = var_10253_begin_0, end = var_10253_end_0, end_mask = var_10253_end_mask_0, x = value_21_cast_fp16)[name = tensor("op_10253_cast_fp16")]; + tensor var_10257_begin_0 = const()[name = tensor("op_10257_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_10257_end_0 = const()[name = tensor("op_10257_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_10257_end_mask_0 = const()[name = tensor("op_10257_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10257_cast_fp16 = slice_by_index(begin = var_10257_begin_0, end = var_10257_end_0, end_mask = var_10257_end_mask_0, x = value_21_cast_fp16)[name = tensor("op_10257_cast_fp16")]; + tensor var_10261_begin_0 = const()[name = tensor("op_10261_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_10261_end_0 = const()[name = tensor("op_10261_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_10261_end_mask_0 = const()[name = tensor("op_10261_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10261_cast_fp16 = slice_by_index(begin = var_10261_begin_0, end = var_10261_end_0, end_mask = var_10261_end_mask_0, x = value_21_cast_fp16)[name = tensor("op_10261_cast_fp16")]; + tensor var_10265_begin_0 = const()[name = tensor("op_10265_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_10265_end_0 = const()[name = tensor("op_10265_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_10265_end_mask_0 = const()[name = tensor("op_10265_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10265_cast_fp16 = slice_by_index(begin = var_10265_begin_0, end = var_10265_end_0, end_mask = var_10265_end_mask_0, x = value_21_cast_fp16)[name = tensor("op_10265_cast_fp16")]; + tensor var_10269_begin_0 = const()[name = tensor("op_10269_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_10269_end_0 = const()[name = tensor("op_10269_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_10269_end_mask_0 = const()[name = tensor("op_10269_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10269_cast_fp16 = slice_by_index(begin = var_10269_begin_0, end = var_10269_end_0, end_mask = var_10269_end_mask_0, x = value_21_cast_fp16)[name = tensor("op_10269_cast_fp16")]; + tensor var_10273_begin_0 = const()[name = tensor("op_10273_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_10273_end_0 = const()[name = tensor("op_10273_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_10273_end_mask_0 = const()[name = tensor("op_10273_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10273_cast_fp16 = slice_by_index(begin = var_10273_begin_0, end = var_10273_end_0, end_mask = var_10273_end_mask_0, x = value_21_cast_fp16)[name = tensor("op_10273_cast_fp16")]; + tensor var_10277_equation_0 = const()[name = tensor("op_10277_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10277_cast_fp16 = einsum(equation = var_10277_equation_0, values = (var_10183_cast_fp16, var_9849_cast_fp16))[name = tensor("op_10277_cast_fp16")]; + tensor var_10278_to_fp16 = const()[name = tensor("op_10278_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_961_cast_fp16 = mul(x = var_10277_cast_fp16, y = var_10278_to_fp16)[name = tensor("aw_chunk_961_cast_fp16")]; + tensor var_10281_equation_0 = const()[name = tensor("op_10281_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10281_cast_fp16 = einsum(equation = var_10281_equation_0, values = (var_10183_cast_fp16, var_9856_cast_fp16))[name = tensor("op_10281_cast_fp16")]; + tensor var_10282_to_fp16 = const()[name = tensor("op_10282_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_963_cast_fp16 = mul(x = var_10281_cast_fp16, y = var_10282_to_fp16)[name = tensor("aw_chunk_963_cast_fp16")]; + tensor var_10285_equation_0 = const()[name = tensor("op_10285_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10285_cast_fp16 = einsum(equation = var_10285_equation_0, values = (var_10183_cast_fp16, var_9863_cast_fp16))[name = tensor("op_10285_cast_fp16")]; + tensor var_10286_to_fp16 = const()[name = tensor("op_10286_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_965_cast_fp16 = mul(x = var_10285_cast_fp16, y = var_10286_to_fp16)[name = tensor("aw_chunk_965_cast_fp16")]; + tensor var_10289_equation_0 = const()[name = tensor("op_10289_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10289_cast_fp16 = einsum(equation = var_10289_equation_0, values = (var_10183_cast_fp16, var_9870_cast_fp16))[name = tensor("op_10289_cast_fp16")]; + tensor var_10290_to_fp16 = const()[name = tensor("op_10290_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_967_cast_fp16 = mul(x = var_10289_cast_fp16, y = var_10290_to_fp16)[name = tensor("aw_chunk_967_cast_fp16")]; + tensor var_10293_equation_0 = const()[name = tensor("op_10293_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10293_cast_fp16 = einsum(equation = var_10293_equation_0, values = (var_10187_cast_fp16, var_9877_cast_fp16))[name = tensor("op_10293_cast_fp16")]; + tensor var_10294_to_fp16 = const()[name = tensor("op_10294_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_969_cast_fp16 = mul(x = var_10293_cast_fp16, y = var_10294_to_fp16)[name = tensor("aw_chunk_969_cast_fp16")]; + tensor var_10297_equation_0 = const()[name = tensor("op_10297_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10297_cast_fp16 = einsum(equation = var_10297_equation_0, values = (var_10187_cast_fp16, var_9884_cast_fp16))[name = tensor("op_10297_cast_fp16")]; + tensor var_10298_to_fp16 = const()[name = tensor("op_10298_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_971_cast_fp16 = mul(x = var_10297_cast_fp16, y = var_10298_to_fp16)[name = tensor("aw_chunk_971_cast_fp16")]; + tensor var_10301_equation_0 = const()[name = tensor("op_10301_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10301_cast_fp16 = einsum(equation = var_10301_equation_0, values = (var_10187_cast_fp16, var_9891_cast_fp16))[name = tensor("op_10301_cast_fp16")]; + tensor var_10302_to_fp16 = const()[name = tensor("op_10302_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_973_cast_fp16 = mul(x = var_10301_cast_fp16, y = var_10302_to_fp16)[name = tensor("aw_chunk_973_cast_fp16")]; + tensor var_10305_equation_0 = const()[name = tensor("op_10305_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10305_cast_fp16 = einsum(equation = var_10305_equation_0, values = (var_10187_cast_fp16, var_9898_cast_fp16))[name = tensor("op_10305_cast_fp16")]; + tensor var_10306_to_fp16 = const()[name = tensor("op_10306_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_975_cast_fp16 = mul(x = var_10305_cast_fp16, y = var_10306_to_fp16)[name = tensor("aw_chunk_975_cast_fp16")]; + tensor var_10309_equation_0 = const()[name = tensor("op_10309_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10309_cast_fp16 = einsum(equation = var_10309_equation_0, values = (var_10191_cast_fp16, var_9905_cast_fp16))[name = tensor("op_10309_cast_fp16")]; + tensor var_10310_to_fp16 = const()[name = tensor("op_10310_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_977_cast_fp16 = mul(x = var_10309_cast_fp16, y = var_10310_to_fp16)[name = tensor("aw_chunk_977_cast_fp16")]; + tensor var_10313_equation_0 = const()[name = tensor("op_10313_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10313_cast_fp16 = einsum(equation = var_10313_equation_0, values = (var_10191_cast_fp16, var_9912_cast_fp16))[name = tensor("op_10313_cast_fp16")]; + tensor var_10314_to_fp16 = const()[name = tensor("op_10314_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_979_cast_fp16 = mul(x = var_10313_cast_fp16, y = var_10314_to_fp16)[name = tensor("aw_chunk_979_cast_fp16")]; + tensor var_10317_equation_0 = const()[name = tensor("op_10317_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10317_cast_fp16 = einsum(equation = var_10317_equation_0, values = (var_10191_cast_fp16, var_9919_cast_fp16))[name = tensor("op_10317_cast_fp16")]; + tensor var_10318_to_fp16 = const()[name = tensor("op_10318_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_981_cast_fp16 = mul(x = var_10317_cast_fp16, y = var_10318_to_fp16)[name = tensor("aw_chunk_981_cast_fp16")]; + tensor var_10321_equation_0 = const()[name = tensor("op_10321_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10321_cast_fp16 = einsum(equation = var_10321_equation_0, values = (var_10191_cast_fp16, var_9926_cast_fp16))[name = tensor("op_10321_cast_fp16")]; + tensor var_10322_to_fp16 = const()[name = tensor("op_10322_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_983_cast_fp16 = mul(x = var_10321_cast_fp16, y = var_10322_to_fp16)[name = tensor("aw_chunk_983_cast_fp16")]; + tensor var_10325_equation_0 = const()[name = tensor("op_10325_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10325_cast_fp16 = einsum(equation = var_10325_equation_0, values = (var_10195_cast_fp16, var_9933_cast_fp16))[name = tensor("op_10325_cast_fp16")]; + tensor var_10326_to_fp16 = const()[name = tensor("op_10326_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_985_cast_fp16 = mul(x = var_10325_cast_fp16, y = var_10326_to_fp16)[name = tensor("aw_chunk_985_cast_fp16")]; + tensor var_10329_equation_0 = const()[name = tensor("op_10329_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10329_cast_fp16 = einsum(equation = var_10329_equation_0, values = (var_10195_cast_fp16, var_9940_cast_fp16))[name = tensor("op_10329_cast_fp16")]; + tensor var_10330_to_fp16 = const()[name = tensor("op_10330_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_987_cast_fp16 = mul(x = var_10329_cast_fp16, y = var_10330_to_fp16)[name = tensor("aw_chunk_987_cast_fp16")]; + tensor var_10333_equation_0 = const()[name = tensor("op_10333_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10333_cast_fp16 = einsum(equation = var_10333_equation_0, values = (var_10195_cast_fp16, var_9947_cast_fp16))[name = tensor("op_10333_cast_fp16")]; + tensor var_10334_to_fp16 = const()[name = tensor("op_10334_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_989_cast_fp16 = mul(x = var_10333_cast_fp16, y = var_10334_to_fp16)[name = tensor("aw_chunk_989_cast_fp16")]; + tensor var_10337_equation_0 = const()[name = tensor("op_10337_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10337_cast_fp16 = einsum(equation = var_10337_equation_0, values = (var_10195_cast_fp16, var_9954_cast_fp16))[name = tensor("op_10337_cast_fp16")]; + tensor var_10338_to_fp16 = const()[name = tensor("op_10338_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_991_cast_fp16 = mul(x = var_10337_cast_fp16, y = var_10338_to_fp16)[name = tensor("aw_chunk_991_cast_fp16")]; + tensor var_10341_equation_0 = const()[name = tensor("op_10341_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10341_cast_fp16 = einsum(equation = var_10341_equation_0, values = (var_10199_cast_fp16, var_9961_cast_fp16))[name = tensor("op_10341_cast_fp16")]; + tensor var_10342_to_fp16 = const()[name = tensor("op_10342_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_993_cast_fp16 = mul(x = var_10341_cast_fp16, y = var_10342_to_fp16)[name = tensor("aw_chunk_993_cast_fp16")]; + tensor var_10345_equation_0 = const()[name = tensor("op_10345_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10345_cast_fp16 = einsum(equation = var_10345_equation_0, values = (var_10199_cast_fp16, var_9968_cast_fp16))[name = tensor("op_10345_cast_fp16")]; + tensor var_10346_to_fp16 = const()[name = tensor("op_10346_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_995_cast_fp16 = mul(x = var_10345_cast_fp16, y = var_10346_to_fp16)[name = tensor("aw_chunk_995_cast_fp16")]; + tensor var_10349_equation_0 = const()[name = tensor("op_10349_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10349_cast_fp16 = einsum(equation = var_10349_equation_0, values = (var_10199_cast_fp16, var_9975_cast_fp16))[name = tensor("op_10349_cast_fp16")]; + tensor var_10350_to_fp16 = const()[name = tensor("op_10350_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_997_cast_fp16 = mul(x = var_10349_cast_fp16, y = var_10350_to_fp16)[name = tensor("aw_chunk_997_cast_fp16")]; + tensor var_10353_equation_0 = const()[name = tensor("op_10353_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10353_cast_fp16 = einsum(equation = var_10353_equation_0, values = (var_10199_cast_fp16, var_9982_cast_fp16))[name = tensor("op_10353_cast_fp16")]; + tensor var_10354_to_fp16 = const()[name = tensor("op_10354_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_999_cast_fp16 = mul(x = var_10353_cast_fp16, y = var_10354_to_fp16)[name = tensor("aw_chunk_999_cast_fp16")]; + tensor var_10357_equation_0 = const()[name = tensor("op_10357_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10357_cast_fp16 = einsum(equation = var_10357_equation_0, values = (var_10203_cast_fp16, var_9989_cast_fp16))[name = tensor("op_10357_cast_fp16")]; + tensor var_10358_to_fp16 = const()[name = tensor("op_10358_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1001_cast_fp16 = mul(x = var_10357_cast_fp16, y = var_10358_to_fp16)[name = tensor("aw_chunk_1001_cast_fp16")]; + tensor var_10361_equation_0 = const()[name = tensor("op_10361_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10361_cast_fp16 = einsum(equation = var_10361_equation_0, values = (var_10203_cast_fp16, var_9996_cast_fp16))[name = tensor("op_10361_cast_fp16")]; + tensor var_10362_to_fp16 = const()[name = tensor("op_10362_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1003_cast_fp16 = mul(x = var_10361_cast_fp16, y = var_10362_to_fp16)[name = tensor("aw_chunk_1003_cast_fp16")]; + tensor var_10365_equation_0 = const()[name = tensor("op_10365_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10365_cast_fp16 = einsum(equation = var_10365_equation_0, values = (var_10203_cast_fp16, var_10003_cast_fp16))[name = tensor("op_10365_cast_fp16")]; + tensor var_10366_to_fp16 = const()[name = tensor("op_10366_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1005_cast_fp16 = mul(x = var_10365_cast_fp16, y = var_10366_to_fp16)[name = tensor("aw_chunk_1005_cast_fp16")]; + tensor var_10369_equation_0 = const()[name = tensor("op_10369_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10369_cast_fp16 = einsum(equation = var_10369_equation_0, values = (var_10203_cast_fp16, var_10010_cast_fp16))[name = tensor("op_10369_cast_fp16")]; + tensor var_10370_to_fp16 = const()[name = tensor("op_10370_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1007_cast_fp16 = mul(x = var_10369_cast_fp16, y = var_10370_to_fp16)[name = tensor("aw_chunk_1007_cast_fp16")]; + tensor var_10373_equation_0 = const()[name = tensor("op_10373_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10373_cast_fp16 = einsum(equation = var_10373_equation_0, values = (var_10207_cast_fp16, var_10017_cast_fp16))[name = tensor("op_10373_cast_fp16")]; + tensor var_10374_to_fp16 = const()[name = tensor("op_10374_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1009_cast_fp16 = mul(x = var_10373_cast_fp16, y = var_10374_to_fp16)[name = tensor("aw_chunk_1009_cast_fp16")]; + tensor var_10377_equation_0 = const()[name = tensor("op_10377_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10377_cast_fp16 = einsum(equation = var_10377_equation_0, values = (var_10207_cast_fp16, var_10024_cast_fp16))[name = tensor("op_10377_cast_fp16")]; + tensor var_10378_to_fp16 = const()[name = tensor("op_10378_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1011_cast_fp16 = mul(x = var_10377_cast_fp16, y = var_10378_to_fp16)[name = tensor("aw_chunk_1011_cast_fp16")]; + tensor var_10381_equation_0 = const()[name = tensor("op_10381_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10381_cast_fp16 = einsum(equation = var_10381_equation_0, values = (var_10207_cast_fp16, var_10031_cast_fp16))[name = tensor("op_10381_cast_fp16")]; + tensor var_10382_to_fp16 = const()[name = tensor("op_10382_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1013_cast_fp16 = mul(x = var_10381_cast_fp16, y = var_10382_to_fp16)[name = tensor("aw_chunk_1013_cast_fp16")]; + tensor var_10385_equation_0 = const()[name = tensor("op_10385_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10385_cast_fp16 = einsum(equation = var_10385_equation_0, values = (var_10207_cast_fp16, var_10038_cast_fp16))[name = tensor("op_10385_cast_fp16")]; + tensor var_10386_to_fp16 = const()[name = tensor("op_10386_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1015_cast_fp16 = mul(x = var_10385_cast_fp16, y = var_10386_to_fp16)[name = tensor("aw_chunk_1015_cast_fp16")]; + tensor var_10389_equation_0 = const()[name = tensor("op_10389_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10389_cast_fp16 = einsum(equation = var_10389_equation_0, values = (var_10211_cast_fp16, var_10045_cast_fp16))[name = tensor("op_10389_cast_fp16")]; + tensor var_10390_to_fp16 = const()[name = tensor("op_10390_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1017_cast_fp16 = mul(x = var_10389_cast_fp16, y = var_10390_to_fp16)[name = tensor("aw_chunk_1017_cast_fp16")]; + tensor var_10393_equation_0 = const()[name = tensor("op_10393_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10393_cast_fp16 = einsum(equation = var_10393_equation_0, values = (var_10211_cast_fp16, var_10052_cast_fp16))[name = tensor("op_10393_cast_fp16")]; + tensor var_10394_to_fp16 = const()[name = tensor("op_10394_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1019_cast_fp16 = mul(x = var_10393_cast_fp16, y = var_10394_to_fp16)[name = tensor("aw_chunk_1019_cast_fp16")]; + tensor var_10397_equation_0 = const()[name = tensor("op_10397_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10397_cast_fp16 = einsum(equation = var_10397_equation_0, values = (var_10211_cast_fp16, var_10059_cast_fp16))[name = tensor("op_10397_cast_fp16")]; + tensor var_10398_to_fp16 = const()[name = tensor("op_10398_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1021_cast_fp16 = mul(x = var_10397_cast_fp16, y = var_10398_to_fp16)[name = tensor("aw_chunk_1021_cast_fp16")]; + tensor var_10401_equation_0 = const()[name = tensor("op_10401_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10401_cast_fp16 = einsum(equation = var_10401_equation_0, values = (var_10211_cast_fp16, var_10066_cast_fp16))[name = tensor("op_10401_cast_fp16")]; + tensor var_10402_to_fp16 = const()[name = tensor("op_10402_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1023_cast_fp16 = mul(x = var_10401_cast_fp16, y = var_10402_to_fp16)[name = tensor("aw_chunk_1023_cast_fp16")]; + tensor var_10405_equation_0 = const()[name = tensor("op_10405_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10405_cast_fp16 = einsum(equation = var_10405_equation_0, values = (var_10215_cast_fp16, var_10073_cast_fp16))[name = tensor("op_10405_cast_fp16")]; + tensor var_10406_to_fp16 = const()[name = tensor("op_10406_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1025_cast_fp16 = mul(x = var_10405_cast_fp16, y = var_10406_to_fp16)[name = tensor("aw_chunk_1025_cast_fp16")]; + tensor var_10409_equation_0 = const()[name = tensor("op_10409_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10409_cast_fp16 = einsum(equation = var_10409_equation_0, values = (var_10215_cast_fp16, var_10080_cast_fp16))[name = tensor("op_10409_cast_fp16")]; + tensor var_10410_to_fp16 = const()[name = tensor("op_10410_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1027_cast_fp16 = mul(x = var_10409_cast_fp16, y = var_10410_to_fp16)[name = tensor("aw_chunk_1027_cast_fp16")]; + tensor var_10413_equation_0 = const()[name = tensor("op_10413_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10413_cast_fp16 = einsum(equation = var_10413_equation_0, values = (var_10215_cast_fp16, var_10087_cast_fp16))[name = tensor("op_10413_cast_fp16")]; + tensor var_10414_to_fp16 = const()[name = tensor("op_10414_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1029_cast_fp16 = mul(x = var_10413_cast_fp16, y = var_10414_to_fp16)[name = tensor("aw_chunk_1029_cast_fp16")]; + tensor var_10417_equation_0 = const()[name = tensor("op_10417_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10417_cast_fp16 = einsum(equation = var_10417_equation_0, values = (var_10215_cast_fp16, var_10094_cast_fp16))[name = tensor("op_10417_cast_fp16")]; + tensor var_10418_to_fp16 = const()[name = tensor("op_10418_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1031_cast_fp16 = mul(x = var_10417_cast_fp16, y = var_10418_to_fp16)[name = tensor("aw_chunk_1031_cast_fp16")]; + tensor var_10421_equation_0 = const()[name = tensor("op_10421_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10421_cast_fp16 = einsum(equation = var_10421_equation_0, values = (var_10219_cast_fp16, var_10101_cast_fp16))[name = tensor("op_10421_cast_fp16")]; + tensor var_10422_to_fp16 = const()[name = tensor("op_10422_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1033_cast_fp16 = mul(x = var_10421_cast_fp16, y = var_10422_to_fp16)[name = tensor("aw_chunk_1033_cast_fp16")]; + tensor var_10425_equation_0 = const()[name = tensor("op_10425_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10425_cast_fp16 = einsum(equation = var_10425_equation_0, values = (var_10219_cast_fp16, var_10108_cast_fp16))[name = tensor("op_10425_cast_fp16")]; + tensor var_10426_to_fp16 = const()[name = tensor("op_10426_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1035_cast_fp16 = mul(x = var_10425_cast_fp16, y = var_10426_to_fp16)[name = tensor("aw_chunk_1035_cast_fp16")]; + tensor var_10429_equation_0 = const()[name = tensor("op_10429_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10429_cast_fp16 = einsum(equation = var_10429_equation_0, values = (var_10219_cast_fp16, var_10115_cast_fp16))[name = tensor("op_10429_cast_fp16")]; + tensor var_10430_to_fp16 = const()[name = tensor("op_10430_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1037_cast_fp16 = mul(x = var_10429_cast_fp16, y = var_10430_to_fp16)[name = tensor("aw_chunk_1037_cast_fp16")]; + tensor var_10433_equation_0 = const()[name = tensor("op_10433_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10433_cast_fp16 = einsum(equation = var_10433_equation_0, values = (var_10219_cast_fp16, var_10122_cast_fp16))[name = tensor("op_10433_cast_fp16")]; + tensor var_10434_to_fp16 = const()[name = tensor("op_10434_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1039_cast_fp16 = mul(x = var_10433_cast_fp16, y = var_10434_to_fp16)[name = tensor("aw_chunk_1039_cast_fp16")]; + tensor var_10437_equation_0 = const()[name = tensor("op_10437_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10437_cast_fp16 = einsum(equation = var_10437_equation_0, values = (var_10223_cast_fp16, var_10129_cast_fp16))[name = tensor("op_10437_cast_fp16")]; + tensor var_10438_to_fp16 = const()[name = tensor("op_10438_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1041_cast_fp16 = mul(x = var_10437_cast_fp16, y = var_10438_to_fp16)[name = tensor("aw_chunk_1041_cast_fp16")]; + tensor var_10441_equation_0 = const()[name = tensor("op_10441_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10441_cast_fp16 = einsum(equation = var_10441_equation_0, values = (var_10223_cast_fp16, var_10136_cast_fp16))[name = tensor("op_10441_cast_fp16")]; + tensor var_10442_to_fp16 = const()[name = tensor("op_10442_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1043_cast_fp16 = mul(x = var_10441_cast_fp16, y = var_10442_to_fp16)[name = tensor("aw_chunk_1043_cast_fp16")]; + tensor var_10445_equation_0 = const()[name = tensor("op_10445_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10445_cast_fp16 = einsum(equation = var_10445_equation_0, values = (var_10223_cast_fp16, var_10143_cast_fp16))[name = tensor("op_10445_cast_fp16")]; + tensor var_10446_to_fp16 = const()[name = tensor("op_10446_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1045_cast_fp16 = mul(x = var_10445_cast_fp16, y = var_10446_to_fp16)[name = tensor("aw_chunk_1045_cast_fp16")]; + tensor var_10449_equation_0 = const()[name = tensor("op_10449_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10449_cast_fp16 = einsum(equation = var_10449_equation_0, values = (var_10223_cast_fp16, var_10150_cast_fp16))[name = tensor("op_10449_cast_fp16")]; + tensor var_10450_to_fp16 = const()[name = tensor("op_10450_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1047_cast_fp16 = mul(x = var_10449_cast_fp16, y = var_10450_to_fp16)[name = tensor("aw_chunk_1047_cast_fp16")]; + tensor var_10453_equation_0 = const()[name = tensor("op_10453_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10453_cast_fp16 = einsum(equation = var_10453_equation_0, values = (var_10227_cast_fp16, var_10157_cast_fp16))[name = tensor("op_10453_cast_fp16")]; + tensor var_10454_to_fp16 = const()[name = tensor("op_10454_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1049_cast_fp16 = mul(x = var_10453_cast_fp16, y = var_10454_to_fp16)[name = tensor("aw_chunk_1049_cast_fp16")]; + tensor var_10457_equation_0 = const()[name = tensor("op_10457_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10457_cast_fp16 = einsum(equation = var_10457_equation_0, values = (var_10227_cast_fp16, var_10164_cast_fp16))[name = tensor("op_10457_cast_fp16")]; + tensor var_10458_to_fp16 = const()[name = tensor("op_10458_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1051_cast_fp16 = mul(x = var_10457_cast_fp16, y = var_10458_to_fp16)[name = tensor("aw_chunk_1051_cast_fp16")]; + tensor var_10461_equation_0 = const()[name = tensor("op_10461_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10461_cast_fp16 = einsum(equation = var_10461_equation_0, values = (var_10227_cast_fp16, var_10171_cast_fp16))[name = tensor("op_10461_cast_fp16")]; + tensor var_10462_to_fp16 = const()[name = tensor("op_10462_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1053_cast_fp16 = mul(x = var_10461_cast_fp16, y = var_10462_to_fp16)[name = tensor("aw_chunk_1053_cast_fp16")]; + tensor var_10465_equation_0 = const()[name = tensor("op_10465_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_10465_cast_fp16 = einsum(equation = var_10465_equation_0, values = (var_10227_cast_fp16, var_10178_cast_fp16))[name = tensor("op_10465_cast_fp16")]; + tensor var_10466_to_fp16 = const()[name = tensor("op_10466_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1055_cast_fp16 = mul(x = var_10465_cast_fp16, y = var_10466_to_fp16)[name = tensor("aw_chunk_1055_cast_fp16")]; + tensor var_10468_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_961_cast_fp16)[name = tensor("op_10468_cast_fp16")]; + tensor var_10469_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_963_cast_fp16)[name = tensor("op_10469_cast_fp16")]; + tensor var_10470_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_965_cast_fp16)[name = tensor("op_10470_cast_fp16")]; + tensor var_10471_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_967_cast_fp16)[name = tensor("op_10471_cast_fp16")]; + tensor var_10472_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_969_cast_fp16)[name = tensor("op_10472_cast_fp16")]; + tensor var_10473_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_971_cast_fp16)[name = tensor("op_10473_cast_fp16")]; + tensor var_10474_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_973_cast_fp16)[name = tensor("op_10474_cast_fp16")]; + tensor var_10475_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_975_cast_fp16)[name = tensor("op_10475_cast_fp16")]; + tensor var_10476_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_977_cast_fp16)[name = tensor("op_10476_cast_fp16")]; + tensor var_10477_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_979_cast_fp16)[name = tensor("op_10477_cast_fp16")]; + tensor var_10478_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_981_cast_fp16)[name = tensor("op_10478_cast_fp16")]; + tensor var_10479_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_983_cast_fp16)[name = tensor("op_10479_cast_fp16")]; + tensor var_10480_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_985_cast_fp16)[name = tensor("op_10480_cast_fp16")]; + tensor var_10481_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_987_cast_fp16)[name = tensor("op_10481_cast_fp16")]; + tensor var_10482_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_989_cast_fp16)[name = tensor("op_10482_cast_fp16")]; + tensor var_10483_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_991_cast_fp16)[name = tensor("op_10483_cast_fp16")]; + tensor var_10484_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_993_cast_fp16)[name = tensor("op_10484_cast_fp16")]; + tensor var_10485_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_995_cast_fp16)[name = tensor("op_10485_cast_fp16")]; + tensor var_10486_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_997_cast_fp16)[name = tensor("op_10486_cast_fp16")]; + tensor var_10487_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_999_cast_fp16)[name = tensor("op_10487_cast_fp16")]; + tensor var_10488_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1001_cast_fp16)[name = tensor("op_10488_cast_fp16")]; + tensor var_10489_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1003_cast_fp16)[name = tensor("op_10489_cast_fp16")]; + tensor var_10490_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1005_cast_fp16)[name = tensor("op_10490_cast_fp16")]; + tensor var_10491_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1007_cast_fp16)[name = tensor("op_10491_cast_fp16")]; + tensor var_10492_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1009_cast_fp16)[name = tensor("op_10492_cast_fp16")]; + tensor var_10493_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1011_cast_fp16)[name = tensor("op_10493_cast_fp16")]; + tensor var_10494_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1013_cast_fp16)[name = tensor("op_10494_cast_fp16")]; + tensor var_10495_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1015_cast_fp16)[name = tensor("op_10495_cast_fp16")]; + tensor var_10496_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1017_cast_fp16)[name = tensor("op_10496_cast_fp16")]; + tensor var_10497_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1019_cast_fp16)[name = tensor("op_10497_cast_fp16")]; + tensor var_10498_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1021_cast_fp16)[name = tensor("op_10498_cast_fp16")]; + tensor var_10499_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1023_cast_fp16)[name = tensor("op_10499_cast_fp16")]; + tensor var_10500_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1025_cast_fp16)[name = tensor("op_10500_cast_fp16")]; + tensor var_10501_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1027_cast_fp16)[name = tensor("op_10501_cast_fp16")]; + tensor var_10502_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1029_cast_fp16)[name = tensor("op_10502_cast_fp16")]; + tensor var_10503_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1031_cast_fp16)[name = tensor("op_10503_cast_fp16")]; + tensor var_10504_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1033_cast_fp16)[name = tensor("op_10504_cast_fp16")]; + tensor var_10505_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1035_cast_fp16)[name = tensor("op_10505_cast_fp16")]; + tensor var_10506_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1037_cast_fp16)[name = tensor("op_10506_cast_fp16")]; + tensor var_10507_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1039_cast_fp16)[name = tensor("op_10507_cast_fp16")]; + tensor var_10508_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1041_cast_fp16)[name = tensor("op_10508_cast_fp16")]; + tensor var_10509_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1043_cast_fp16)[name = tensor("op_10509_cast_fp16")]; + tensor var_10510_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1045_cast_fp16)[name = tensor("op_10510_cast_fp16")]; + tensor var_10511_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1047_cast_fp16)[name = tensor("op_10511_cast_fp16")]; + tensor var_10512_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1049_cast_fp16)[name = tensor("op_10512_cast_fp16")]; + tensor var_10513_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1051_cast_fp16)[name = tensor("op_10513_cast_fp16")]; + tensor var_10514_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1053_cast_fp16)[name = tensor("op_10514_cast_fp16")]; + tensor var_10515_cast_fp16 = softmax(axis = var_9741, x = aw_chunk_1055_cast_fp16)[name = tensor("op_10515_cast_fp16")]; + tensor var_10517_equation_0 = const()[name = tensor("op_10517_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10517_cast_fp16 = einsum(equation = var_10517_equation_0, values = (var_10229_cast_fp16, var_10468_cast_fp16))[name = tensor("op_10517_cast_fp16")]; + tensor var_10519_equation_0 = const()[name = tensor("op_10519_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10519_cast_fp16 = einsum(equation = var_10519_equation_0, values = (var_10229_cast_fp16, var_10469_cast_fp16))[name = tensor("op_10519_cast_fp16")]; + tensor var_10521_equation_0 = const()[name = tensor("op_10521_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10521_cast_fp16 = einsum(equation = var_10521_equation_0, values = (var_10229_cast_fp16, var_10470_cast_fp16))[name = tensor("op_10521_cast_fp16")]; + tensor var_10523_equation_0 = const()[name = tensor("op_10523_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10523_cast_fp16 = einsum(equation = var_10523_equation_0, values = (var_10229_cast_fp16, var_10471_cast_fp16))[name = tensor("op_10523_cast_fp16")]; + tensor var_10525_equation_0 = const()[name = tensor("op_10525_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10525_cast_fp16 = einsum(equation = var_10525_equation_0, values = (var_10233_cast_fp16, var_10472_cast_fp16))[name = tensor("op_10525_cast_fp16")]; + tensor var_10527_equation_0 = const()[name = tensor("op_10527_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10527_cast_fp16 = einsum(equation = var_10527_equation_0, values = (var_10233_cast_fp16, var_10473_cast_fp16))[name = tensor("op_10527_cast_fp16")]; + tensor var_10529_equation_0 = const()[name = tensor("op_10529_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10529_cast_fp16 = einsum(equation = var_10529_equation_0, values = (var_10233_cast_fp16, var_10474_cast_fp16))[name = tensor("op_10529_cast_fp16")]; + tensor var_10531_equation_0 = const()[name = tensor("op_10531_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10531_cast_fp16 = einsum(equation = var_10531_equation_0, values = (var_10233_cast_fp16, var_10475_cast_fp16))[name = tensor("op_10531_cast_fp16")]; + tensor var_10533_equation_0 = const()[name = tensor("op_10533_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10533_cast_fp16 = einsum(equation = var_10533_equation_0, values = (var_10237_cast_fp16, var_10476_cast_fp16))[name = tensor("op_10533_cast_fp16")]; + tensor var_10535_equation_0 = const()[name = tensor("op_10535_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10535_cast_fp16 = einsum(equation = var_10535_equation_0, values = (var_10237_cast_fp16, var_10477_cast_fp16))[name = tensor("op_10535_cast_fp16")]; + tensor var_10537_equation_0 = const()[name = tensor("op_10537_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10537_cast_fp16 = einsum(equation = var_10537_equation_0, values = (var_10237_cast_fp16, var_10478_cast_fp16))[name = tensor("op_10537_cast_fp16")]; + tensor var_10539_equation_0 = const()[name = tensor("op_10539_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10539_cast_fp16 = einsum(equation = var_10539_equation_0, values = (var_10237_cast_fp16, var_10479_cast_fp16))[name = tensor("op_10539_cast_fp16")]; + tensor var_10541_equation_0 = const()[name = tensor("op_10541_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10541_cast_fp16 = einsum(equation = var_10541_equation_0, values = (var_10241_cast_fp16, var_10480_cast_fp16))[name = tensor("op_10541_cast_fp16")]; + tensor var_10543_equation_0 = const()[name = tensor("op_10543_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10543_cast_fp16 = einsum(equation = var_10543_equation_0, values = (var_10241_cast_fp16, var_10481_cast_fp16))[name = tensor("op_10543_cast_fp16")]; + tensor var_10545_equation_0 = const()[name = tensor("op_10545_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10545_cast_fp16 = einsum(equation = var_10545_equation_0, values = (var_10241_cast_fp16, var_10482_cast_fp16))[name = tensor("op_10545_cast_fp16")]; + tensor var_10547_equation_0 = const()[name = tensor("op_10547_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10547_cast_fp16 = einsum(equation = var_10547_equation_0, values = (var_10241_cast_fp16, var_10483_cast_fp16))[name = tensor("op_10547_cast_fp16")]; + tensor var_10549_equation_0 = const()[name = tensor("op_10549_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10549_cast_fp16 = einsum(equation = var_10549_equation_0, values = (var_10245_cast_fp16, var_10484_cast_fp16))[name = tensor("op_10549_cast_fp16")]; + tensor var_10551_equation_0 = const()[name = tensor("op_10551_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10551_cast_fp16 = einsum(equation = var_10551_equation_0, values = (var_10245_cast_fp16, var_10485_cast_fp16))[name = tensor("op_10551_cast_fp16")]; + tensor var_10553_equation_0 = const()[name = tensor("op_10553_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10553_cast_fp16 = einsum(equation = var_10553_equation_0, values = (var_10245_cast_fp16, var_10486_cast_fp16))[name = tensor("op_10553_cast_fp16")]; + tensor var_10555_equation_0 = const()[name = tensor("op_10555_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10555_cast_fp16 = einsum(equation = var_10555_equation_0, values = (var_10245_cast_fp16, var_10487_cast_fp16))[name = tensor("op_10555_cast_fp16")]; + tensor var_10557_equation_0 = const()[name = tensor("op_10557_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10557_cast_fp16 = einsum(equation = var_10557_equation_0, values = (var_10249_cast_fp16, var_10488_cast_fp16))[name = tensor("op_10557_cast_fp16")]; + tensor var_10559_equation_0 = const()[name = tensor("op_10559_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10559_cast_fp16 = einsum(equation = var_10559_equation_0, values = (var_10249_cast_fp16, var_10489_cast_fp16))[name = tensor("op_10559_cast_fp16")]; + tensor var_10561_equation_0 = const()[name = tensor("op_10561_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10561_cast_fp16 = einsum(equation = var_10561_equation_0, values = (var_10249_cast_fp16, var_10490_cast_fp16))[name = tensor("op_10561_cast_fp16")]; + tensor var_10563_equation_0 = const()[name = tensor("op_10563_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10563_cast_fp16 = einsum(equation = var_10563_equation_0, values = (var_10249_cast_fp16, var_10491_cast_fp16))[name = tensor("op_10563_cast_fp16")]; + tensor var_10565_equation_0 = const()[name = tensor("op_10565_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10565_cast_fp16 = einsum(equation = var_10565_equation_0, values = (var_10253_cast_fp16, var_10492_cast_fp16))[name = tensor("op_10565_cast_fp16")]; + tensor var_10567_equation_0 = const()[name = tensor("op_10567_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10567_cast_fp16 = einsum(equation = var_10567_equation_0, values = (var_10253_cast_fp16, var_10493_cast_fp16))[name = tensor("op_10567_cast_fp16")]; + tensor var_10569_equation_0 = const()[name = tensor("op_10569_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10569_cast_fp16 = einsum(equation = var_10569_equation_0, values = (var_10253_cast_fp16, var_10494_cast_fp16))[name = tensor("op_10569_cast_fp16")]; + tensor var_10571_equation_0 = const()[name = tensor("op_10571_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10571_cast_fp16 = einsum(equation = var_10571_equation_0, values = (var_10253_cast_fp16, var_10495_cast_fp16))[name = tensor("op_10571_cast_fp16")]; + tensor var_10573_equation_0 = const()[name = tensor("op_10573_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10573_cast_fp16 = einsum(equation = var_10573_equation_0, values = (var_10257_cast_fp16, var_10496_cast_fp16))[name = tensor("op_10573_cast_fp16")]; + tensor var_10575_equation_0 = const()[name = tensor("op_10575_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10575_cast_fp16 = einsum(equation = var_10575_equation_0, values = (var_10257_cast_fp16, var_10497_cast_fp16))[name = tensor("op_10575_cast_fp16")]; + tensor var_10577_equation_0 = const()[name = tensor("op_10577_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10577_cast_fp16 = einsum(equation = var_10577_equation_0, values = (var_10257_cast_fp16, var_10498_cast_fp16))[name = tensor("op_10577_cast_fp16")]; + tensor var_10579_equation_0 = const()[name = tensor("op_10579_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10579_cast_fp16 = einsum(equation = var_10579_equation_0, values = (var_10257_cast_fp16, var_10499_cast_fp16))[name = tensor("op_10579_cast_fp16")]; + tensor var_10581_equation_0 = const()[name = tensor("op_10581_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10581_cast_fp16 = einsum(equation = var_10581_equation_0, values = (var_10261_cast_fp16, var_10500_cast_fp16))[name = tensor("op_10581_cast_fp16")]; + tensor var_10583_equation_0 = const()[name = tensor("op_10583_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10583_cast_fp16 = einsum(equation = var_10583_equation_0, values = (var_10261_cast_fp16, var_10501_cast_fp16))[name = tensor("op_10583_cast_fp16")]; + tensor var_10585_equation_0 = const()[name = tensor("op_10585_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10585_cast_fp16 = einsum(equation = var_10585_equation_0, values = (var_10261_cast_fp16, var_10502_cast_fp16))[name = tensor("op_10585_cast_fp16")]; + tensor var_10587_equation_0 = const()[name = tensor("op_10587_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10587_cast_fp16 = einsum(equation = var_10587_equation_0, values = (var_10261_cast_fp16, var_10503_cast_fp16))[name = tensor("op_10587_cast_fp16")]; + tensor var_10589_equation_0 = const()[name = tensor("op_10589_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10589_cast_fp16 = einsum(equation = var_10589_equation_0, values = (var_10265_cast_fp16, var_10504_cast_fp16))[name = tensor("op_10589_cast_fp16")]; + tensor var_10591_equation_0 = const()[name = tensor("op_10591_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10591_cast_fp16 = einsum(equation = var_10591_equation_0, values = (var_10265_cast_fp16, var_10505_cast_fp16))[name = tensor("op_10591_cast_fp16")]; + tensor var_10593_equation_0 = const()[name = tensor("op_10593_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10593_cast_fp16 = einsum(equation = var_10593_equation_0, values = (var_10265_cast_fp16, var_10506_cast_fp16))[name = tensor("op_10593_cast_fp16")]; + tensor var_10595_equation_0 = const()[name = tensor("op_10595_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10595_cast_fp16 = einsum(equation = var_10595_equation_0, values = (var_10265_cast_fp16, var_10507_cast_fp16))[name = tensor("op_10595_cast_fp16")]; + tensor var_10597_equation_0 = const()[name = tensor("op_10597_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10597_cast_fp16 = einsum(equation = var_10597_equation_0, values = (var_10269_cast_fp16, var_10508_cast_fp16))[name = tensor("op_10597_cast_fp16")]; + tensor var_10599_equation_0 = const()[name = tensor("op_10599_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10599_cast_fp16 = einsum(equation = var_10599_equation_0, values = (var_10269_cast_fp16, var_10509_cast_fp16))[name = tensor("op_10599_cast_fp16")]; + tensor var_10601_equation_0 = const()[name = tensor("op_10601_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10601_cast_fp16 = einsum(equation = var_10601_equation_0, values = (var_10269_cast_fp16, var_10510_cast_fp16))[name = tensor("op_10601_cast_fp16")]; + tensor var_10603_equation_0 = const()[name = tensor("op_10603_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10603_cast_fp16 = einsum(equation = var_10603_equation_0, values = (var_10269_cast_fp16, var_10511_cast_fp16))[name = tensor("op_10603_cast_fp16")]; + tensor var_10605_equation_0 = const()[name = tensor("op_10605_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10605_cast_fp16 = einsum(equation = var_10605_equation_0, values = (var_10273_cast_fp16, var_10512_cast_fp16))[name = tensor("op_10605_cast_fp16")]; + tensor var_10607_equation_0 = const()[name = tensor("op_10607_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10607_cast_fp16 = einsum(equation = var_10607_equation_0, values = (var_10273_cast_fp16, var_10513_cast_fp16))[name = tensor("op_10607_cast_fp16")]; + tensor var_10609_equation_0 = const()[name = tensor("op_10609_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10609_cast_fp16 = einsum(equation = var_10609_equation_0, values = (var_10273_cast_fp16, var_10514_cast_fp16))[name = tensor("op_10609_cast_fp16")]; + tensor var_10611_equation_0 = const()[name = tensor("op_10611_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_10611_cast_fp16 = einsum(equation = var_10611_equation_0, values = (var_10273_cast_fp16, var_10515_cast_fp16))[name = tensor("op_10611_cast_fp16")]; + tensor var_10613_interleave_0 = const()[name = tensor("op_10613_interleave_0"), val = tensor(false)]; + tensor var_10613_cast_fp16 = concat(axis = var_9724, interleave = var_10613_interleave_0, values = (var_10517_cast_fp16, var_10519_cast_fp16, var_10521_cast_fp16, var_10523_cast_fp16))[name = tensor("op_10613_cast_fp16")]; + tensor var_10615_interleave_0 = const()[name = tensor("op_10615_interleave_0"), val = tensor(false)]; + tensor var_10615_cast_fp16 = concat(axis = var_9724, interleave = var_10615_interleave_0, values = (var_10525_cast_fp16, var_10527_cast_fp16, var_10529_cast_fp16, var_10531_cast_fp16))[name = tensor("op_10615_cast_fp16")]; + tensor var_10617_interleave_0 = const()[name = tensor("op_10617_interleave_0"), val = tensor(false)]; + tensor var_10617_cast_fp16 = concat(axis = var_9724, interleave = var_10617_interleave_0, values = (var_10533_cast_fp16, var_10535_cast_fp16, var_10537_cast_fp16, var_10539_cast_fp16))[name = tensor("op_10617_cast_fp16")]; + tensor var_10619_interleave_0 = const()[name = tensor("op_10619_interleave_0"), val = tensor(false)]; + tensor var_10619_cast_fp16 = concat(axis = var_9724, interleave = var_10619_interleave_0, values = (var_10541_cast_fp16, var_10543_cast_fp16, var_10545_cast_fp16, var_10547_cast_fp16))[name = tensor("op_10619_cast_fp16")]; + tensor var_10621_interleave_0 = const()[name = tensor("op_10621_interleave_0"), val = tensor(false)]; + tensor var_10621_cast_fp16 = concat(axis = var_9724, interleave = var_10621_interleave_0, values = (var_10549_cast_fp16, var_10551_cast_fp16, var_10553_cast_fp16, var_10555_cast_fp16))[name = tensor("op_10621_cast_fp16")]; + tensor var_10623_interleave_0 = const()[name = tensor("op_10623_interleave_0"), val = tensor(false)]; + tensor var_10623_cast_fp16 = concat(axis = var_9724, interleave = var_10623_interleave_0, values = (var_10557_cast_fp16, var_10559_cast_fp16, var_10561_cast_fp16, var_10563_cast_fp16))[name = tensor("op_10623_cast_fp16")]; + tensor var_10625_interleave_0 = const()[name = tensor("op_10625_interleave_0"), val = tensor(false)]; + tensor var_10625_cast_fp16 = concat(axis = var_9724, interleave = var_10625_interleave_0, values = (var_10565_cast_fp16, var_10567_cast_fp16, var_10569_cast_fp16, var_10571_cast_fp16))[name = tensor("op_10625_cast_fp16")]; + tensor var_10627_interleave_0 = const()[name = tensor("op_10627_interleave_0"), val = tensor(false)]; + tensor var_10627_cast_fp16 = concat(axis = var_9724, interleave = var_10627_interleave_0, values = (var_10573_cast_fp16, var_10575_cast_fp16, var_10577_cast_fp16, var_10579_cast_fp16))[name = tensor("op_10627_cast_fp16")]; + tensor var_10629_interleave_0 = const()[name = tensor("op_10629_interleave_0"), val = tensor(false)]; + tensor var_10629_cast_fp16 = concat(axis = var_9724, interleave = var_10629_interleave_0, values = (var_10581_cast_fp16, var_10583_cast_fp16, var_10585_cast_fp16, var_10587_cast_fp16))[name = tensor("op_10629_cast_fp16")]; + tensor var_10631_interleave_0 = const()[name = tensor("op_10631_interleave_0"), val = tensor(false)]; + tensor var_10631_cast_fp16 = concat(axis = var_9724, interleave = var_10631_interleave_0, values = (var_10589_cast_fp16, var_10591_cast_fp16, var_10593_cast_fp16, var_10595_cast_fp16))[name = tensor("op_10631_cast_fp16")]; + tensor var_10633_interleave_0 = const()[name = tensor("op_10633_interleave_0"), val = tensor(false)]; + tensor var_10633_cast_fp16 = concat(axis = var_9724, interleave = var_10633_interleave_0, values = (var_10597_cast_fp16, var_10599_cast_fp16, var_10601_cast_fp16, var_10603_cast_fp16))[name = tensor("op_10633_cast_fp16")]; + tensor var_10635_interleave_0 = const()[name = tensor("op_10635_interleave_0"), val = tensor(false)]; + tensor var_10635_cast_fp16 = concat(axis = var_9724, interleave = var_10635_interleave_0, values = (var_10605_cast_fp16, var_10607_cast_fp16, var_10609_cast_fp16, var_10611_cast_fp16))[name = tensor("op_10635_cast_fp16")]; + tensor input_81_interleave_0 = const()[name = tensor("input_81_interleave_0"), val = tensor(false)]; + tensor input_81_cast_fp16 = concat(axis = var_9741, interleave = input_81_interleave_0, values = (var_10613_cast_fp16, var_10615_cast_fp16, var_10617_cast_fp16, var_10619_cast_fp16, var_10621_cast_fp16, var_10623_cast_fp16, var_10625_cast_fp16, var_10627_cast_fp16, var_10629_cast_fp16, var_10631_cast_fp16, var_10633_cast_fp16, var_10635_cast_fp16))[name = tensor("input_81_cast_fp16")]; + tensor var_10640 = const()[name = tensor("op_10640"), val = tensor([1, 1])]; + tensor var_10642 = const()[name = tensor("op_10642"), val = tensor([1, 1])]; + tensor obj_43_pad_type_0 = const()[name = tensor("obj_43_pad_type_0"), val = tensor("custom")]; + tensor obj_43_pad_0 = const()[name = tensor("obj_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151515456)))]; + tensor layers_10_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(152695168)))]; + tensor obj_43_cast_fp16 = conv(bias = layers_10_self_attn_o_proj_bias_to_fp16, dilations = var_10642, groups = var_9741, pad = obj_43_pad_0, pad_type = obj_43_pad_type_0, strides = var_10640, weight = layers_10_self_attn_o_proj_weight_to_fp16, x = input_81_cast_fp16)[name = tensor("obj_43_cast_fp16")]; + tensor inputs_43_cast_fp16 = add(x = inputs_41_cast_fp16, y = obj_43_cast_fp16)[name = tensor("inputs_43_cast_fp16")]; + tensor var_10648 = const()[name = tensor("op_10648"), val = tensor([1])]; + tensor channels_mean_43_cast_fp16 = reduce_mean(axes = var_10648, keep_dims = var_9742, x = inputs_43_cast_fp16)[name = tensor("channels_mean_43_cast_fp16")]; + tensor zero_mean_43_cast_fp16 = sub(x = inputs_43_cast_fp16, y = channels_mean_43_cast_fp16)[name = tensor("zero_mean_43_cast_fp16")]; + tensor zero_mean_sq_43_cast_fp16 = mul(x = zero_mean_43_cast_fp16, y = zero_mean_43_cast_fp16)[name = tensor("zero_mean_sq_43_cast_fp16")]; + tensor var_10652 = const()[name = tensor("op_10652"), val = tensor([1])]; + tensor var_10653_cast_fp16 = reduce_mean(axes = var_10652, keep_dims = var_9742, x = zero_mean_sq_43_cast_fp16)[name = tensor("op_10653_cast_fp16")]; + tensor var_10654_to_fp16 = const()[name = tensor("op_10654_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_10655_cast_fp16 = add(x = var_10653_cast_fp16, y = var_10654_to_fp16)[name = tensor("op_10655_cast_fp16")]; + tensor denom_43_epsilon_0_to_fp16 = const()[name = tensor("denom_43_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_43_cast_fp16 = rsqrt(epsilon = denom_43_epsilon_0_to_fp16, x = var_10655_cast_fp16)[name = tensor("denom_43_cast_fp16")]; + tensor out_43_cast_fp16 = mul(x = zero_mean_43_cast_fp16, y = denom_43_cast_fp16)[name = tensor("out_43_cast_fp16")]; + tensor input_83_gamma_0_to_fp16 = const()[name = tensor("input_83_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(152696768)))]; + tensor input_83_beta_0_to_fp16 = const()[name = tensor("input_83_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(152698368)))]; + tensor input_83_epsilon_0_to_fp16 = const()[name = tensor("input_83_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_83_cast_fp16 = batch_norm(beta = input_83_beta_0_to_fp16, epsilon = input_83_epsilon_0_to_fp16, gamma = input_83_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_43_cast_fp16)[name = tensor("input_83_cast_fp16")]; + tensor var_10666 = const()[name = tensor("op_10666"), val = tensor([1, 1])]; + tensor var_10668 = const()[name = tensor("op_10668"), val = tensor([1, 1])]; + tensor input_85_pad_type_0 = const()[name = tensor("input_85_pad_type_0"), val = tensor("custom")]; + tensor input_85_pad_0 = const()[name = tensor("input_85_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_fc1_weight_to_fp16 = const()[name = tensor("layers_10_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(152699968)))]; + tensor layers_10_fc1_bias_to_fp16 = const()[name = tensor("layers_10_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(157418624)))]; + tensor input_85_cast_fp16 = conv(bias = layers_10_fc1_bias_to_fp16, dilations = var_10668, groups = var_9741, pad = input_85_pad_0, pad_type = input_85_pad_type_0, strides = var_10666, weight = layers_10_fc1_weight_to_fp16, x = input_83_cast_fp16)[name = tensor("input_85_cast_fp16")]; + tensor input_87_mode_0 = const()[name = tensor("input_87_mode_0"), val = tensor("EXACT")]; + tensor input_87_cast_fp16 = gelu(mode = input_87_mode_0, x = input_85_cast_fp16)[name = tensor("input_87_cast_fp16")]; + tensor var_10674 = const()[name = tensor("op_10674"), val = tensor([1, 1])]; + tensor var_10676 = const()[name = tensor("op_10676"), val = tensor([1, 1])]; + tensor hidden_states_25_pad_type_0 = const()[name = tensor("hidden_states_25_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_25_pad_0 = const()[name = tensor("hidden_states_25_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_fc2_weight_to_fp16 = const()[name = tensor("layers_10_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(157424832)))]; + tensor layers_10_fc2_bias_to_fp16 = const()[name = tensor("layers_10_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(162143488)))]; + tensor hidden_states_25_cast_fp16 = conv(bias = layers_10_fc2_bias_to_fp16, dilations = var_10676, groups = var_9741, pad = hidden_states_25_pad_0, pad_type = hidden_states_25_pad_type_0, strides = var_10674, weight = layers_10_fc2_weight_to_fp16, x = input_87_cast_fp16)[name = tensor("hidden_states_25_cast_fp16")]; + tensor inputs_45_cast_fp16 = add(x = inputs_43_cast_fp16, y = hidden_states_25_cast_fp16)[name = tensor("inputs_45_cast_fp16")]; + tensor var_10683 = const()[name = tensor("op_10683"), val = tensor(3)]; + tensor var_10700 = const()[name = tensor("op_10700"), val = tensor(1)]; + tensor var_10701 = const()[name = tensor("op_10701"), val = tensor(true)]; + tensor var_10711 = const()[name = tensor("op_10711"), val = tensor([1])]; + tensor channels_mean_45_cast_fp16 = reduce_mean(axes = var_10711, keep_dims = var_10701, x = inputs_45_cast_fp16)[name = tensor("channels_mean_45_cast_fp16")]; + tensor zero_mean_45_cast_fp16 = sub(x = inputs_45_cast_fp16, y = channels_mean_45_cast_fp16)[name = tensor("zero_mean_45_cast_fp16")]; + tensor zero_mean_sq_45_cast_fp16 = mul(x = zero_mean_45_cast_fp16, y = zero_mean_45_cast_fp16)[name = tensor("zero_mean_sq_45_cast_fp16")]; + tensor var_10715 = const()[name = tensor("op_10715"), val = tensor([1])]; + tensor var_10716_cast_fp16 = reduce_mean(axes = var_10715, keep_dims = var_10701, x = zero_mean_sq_45_cast_fp16)[name = tensor("op_10716_cast_fp16")]; + tensor var_10717_to_fp16 = const()[name = tensor("op_10717_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_10718_cast_fp16 = add(x = var_10716_cast_fp16, y = var_10717_to_fp16)[name = tensor("op_10718_cast_fp16")]; + tensor denom_45_epsilon_0_to_fp16 = const()[name = tensor("denom_45_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_45_cast_fp16 = rsqrt(epsilon = denom_45_epsilon_0_to_fp16, x = var_10718_cast_fp16)[name = tensor("denom_45_cast_fp16")]; + tensor out_45_cast_fp16 = mul(x = zero_mean_45_cast_fp16, y = denom_45_cast_fp16)[name = tensor("out_45_cast_fp16")]; + tensor obj_45_gamma_0_to_fp16 = const()[name = tensor("obj_45_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(162145088)))]; + tensor obj_45_beta_0_to_fp16 = const()[name = tensor("obj_45_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(162146688)))]; + tensor obj_45_epsilon_0_to_fp16 = const()[name = tensor("obj_45_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_45_cast_fp16 = batch_norm(beta = obj_45_beta_0_to_fp16, epsilon = obj_45_epsilon_0_to_fp16, gamma = obj_45_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_45_cast_fp16)[name = tensor("obj_45_cast_fp16")]; + tensor var_10733 = const()[name = tensor("op_10733"), val = tensor([1, 1])]; + tensor var_10735 = const()[name = tensor("op_10735"), val = tensor([1, 1])]; + tensor query_pad_type_0 = const()[name = tensor("query_pad_type_0"), val = tensor("custom")]; + tensor query_pad_0 = const()[name = tensor("query_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(162148288)))]; + tensor layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(163328000)))]; + tensor query_cast_fp16 = conv(bias = layers_11_self_attn_q_proj_bias_to_fp16, dilations = var_10735, groups = var_10700, pad = query_pad_0, pad_type = query_pad_type_0, strides = var_10733, weight = layers_11_self_attn_q_proj_weight_to_fp16, x = obj_45_cast_fp16)[name = tensor("query_cast_fp16")]; + tensor var_10739 = const()[name = tensor("op_10739"), val = tensor([1, 1])]; + tensor var_10741 = const()[name = tensor("op_10741"), val = tensor([1, 1])]; + tensor key_pad_type_0 = const()[name = tensor("key_pad_type_0"), val = tensor("custom")]; + tensor key_pad_0 = const()[name = tensor("key_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(163329600)))]; + tensor key_cast_fp16 = conv(dilations = var_10741, groups = var_10700, pad = key_pad_0, pad_type = key_pad_type_0, strides = var_10739, weight = layers_11_self_attn_k_proj_weight_to_fp16, x = obj_45_cast_fp16)[name = tensor("key_cast_fp16")]; + tensor var_10746 = const()[name = tensor("op_10746"), val = tensor([1, 1])]; + tensor var_10748 = const()[name = tensor("op_10748"), val = tensor([1, 1])]; + tensor value_pad_type_0 = const()[name = tensor("value_pad_type_0"), val = tensor("custom")]; + tensor value_pad_0 = const()[name = tensor("value_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164509312)))]; + tensor layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165689024)))]; + tensor value_cast_fp16 = conv(bias = layers_11_self_attn_v_proj_bias_to_fp16, dilations = var_10748, groups = var_10700, pad = value_pad_0, pad_type = value_pad_type_0, strides = var_10746, weight = layers_11_self_attn_v_proj_weight_to_fp16, x = obj_45_cast_fp16)[name = tensor("value_cast_fp16")]; + tensor var_10755_begin_0 = const()[name = tensor("op_10755_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10755_end_0 = const()[name = tensor("op_10755_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10755_end_mask_0 = const()[name = tensor("op_10755_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10755_cast_fp16 = slice_by_index(begin = var_10755_begin_0, end = var_10755_end_0, end_mask = var_10755_end_mask_0, x = query_cast_fp16)[name = tensor("op_10755_cast_fp16")]; + tensor var_10759_begin_0 = const()[name = tensor("op_10759_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_10759_end_0 = const()[name = tensor("op_10759_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_10759_end_mask_0 = const()[name = tensor("op_10759_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10759_cast_fp16 = slice_by_index(begin = var_10759_begin_0, end = var_10759_end_0, end_mask = var_10759_end_mask_0, x = query_cast_fp16)[name = tensor("op_10759_cast_fp16")]; + tensor var_10763_begin_0 = const()[name = tensor("op_10763_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_10763_end_0 = const()[name = tensor("op_10763_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_10763_end_mask_0 = const()[name = tensor("op_10763_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10763_cast_fp16 = slice_by_index(begin = var_10763_begin_0, end = var_10763_end_0, end_mask = var_10763_end_mask_0, x = query_cast_fp16)[name = tensor("op_10763_cast_fp16")]; + tensor var_10767_begin_0 = const()[name = tensor("op_10767_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_10767_end_0 = const()[name = tensor("op_10767_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_10767_end_mask_0 = const()[name = tensor("op_10767_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10767_cast_fp16 = slice_by_index(begin = var_10767_begin_0, end = var_10767_end_0, end_mask = var_10767_end_mask_0, x = query_cast_fp16)[name = tensor("op_10767_cast_fp16")]; + tensor var_10771_begin_0 = const()[name = tensor("op_10771_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_10771_end_0 = const()[name = tensor("op_10771_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_10771_end_mask_0 = const()[name = tensor("op_10771_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10771_cast_fp16 = slice_by_index(begin = var_10771_begin_0, end = var_10771_end_0, end_mask = var_10771_end_mask_0, x = query_cast_fp16)[name = tensor("op_10771_cast_fp16")]; + tensor var_10775_begin_0 = const()[name = tensor("op_10775_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_10775_end_0 = const()[name = tensor("op_10775_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_10775_end_mask_0 = const()[name = tensor("op_10775_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10775_cast_fp16 = slice_by_index(begin = var_10775_begin_0, end = var_10775_end_0, end_mask = var_10775_end_mask_0, x = query_cast_fp16)[name = tensor("op_10775_cast_fp16")]; + tensor var_10779_begin_0 = const()[name = tensor("op_10779_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_10779_end_0 = const()[name = tensor("op_10779_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_10779_end_mask_0 = const()[name = tensor("op_10779_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10779_cast_fp16 = slice_by_index(begin = var_10779_begin_0, end = var_10779_end_0, end_mask = var_10779_end_mask_0, x = query_cast_fp16)[name = tensor("op_10779_cast_fp16")]; + tensor var_10783_begin_0 = const()[name = tensor("op_10783_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_10783_end_0 = const()[name = tensor("op_10783_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_10783_end_mask_0 = const()[name = tensor("op_10783_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10783_cast_fp16 = slice_by_index(begin = var_10783_begin_0, end = var_10783_end_0, end_mask = var_10783_end_mask_0, x = query_cast_fp16)[name = tensor("op_10783_cast_fp16")]; + tensor var_10787_begin_0 = const()[name = tensor("op_10787_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_10787_end_0 = const()[name = tensor("op_10787_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_10787_end_mask_0 = const()[name = tensor("op_10787_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10787_cast_fp16 = slice_by_index(begin = var_10787_begin_0, end = var_10787_end_0, end_mask = var_10787_end_mask_0, x = query_cast_fp16)[name = tensor("op_10787_cast_fp16")]; + tensor var_10791_begin_0 = const()[name = tensor("op_10791_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_10791_end_0 = const()[name = tensor("op_10791_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_10791_end_mask_0 = const()[name = tensor("op_10791_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10791_cast_fp16 = slice_by_index(begin = var_10791_begin_0, end = var_10791_end_0, end_mask = var_10791_end_mask_0, x = query_cast_fp16)[name = tensor("op_10791_cast_fp16")]; + tensor var_10795_begin_0 = const()[name = tensor("op_10795_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_10795_end_0 = const()[name = tensor("op_10795_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_10795_end_mask_0 = const()[name = tensor("op_10795_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10795_cast_fp16 = slice_by_index(begin = var_10795_begin_0, end = var_10795_end_0, end_mask = var_10795_end_mask_0, x = query_cast_fp16)[name = tensor("op_10795_cast_fp16")]; + tensor var_10799_begin_0 = const()[name = tensor("op_10799_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_10799_end_0 = const()[name = tensor("op_10799_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_10799_end_mask_0 = const()[name = tensor("op_10799_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_10799_cast_fp16 = slice_by_index(begin = var_10799_begin_0, end = var_10799_end_0, end_mask = var_10799_end_mask_0, x = query_cast_fp16)[name = tensor("op_10799_cast_fp16")]; + tensor var_10808_begin_0 = const()[name = tensor("op_10808_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10808_end_0 = const()[name = tensor("op_10808_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_10808_end_mask_0 = const()[name = tensor("op_10808_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10808_cast_fp16 = slice_by_index(begin = var_10808_begin_0, end = var_10808_end_0, end_mask = var_10808_end_mask_0, x = var_10755_cast_fp16)[name = tensor("op_10808_cast_fp16")]; + tensor var_10815_begin_0 = const()[name = tensor("op_10815_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_10815_end_0 = const()[name = tensor("op_10815_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_10815_end_mask_0 = const()[name = tensor("op_10815_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10815_cast_fp16 = slice_by_index(begin = var_10815_begin_0, end = var_10815_end_0, end_mask = var_10815_end_mask_0, x = var_10755_cast_fp16)[name = tensor("op_10815_cast_fp16")]; + tensor var_10822_begin_0 = const()[name = tensor("op_10822_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_10822_end_0 = const()[name = tensor("op_10822_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_10822_end_mask_0 = const()[name = tensor("op_10822_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10822_cast_fp16 = slice_by_index(begin = var_10822_begin_0, end = var_10822_end_0, end_mask = var_10822_end_mask_0, x = var_10755_cast_fp16)[name = tensor("op_10822_cast_fp16")]; + tensor var_10829_begin_0 = const()[name = tensor("op_10829_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_10829_end_0 = const()[name = tensor("op_10829_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10829_end_mask_0 = const()[name = tensor("op_10829_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10829_cast_fp16 = slice_by_index(begin = var_10829_begin_0, end = var_10829_end_0, end_mask = var_10829_end_mask_0, x = var_10755_cast_fp16)[name = tensor("op_10829_cast_fp16")]; + tensor var_10836_begin_0 = const()[name = tensor("op_10836_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10836_end_0 = const()[name = tensor("op_10836_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_10836_end_mask_0 = const()[name = tensor("op_10836_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10836_cast_fp16 = slice_by_index(begin = var_10836_begin_0, end = var_10836_end_0, end_mask = var_10836_end_mask_0, x = var_10759_cast_fp16)[name = tensor("op_10836_cast_fp16")]; + tensor var_10843_begin_0 = const()[name = tensor("op_10843_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_10843_end_0 = const()[name = tensor("op_10843_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_10843_end_mask_0 = const()[name = tensor("op_10843_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10843_cast_fp16 = slice_by_index(begin = var_10843_begin_0, end = var_10843_end_0, end_mask = var_10843_end_mask_0, x = var_10759_cast_fp16)[name = tensor("op_10843_cast_fp16")]; + tensor var_10850_begin_0 = const()[name = tensor("op_10850_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_10850_end_0 = const()[name = tensor("op_10850_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_10850_end_mask_0 = const()[name = tensor("op_10850_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10850_cast_fp16 = slice_by_index(begin = var_10850_begin_0, end = var_10850_end_0, end_mask = var_10850_end_mask_0, x = var_10759_cast_fp16)[name = tensor("op_10850_cast_fp16")]; + tensor var_10857_begin_0 = const()[name = tensor("op_10857_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_10857_end_0 = const()[name = tensor("op_10857_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10857_end_mask_0 = const()[name = tensor("op_10857_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10857_cast_fp16 = slice_by_index(begin = var_10857_begin_0, end = var_10857_end_0, end_mask = var_10857_end_mask_0, x = var_10759_cast_fp16)[name = tensor("op_10857_cast_fp16")]; + tensor var_10864_begin_0 = const()[name = tensor("op_10864_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10864_end_0 = const()[name = tensor("op_10864_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_10864_end_mask_0 = const()[name = tensor("op_10864_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10864_cast_fp16 = slice_by_index(begin = var_10864_begin_0, end = var_10864_end_0, end_mask = var_10864_end_mask_0, x = var_10763_cast_fp16)[name = tensor("op_10864_cast_fp16")]; + tensor var_10871_begin_0 = const()[name = tensor("op_10871_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_10871_end_0 = const()[name = tensor("op_10871_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_10871_end_mask_0 = const()[name = tensor("op_10871_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10871_cast_fp16 = slice_by_index(begin = var_10871_begin_0, end = var_10871_end_0, end_mask = var_10871_end_mask_0, x = var_10763_cast_fp16)[name = tensor("op_10871_cast_fp16")]; + tensor var_10878_begin_0 = const()[name = tensor("op_10878_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_10878_end_0 = const()[name = tensor("op_10878_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_10878_end_mask_0 = const()[name = tensor("op_10878_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10878_cast_fp16 = slice_by_index(begin = var_10878_begin_0, end = var_10878_end_0, end_mask = var_10878_end_mask_0, x = var_10763_cast_fp16)[name = tensor("op_10878_cast_fp16")]; + tensor var_10885_begin_0 = const()[name = tensor("op_10885_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_10885_end_0 = const()[name = tensor("op_10885_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10885_end_mask_0 = const()[name = tensor("op_10885_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10885_cast_fp16 = slice_by_index(begin = var_10885_begin_0, end = var_10885_end_0, end_mask = var_10885_end_mask_0, x = var_10763_cast_fp16)[name = tensor("op_10885_cast_fp16")]; + tensor var_10892_begin_0 = const()[name = tensor("op_10892_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10892_end_0 = const()[name = tensor("op_10892_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_10892_end_mask_0 = const()[name = tensor("op_10892_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10892_cast_fp16 = slice_by_index(begin = var_10892_begin_0, end = var_10892_end_0, end_mask = var_10892_end_mask_0, x = var_10767_cast_fp16)[name = tensor("op_10892_cast_fp16")]; + tensor var_10899_begin_0 = const()[name = tensor("op_10899_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_10899_end_0 = const()[name = tensor("op_10899_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_10899_end_mask_0 = const()[name = tensor("op_10899_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10899_cast_fp16 = slice_by_index(begin = var_10899_begin_0, end = var_10899_end_0, end_mask = var_10899_end_mask_0, x = var_10767_cast_fp16)[name = tensor("op_10899_cast_fp16")]; + tensor var_10906_begin_0 = const()[name = tensor("op_10906_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_10906_end_0 = const()[name = tensor("op_10906_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_10906_end_mask_0 = const()[name = tensor("op_10906_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10906_cast_fp16 = slice_by_index(begin = var_10906_begin_0, end = var_10906_end_0, end_mask = var_10906_end_mask_0, x = var_10767_cast_fp16)[name = tensor("op_10906_cast_fp16")]; + tensor var_10913_begin_0 = const()[name = tensor("op_10913_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_10913_end_0 = const()[name = tensor("op_10913_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10913_end_mask_0 = const()[name = tensor("op_10913_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10913_cast_fp16 = slice_by_index(begin = var_10913_begin_0, end = var_10913_end_0, end_mask = var_10913_end_mask_0, x = var_10767_cast_fp16)[name = tensor("op_10913_cast_fp16")]; + tensor var_10920_begin_0 = const()[name = tensor("op_10920_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10920_end_0 = const()[name = tensor("op_10920_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_10920_end_mask_0 = const()[name = tensor("op_10920_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10920_cast_fp16 = slice_by_index(begin = var_10920_begin_0, end = var_10920_end_0, end_mask = var_10920_end_mask_0, x = var_10771_cast_fp16)[name = tensor("op_10920_cast_fp16")]; + tensor var_10927_begin_0 = const()[name = tensor("op_10927_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_10927_end_0 = const()[name = tensor("op_10927_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_10927_end_mask_0 = const()[name = tensor("op_10927_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10927_cast_fp16 = slice_by_index(begin = var_10927_begin_0, end = var_10927_end_0, end_mask = var_10927_end_mask_0, x = var_10771_cast_fp16)[name = tensor("op_10927_cast_fp16")]; + tensor var_10934_begin_0 = const()[name = tensor("op_10934_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_10934_end_0 = const()[name = tensor("op_10934_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_10934_end_mask_0 = const()[name = tensor("op_10934_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10934_cast_fp16 = slice_by_index(begin = var_10934_begin_0, end = var_10934_end_0, end_mask = var_10934_end_mask_0, x = var_10771_cast_fp16)[name = tensor("op_10934_cast_fp16")]; + tensor var_10941_begin_0 = const()[name = tensor("op_10941_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_10941_end_0 = const()[name = tensor("op_10941_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10941_end_mask_0 = const()[name = tensor("op_10941_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10941_cast_fp16 = slice_by_index(begin = var_10941_begin_0, end = var_10941_end_0, end_mask = var_10941_end_mask_0, x = var_10771_cast_fp16)[name = tensor("op_10941_cast_fp16")]; + tensor var_10948_begin_0 = const()[name = tensor("op_10948_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10948_end_0 = const()[name = tensor("op_10948_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_10948_end_mask_0 = const()[name = tensor("op_10948_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10948_cast_fp16 = slice_by_index(begin = var_10948_begin_0, end = var_10948_end_0, end_mask = var_10948_end_mask_0, x = var_10775_cast_fp16)[name = tensor("op_10948_cast_fp16")]; + tensor var_10955_begin_0 = const()[name = tensor("op_10955_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_10955_end_0 = const()[name = tensor("op_10955_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_10955_end_mask_0 = const()[name = tensor("op_10955_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10955_cast_fp16 = slice_by_index(begin = var_10955_begin_0, end = var_10955_end_0, end_mask = var_10955_end_mask_0, x = var_10775_cast_fp16)[name = tensor("op_10955_cast_fp16")]; + tensor var_10962_begin_0 = const()[name = tensor("op_10962_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_10962_end_0 = const()[name = tensor("op_10962_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_10962_end_mask_0 = const()[name = tensor("op_10962_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10962_cast_fp16 = slice_by_index(begin = var_10962_begin_0, end = var_10962_end_0, end_mask = var_10962_end_mask_0, x = var_10775_cast_fp16)[name = tensor("op_10962_cast_fp16")]; + tensor var_10969_begin_0 = const()[name = tensor("op_10969_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_10969_end_0 = const()[name = tensor("op_10969_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10969_end_mask_0 = const()[name = tensor("op_10969_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10969_cast_fp16 = slice_by_index(begin = var_10969_begin_0, end = var_10969_end_0, end_mask = var_10969_end_mask_0, x = var_10775_cast_fp16)[name = tensor("op_10969_cast_fp16")]; + tensor var_10976_begin_0 = const()[name = tensor("op_10976_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_10976_end_0 = const()[name = tensor("op_10976_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_10976_end_mask_0 = const()[name = tensor("op_10976_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10976_cast_fp16 = slice_by_index(begin = var_10976_begin_0, end = var_10976_end_0, end_mask = var_10976_end_mask_0, x = var_10779_cast_fp16)[name = tensor("op_10976_cast_fp16")]; + tensor var_10983_begin_0 = const()[name = tensor("op_10983_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_10983_end_0 = const()[name = tensor("op_10983_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_10983_end_mask_0 = const()[name = tensor("op_10983_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10983_cast_fp16 = slice_by_index(begin = var_10983_begin_0, end = var_10983_end_0, end_mask = var_10983_end_mask_0, x = var_10779_cast_fp16)[name = tensor("op_10983_cast_fp16")]; + tensor var_10990_begin_0 = const()[name = tensor("op_10990_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_10990_end_0 = const()[name = tensor("op_10990_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_10990_end_mask_0 = const()[name = tensor("op_10990_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10990_cast_fp16 = slice_by_index(begin = var_10990_begin_0, end = var_10990_end_0, end_mask = var_10990_end_mask_0, x = var_10779_cast_fp16)[name = tensor("op_10990_cast_fp16")]; + tensor var_10997_begin_0 = const()[name = tensor("op_10997_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_10997_end_0 = const()[name = tensor("op_10997_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_10997_end_mask_0 = const()[name = tensor("op_10997_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_10997_cast_fp16 = slice_by_index(begin = var_10997_begin_0, end = var_10997_end_0, end_mask = var_10997_end_mask_0, x = var_10779_cast_fp16)[name = tensor("op_10997_cast_fp16")]; + tensor var_11004_begin_0 = const()[name = tensor("op_11004_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_11004_end_0 = const()[name = tensor("op_11004_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_11004_end_mask_0 = const()[name = tensor("op_11004_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11004_cast_fp16 = slice_by_index(begin = var_11004_begin_0, end = var_11004_end_0, end_mask = var_11004_end_mask_0, x = var_10783_cast_fp16)[name = tensor("op_11004_cast_fp16")]; + tensor var_11011_begin_0 = const()[name = tensor("op_11011_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_11011_end_0 = const()[name = tensor("op_11011_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_11011_end_mask_0 = const()[name = tensor("op_11011_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11011_cast_fp16 = slice_by_index(begin = var_11011_begin_0, end = var_11011_end_0, end_mask = var_11011_end_mask_0, x = var_10783_cast_fp16)[name = tensor("op_11011_cast_fp16")]; + tensor var_11018_begin_0 = const()[name = tensor("op_11018_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_11018_end_0 = const()[name = tensor("op_11018_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_11018_end_mask_0 = const()[name = tensor("op_11018_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11018_cast_fp16 = slice_by_index(begin = var_11018_begin_0, end = var_11018_end_0, end_mask = var_11018_end_mask_0, x = var_10783_cast_fp16)[name = tensor("op_11018_cast_fp16")]; + tensor var_11025_begin_0 = const()[name = tensor("op_11025_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_11025_end_0 = const()[name = tensor("op_11025_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_11025_end_mask_0 = const()[name = tensor("op_11025_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11025_cast_fp16 = slice_by_index(begin = var_11025_begin_0, end = var_11025_end_0, end_mask = var_11025_end_mask_0, x = var_10783_cast_fp16)[name = tensor("op_11025_cast_fp16")]; + tensor var_11032_begin_0 = const()[name = tensor("op_11032_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_11032_end_0 = const()[name = tensor("op_11032_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_11032_end_mask_0 = const()[name = tensor("op_11032_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11032_cast_fp16 = slice_by_index(begin = var_11032_begin_0, end = var_11032_end_0, end_mask = var_11032_end_mask_0, x = var_10787_cast_fp16)[name = tensor("op_11032_cast_fp16")]; + tensor var_11039_begin_0 = const()[name = tensor("op_11039_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_11039_end_0 = const()[name = tensor("op_11039_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_11039_end_mask_0 = const()[name = tensor("op_11039_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11039_cast_fp16 = slice_by_index(begin = var_11039_begin_0, end = var_11039_end_0, end_mask = var_11039_end_mask_0, x = var_10787_cast_fp16)[name = tensor("op_11039_cast_fp16")]; + tensor var_11046_begin_0 = const()[name = tensor("op_11046_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_11046_end_0 = const()[name = tensor("op_11046_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_11046_end_mask_0 = const()[name = tensor("op_11046_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11046_cast_fp16 = slice_by_index(begin = var_11046_begin_0, end = var_11046_end_0, end_mask = var_11046_end_mask_0, x = var_10787_cast_fp16)[name = tensor("op_11046_cast_fp16")]; + tensor var_11053_begin_0 = const()[name = tensor("op_11053_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_11053_end_0 = const()[name = tensor("op_11053_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_11053_end_mask_0 = const()[name = tensor("op_11053_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11053_cast_fp16 = slice_by_index(begin = var_11053_begin_0, end = var_11053_end_0, end_mask = var_11053_end_mask_0, x = var_10787_cast_fp16)[name = tensor("op_11053_cast_fp16")]; + tensor var_11060_begin_0 = const()[name = tensor("op_11060_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_11060_end_0 = const()[name = tensor("op_11060_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_11060_end_mask_0 = const()[name = tensor("op_11060_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11060_cast_fp16 = slice_by_index(begin = var_11060_begin_0, end = var_11060_end_0, end_mask = var_11060_end_mask_0, x = var_10791_cast_fp16)[name = tensor("op_11060_cast_fp16")]; + tensor var_11067_begin_0 = const()[name = tensor("op_11067_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_11067_end_0 = const()[name = tensor("op_11067_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_11067_end_mask_0 = const()[name = tensor("op_11067_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11067_cast_fp16 = slice_by_index(begin = var_11067_begin_0, end = var_11067_end_0, end_mask = var_11067_end_mask_0, x = var_10791_cast_fp16)[name = tensor("op_11067_cast_fp16")]; + tensor var_11074_begin_0 = const()[name = tensor("op_11074_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_11074_end_0 = const()[name = tensor("op_11074_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_11074_end_mask_0 = const()[name = tensor("op_11074_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11074_cast_fp16 = slice_by_index(begin = var_11074_begin_0, end = var_11074_end_0, end_mask = var_11074_end_mask_0, x = var_10791_cast_fp16)[name = tensor("op_11074_cast_fp16")]; + tensor var_11081_begin_0 = const()[name = tensor("op_11081_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_11081_end_0 = const()[name = tensor("op_11081_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_11081_end_mask_0 = const()[name = tensor("op_11081_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11081_cast_fp16 = slice_by_index(begin = var_11081_begin_0, end = var_11081_end_0, end_mask = var_11081_end_mask_0, x = var_10791_cast_fp16)[name = tensor("op_11081_cast_fp16")]; + tensor var_11088_begin_0 = const()[name = tensor("op_11088_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_11088_end_0 = const()[name = tensor("op_11088_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_11088_end_mask_0 = const()[name = tensor("op_11088_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11088_cast_fp16 = slice_by_index(begin = var_11088_begin_0, end = var_11088_end_0, end_mask = var_11088_end_mask_0, x = var_10795_cast_fp16)[name = tensor("op_11088_cast_fp16")]; + tensor var_11095_begin_0 = const()[name = tensor("op_11095_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_11095_end_0 = const()[name = tensor("op_11095_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_11095_end_mask_0 = const()[name = tensor("op_11095_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11095_cast_fp16 = slice_by_index(begin = var_11095_begin_0, end = var_11095_end_0, end_mask = var_11095_end_mask_0, x = var_10795_cast_fp16)[name = tensor("op_11095_cast_fp16")]; + tensor var_11102_begin_0 = const()[name = tensor("op_11102_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_11102_end_0 = const()[name = tensor("op_11102_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_11102_end_mask_0 = const()[name = tensor("op_11102_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11102_cast_fp16 = slice_by_index(begin = var_11102_begin_0, end = var_11102_end_0, end_mask = var_11102_end_mask_0, x = var_10795_cast_fp16)[name = tensor("op_11102_cast_fp16")]; + tensor var_11109_begin_0 = const()[name = tensor("op_11109_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_11109_end_0 = const()[name = tensor("op_11109_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_11109_end_mask_0 = const()[name = tensor("op_11109_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11109_cast_fp16 = slice_by_index(begin = var_11109_begin_0, end = var_11109_end_0, end_mask = var_11109_end_mask_0, x = var_10795_cast_fp16)[name = tensor("op_11109_cast_fp16")]; + tensor var_11116_begin_0 = const()[name = tensor("op_11116_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_11116_end_0 = const()[name = tensor("op_11116_end_0"), val = tensor([1, 64, 1, 375])]; + tensor var_11116_end_mask_0 = const()[name = tensor("op_11116_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11116_cast_fp16 = slice_by_index(begin = var_11116_begin_0, end = var_11116_end_0, end_mask = var_11116_end_mask_0, x = var_10799_cast_fp16)[name = tensor("op_11116_cast_fp16")]; + tensor var_11123_begin_0 = const()[name = tensor("op_11123_begin_0"), val = tensor([0, 0, 0, 375])]; + tensor var_11123_end_0 = const()[name = tensor("op_11123_end_0"), val = tensor([1, 64, 1, 750])]; + tensor var_11123_end_mask_0 = const()[name = tensor("op_11123_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11123_cast_fp16 = slice_by_index(begin = var_11123_begin_0, end = var_11123_end_0, end_mask = var_11123_end_mask_0, x = var_10799_cast_fp16)[name = tensor("op_11123_cast_fp16")]; + tensor var_11130_begin_0 = const()[name = tensor("op_11130_begin_0"), val = tensor([0, 0, 0, 750])]; + tensor var_11130_end_0 = const()[name = tensor("op_11130_end_0"), val = tensor([1, 64, 1, 1125])]; + tensor var_11130_end_mask_0 = const()[name = tensor("op_11130_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11130_cast_fp16 = slice_by_index(begin = var_11130_begin_0, end = var_11130_end_0, end_mask = var_11130_end_mask_0, x = var_10799_cast_fp16)[name = tensor("op_11130_cast_fp16")]; + tensor var_11137_begin_0 = const()[name = tensor("op_11137_begin_0"), val = tensor([0, 0, 0, 1125])]; + tensor var_11137_end_0 = const()[name = tensor("op_11137_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_11137_end_mask_0 = const()[name = tensor("op_11137_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11137_cast_fp16 = slice_by_index(begin = var_11137_begin_0, end = var_11137_end_0, end_mask = var_11137_end_mask_0, x = var_10799_cast_fp16)[name = tensor("op_11137_cast_fp16")]; + tensor k_perm_0 = const()[name = tensor("k_perm_0"), val = tensor([0, 3, 2, 1])]; + tensor var_11142_begin_0 = const()[name = tensor("op_11142_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_11142_end_0 = const()[name = tensor("op_11142_end_0"), val = tensor([1, 1500, 1, 64])]; + tensor var_11142_end_mask_0 = const()[name = tensor("op_11142_end_mask_0"), val = tensor([true, true, true, false])]; + tensor transpose_0 = transpose(perm = k_perm_0, x = key_cast_fp16)[name = tensor("transpose_0")]; + tensor var_11142_cast_fp16 = slice_by_index(begin = var_11142_begin_0, end = var_11142_end_0, end_mask = var_11142_end_mask_0, x = transpose_0)[name = tensor("op_11142_cast_fp16")]; + tensor var_11146_begin_0 = const()[name = tensor("op_11146_begin_0"), val = tensor([0, 0, 0, 64])]; + tensor var_11146_end_0 = const()[name = tensor("op_11146_end_0"), val = tensor([1, 1500, 1, 128])]; + tensor var_11146_end_mask_0 = const()[name = tensor("op_11146_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11146_cast_fp16 = slice_by_index(begin = var_11146_begin_0, end = var_11146_end_0, end_mask = var_11146_end_mask_0, x = transpose_0)[name = tensor("op_11146_cast_fp16")]; + tensor var_11150_begin_0 = const()[name = tensor("op_11150_begin_0"), val = tensor([0, 0, 0, 128])]; + tensor var_11150_end_0 = const()[name = tensor("op_11150_end_0"), val = tensor([1, 1500, 1, 192])]; + tensor var_11150_end_mask_0 = const()[name = tensor("op_11150_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11150_cast_fp16 = slice_by_index(begin = var_11150_begin_0, end = var_11150_end_0, end_mask = var_11150_end_mask_0, x = transpose_0)[name = tensor("op_11150_cast_fp16")]; + tensor var_11154_begin_0 = const()[name = tensor("op_11154_begin_0"), val = tensor([0, 0, 0, 192])]; + tensor var_11154_end_0 = const()[name = tensor("op_11154_end_0"), val = tensor([1, 1500, 1, 256])]; + tensor var_11154_end_mask_0 = const()[name = tensor("op_11154_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11154_cast_fp16 = slice_by_index(begin = var_11154_begin_0, end = var_11154_end_0, end_mask = var_11154_end_mask_0, x = transpose_0)[name = tensor("op_11154_cast_fp16")]; + tensor var_11158_begin_0 = const()[name = tensor("op_11158_begin_0"), val = tensor([0, 0, 0, 256])]; + tensor var_11158_end_0 = const()[name = tensor("op_11158_end_0"), val = tensor([1, 1500, 1, 320])]; + tensor var_11158_end_mask_0 = const()[name = tensor("op_11158_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11158_cast_fp16 = slice_by_index(begin = var_11158_begin_0, end = var_11158_end_0, end_mask = var_11158_end_mask_0, x = transpose_0)[name = tensor("op_11158_cast_fp16")]; + tensor var_11162_begin_0 = const()[name = tensor("op_11162_begin_0"), val = tensor([0, 0, 0, 320])]; + tensor var_11162_end_0 = const()[name = tensor("op_11162_end_0"), val = tensor([1, 1500, 1, 384])]; + tensor var_11162_end_mask_0 = const()[name = tensor("op_11162_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11162_cast_fp16 = slice_by_index(begin = var_11162_begin_0, end = var_11162_end_0, end_mask = var_11162_end_mask_0, x = transpose_0)[name = tensor("op_11162_cast_fp16")]; + tensor var_11166_begin_0 = const()[name = tensor("op_11166_begin_0"), val = tensor([0, 0, 0, 384])]; + tensor var_11166_end_0 = const()[name = tensor("op_11166_end_0"), val = tensor([1, 1500, 1, 448])]; + tensor var_11166_end_mask_0 = const()[name = tensor("op_11166_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11166_cast_fp16 = slice_by_index(begin = var_11166_begin_0, end = var_11166_end_0, end_mask = var_11166_end_mask_0, x = transpose_0)[name = tensor("op_11166_cast_fp16")]; + tensor var_11170_begin_0 = const()[name = tensor("op_11170_begin_0"), val = tensor([0, 0, 0, 448])]; + tensor var_11170_end_0 = const()[name = tensor("op_11170_end_0"), val = tensor([1, 1500, 1, 512])]; + tensor var_11170_end_mask_0 = const()[name = tensor("op_11170_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11170_cast_fp16 = slice_by_index(begin = var_11170_begin_0, end = var_11170_end_0, end_mask = var_11170_end_mask_0, x = transpose_0)[name = tensor("op_11170_cast_fp16")]; + tensor var_11174_begin_0 = const()[name = tensor("op_11174_begin_0"), val = tensor([0, 0, 0, 512])]; + tensor var_11174_end_0 = const()[name = tensor("op_11174_end_0"), val = tensor([1, 1500, 1, 576])]; + tensor var_11174_end_mask_0 = const()[name = tensor("op_11174_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11174_cast_fp16 = slice_by_index(begin = var_11174_begin_0, end = var_11174_end_0, end_mask = var_11174_end_mask_0, x = transpose_0)[name = tensor("op_11174_cast_fp16")]; + tensor var_11178_begin_0 = const()[name = tensor("op_11178_begin_0"), val = tensor([0, 0, 0, 576])]; + tensor var_11178_end_0 = const()[name = tensor("op_11178_end_0"), val = tensor([1, 1500, 1, 640])]; + tensor var_11178_end_mask_0 = const()[name = tensor("op_11178_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11178_cast_fp16 = slice_by_index(begin = var_11178_begin_0, end = var_11178_end_0, end_mask = var_11178_end_mask_0, x = transpose_0)[name = tensor("op_11178_cast_fp16")]; + tensor var_11182_begin_0 = const()[name = tensor("op_11182_begin_0"), val = tensor([0, 0, 0, 640])]; + tensor var_11182_end_0 = const()[name = tensor("op_11182_end_0"), val = tensor([1, 1500, 1, 704])]; + tensor var_11182_end_mask_0 = const()[name = tensor("op_11182_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11182_cast_fp16 = slice_by_index(begin = var_11182_begin_0, end = var_11182_end_0, end_mask = var_11182_end_mask_0, x = transpose_0)[name = tensor("op_11182_cast_fp16")]; + tensor var_11186_begin_0 = const()[name = tensor("op_11186_begin_0"), val = tensor([0, 0, 0, 704])]; + tensor var_11186_end_0 = const()[name = tensor("op_11186_end_0"), val = tensor([1, 1500, 1, 768])]; + tensor var_11186_end_mask_0 = const()[name = tensor("op_11186_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_11186_cast_fp16 = slice_by_index(begin = var_11186_begin_0, end = var_11186_end_0, end_mask = var_11186_end_mask_0, x = transpose_0)[name = tensor("op_11186_cast_fp16")]; + tensor var_11188_begin_0 = const()[name = tensor("op_11188_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_11188_end_0 = const()[name = tensor("op_11188_end_0"), val = tensor([1, 64, 1, 1500])]; + tensor var_11188_end_mask_0 = const()[name = tensor("op_11188_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_11188_cast_fp16 = slice_by_index(begin = var_11188_begin_0, end = var_11188_end_0, end_mask = var_11188_end_mask_0, x = value_cast_fp16)[name = tensor("op_11188_cast_fp16")]; + tensor var_11192_begin_0 = const()[name = tensor("op_11192_begin_0"), val = tensor([0, 64, 0, 0])]; + tensor var_11192_end_0 = const()[name = tensor("op_11192_end_0"), val = tensor([1, 128, 1, 1500])]; + tensor var_11192_end_mask_0 = const()[name = tensor("op_11192_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_11192_cast_fp16 = slice_by_index(begin = var_11192_begin_0, end = var_11192_end_0, end_mask = var_11192_end_mask_0, x = value_cast_fp16)[name = tensor("op_11192_cast_fp16")]; + tensor var_11196_begin_0 = const()[name = tensor("op_11196_begin_0"), val = tensor([0, 128, 0, 0])]; + tensor var_11196_end_0 = const()[name = tensor("op_11196_end_0"), val = tensor([1, 192, 1, 1500])]; + tensor var_11196_end_mask_0 = const()[name = tensor("op_11196_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_11196_cast_fp16 = slice_by_index(begin = var_11196_begin_0, end = var_11196_end_0, end_mask = var_11196_end_mask_0, x = value_cast_fp16)[name = tensor("op_11196_cast_fp16")]; + tensor var_11200_begin_0 = const()[name = tensor("op_11200_begin_0"), val = tensor([0, 192, 0, 0])]; + tensor var_11200_end_0 = const()[name = tensor("op_11200_end_0"), val = tensor([1, 256, 1, 1500])]; + tensor var_11200_end_mask_0 = const()[name = tensor("op_11200_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_11200_cast_fp16 = slice_by_index(begin = var_11200_begin_0, end = var_11200_end_0, end_mask = var_11200_end_mask_0, x = value_cast_fp16)[name = tensor("op_11200_cast_fp16")]; + tensor var_11204_begin_0 = const()[name = tensor("op_11204_begin_0"), val = tensor([0, 256, 0, 0])]; + tensor var_11204_end_0 = const()[name = tensor("op_11204_end_0"), val = tensor([1, 320, 1, 1500])]; + tensor var_11204_end_mask_0 = const()[name = tensor("op_11204_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_11204_cast_fp16 = slice_by_index(begin = var_11204_begin_0, end = var_11204_end_0, end_mask = var_11204_end_mask_0, x = value_cast_fp16)[name = tensor("op_11204_cast_fp16")]; + tensor var_11208_begin_0 = const()[name = tensor("op_11208_begin_0"), val = tensor([0, 320, 0, 0])]; + tensor var_11208_end_0 = const()[name = tensor("op_11208_end_0"), val = tensor([1, 384, 1, 1500])]; + tensor var_11208_end_mask_0 = const()[name = tensor("op_11208_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_11208_cast_fp16 = slice_by_index(begin = var_11208_begin_0, end = var_11208_end_0, end_mask = var_11208_end_mask_0, x = value_cast_fp16)[name = tensor("op_11208_cast_fp16")]; + tensor var_11212_begin_0 = const()[name = tensor("op_11212_begin_0"), val = tensor([0, 384, 0, 0])]; + tensor var_11212_end_0 = const()[name = tensor("op_11212_end_0"), val = tensor([1, 448, 1, 1500])]; + tensor var_11212_end_mask_0 = const()[name = tensor("op_11212_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_11212_cast_fp16 = slice_by_index(begin = var_11212_begin_0, end = var_11212_end_0, end_mask = var_11212_end_mask_0, x = value_cast_fp16)[name = tensor("op_11212_cast_fp16")]; + tensor var_11216_begin_0 = const()[name = tensor("op_11216_begin_0"), val = tensor([0, 448, 0, 0])]; + tensor var_11216_end_0 = const()[name = tensor("op_11216_end_0"), val = tensor([1, 512, 1, 1500])]; + tensor var_11216_end_mask_0 = const()[name = tensor("op_11216_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_11216_cast_fp16 = slice_by_index(begin = var_11216_begin_0, end = var_11216_end_0, end_mask = var_11216_end_mask_0, x = value_cast_fp16)[name = tensor("op_11216_cast_fp16")]; + tensor var_11220_begin_0 = const()[name = tensor("op_11220_begin_0"), val = tensor([0, 512, 0, 0])]; + tensor var_11220_end_0 = const()[name = tensor("op_11220_end_0"), val = tensor([1, 576, 1, 1500])]; + tensor var_11220_end_mask_0 = const()[name = tensor("op_11220_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_11220_cast_fp16 = slice_by_index(begin = var_11220_begin_0, end = var_11220_end_0, end_mask = var_11220_end_mask_0, x = value_cast_fp16)[name = tensor("op_11220_cast_fp16")]; + tensor var_11224_begin_0 = const()[name = tensor("op_11224_begin_0"), val = tensor([0, 576, 0, 0])]; + tensor var_11224_end_0 = const()[name = tensor("op_11224_end_0"), val = tensor([1, 640, 1, 1500])]; + tensor var_11224_end_mask_0 = const()[name = tensor("op_11224_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_11224_cast_fp16 = slice_by_index(begin = var_11224_begin_0, end = var_11224_end_0, end_mask = var_11224_end_mask_0, x = value_cast_fp16)[name = tensor("op_11224_cast_fp16")]; + tensor var_11228_begin_0 = const()[name = tensor("op_11228_begin_0"), val = tensor([0, 640, 0, 0])]; + tensor var_11228_end_0 = const()[name = tensor("op_11228_end_0"), val = tensor([1, 704, 1, 1500])]; + tensor var_11228_end_mask_0 = const()[name = tensor("op_11228_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_11228_cast_fp16 = slice_by_index(begin = var_11228_begin_0, end = var_11228_end_0, end_mask = var_11228_end_mask_0, x = value_cast_fp16)[name = tensor("op_11228_cast_fp16")]; + tensor var_11232_begin_0 = const()[name = tensor("op_11232_begin_0"), val = tensor([0, 704, 0, 0])]; + tensor var_11232_end_0 = const()[name = tensor("op_11232_end_0"), val = tensor([1, 768, 1, 1500])]; + tensor var_11232_end_mask_0 = const()[name = tensor("op_11232_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_11232_cast_fp16 = slice_by_index(begin = var_11232_begin_0, end = var_11232_end_0, end_mask = var_11232_end_mask_0, x = value_cast_fp16)[name = tensor("op_11232_cast_fp16")]; + tensor var_11236_equation_0 = const()[name = tensor("op_11236_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11236_cast_fp16 = einsum(equation = var_11236_equation_0, values = (var_11142_cast_fp16, var_10808_cast_fp16))[name = tensor("op_11236_cast_fp16")]; + tensor var_11237_to_fp16 = const()[name = tensor("op_11237_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1057_cast_fp16 = mul(x = var_11236_cast_fp16, y = var_11237_to_fp16)[name = tensor("aw_chunk_1057_cast_fp16")]; + tensor var_11240_equation_0 = const()[name = tensor("op_11240_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11240_cast_fp16 = einsum(equation = var_11240_equation_0, values = (var_11142_cast_fp16, var_10815_cast_fp16))[name = tensor("op_11240_cast_fp16")]; + tensor var_11241_to_fp16 = const()[name = tensor("op_11241_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1059_cast_fp16 = mul(x = var_11240_cast_fp16, y = var_11241_to_fp16)[name = tensor("aw_chunk_1059_cast_fp16")]; + tensor var_11244_equation_0 = const()[name = tensor("op_11244_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11244_cast_fp16 = einsum(equation = var_11244_equation_0, values = (var_11142_cast_fp16, var_10822_cast_fp16))[name = tensor("op_11244_cast_fp16")]; + tensor var_11245_to_fp16 = const()[name = tensor("op_11245_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1061_cast_fp16 = mul(x = var_11244_cast_fp16, y = var_11245_to_fp16)[name = tensor("aw_chunk_1061_cast_fp16")]; + tensor var_11248_equation_0 = const()[name = tensor("op_11248_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11248_cast_fp16 = einsum(equation = var_11248_equation_0, values = (var_11142_cast_fp16, var_10829_cast_fp16))[name = tensor("op_11248_cast_fp16")]; + tensor var_11249_to_fp16 = const()[name = tensor("op_11249_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1063_cast_fp16 = mul(x = var_11248_cast_fp16, y = var_11249_to_fp16)[name = tensor("aw_chunk_1063_cast_fp16")]; + tensor var_11252_equation_0 = const()[name = tensor("op_11252_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11252_cast_fp16 = einsum(equation = var_11252_equation_0, values = (var_11146_cast_fp16, var_10836_cast_fp16))[name = tensor("op_11252_cast_fp16")]; + tensor var_11253_to_fp16 = const()[name = tensor("op_11253_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1065_cast_fp16 = mul(x = var_11252_cast_fp16, y = var_11253_to_fp16)[name = tensor("aw_chunk_1065_cast_fp16")]; + tensor var_11256_equation_0 = const()[name = tensor("op_11256_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11256_cast_fp16 = einsum(equation = var_11256_equation_0, values = (var_11146_cast_fp16, var_10843_cast_fp16))[name = tensor("op_11256_cast_fp16")]; + tensor var_11257_to_fp16 = const()[name = tensor("op_11257_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1067_cast_fp16 = mul(x = var_11256_cast_fp16, y = var_11257_to_fp16)[name = tensor("aw_chunk_1067_cast_fp16")]; + tensor var_11260_equation_0 = const()[name = tensor("op_11260_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11260_cast_fp16 = einsum(equation = var_11260_equation_0, values = (var_11146_cast_fp16, var_10850_cast_fp16))[name = tensor("op_11260_cast_fp16")]; + tensor var_11261_to_fp16 = const()[name = tensor("op_11261_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1069_cast_fp16 = mul(x = var_11260_cast_fp16, y = var_11261_to_fp16)[name = tensor("aw_chunk_1069_cast_fp16")]; + tensor var_11264_equation_0 = const()[name = tensor("op_11264_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11264_cast_fp16 = einsum(equation = var_11264_equation_0, values = (var_11146_cast_fp16, var_10857_cast_fp16))[name = tensor("op_11264_cast_fp16")]; + tensor var_11265_to_fp16 = const()[name = tensor("op_11265_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1071_cast_fp16 = mul(x = var_11264_cast_fp16, y = var_11265_to_fp16)[name = tensor("aw_chunk_1071_cast_fp16")]; + tensor var_11268_equation_0 = const()[name = tensor("op_11268_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11268_cast_fp16 = einsum(equation = var_11268_equation_0, values = (var_11150_cast_fp16, var_10864_cast_fp16))[name = tensor("op_11268_cast_fp16")]; + tensor var_11269_to_fp16 = const()[name = tensor("op_11269_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1073_cast_fp16 = mul(x = var_11268_cast_fp16, y = var_11269_to_fp16)[name = tensor("aw_chunk_1073_cast_fp16")]; + tensor var_11272_equation_0 = const()[name = tensor("op_11272_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11272_cast_fp16 = einsum(equation = var_11272_equation_0, values = (var_11150_cast_fp16, var_10871_cast_fp16))[name = tensor("op_11272_cast_fp16")]; + tensor var_11273_to_fp16 = const()[name = tensor("op_11273_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1075_cast_fp16 = mul(x = var_11272_cast_fp16, y = var_11273_to_fp16)[name = tensor("aw_chunk_1075_cast_fp16")]; + tensor var_11276_equation_0 = const()[name = tensor("op_11276_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11276_cast_fp16 = einsum(equation = var_11276_equation_0, values = (var_11150_cast_fp16, var_10878_cast_fp16))[name = tensor("op_11276_cast_fp16")]; + tensor var_11277_to_fp16 = const()[name = tensor("op_11277_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1077_cast_fp16 = mul(x = var_11276_cast_fp16, y = var_11277_to_fp16)[name = tensor("aw_chunk_1077_cast_fp16")]; + tensor var_11280_equation_0 = const()[name = tensor("op_11280_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11280_cast_fp16 = einsum(equation = var_11280_equation_0, values = (var_11150_cast_fp16, var_10885_cast_fp16))[name = tensor("op_11280_cast_fp16")]; + tensor var_11281_to_fp16 = const()[name = tensor("op_11281_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1079_cast_fp16 = mul(x = var_11280_cast_fp16, y = var_11281_to_fp16)[name = tensor("aw_chunk_1079_cast_fp16")]; + tensor var_11284_equation_0 = const()[name = tensor("op_11284_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11284_cast_fp16 = einsum(equation = var_11284_equation_0, values = (var_11154_cast_fp16, var_10892_cast_fp16))[name = tensor("op_11284_cast_fp16")]; + tensor var_11285_to_fp16 = const()[name = tensor("op_11285_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1081_cast_fp16 = mul(x = var_11284_cast_fp16, y = var_11285_to_fp16)[name = tensor("aw_chunk_1081_cast_fp16")]; + tensor var_11288_equation_0 = const()[name = tensor("op_11288_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11288_cast_fp16 = einsum(equation = var_11288_equation_0, values = (var_11154_cast_fp16, var_10899_cast_fp16))[name = tensor("op_11288_cast_fp16")]; + tensor var_11289_to_fp16 = const()[name = tensor("op_11289_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1083_cast_fp16 = mul(x = var_11288_cast_fp16, y = var_11289_to_fp16)[name = tensor("aw_chunk_1083_cast_fp16")]; + tensor var_11292_equation_0 = const()[name = tensor("op_11292_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11292_cast_fp16 = einsum(equation = var_11292_equation_0, values = (var_11154_cast_fp16, var_10906_cast_fp16))[name = tensor("op_11292_cast_fp16")]; + tensor var_11293_to_fp16 = const()[name = tensor("op_11293_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1085_cast_fp16 = mul(x = var_11292_cast_fp16, y = var_11293_to_fp16)[name = tensor("aw_chunk_1085_cast_fp16")]; + tensor var_11296_equation_0 = const()[name = tensor("op_11296_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11296_cast_fp16 = einsum(equation = var_11296_equation_0, values = (var_11154_cast_fp16, var_10913_cast_fp16))[name = tensor("op_11296_cast_fp16")]; + tensor var_11297_to_fp16 = const()[name = tensor("op_11297_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1087_cast_fp16 = mul(x = var_11296_cast_fp16, y = var_11297_to_fp16)[name = tensor("aw_chunk_1087_cast_fp16")]; + tensor var_11300_equation_0 = const()[name = tensor("op_11300_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11300_cast_fp16 = einsum(equation = var_11300_equation_0, values = (var_11158_cast_fp16, var_10920_cast_fp16))[name = tensor("op_11300_cast_fp16")]; + tensor var_11301_to_fp16 = const()[name = tensor("op_11301_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1089_cast_fp16 = mul(x = var_11300_cast_fp16, y = var_11301_to_fp16)[name = tensor("aw_chunk_1089_cast_fp16")]; + tensor var_11304_equation_0 = const()[name = tensor("op_11304_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11304_cast_fp16 = einsum(equation = var_11304_equation_0, values = (var_11158_cast_fp16, var_10927_cast_fp16))[name = tensor("op_11304_cast_fp16")]; + tensor var_11305_to_fp16 = const()[name = tensor("op_11305_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1091_cast_fp16 = mul(x = var_11304_cast_fp16, y = var_11305_to_fp16)[name = tensor("aw_chunk_1091_cast_fp16")]; + tensor var_11308_equation_0 = const()[name = tensor("op_11308_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11308_cast_fp16 = einsum(equation = var_11308_equation_0, values = (var_11158_cast_fp16, var_10934_cast_fp16))[name = tensor("op_11308_cast_fp16")]; + tensor var_11309_to_fp16 = const()[name = tensor("op_11309_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1093_cast_fp16 = mul(x = var_11308_cast_fp16, y = var_11309_to_fp16)[name = tensor("aw_chunk_1093_cast_fp16")]; + tensor var_11312_equation_0 = const()[name = tensor("op_11312_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11312_cast_fp16 = einsum(equation = var_11312_equation_0, values = (var_11158_cast_fp16, var_10941_cast_fp16))[name = tensor("op_11312_cast_fp16")]; + tensor var_11313_to_fp16 = const()[name = tensor("op_11313_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1095_cast_fp16 = mul(x = var_11312_cast_fp16, y = var_11313_to_fp16)[name = tensor("aw_chunk_1095_cast_fp16")]; + tensor var_11316_equation_0 = const()[name = tensor("op_11316_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11316_cast_fp16 = einsum(equation = var_11316_equation_0, values = (var_11162_cast_fp16, var_10948_cast_fp16))[name = tensor("op_11316_cast_fp16")]; + tensor var_11317_to_fp16 = const()[name = tensor("op_11317_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1097_cast_fp16 = mul(x = var_11316_cast_fp16, y = var_11317_to_fp16)[name = tensor("aw_chunk_1097_cast_fp16")]; + tensor var_11320_equation_0 = const()[name = tensor("op_11320_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11320_cast_fp16 = einsum(equation = var_11320_equation_0, values = (var_11162_cast_fp16, var_10955_cast_fp16))[name = tensor("op_11320_cast_fp16")]; + tensor var_11321_to_fp16 = const()[name = tensor("op_11321_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1099_cast_fp16 = mul(x = var_11320_cast_fp16, y = var_11321_to_fp16)[name = tensor("aw_chunk_1099_cast_fp16")]; + tensor var_11324_equation_0 = const()[name = tensor("op_11324_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11324_cast_fp16 = einsum(equation = var_11324_equation_0, values = (var_11162_cast_fp16, var_10962_cast_fp16))[name = tensor("op_11324_cast_fp16")]; + tensor var_11325_to_fp16 = const()[name = tensor("op_11325_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1101_cast_fp16 = mul(x = var_11324_cast_fp16, y = var_11325_to_fp16)[name = tensor("aw_chunk_1101_cast_fp16")]; + tensor var_11328_equation_0 = const()[name = tensor("op_11328_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11328_cast_fp16 = einsum(equation = var_11328_equation_0, values = (var_11162_cast_fp16, var_10969_cast_fp16))[name = tensor("op_11328_cast_fp16")]; + tensor var_11329_to_fp16 = const()[name = tensor("op_11329_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1103_cast_fp16 = mul(x = var_11328_cast_fp16, y = var_11329_to_fp16)[name = tensor("aw_chunk_1103_cast_fp16")]; + tensor var_11332_equation_0 = const()[name = tensor("op_11332_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11332_cast_fp16 = einsum(equation = var_11332_equation_0, values = (var_11166_cast_fp16, var_10976_cast_fp16))[name = tensor("op_11332_cast_fp16")]; + tensor var_11333_to_fp16 = const()[name = tensor("op_11333_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1105_cast_fp16 = mul(x = var_11332_cast_fp16, y = var_11333_to_fp16)[name = tensor("aw_chunk_1105_cast_fp16")]; + tensor var_11336_equation_0 = const()[name = tensor("op_11336_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11336_cast_fp16 = einsum(equation = var_11336_equation_0, values = (var_11166_cast_fp16, var_10983_cast_fp16))[name = tensor("op_11336_cast_fp16")]; + tensor var_11337_to_fp16 = const()[name = tensor("op_11337_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1107_cast_fp16 = mul(x = var_11336_cast_fp16, y = var_11337_to_fp16)[name = tensor("aw_chunk_1107_cast_fp16")]; + tensor var_11340_equation_0 = const()[name = tensor("op_11340_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11340_cast_fp16 = einsum(equation = var_11340_equation_0, values = (var_11166_cast_fp16, var_10990_cast_fp16))[name = tensor("op_11340_cast_fp16")]; + tensor var_11341_to_fp16 = const()[name = tensor("op_11341_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1109_cast_fp16 = mul(x = var_11340_cast_fp16, y = var_11341_to_fp16)[name = tensor("aw_chunk_1109_cast_fp16")]; + tensor var_11344_equation_0 = const()[name = tensor("op_11344_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11344_cast_fp16 = einsum(equation = var_11344_equation_0, values = (var_11166_cast_fp16, var_10997_cast_fp16))[name = tensor("op_11344_cast_fp16")]; + tensor var_11345_to_fp16 = const()[name = tensor("op_11345_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1111_cast_fp16 = mul(x = var_11344_cast_fp16, y = var_11345_to_fp16)[name = tensor("aw_chunk_1111_cast_fp16")]; + tensor var_11348_equation_0 = const()[name = tensor("op_11348_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11348_cast_fp16 = einsum(equation = var_11348_equation_0, values = (var_11170_cast_fp16, var_11004_cast_fp16))[name = tensor("op_11348_cast_fp16")]; + tensor var_11349_to_fp16 = const()[name = tensor("op_11349_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1113_cast_fp16 = mul(x = var_11348_cast_fp16, y = var_11349_to_fp16)[name = tensor("aw_chunk_1113_cast_fp16")]; + tensor var_11352_equation_0 = const()[name = tensor("op_11352_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11352_cast_fp16 = einsum(equation = var_11352_equation_0, values = (var_11170_cast_fp16, var_11011_cast_fp16))[name = tensor("op_11352_cast_fp16")]; + tensor var_11353_to_fp16 = const()[name = tensor("op_11353_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1115_cast_fp16 = mul(x = var_11352_cast_fp16, y = var_11353_to_fp16)[name = tensor("aw_chunk_1115_cast_fp16")]; + tensor var_11356_equation_0 = const()[name = tensor("op_11356_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11356_cast_fp16 = einsum(equation = var_11356_equation_0, values = (var_11170_cast_fp16, var_11018_cast_fp16))[name = tensor("op_11356_cast_fp16")]; + tensor var_11357_to_fp16 = const()[name = tensor("op_11357_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1117_cast_fp16 = mul(x = var_11356_cast_fp16, y = var_11357_to_fp16)[name = tensor("aw_chunk_1117_cast_fp16")]; + tensor var_11360_equation_0 = const()[name = tensor("op_11360_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11360_cast_fp16 = einsum(equation = var_11360_equation_0, values = (var_11170_cast_fp16, var_11025_cast_fp16))[name = tensor("op_11360_cast_fp16")]; + tensor var_11361_to_fp16 = const()[name = tensor("op_11361_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1119_cast_fp16 = mul(x = var_11360_cast_fp16, y = var_11361_to_fp16)[name = tensor("aw_chunk_1119_cast_fp16")]; + tensor var_11364_equation_0 = const()[name = tensor("op_11364_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11364_cast_fp16 = einsum(equation = var_11364_equation_0, values = (var_11174_cast_fp16, var_11032_cast_fp16))[name = tensor("op_11364_cast_fp16")]; + tensor var_11365_to_fp16 = const()[name = tensor("op_11365_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1121_cast_fp16 = mul(x = var_11364_cast_fp16, y = var_11365_to_fp16)[name = tensor("aw_chunk_1121_cast_fp16")]; + tensor var_11368_equation_0 = const()[name = tensor("op_11368_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11368_cast_fp16 = einsum(equation = var_11368_equation_0, values = (var_11174_cast_fp16, var_11039_cast_fp16))[name = tensor("op_11368_cast_fp16")]; + tensor var_11369_to_fp16 = const()[name = tensor("op_11369_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1123_cast_fp16 = mul(x = var_11368_cast_fp16, y = var_11369_to_fp16)[name = tensor("aw_chunk_1123_cast_fp16")]; + tensor var_11372_equation_0 = const()[name = tensor("op_11372_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11372_cast_fp16 = einsum(equation = var_11372_equation_0, values = (var_11174_cast_fp16, var_11046_cast_fp16))[name = tensor("op_11372_cast_fp16")]; + tensor var_11373_to_fp16 = const()[name = tensor("op_11373_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1125_cast_fp16 = mul(x = var_11372_cast_fp16, y = var_11373_to_fp16)[name = tensor("aw_chunk_1125_cast_fp16")]; + tensor var_11376_equation_0 = const()[name = tensor("op_11376_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11376_cast_fp16 = einsum(equation = var_11376_equation_0, values = (var_11174_cast_fp16, var_11053_cast_fp16))[name = tensor("op_11376_cast_fp16")]; + tensor var_11377_to_fp16 = const()[name = tensor("op_11377_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1127_cast_fp16 = mul(x = var_11376_cast_fp16, y = var_11377_to_fp16)[name = tensor("aw_chunk_1127_cast_fp16")]; + tensor var_11380_equation_0 = const()[name = tensor("op_11380_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11380_cast_fp16 = einsum(equation = var_11380_equation_0, values = (var_11178_cast_fp16, var_11060_cast_fp16))[name = tensor("op_11380_cast_fp16")]; + tensor var_11381_to_fp16 = const()[name = tensor("op_11381_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1129_cast_fp16 = mul(x = var_11380_cast_fp16, y = var_11381_to_fp16)[name = tensor("aw_chunk_1129_cast_fp16")]; + tensor var_11384_equation_0 = const()[name = tensor("op_11384_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11384_cast_fp16 = einsum(equation = var_11384_equation_0, values = (var_11178_cast_fp16, var_11067_cast_fp16))[name = tensor("op_11384_cast_fp16")]; + tensor var_11385_to_fp16 = const()[name = tensor("op_11385_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1131_cast_fp16 = mul(x = var_11384_cast_fp16, y = var_11385_to_fp16)[name = tensor("aw_chunk_1131_cast_fp16")]; + tensor var_11388_equation_0 = const()[name = tensor("op_11388_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11388_cast_fp16 = einsum(equation = var_11388_equation_0, values = (var_11178_cast_fp16, var_11074_cast_fp16))[name = tensor("op_11388_cast_fp16")]; + tensor var_11389_to_fp16 = const()[name = tensor("op_11389_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1133_cast_fp16 = mul(x = var_11388_cast_fp16, y = var_11389_to_fp16)[name = tensor("aw_chunk_1133_cast_fp16")]; + tensor var_11392_equation_0 = const()[name = tensor("op_11392_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11392_cast_fp16 = einsum(equation = var_11392_equation_0, values = (var_11178_cast_fp16, var_11081_cast_fp16))[name = tensor("op_11392_cast_fp16")]; + tensor var_11393_to_fp16 = const()[name = tensor("op_11393_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1135_cast_fp16 = mul(x = var_11392_cast_fp16, y = var_11393_to_fp16)[name = tensor("aw_chunk_1135_cast_fp16")]; + tensor var_11396_equation_0 = const()[name = tensor("op_11396_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11396_cast_fp16 = einsum(equation = var_11396_equation_0, values = (var_11182_cast_fp16, var_11088_cast_fp16))[name = tensor("op_11396_cast_fp16")]; + tensor var_11397_to_fp16 = const()[name = tensor("op_11397_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1137_cast_fp16 = mul(x = var_11396_cast_fp16, y = var_11397_to_fp16)[name = tensor("aw_chunk_1137_cast_fp16")]; + tensor var_11400_equation_0 = const()[name = tensor("op_11400_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11400_cast_fp16 = einsum(equation = var_11400_equation_0, values = (var_11182_cast_fp16, var_11095_cast_fp16))[name = tensor("op_11400_cast_fp16")]; + tensor var_11401_to_fp16 = const()[name = tensor("op_11401_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1139_cast_fp16 = mul(x = var_11400_cast_fp16, y = var_11401_to_fp16)[name = tensor("aw_chunk_1139_cast_fp16")]; + tensor var_11404_equation_0 = const()[name = tensor("op_11404_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11404_cast_fp16 = einsum(equation = var_11404_equation_0, values = (var_11182_cast_fp16, var_11102_cast_fp16))[name = tensor("op_11404_cast_fp16")]; + tensor var_11405_to_fp16 = const()[name = tensor("op_11405_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1141_cast_fp16 = mul(x = var_11404_cast_fp16, y = var_11405_to_fp16)[name = tensor("aw_chunk_1141_cast_fp16")]; + tensor var_11408_equation_0 = const()[name = tensor("op_11408_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11408_cast_fp16 = einsum(equation = var_11408_equation_0, values = (var_11182_cast_fp16, var_11109_cast_fp16))[name = tensor("op_11408_cast_fp16")]; + tensor var_11409_to_fp16 = const()[name = tensor("op_11409_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1143_cast_fp16 = mul(x = var_11408_cast_fp16, y = var_11409_to_fp16)[name = tensor("aw_chunk_1143_cast_fp16")]; + tensor var_11412_equation_0 = const()[name = tensor("op_11412_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11412_cast_fp16 = einsum(equation = var_11412_equation_0, values = (var_11186_cast_fp16, var_11116_cast_fp16))[name = tensor("op_11412_cast_fp16")]; + tensor var_11413_to_fp16 = const()[name = tensor("op_11413_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1145_cast_fp16 = mul(x = var_11412_cast_fp16, y = var_11413_to_fp16)[name = tensor("aw_chunk_1145_cast_fp16")]; + tensor var_11416_equation_0 = const()[name = tensor("op_11416_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11416_cast_fp16 = einsum(equation = var_11416_equation_0, values = (var_11186_cast_fp16, var_11123_cast_fp16))[name = tensor("op_11416_cast_fp16")]; + tensor var_11417_to_fp16 = const()[name = tensor("op_11417_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1147_cast_fp16 = mul(x = var_11416_cast_fp16, y = var_11417_to_fp16)[name = tensor("aw_chunk_1147_cast_fp16")]; + tensor var_11420_equation_0 = const()[name = tensor("op_11420_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11420_cast_fp16 = einsum(equation = var_11420_equation_0, values = (var_11186_cast_fp16, var_11130_cast_fp16))[name = tensor("op_11420_cast_fp16")]; + tensor var_11421_to_fp16 = const()[name = tensor("op_11421_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_1149_cast_fp16 = mul(x = var_11420_cast_fp16, y = var_11421_to_fp16)[name = tensor("aw_chunk_1149_cast_fp16")]; + tensor var_11424_equation_0 = const()[name = tensor("op_11424_equation_0"), val = tensor("bkhc,bchq->bkhq")]; + tensor var_11424_cast_fp16 = einsum(equation = var_11424_equation_0, values = (var_11186_cast_fp16, var_11137_cast_fp16))[name = tensor("op_11424_cast_fp16")]; + tensor var_11425_to_fp16 = const()[name = tensor("op_11425_to_fp16"), val = tensor(0x1p-3)]; + tensor aw_chunk_cast_fp16 = mul(x = var_11424_cast_fp16, y = var_11425_to_fp16)[name = tensor("aw_chunk_cast_fp16")]; + tensor var_11427_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1057_cast_fp16)[name = tensor("op_11427_cast_fp16")]; + tensor var_11428_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1059_cast_fp16)[name = tensor("op_11428_cast_fp16")]; + tensor var_11429_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1061_cast_fp16)[name = tensor("op_11429_cast_fp16")]; + tensor var_11430_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1063_cast_fp16)[name = tensor("op_11430_cast_fp16")]; + tensor var_11431_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1065_cast_fp16)[name = tensor("op_11431_cast_fp16")]; + tensor var_11432_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1067_cast_fp16)[name = tensor("op_11432_cast_fp16")]; + tensor var_11433_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1069_cast_fp16)[name = tensor("op_11433_cast_fp16")]; + tensor var_11434_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1071_cast_fp16)[name = tensor("op_11434_cast_fp16")]; + tensor var_11435_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1073_cast_fp16)[name = tensor("op_11435_cast_fp16")]; + tensor var_11436_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1075_cast_fp16)[name = tensor("op_11436_cast_fp16")]; + tensor var_11437_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1077_cast_fp16)[name = tensor("op_11437_cast_fp16")]; + tensor var_11438_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1079_cast_fp16)[name = tensor("op_11438_cast_fp16")]; + tensor var_11439_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1081_cast_fp16)[name = tensor("op_11439_cast_fp16")]; + tensor var_11440_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1083_cast_fp16)[name = tensor("op_11440_cast_fp16")]; + tensor var_11441_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1085_cast_fp16)[name = tensor("op_11441_cast_fp16")]; + tensor var_11442_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1087_cast_fp16)[name = tensor("op_11442_cast_fp16")]; + tensor var_11443_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1089_cast_fp16)[name = tensor("op_11443_cast_fp16")]; + tensor var_11444_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1091_cast_fp16)[name = tensor("op_11444_cast_fp16")]; + tensor var_11445_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1093_cast_fp16)[name = tensor("op_11445_cast_fp16")]; + tensor var_11446_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1095_cast_fp16)[name = tensor("op_11446_cast_fp16")]; + tensor var_11447_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1097_cast_fp16)[name = tensor("op_11447_cast_fp16")]; + tensor var_11448_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1099_cast_fp16)[name = tensor("op_11448_cast_fp16")]; + tensor var_11449_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1101_cast_fp16)[name = tensor("op_11449_cast_fp16")]; + tensor var_11450_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1103_cast_fp16)[name = tensor("op_11450_cast_fp16")]; + tensor var_11451_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1105_cast_fp16)[name = tensor("op_11451_cast_fp16")]; + tensor var_11452_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1107_cast_fp16)[name = tensor("op_11452_cast_fp16")]; + tensor var_11453_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1109_cast_fp16)[name = tensor("op_11453_cast_fp16")]; + tensor var_11454_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1111_cast_fp16)[name = tensor("op_11454_cast_fp16")]; + tensor var_11455_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1113_cast_fp16)[name = tensor("op_11455_cast_fp16")]; + tensor var_11456_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1115_cast_fp16)[name = tensor("op_11456_cast_fp16")]; + tensor var_11457_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1117_cast_fp16)[name = tensor("op_11457_cast_fp16")]; + tensor var_11458_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1119_cast_fp16)[name = tensor("op_11458_cast_fp16")]; + tensor var_11459_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1121_cast_fp16)[name = tensor("op_11459_cast_fp16")]; + tensor var_11460_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1123_cast_fp16)[name = tensor("op_11460_cast_fp16")]; + tensor var_11461_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1125_cast_fp16)[name = tensor("op_11461_cast_fp16")]; + tensor var_11462_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1127_cast_fp16)[name = tensor("op_11462_cast_fp16")]; + tensor var_11463_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1129_cast_fp16)[name = tensor("op_11463_cast_fp16")]; + tensor var_11464_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1131_cast_fp16)[name = tensor("op_11464_cast_fp16")]; + tensor var_11465_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1133_cast_fp16)[name = tensor("op_11465_cast_fp16")]; + tensor var_11466_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1135_cast_fp16)[name = tensor("op_11466_cast_fp16")]; + tensor var_11467_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1137_cast_fp16)[name = tensor("op_11467_cast_fp16")]; + tensor var_11468_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1139_cast_fp16)[name = tensor("op_11468_cast_fp16")]; + tensor var_11469_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1141_cast_fp16)[name = tensor("op_11469_cast_fp16")]; + tensor var_11470_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1143_cast_fp16)[name = tensor("op_11470_cast_fp16")]; + tensor var_11471_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1145_cast_fp16)[name = tensor("op_11471_cast_fp16")]; + tensor var_11472_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1147_cast_fp16)[name = tensor("op_11472_cast_fp16")]; + tensor var_11473_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_1149_cast_fp16)[name = tensor("op_11473_cast_fp16")]; + tensor var_11474_cast_fp16 = softmax(axis = var_10700, x = aw_chunk_cast_fp16)[name = tensor("op_11474_cast_fp16")]; + tensor var_11476_equation_0 = const()[name = tensor("op_11476_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11476_cast_fp16 = einsum(equation = var_11476_equation_0, values = (var_11188_cast_fp16, var_11427_cast_fp16))[name = tensor("op_11476_cast_fp16")]; + tensor var_11478_equation_0 = const()[name = tensor("op_11478_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11478_cast_fp16 = einsum(equation = var_11478_equation_0, values = (var_11188_cast_fp16, var_11428_cast_fp16))[name = tensor("op_11478_cast_fp16")]; + tensor var_11480_equation_0 = const()[name = tensor("op_11480_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11480_cast_fp16 = einsum(equation = var_11480_equation_0, values = (var_11188_cast_fp16, var_11429_cast_fp16))[name = tensor("op_11480_cast_fp16")]; + tensor var_11482_equation_0 = const()[name = tensor("op_11482_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11482_cast_fp16 = einsum(equation = var_11482_equation_0, values = (var_11188_cast_fp16, var_11430_cast_fp16))[name = tensor("op_11482_cast_fp16")]; + tensor var_11484_equation_0 = const()[name = tensor("op_11484_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11484_cast_fp16 = einsum(equation = var_11484_equation_0, values = (var_11192_cast_fp16, var_11431_cast_fp16))[name = tensor("op_11484_cast_fp16")]; + tensor var_11486_equation_0 = const()[name = tensor("op_11486_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11486_cast_fp16 = einsum(equation = var_11486_equation_0, values = (var_11192_cast_fp16, var_11432_cast_fp16))[name = tensor("op_11486_cast_fp16")]; + tensor var_11488_equation_0 = const()[name = tensor("op_11488_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11488_cast_fp16 = einsum(equation = var_11488_equation_0, values = (var_11192_cast_fp16, var_11433_cast_fp16))[name = tensor("op_11488_cast_fp16")]; + tensor var_11490_equation_0 = const()[name = tensor("op_11490_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11490_cast_fp16 = einsum(equation = var_11490_equation_0, values = (var_11192_cast_fp16, var_11434_cast_fp16))[name = tensor("op_11490_cast_fp16")]; + tensor var_11492_equation_0 = const()[name = tensor("op_11492_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11492_cast_fp16 = einsum(equation = var_11492_equation_0, values = (var_11196_cast_fp16, var_11435_cast_fp16))[name = tensor("op_11492_cast_fp16")]; + tensor var_11494_equation_0 = const()[name = tensor("op_11494_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11494_cast_fp16 = einsum(equation = var_11494_equation_0, values = (var_11196_cast_fp16, var_11436_cast_fp16))[name = tensor("op_11494_cast_fp16")]; + tensor var_11496_equation_0 = const()[name = tensor("op_11496_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11496_cast_fp16 = einsum(equation = var_11496_equation_0, values = (var_11196_cast_fp16, var_11437_cast_fp16))[name = tensor("op_11496_cast_fp16")]; + tensor var_11498_equation_0 = const()[name = tensor("op_11498_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11498_cast_fp16 = einsum(equation = var_11498_equation_0, values = (var_11196_cast_fp16, var_11438_cast_fp16))[name = tensor("op_11498_cast_fp16")]; + tensor var_11500_equation_0 = const()[name = tensor("op_11500_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11500_cast_fp16 = einsum(equation = var_11500_equation_0, values = (var_11200_cast_fp16, var_11439_cast_fp16))[name = tensor("op_11500_cast_fp16")]; + tensor var_11502_equation_0 = const()[name = tensor("op_11502_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11502_cast_fp16 = einsum(equation = var_11502_equation_0, values = (var_11200_cast_fp16, var_11440_cast_fp16))[name = tensor("op_11502_cast_fp16")]; + tensor var_11504_equation_0 = const()[name = tensor("op_11504_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11504_cast_fp16 = einsum(equation = var_11504_equation_0, values = (var_11200_cast_fp16, var_11441_cast_fp16))[name = tensor("op_11504_cast_fp16")]; + tensor var_11506_equation_0 = const()[name = tensor("op_11506_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11506_cast_fp16 = einsum(equation = var_11506_equation_0, values = (var_11200_cast_fp16, var_11442_cast_fp16))[name = tensor("op_11506_cast_fp16")]; + tensor var_11508_equation_0 = const()[name = tensor("op_11508_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11508_cast_fp16 = einsum(equation = var_11508_equation_0, values = (var_11204_cast_fp16, var_11443_cast_fp16))[name = tensor("op_11508_cast_fp16")]; + tensor var_11510_equation_0 = const()[name = tensor("op_11510_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11510_cast_fp16 = einsum(equation = var_11510_equation_0, values = (var_11204_cast_fp16, var_11444_cast_fp16))[name = tensor("op_11510_cast_fp16")]; + tensor var_11512_equation_0 = const()[name = tensor("op_11512_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11512_cast_fp16 = einsum(equation = var_11512_equation_0, values = (var_11204_cast_fp16, var_11445_cast_fp16))[name = tensor("op_11512_cast_fp16")]; + tensor var_11514_equation_0 = const()[name = tensor("op_11514_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11514_cast_fp16 = einsum(equation = var_11514_equation_0, values = (var_11204_cast_fp16, var_11446_cast_fp16))[name = tensor("op_11514_cast_fp16")]; + tensor var_11516_equation_0 = const()[name = tensor("op_11516_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11516_cast_fp16 = einsum(equation = var_11516_equation_0, values = (var_11208_cast_fp16, var_11447_cast_fp16))[name = tensor("op_11516_cast_fp16")]; + tensor var_11518_equation_0 = const()[name = tensor("op_11518_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11518_cast_fp16 = einsum(equation = var_11518_equation_0, values = (var_11208_cast_fp16, var_11448_cast_fp16))[name = tensor("op_11518_cast_fp16")]; + tensor var_11520_equation_0 = const()[name = tensor("op_11520_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11520_cast_fp16 = einsum(equation = var_11520_equation_0, values = (var_11208_cast_fp16, var_11449_cast_fp16))[name = tensor("op_11520_cast_fp16")]; + tensor var_11522_equation_0 = const()[name = tensor("op_11522_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11522_cast_fp16 = einsum(equation = var_11522_equation_0, values = (var_11208_cast_fp16, var_11450_cast_fp16))[name = tensor("op_11522_cast_fp16")]; + tensor var_11524_equation_0 = const()[name = tensor("op_11524_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11524_cast_fp16 = einsum(equation = var_11524_equation_0, values = (var_11212_cast_fp16, var_11451_cast_fp16))[name = tensor("op_11524_cast_fp16")]; + tensor var_11526_equation_0 = const()[name = tensor("op_11526_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11526_cast_fp16 = einsum(equation = var_11526_equation_0, values = (var_11212_cast_fp16, var_11452_cast_fp16))[name = tensor("op_11526_cast_fp16")]; + tensor var_11528_equation_0 = const()[name = tensor("op_11528_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11528_cast_fp16 = einsum(equation = var_11528_equation_0, values = (var_11212_cast_fp16, var_11453_cast_fp16))[name = tensor("op_11528_cast_fp16")]; + tensor var_11530_equation_0 = const()[name = tensor("op_11530_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11530_cast_fp16 = einsum(equation = var_11530_equation_0, values = (var_11212_cast_fp16, var_11454_cast_fp16))[name = tensor("op_11530_cast_fp16")]; + tensor var_11532_equation_0 = const()[name = tensor("op_11532_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11532_cast_fp16 = einsum(equation = var_11532_equation_0, values = (var_11216_cast_fp16, var_11455_cast_fp16))[name = tensor("op_11532_cast_fp16")]; + tensor var_11534_equation_0 = const()[name = tensor("op_11534_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11534_cast_fp16 = einsum(equation = var_11534_equation_0, values = (var_11216_cast_fp16, var_11456_cast_fp16))[name = tensor("op_11534_cast_fp16")]; + tensor var_11536_equation_0 = const()[name = tensor("op_11536_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11536_cast_fp16 = einsum(equation = var_11536_equation_0, values = (var_11216_cast_fp16, var_11457_cast_fp16))[name = tensor("op_11536_cast_fp16")]; + tensor var_11538_equation_0 = const()[name = tensor("op_11538_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11538_cast_fp16 = einsum(equation = var_11538_equation_0, values = (var_11216_cast_fp16, var_11458_cast_fp16))[name = tensor("op_11538_cast_fp16")]; + tensor var_11540_equation_0 = const()[name = tensor("op_11540_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11540_cast_fp16 = einsum(equation = var_11540_equation_0, values = (var_11220_cast_fp16, var_11459_cast_fp16))[name = tensor("op_11540_cast_fp16")]; + tensor var_11542_equation_0 = const()[name = tensor("op_11542_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11542_cast_fp16 = einsum(equation = var_11542_equation_0, values = (var_11220_cast_fp16, var_11460_cast_fp16))[name = tensor("op_11542_cast_fp16")]; + tensor var_11544_equation_0 = const()[name = tensor("op_11544_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11544_cast_fp16 = einsum(equation = var_11544_equation_0, values = (var_11220_cast_fp16, var_11461_cast_fp16))[name = tensor("op_11544_cast_fp16")]; + tensor var_11546_equation_0 = const()[name = tensor("op_11546_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11546_cast_fp16 = einsum(equation = var_11546_equation_0, values = (var_11220_cast_fp16, var_11462_cast_fp16))[name = tensor("op_11546_cast_fp16")]; + tensor var_11548_equation_0 = const()[name = tensor("op_11548_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11548_cast_fp16 = einsum(equation = var_11548_equation_0, values = (var_11224_cast_fp16, var_11463_cast_fp16))[name = tensor("op_11548_cast_fp16")]; + tensor var_11550_equation_0 = const()[name = tensor("op_11550_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11550_cast_fp16 = einsum(equation = var_11550_equation_0, values = (var_11224_cast_fp16, var_11464_cast_fp16))[name = tensor("op_11550_cast_fp16")]; + tensor var_11552_equation_0 = const()[name = tensor("op_11552_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11552_cast_fp16 = einsum(equation = var_11552_equation_0, values = (var_11224_cast_fp16, var_11465_cast_fp16))[name = tensor("op_11552_cast_fp16")]; + tensor var_11554_equation_0 = const()[name = tensor("op_11554_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11554_cast_fp16 = einsum(equation = var_11554_equation_0, values = (var_11224_cast_fp16, var_11466_cast_fp16))[name = tensor("op_11554_cast_fp16")]; + tensor var_11556_equation_0 = const()[name = tensor("op_11556_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11556_cast_fp16 = einsum(equation = var_11556_equation_0, values = (var_11228_cast_fp16, var_11467_cast_fp16))[name = tensor("op_11556_cast_fp16")]; + tensor var_11558_equation_0 = const()[name = tensor("op_11558_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11558_cast_fp16 = einsum(equation = var_11558_equation_0, values = (var_11228_cast_fp16, var_11468_cast_fp16))[name = tensor("op_11558_cast_fp16")]; + tensor var_11560_equation_0 = const()[name = tensor("op_11560_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11560_cast_fp16 = einsum(equation = var_11560_equation_0, values = (var_11228_cast_fp16, var_11469_cast_fp16))[name = tensor("op_11560_cast_fp16")]; + tensor var_11562_equation_0 = const()[name = tensor("op_11562_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11562_cast_fp16 = einsum(equation = var_11562_equation_0, values = (var_11228_cast_fp16, var_11470_cast_fp16))[name = tensor("op_11562_cast_fp16")]; + tensor var_11564_equation_0 = const()[name = tensor("op_11564_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11564_cast_fp16 = einsum(equation = var_11564_equation_0, values = (var_11232_cast_fp16, var_11471_cast_fp16))[name = tensor("op_11564_cast_fp16")]; + tensor var_11566_equation_0 = const()[name = tensor("op_11566_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11566_cast_fp16 = einsum(equation = var_11566_equation_0, values = (var_11232_cast_fp16, var_11472_cast_fp16))[name = tensor("op_11566_cast_fp16")]; + tensor var_11568_equation_0 = const()[name = tensor("op_11568_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11568_cast_fp16 = einsum(equation = var_11568_equation_0, values = (var_11232_cast_fp16, var_11473_cast_fp16))[name = tensor("op_11568_cast_fp16")]; + tensor var_11570_equation_0 = const()[name = tensor("op_11570_equation_0"), val = tensor("bchk,bkhq->bchq")]; + tensor var_11570_cast_fp16 = einsum(equation = var_11570_equation_0, values = (var_11232_cast_fp16, var_11474_cast_fp16))[name = tensor("op_11570_cast_fp16")]; + tensor var_11572_interleave_0 = const()[name = tensor("op_11572_interleave_0"), val = tensor(false)]; + tensor var_11572_cast_fp16 = concat(axis = var_10683, interleave = var_11572_interleave_0, values = (var_11476_cast_fp16, var_11478_cast_fp16, var_11480_cast_fp16, var_11482_cast_fp16))[name = tensor("op_11572_cast_fp16")]; + tensor var_11574_interleave_0 = const()[name = tensor("op_11574_interleave_0"), val = tensor(false)]; + tensor var_11574_cast_fp16 = concat(axis = var_10683, interleave = var_11574_interleave_0, values = (var_11484_cast_fp16, var_11486_cast_fp16, var_11488_cast_fp16, var_11490_cast_fp16))[name = tensor("op_11574_cast_fp16")]; + tensor var_11576_interleave_0 = const()[name = tensor("op_11576_interleave_0"), val = tensor(false)]; + tensor var_11576_cast_fp16 = concat(axis = var_10683, interleave = var_11576_interleave_0, values = (var_11492_cast_fp16, var_11494_cast_fp16, var_11496_cast_fp16, var_11498_cast_fp16))[name = tensor("op_11576_cast_fp16")]; + tensor var_11578_interleave_0 = const()[name = tensor("op_11578_interleave_0"), val = tensor(false)]; + tensor var_11578_cast_fp16 = concat(axis = var_10683, interleave = var_11578_interleave_0, values = (var_11500_cast_fp16, var_11502_cast_fp16, var_11504_cast_fp16, var_11506_cast_fp16))[name = tensor("op_11578_cast_fp16")]; + tensor var_11580_interleave_0 = const()[name = tensor("op_11580_interleave_0"), val = tensor(false)]; + tensor var_11580_cast_fp16 = concat(axis = var_10683, interleave = var_11580_interleave_0, values = (var_11508_cast_fp16, var_11510_cast_fp16, var_11512_cast_fp16, var_11514_cast_fp16))[name = tensor("op_11580_cast_fp16")]; + tensor var_11582_interleave_0 = const()[name = tensor("op_11582_interleave_0"), val = tensor(false)]; + tensor var_11582_cast_fp16 = concat(axis = var_10683, interleave = var_11582_interleave_0, values = (var_11516_cast_fp16, var_11518_cast_fp16, var_11520_cast_fp16, var_11522_cast_fp16))[name = tensor("op_11582_cast_fp16")]; + tensor var_11584_interleave_0 = const()[name = tensor("op_11584_interleave_0"), val = tensor(false)]; + tensor var_11584_cast_fp16 = concat(axis = var_10683, interleave = var_11584_interleave_0, values = (var_11524_cast_fp16, var_11526_cast_fp16, var_11528_cast_fp16, var_11530_cast_fp16))[name = tensor("op_11584_cast_fp16")]; + tensor var_11586_interleave_0 = const()[name = tensor("op_11586_interleave_0"), val = tensor(false)]; + tensor var_11586_cast_fp16 = concat(axis = var_10683, interleave = var_11586_interleave_0, values = (var_11532_cast_fp16, var_11534_cast_fp16, var_11536_cast_fp16, var_11538_cast_fp16))[name = tensor("op_11586_cast_fp16")]; + tensor var_11588_interleave_0 = const()[name = tensor("op_11588_interleave_0"), val = tensor(false)]; + tensor var_11588_cast_fp16 = concat(axis = var_10683, interleave = var_11588_interleave_0, values = (var_11540_cast_fp16, var_11542_cast_fp16, var_11544_cast_fp16, var_11546_cast_fp16))[name = tensor("op_11588_cast_fp16")]; + tensor var_11590_interleave_0 = const()[name = tensor("op_11590_interleave_0"), val = tensor(false)]; + tensor var_11590_cast_fp16 = concat(axis = var_10683, interleave = var_11590_interleave_0, values = (var_11548_cast_fp16, var_11550_cast_fp16, var_11552_cast_fp16, var_11554_cast_fp16))[name = tensor("op_11590_cast_fp16")]; + tensor var_11592_interleave_0 = const()[name = tensor("op_11592_interleave_0"), val = tensor(false)]; + tensor var_11592_cast_fp16 = concat(axis = var_10683, interleave = var_11592_interleave_0, values = (var_11556_cast_fp16, var_11558_cast_fp16, var_11560_cast_fp16, var_11562_cast_fp16))[name = tensor("op_11592_cast_fp16")]; + tensor var_11594_interleave_0 = const()[name = tensor("op_11594_interleave_0"), val = tensor(false)]; + tensor var_11594_cast_fp16 = concat(axis = var_10683, interleave = var_11594_interleave_0, values = (var_11564_cast_fp16, var_11566_cast_fp16, var_11568_cast_fp16, var_11570_cast_fp16))[name = tensor("op_11594_cast_fp16")]; + tensor input_89_interleave_0 = const()[name = tensor("input_89_interleave_0"), val = tensor(false)]; + tensor input_89_cast_fp16 = concat(axis = var_10700, interleave = input_89_interleave_0, values = (var_11572_cast_fp16, var_11574_cast_fp16, var_11576_cast_fp16, var_11578_cast_fp16, var_11580_cast_fp16, var_11582_cast_fp16, var_11584_cast_fp16, var_11586_cast_fp16, var_11588_cast_fp16, var_11590_cast_fp16, var_11592_cast_fp16, var_11594_cast_fp16))[name = tensor("input_89_cast_fp16")]; + tensor var_11599 = const()[name = tensor("op_11599"), val = tensor([1, 1])]; + tensor var_11601 = const()[name = tensor("op_11601"), val = tensor([1, 1])]; + tensor obj_pad_type_0 = const()[name = tensor("obj_pad_type_0"), val = tensor("custom")]; + tensor obj_pad_0 = const()[name = tensor("obj_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165690624)))]; + tensor layers_11_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166870336)))]; + tensor obj_cast_fp16 = conv(bias = layers_11_self_attn_o_proj_bias_to_fp16, dilations = var_11601, groups = var_10700, pad = obj_pad_0, pad_type = obj_pad_type_0, strides = var_11599, weight = layers_11_self_attn_o_proj_weight_to_fp16, x = input_89_cast_fp16)[name = tensor("obj_cast_fp16")]; + tensor inputs_47_cast_fp16 = add(x = inputs_45_cast_fp16, y = obj_cast_fp16)[name = tensor("inputs_47_cast_fp16")]; + tensor var_11607 = const()[name = tensor("op_11607"), val = tensor([1])]; + tensor channels_mean_47_cast_fp16 = reduce_mean(axes = var_11607, keep_dims = var_10701, x = inputs_47_cast_fp16)[name = tensor("channels_mean_47_cast_fp16")]; + tensor zero_mean_47_cast_fp16 = sub(x = inputs_47_cast_fp16, y = channels_mean_47_cast_fp16)[name = tensor("zero_mean_47_cast_fp16")]; + tensor zero_mean_sq_47_cast_fp16 = mul(x = zero_mean_47_cast_fp16, y = zero_mean_47_cast_fp16)[name = tensor("zero_mean_sq_47_cast_fp16")]; + tensor var_11611 = const()[name = tensor("op_11611"), val = tensor([1])]; + tensor var_11612_cast_fp16 = reduce_mean(axes = var_11611, keep_dims = var_10701, x = zero_mean_sq_47_cast_fp16)[name = tensor("op_11612_cast_fp16")]; + tensor var_11613_to_fp16 = const()[name = tensor("op_11613_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_11614_cast_fp16 = add(x = var_11612_cast_fp16, y = var_11613_to_fp16)[name = tensor("op_11614_cast_fp16")]; + tensor denom_47_epsilon_0_to_fp16 = const()[name = tensor("denom_47_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_47_cast_fp16 = rsqrt(epsilon = denom_47_epsilon_0_to_fp16, x = var_11614_cast_fp16)[name = tensor("denom_47_cast_fp16")]; + tensor out_47_cast_fp16 = mul(x = zero_mean_47_cast_fp16, y = denom_47_cast_fp16)[name = tensor("out_47_cast_fp16")]; + tensor input_91_gamma_0_to_fp16 = const()[name = tensor("input_91_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166871936)))]; + tensor input_91_beta_0_to_fp16 = const()[name = tensor("input_91_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166873536)))]; + tensor input_91_epsilon_0_to_fp16 = const()[name = tensor("input_91_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_91_cast_fp16 = batch_norm(beta = input_91_beta_0_to_fp16, epsilon = input_91_epsilon_0_to_fp16, gamma = input_91_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_47_cast_fp16)[name = tensor("input_91_cast_fp16")]; + tensor var_11625 = const()[name = tensor("op_11625"), val = tensor([1, 1])]; + tensor var_11627 = const()[name = tensor("op_11627"), val = tensor([1, 1])]; + tensor input_93_pad_type_0 = const()[name = tensor("input_93_pad_type_0"), val = tensor("custom")]; + tensor input_93_pad_0 = const()[name = tensor("input_93_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_fc1_weight_to_fp16 = const()[name = tensor("layers_11_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166875136)))]; + tensor layers_11_fc1_bias_to_fp16 = const()[name = tensor("layers_11_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(171593792)))]; + tensor input_93_cast_fp16 = conv(bias = layers_11_fc1_bias_to_fp16, dilations = var_11627, groups = var_10700, pad = input_93_pad_0, pad_type = input_93_pad_type_0, strides = var_11625, weight = layers_11_fc1_weight_to_fp16, x = input_91_cast_fp16)[name = tensor("input_93_cast_fp16")]; + tensor input_mode_0 = const()[name = tensor("input_mode_0"), val = tensor("EXACT")]; + tensor input_cast_fp16 = gelu(mode = input_mode_0, x = input_93_cast_fp16)[name = tensor("input_cast_fp16")]; + tensor var_11633 = const()[name = tensor("op_11633"), val = tensor([1, 1])]; + tensor var_11635 = const()[name = tensor("op_11635"), val = tensor([1, 1])]; + tensor hidden_states_pad_type_0 = const()[name = tensor("hidden_states_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_pad_0 = const()[name = tensor("hidden_states_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_fc2_weight_to_fp16 = const()[name = tensor("layers_11_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(171600000)))]; + tensor layers_11_fc2_bias_to_fp16 = const()[name = tensor("layers_11_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176318656)))]; + tensor hidden_states_cast_fp16 = conv(bias = layers_11_fc2_bias_to_fp16, dilations = var_11635, groups = var_10700, pad = hidden_states_pad_0, pad_type = hidden_states_pad_type_0, strides = var_11633, weight = layers_11_fc2_weight_to_fp16, x = input_cast_fp16)[name = tensor("hidden_states_cast_fp16")]; + tensor inputs_cast_fp16 = add(x = inputs_47_cast_fp16, y = hidden_states_cast_fp16)[name = tensor("inputs_cast_fp16")]; + tensor var_11641 = const()[name = tensor("op_11641"), val = tensor(true)]; + tensor var_11645 = const()[name = tensor("op_11645"), val = tensor([1])]; + tensor channels_mean_cast_fp16 = reduce_mean(axes = var_11645, keep_dims = var_11641, x = inputs_cast_fp16)[name = tensor("channels_mean_cast_fp16")]; + tensor zero_mean_cast_fp16 = sub(x = inputs_cast_fp16, y = channels_mean_cast_fp16)[name = tensor("zero_mean_cast_fp16")]; + tensor zero_mean_sq_cast_fp16 = mul(x = zero_mean_cast_fp16, y = zero_mean_cast_fp16)[name = tensor("zero_mean_sq_cast_fp16")]; + tensor var_11649 = const()[name = tensor("op_11649"), val = tensor([1])]; + tensor var_11650_cast_fp16 = reduce_mean(axes = var_11649, keep_dims = var_11641, x = zero_mean_sq_cast_fp16)[name = tensor("op_11650_cast_fp16")]; + tensor var_11651_to_fp16 = const()[name = tensor("op_11651_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_11652_cast_fp16 = add(x = var_11650_cast_fp16, y = var_11651_to_fp16)[name = tensor("op_11652_cast_fp16")]; + tensor denom_epsilon_0_to_fp16 = const()[name = tensor("denom_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_cast_fp16 = rsqrt(epsilon = denom_epsilon_0_to_fp16, x = var_11652_cast_fp16)[name = tensor("denom_cast_fp16")]; + tensor out_cast_fp16 = mul(x = zero_mean_cast_fp16, y = denom_cast_fp16)[name = tensor("out_cast_fp16")]; + tensor encoder_output_embeds_type_fp32_gamma_0_to_fp16 = const()[name = tensor("encoder_output_embeds_type_fp32_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176320256)))]; + tensor encoder_output_embeds_type_fp32_beta_0_to_fp16 = const()[name = tensor("encoder_output_embeds_type_fp32_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176321856)))]; + tensor encoder_output_embeds_type_fp32_epsilon_0_to_fp16 = const()[name = tensor("encoder_output_embeds_type_fp32_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor encoder_output_embeds = batch_norm(beta = encoder_output_embeds_type_fp32_beta_0_to_fp16, epsilon = encoder_output_embeds_type_fp32_epsilon_0_to_fp16, gamma = encoder_output_embeds_type_fp32_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_cast_fp16)[name = tensor("encoder_output_embeds_type_fp32_cast_fp16")]; + } -> (encoder_output_embeds); +} \ No newline at end of file diff --git a/openai_whisper-small/AudioEncoder.mlmodelc/model.mlmodel b/openai_whisper-small/AudioEncoder.mlmodelc/model.mlmodel new file mode 100644 index 0000000000000000000000000000000000000000..b6314fec31f6cf5901665aba75ae05333313cc2c --- /dev/null +++ b/openai_whisper-small/AudioEncoder.mlmodelc/model.mlmodel @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:68ca04660b8b050c68ca54c27d97c47e4133bc591422cb7009de8922d56fb8c9 +size 155271 diff --git 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a/openai_whisper-small/MelSpectrogram.mlmodelc/coremldata.bin b/openai_whisper-small/MelSpectrogram.mlmodelc/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..b1d9e7a102f740c68cdfc7272dc5b8007c48416a --- /dev/null +++ b/openai_whisper-small/MelSpectrogram.mlmodelc/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dabdc5aa69f6ef4d97dc9499f5c30514e00e96b53b750b33a5a6471363c71662 +size 328 diff --git a/openai_whisper-small/MelSpectrogram.mlmodelc/metadata.json b/openai_whisper-small/MelSpectrogram.mlmodelc/metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..022c382ec7041de63c59dd98893c3134d01b23aa --- /dev/null +++ b/openai_whisper-small/MelSpectrogram.mlmodelc/metadata.json @@ -0,0 +1,71 @@ +[ + { + "metadataOutputVersion" : "3.0", + "storagePrecision" : "Float16", + "outputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float16", + "formattedType" : "MultiArray (Float16 1 × 80 × 1 × 3000)", + "shortDescription" : "", + "shape" : "[1, 80, 1, 3000]", + "name" : "melspectrogram_features", + "type" : "MultiArray" + } + ], + "modelParameters" : [ + + ], + "specificationVersion" : 7, + "mlProgramOperationTypeHistogram" : { + "Pad" : 1, + "Ios16.mul" : 2, + "SliceByIndex" : 1, + "Ios16.sub" : 1, + "Ios16.log" : 1, + "Ios16.conv" : 2, + "Ios16.add" : 3, + "Ios16.square" : 2, + "Ios16.matmul" : 1, + "Squeeze" : 2, + "Ios16.maximum" : 1, + "ExpandDims" : 4, + "Ios16.reduceMax" : 1, + "Identity" : 1, + "Ios16.reshape" : 2 + }, + "computePrecision" : "Mixed (Float16, Int32)", + "isUpdatable" : "0", + "availability" : { + "macOS" : "13.0", + "tvOS" : "16.0", + "visionOS" : "1.0", + "watchOS" : "9.0", + "iOS" : "16.0", + "macCatalyst" : "16.0" + }, + "modelType" : { + "name" : "MLModelType_mlProgram" + }, + "userDefinedMetadata" : { + "com.github.apple.coremltools.source_dialect" : "TorchScript", + "com.github.apple.coremltools.source" : "torch==2.2.1", + "com.github.apple.coremltools.version" : "7.1" + }, + "inputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float16", + "formattedType" : "MultiArray (Float16 480000)", + "shortDescription" : "", + "shape" : "[480000]", + "name" : "audio", + "type" : "MultiArray" + } + ], + "generatedClassName" : "MelSpectrogram", + "method" : "predict" + } +] \ No newline at end of file diff --git a/openai_whisper-small/MelSpectrogram.mlmodelc/model.mil b/openai_whisper-small/MelSpectrogram.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..a63d7fa99d6d86db1b76a1f53640cb4aa25e0210 --- /dev/null +++ b/openai_whisper-small/MelSpectrogram.mlmodelc/model.mil @@ -0,0 +1,66 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.2.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})] +{ + func main(tensor audio) { + tensor var_10 = const()[name = tensor("op_10"), val = tensor([1, 1, 480000])]; + tensor input_1_cast_fp16 = reshape(shape = var_10, x = audio)[name = tensor("input_1_cast_fp16")]; + tensor input_3_pad_0 = const()[name = tensor("input_3_pad_0"), val = tensor([0, 0, 0, 0, 200, 200])]; + tensor input_3_mode_0 = const()[name = tensor("input_3_mode_0"), val = tensor("reflect")]; + tensor input_3_constant_val_0_to_fp16 = const()[name = tensor("input_3_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; + tensor input_3_cast_fp16 = pad(constant_val = input_3_constant_val_0_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = tensor("input_3_cast_fp16")]; + tensor var_22 = const()[name = tensor("op_22"), val = tensor([480400])]; + tensor input_cast_fp16 = reshape(shape = var_22, x = input_3_cast_fp16)[name = tensor("input_cast_fp16")]; + tensor expand_dims_0_axes_0 = const()[name = tensor("expand_dims_0_axes_0"), val = tensor([0])]; + tensor expand_dims_0_cast_fp16 = expand_dims(axes = expand_dims_0_axes_0, x = input_cast_fp16)[name = tensor("expand_dims_0_cast_fp16")]; + tensor expand_dims_3 = const()[name = tensor("expand_dims_3"), val = tensor([160])]; + tensor expand_dims_4_axes_0 = const()[name = tensor("expand_dims_4_axes_0"), val = tensor([1])]; + tensor expand_dims_4_cast_fp16 = expand_dims(axes = expand_dims_4_axes_0, x = expand_dims_0_cast_fp16)[name = tensor("expand_dims_4_cast_fp16")]; + tensor conv_0_pad_type_0 = const()[name = tensor("conv_0_pad_type_0"), val = tensor("valid")]; + tensor conv_0_pad_0 = const()[name = tensor("conv_0_pad_0"), val = tensor([0, 0])]; + tensor conv_0_dilations_0 = const()[name = tensor("conv_0_dilations_0"), val = tensor([1])]; + tensor conv_0_groups_0 = const()[name = tensor("conv_0_groups_0"), val = tensor(1)]; + tensor expand_dims_1_to_fp16 = const()[name = tensor("expand_dims_1_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor conv_0_cast_fp16 = conv(dilations = conv_0_dilations_0, groups = conv_0_groups_0, pad = conv_0_pad_0, pad_type = conv_0_pad_type_0, strides = expand_dims_3, weight = expand_dims_1_to_fp16, x = expand_dims_4_cast_fp16)[name = tensor("conv_0_cast_fp16")]; + tensor conv_1_pad_type_0 = const()[name = tensor("conv_1_pad_type_0"), val = tensor("valid")]; + tensor conv_1_pad_0 = const()[name = tensor("conv_1_pad_0"), val = tensor([0, 0])]; + tensor conv_1_dilations_0 = const()[name = tensor("conv_1_dilations_0"), val = tensor([1])]; + tensor conv_1_groups_0 = const()[name = tensor("conv_1_groups_0"), val = tensor(1)]; + tensor expand_dims_2_to_fp16 = const()[name = tensor("expand_dims_2_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160960)))]; + tensor conv_1_cast_fp16 = conv(dilations = conv_1_dilations_0, groups = conv_1_groups_0, pad = conv_1_pad_0, pad_type = conv_1_pad_type_0, strides = expand_dims_3, weight = expand_dims_2_to_fp16, x = expand_dims_4_cast_fp16)[name = tensor("conv_1_cast_fp16")]; + tensor squeeze_0_axes_0 = const()[name = tensor("squeeze_0_axes_0"), val = tensor([0])]; + tensor squeeze_0_cast_fp16 = squeeze(axes = squeeze_0_axes_0, x = conv_0_cast_fp16)[name = tensor("squeeze_0_cast_fp16")]; + tensor squeeze_1_axes_0 = const()[name = tensor("squeeze_1_axes_0"), val = tensor([0])]; + tensor squeeze_1_cast_fp16 = squeeze(axes = squeeze_1_axes_0, x = conv_1_cast_fp16)[name = tensor("squeeze_1_cast_fp16")]; + tensor square_0_cast_fp16 = square(x = squeeze_0_cast_fp16)[name = tensor("square_0_cast_fp16")]; + tensor square_1_cast_fp16 = square(x = squeeze_1_cast_fp16)[name = tensor("square_1_cast_fp16")]; + tensor add_1_cast_fp16 = add(x = square_0_cast_fp16, y = square_1_cast_fp16)[name = tensor("add_1_cast_fp16")]; + tensor magnitudes_1_cast_fp16 = identity(x = add_1_cast_fp16)[name = tensor("magnitudes_1_cast_fp16")]; + tensor magnitudes_begin_0 = const()[name = tensor("magnitudes_begin_0"), val = tensor([0, 0])]; + tensor magnitudes_end_0 = const()[name = tensor("magnitudes_end_0"), val = tensor([201, 3000])]; + tensor magnitudes_end_mask_0 = const()[name = tensor("magnitudes_end_mask_0"), val = tensor([true, false])]; + tensor magnitudes_cast_fp16 = slice_by_index(begin = magnitudes_begin_0, end = magnitudes_end_0, end_mask = magnitudes_end_mask_0, x = magnitudes_1_cast_fp16)[name = tensor("magnitudes_cast_fp16")]; + tensor mel_spec_1_transpose_x_0 = const()[name = tensor("mel_spec_1_transpose_x_0"), val = tensor(false)]; + tensor mel_spec_1_transpose_y_0 = const()[name = tensor("mel_spec_1_transpose_y_0"), val = tensor(false)]; + tensor mel_filters_to_fp16 = const()[name = tensor("mel_filters_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(321856)))]; + tensor mel_spec_1_cast_fp16 = matmul(transpose_x = mel_spec_1_transpose_x_0, transpose_y = mel_spec_1_transpose_y_0, x = mel_filters_to_fp16, y = magnitudes_cast_fp16)[name = tensor("mel_spec_1_cast_fp16")]; + tensor var_41_to_fp16 = const()[name = tensor("op_41_to_fp16"), val = tensor(0x1p-24)]; + tensor mel_spec_cast_fp16 = add(x = mel_spec_1_cast_fp16, y = var_41_to_fp16)[name = tensor("mel_spec_cast_fp16")]; + tensor log_0_epsilon_0_to_fp16 = const()[name = tensor("log_0_epsilon_0_to_fp16"), val = tensor(0x0p+0)]; + tensor log_0_cast_fp16 = log(epsilon = log_0_epsilon_0_to_fp16, x = mel_spec_cast_fp16)[name = tensor("log_0_cast_fp16")]; + tensor mul_0_y_0_to_fp16 = const()[name = tensor("mul_0_y_0_to_fp16"), val = tensor(0x1.bccp-2)]; + tensor mul_0_cast_fp16 = mul(x = log_0_cast_fp16, y = mul_0_y_0_to_fp16)[name = tensor("mul_0_cast_fp16")]; + tensor var_44_keep_dims_0 = const()[name = tensor("op_44_keep_dims_0"), val = tensor(false)]; + tensor var_44_cast_fp16 = reduce_max(keep_dims = var_44_keep_dims_0, x = mul_0_cast_fp16)[name = tensor("op_44_cast_fp16")]; + tensor var_46_to_fp16 = const()[name = tensor("op_46_to_fp16"), val = tensor(0x1p+3)]; + tensor var_47_cast_fp16 = sub(x = var_44_cast_fp16, y = var_46_to_fp16)[name = tensor("op_47_cast_fp16")]; + tensor log_spec_3_cast_fp16 = maximum(x = mul_0_cast_fp16, y = var_47_cast_fp16)[name = tensor("log_spec_3_cast_fp16")]; + tensor var_50_to_fp16 = const()[name = tensor("op_50_to_fp16"), val = tensor(0x1p+2)]; + tensor var_51_cast_fp16 = add(x = log_spec_3_cast_fp16, y = var_50_to_fp16)[name = tensor("op_51_cast_fp16")]; + tensor _inversed_log_spec_y_0_to_fp16 = const()[name = tensor("_inversed_log_spec_y_0_to_fp16"), val = tensor(0x1p-2)]; + tensor _inversed_log_spec_cast_fp16 = mul(x = var_51_cast_fp16, y = _inversed_log_spec_y_0_to_fp16)[name = tensor("_inversed_log_spec_cast_fp16")]; + tensor var_55_axes_0 = const()[name = tensor("op_55_axes_0"), val = tensor([0])]; + tensor var_55_cast_fp16 = expand_dims(axes = var_55_axes_0, x = _inversed_log_spec_cast_fp16)[name = tensor("op_55_cast_fp16")]; + tensor var_62_axes_0 = const()[name = tensor("op_62_axes_0"), val = tensor([2])]; + tensor melspectrogram_features = expand_dims(axes = var_62_axes_0, x = var_55_cast_fp16)[name = tensor("op_62_cast_fp16")]; + } -> (melspectrogram_features); +} \ No newline at end of file diff --git a/openai_whisper-small/MelSpectrogram.mlmodelc/weights/weight.bin b/openai_whisper-small/MelSpectrogram.mlmodelc/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..6110c0f1e30e3ddad047c471f30fb114a2e5562e --- /dev/null +++ b/openai_whisper-small/MelSpectrogram.mlmodelc/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:267017e533b5f542d195fd9a775f2ba649075128283ce8e86c63a2ec20de5b07 +size 354080 diff --git a/openai_whisper-small/TextDecoder.mlmodelc/analytics/coremldata.bin b/openai_whisper-small/TextDecoder.mlmodelc/analytics/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..fcd839bbf91242e087302939502d648dd193dfe8 --- 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"generatedClassName" : "TextDecoder", + "method" : "predict" + } +] \ No newline at end of file diff --git a/openai_whisper-small/TextDecoder.mlmodelc/model.mil b/openai_whisper-small/TextDecoder.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..dca5e408299638f61530c44b7ed4442b8e3b646b --- /dev/null +++ b/openai_whisper-small/TextDecoder.mlmodelc/model.mil @@ -0,0 +1,2105 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.2.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})] +{ + func main(tensor cache_length, tensor decoder_key_padding_mask, tensor encoder_output_embeds, tensor input_ids, tensor key_cache, tensor kv_cache_update_mask, tensor value_cache) { + tensor var_40_axis_0 = const()[name = tensor("op_40_axis_0"), val = tensor(0)]; + tensor var_40_batch_dims_0 = const()[name = tensor("op_40_batch_dims_0"), val = tensor(0)]; + tensor embed_tokens_weight_to_fp16 = const()[name = tensor("embed_tokens_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor var_40_cast_fp16 = gather(axis = var_40_axis_0, batch_dims = var_40_batch_dims_0, indices = input_ids, x = embed_tokens_weight_to_fp16)[name = tensor("op_40_cast_fp16")]; + tensor var_44_axis_0 = const()[name = tensor("op_44_axis_0"), val = tensor(0)]; + tensor var_44_batch_dims_0 = const()[name = tensor("op_44_batch_dims_0"), val = tensor(0)]; + tensor embed_positions_weight_to_fp16 = const()[name = tensor("embed_positions_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79664768)))]; + tensor var_44_cast_fp16 = gather(axis = var_44_axis_0, batch_dims = var_44_batch_dims_0, indices = cache_length, x = embed_positions_weight_to_fp16)[name = tensor("op_44_cast_fp16")]; + tensor hidden_states_1_cast_fp16 = add(x = var_40_cast_fp16, y = var_44_cast_fp16)[name = tensor("hidden_states_1_cast_fp16")]; + tensor var_58_axes_0 = const()[name = tensor("op_58_axes_0"), val = tensor([2])]; + tensor var_58_cast_fp16 = expand_dims(axes = var_58_axes_0, x = hidden_states_1_cast_fp16)[name = tensor("op_58_cast_fp16")]; + tensor inputs_1_axes_0 = const()[name = tensor("inputs_1_axes_0"), val = tensor([3])]; + tensor inputs_1_cast_fp16 = expand_dims(axes = inputs_1_axes_0, x = var_58_cast_fp16)[name = tensor("inputs_1_cast_fp16")]; + tensor tile_0 = const()[name = tensor("tile_0"), val = tensor([768, 768, 768, 768, 768, 768, 768, 768, 768, 768, 768, 768])]; + tensor var_63_axis_0 = const()[name = tensor("op_63_axis_0"), val = tensor(1)]; + tensor var_63_cast_fp16_0, tensor var_63_cast_fp16_1, tensor var_63_cast_fp16_2, tensor var_63_cast_fp16_3, tensor var_63_cast_fp16_4, tensor var_63_cast_fp16_5, tensor var_63_cast_fp16_6, tensor var_63_cast_fp16_7, tensor var_63_cast_fp16_8, tensor var_63_cast_fp16_9, tensor var_63_cast_fp16_10, tensor var_63_cast_fp16_11 = split(axis = var_63_axis_0, split_sizes = tile_0, x = key_cache)[name = tensor("op_63_cast_fp16")]; + tensor tile_1 = const()[name = tensor("tile_1"), val = tensor([768, 768, 768, 768, 768, 768, 768, 768, 768, 768, 768, 768])]; + tensor var_78_axis_0 = const()[name = tensor("op_78_axis_0"), val = tensor(1)]; + tensor var_78_cast_fp16_0, tensor var_78_cast_fp16_1, tensor var_78_cast_fp16_2, tensor var_78_cast_fp16_3, tensor var_78_cast_fp16_4, tensor var_78_cast_fp16_5, tensor var_78_cast_fp16_6, tensor var_78_cast_fp16_7, tensor var_78_cast_fp16_8, tensor var_78_cast_fp16_9, tensor var_78_cast_fp16_10, tensor var_78_cast_fp16_11 = split(axis = var_78_axis_0, split_sizes = tile_1, x = value_cache)[name = tensor("op_78_cast_fp16")]; + tensor var_96 = const()[name = tensor("op_96"), val = tensor(3)]; + tensor var_103 = const()[name = tensor("op_103"), val = tensor(1)]; + tensor var_104 = const()[name = tensor("op_104"), val = tensor(true)]; + tensor var_116 = const()[name = tensor("op_116"), val = tensor([1])]; + tensor channels_mean_1_cast_fp16 = reduce_mean(axes = var_116, keep_dims = var_104, x = inputs_1_cast_fp16)[name = tensor("channels_mean_1_cast_fp16")]; + tensor zero_mean_1_cast_fp16 = sub(x = inputs_1_cast_fp16, y = channels_mean_1_cast_fp16)[name = tensor("zero_mean_1_cast_fp16")]; + tensor zero_mean_sq_1_cast_fp16 = mul(x = zero_mean_1_cast_fp16, y = zero_mean_1_cast_fp16)[name = tensor("zero_mean_sq_1_cast_fp16")]; + tensor var_120 = const()[name = tensor("op_120"), val = tensor([1])]; + tensor var_121_cast_fp16 = reduce_mean(axes = var_120, keep_dims = var_104, x = zero_mean_sq_1_cast_fp16)[name = tensor("op_121_cast_fp16")]; + tensor var_122_to_fp16 = const()[name = tensor("op_122_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_123_cast_fp16 = add(x = var_121_cast_fp16, y = var_122_to_fp16)[name = tensor("op_123_cast_fp16")]; + tensor denom_1_epsilon_0_to_fp16 = const()[name = tensor("denom_1_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_1_cast_fp16 = rsqrt(epsilon = denom_1_epsilon_0_to_fp16, x = var_123_cast_fp16)[name = tensor("denom_1_cast_fp16")]; + tensor out_1_cast_fp16 = mul(x = zero_mean_1_cast_fp16, y = denom_1_cast_fp16)[name = tensor("out_1_cast_fp16")]; + tensor obj_1_mean_0_to_fp16 = const()[name = tensor("obj_1_mean_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80352960)))]; + tensor obj_1_variance_0_to_fp16 = const()[name = tensor("obj_1_variance_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80354560)))]; + tensor obj_1_gamma_0_to_fp16 = const()[name = tensor("obj_1_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80356160)))]; + tensor obj_1_beta_0_to_fp16 = const()[name = tensor("obj_1_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80357760)))]; + tensor obj_1_epsilon_0_to_fp16 = const()[name = tensor("obj_1_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_1_cast_fp16 = batch_norm(beta = obj_1_beta_0_to_fp16, epsilon = obj_1_epsilon_0_to_fp16, gamma = obj_1_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_1_cast_fp16)[name = tensor("obj_1_cast_fp16")]; + tensor var_138 = const()[name = tensor("op_138"), val = tensor([1, 1])]; + tensor var_140 = const()[name = tensor("op_140"), val = tensor([1, 1])]; + tensor query_1_pad_type_0 = const()[name = tensor("query_1_pad_type_0"), val = tensor("custom")]; + tensor query_1_pad_0 = const()[name = tensor("query_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80359360)))]; + tensor layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81539072)))]; + tensor query_1_cast_fp16 = conv(bias = layers_0_self_attn_q_proj_bias_to_fp16, dilations = var_140, groups = var_103, pad = query_1_pad_0, pad_type = query_1_pad_type_0, strides = var_138, weight = layers_0_self_attn_q_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("query_1_cast_fp16")]; + tensor var_144 = const()[name = tensor("op_144"), val = tensor([1, 1])]; + tensor var_146 = const()[name = tensor("op_146"), val = tensor([1, 1])]; + tensor current_key_1_pad_type_0 = const()[name = tensor("current_key_1_pad_type_0"), val = tensor("custom")]; + tensor current_key_1_pad_0 = const()[name = tensor("current_key_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81540672)))]; + tensor current_key_1_cast_fp16 = conv(dilations = var_146, groups = var_103, pad = current_key_1_pad_0, pad_type = current_key_1_pad_type_0, strides = var_144, weight = layers_0_self_attn_k_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("current_key_1_cast_fp16")]; + tensor var_151 = const()[name = tensor("op_151"), val = tensor([1, 1])]; + tensor var_153 = const()[name = tensor("op_153"), val = tensor([1, 1])]; + tensor current_value_1_pad_type_0 = const()[name = tensor("current_value_1_pad_type_0"), val = tensor("custom")]; + tensor current_value_1_pad_0 = const()[name = tensor("current_value_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82720384)))]; + tensor layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83900096)))]; + tensor current_value_1_cast_fp16 = conv(bias = layers_0_self_attn_v_proj_bias_to_fp16, dilations = var_153, groups = var_103, pad = current_value_1_pad_0, pad_type = current_value_1_pad_type_0, strides = var_151, weight = layers_0_self_attn_v_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("current_value_1_cast_fp16")]; + tensor var_157_axes_0 = const()[name = tensor("op_157_axes_0"), val = tensor([1])]; + tensor var_157_cast_fp16 = expand_dims(axes = var_157_axes_0, x = kv_cache_update_mask)[name = tensor("op_157_cast_fp16")]; + tensor var_158_axes_0 = const()[name = tensor("op_158_axes_0"), val = tensor([2])]; + tensor var_158_cast_fp16 = expand_dims(axes = var_158_axes_0, x = var_157_cast_fp16)[name = tensor("op_158_cast_fp16")]; + tensor var_160_cast_fp16 = mul(x = current_key_1_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_160_cast_fp16")]; + tensor var_97_to_fp16 = const()[name = tensor("op_97_to_fp16"), val = tensor(0x1p+0)]; + tensor var_161_cast_fp16 = sub(x = var_97_to_fp16, y = var_158_cast_fp16)[name = tensor("op_161_cast_fp16")]; + tensor var_162_cast_fp16 = mul(x = var_63_cast_fp16_0, y = var_161_cast_fp16)[name = tensor("op_162_cast_fp16")]; + tensor key_1_cast_fp16 = add(x = var_160_cast_fp16, y = var_162_cast_fp16)[name = tensor("key_1_cast_fp16")]; + tensor var_164_cast_fp16 = mul(x = current_value_1_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_164_cast_fp16")]; + tensor var_166_cast_fp16 = mul(x = var_78_cast_fp16_0, y = var_161_cast_fp16)[name = tensor("op_166_cast_fp16")]; + tensor value_1_cast_fp16 = add(x = var_164_cast_fp16, y = var_166_cast_fp16)[name = tensor("value_1_cast_fp16")]; + tensor var_169 = const()[name = tensor("op_169"), val = tensor([1, 12, 64, -1])]; + tensor var_170_cast_fp16 = reshape(shape = var_169, x = query_1_cast_fp16)[name = tensor("op_170_cast_fp16")]; + tensor var_171_to_fp16 = const()[name = tensor("op_171_to_fp16"), val = tensor(0x1p-3)]; + tensor var_172_cast_fp16 = mul(x = var_170_cast_fp16, y = var_171_to_fp16)[name = tensor("op_172_cast_fp16")]; + tensor var_173 = const()[name = tensor("op_173"), val = tensor([1, 12, 64, -1])]; + tensor var_174_cast_fp16 = reshape(shape = var_173, x = key_1_cast_fp16)[name = tensor("op_174_cast_fp16")]; + tensor mh_w_1_transpose_x_0 = const()[name = tensor("mh_w_1_transpose_x_0"), val = tensor(true)]; + tensor mh_w_1_transpose_y_0 = const()[name = tensor("mh_w_1_transpose_y_0"), val = tensor(false)]; + tensor mh_w_1_cast_fp16 = matmul(transpose_x = mh_w_1_transpose_x_0, transpose_y = mh_w_1_transpose_y_0, x = var_172_cast_fp16, y = var_174_cast_fp16)[name = tensor("mh_w_1_cast_fp16")]; + tensor var_178_axes_0 = const()[name = tensor("op_178_axes_0"), val = tensor([1])]; + tensor var_178_cast_fp16 = expand_dims(axes = var_178_axes_0, x = decoder_key_padding_mask)[name = tensor("op_178_cast_fp16")]; + tensor var_179_axes_0 = const()[name = tensor("op_179_axes_0"), val = tensor([2])]; + tensor var_179_cast_fp16 = expand_dims(axes = var_179_axes_0, x = var_178_cast_fp16)[name = tensor("op_179_cast_fp16")]; + tensor mh_w_3_cast_fp16 = add(x = mh_w_1_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_3_cast_fp16")]; + tensor var_182_cast_fp16 = softmax(axis = var_96, x = mh_w_3_cast_fp16)[name = tensor("op_182_cast_fp16")]; + tensor var_183 = const()[name = tensor("op_183"), val = tensor([1, 12, 64, -1])]; + tensor var_184_cast_fp16 = reshape(shape = var_183, x = value_1_cast_fp16)[name = tensor("op_184_cast_fp16")]; + tensor attn_1_transpose_x_0 = const()[name = tensor("attn_1_transpose_x_0"), val = tensor(false)]; + tensor attn_1_transpose_y_0 = const()[name = tensor("attn_1_transpose_y_0"), val = tensor(true)]; + tensor attn_1_cast_fp16 = matmul(transpose_x = attn_1_transpose_x_0, transpose_y = attn_1_transpose_y_0, x = var_184_cast_fp16, y = var_182_cast_fp16)[name = tensor("attn_1_cast_fp16")]; + tensor var_187 = const()[name = tensor("op_187"), val = tensor([1, 768, 1, -1])]; + tensor input_1_cast_fp16 = reshape(shape = var_187, x = attn_1_cast_fp16)[name = tensor("input_1_cast_fp16")]; + tensor var_191 = const()[name = tensor("op_191"), val = tensor([1, 1])]; + tensor var_193 = const()[name = tensor("op_193"), val = tensor([1, 1])]; + tensor obj_7_pad_type_0 = const()[name = tensor("obj_7_pad_type_0"), val = tensor("custom")]; + tensor obj_7_pad_0 = const()[name = tensor("obj_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83901696)))]; + tensor layers_0_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85081408)))]; + tensor obj_7_cast_fp16 = conv(bias = layers_0_self_attn_o_proj_bias_to_fp16, dilations = var_193, groups = var_103, pad = obj_7_pad_0, pad_type = obj_7_pad_type_0, strides = var_191, weight = layers_0_self_attn_o_proj_weight_to_fp16, x = input_1_cast_fp16)[name = tensor("obj_7_cast_fp16")]; + tensor inputs_3_cast_fp16 = add(x = inputs_1_cast_fp16, y = obj_7_cast_fp16)[name = tensor("inputs_3_cast_fp16")]; + tensor var_203 = const()[name = tensor("op_203"), val = tensor([1])]; + tensor channels_mean_3_cast_fp16 = reduce_mean(axes = var_203, keep_dims = var_104, x = inputs_3_cast_fp16)[name = tensor("channels_mean_3_cast_fp16")]; + tensor zero_mean_3_cast_fp16 = sub(x = inputs_3_cast_fp16, y = channels_mean_3_cast_fp16)[name = tensor("zero_mean_3_cast_fp16")]; + tensor zero_mean_sq_3_cast_fp16 = mul(x = zero_mean_3_cast_fp16, y = zero_mean_3_cast_fp16)[name = tensor("zero_mean_sq_3_cast_fp16")]; + tensor var_207 = const()[name = tensor("op_207"), val = tensor([1])]; + tensor var_208_cast_fp16 = reduce_mean(axes = var_207, keep_dims = var_104, x = zero_mean_sq_3_cast_fp16)[name = tensor("op_208_cast_fp16")]; + tensor var_209_to_fp16 = const()[name = tensor("op_209_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_210_cast_fp16 = add(x = var_208_cast_fp16, y = var_209_to_fp16)[name = tensor("op_210_cast_fp16")]; + tensor denom_3_epsilon_0_to_fp16 = const()[name = tensor("denom_3_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_3_cast_fp16 = rsqrt(epsilon = denom_3_epsilon_0_to_fp16, x = var_210_cast_fp16)[name = tensor("denom_3_cast_fp16")]; + tensor out_3_cast_fp16 = mul(x = zero_mean_3_cast_fp16, y = denom_3_cast_fp16)[name = tensor("out_3_cast_fp16")]; + tensor obj_9_gamma_0_to_fp16 = const()[name = tensor("obj_9_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85083008)))]; + tensor obj_9_beta_0_to_fp16 = const()[name = tensor("obj_9_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85084608)))]; + tensor obj_9_epsilon_0_to_fp16 = const()[name = tensor("obj_9_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_9_cast_fp16 = batch_norm(beta = obj_9_beta_0_to_fp16, epsilon = obj_9_epsilon_0_to_fp16, gamma = obj_9_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_3_cast_fp16)[name = tensor("obj_9_cast_fp16")]; + tensor var_225 = const()[name = tensor("op_225"), val = tensor([1, 1])]; + tensor var_227 = const()[name = tensor("op_227"), val = tensor([1, 1])]; + tensor query_3_pad_type_0 = const()[name = tensor("query_3_pad_type_0"), val = tensor("custom")]; + tensor query_3_pad_0 = const()[name = tensor("query_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85086208)))]; + tensor layers_0_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_0_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86265920)))]; + tensor query_3_cast_fp16 = conv(bias = layers_0_encoder_attn_q_proj_bias_to_fp16, dilations = var_227, groups = var_103, pad = query_3_pad_0, pad_type = query_3_pad_type_0, strides = var_225, weight = layers_0_encoder_attn_q_proj_weight_to_fp16, x = obj_9_cast_fp16)[name = tensor("query_3_cast_fp16")]; + tensor var_231 = const()[name = tensor("op_231"), val = tensor([1, 1])]; + tensor var_233 = const()[name = tensor("op_233"), val = tensor([1, 1])]; + tensor key_3_pad_type_0 = const()[name = tensor("key_3_pad_type_0"), val = tensor("custom")]; + tensor key_3_pad_0 = const()[name = tensor("key_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86267520)))]; + tensor key_3_cast_fp16 = conv(dilations = var_233, groups = var_103, pad = key_3_pad_0, pad_type = key_3_pad_type_0, strides = var_231, weight = layers_0_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_3_cast_fp16")]; + tensor var_238 = const()[name = tensor("op_238"), val = tensor([1, 1])]; + tensor var_240 = const()[name = tensor("op_240"), val = tensor([1, 1])]; + tensor value_3_pad_type_0 = const()[name = tensor("value_3_pad_type_0"), val = tensor("custom")]; + tensor value_3_pad_0 = const()[name = tensor("value_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87447232)))]; + tensor layers_0_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_0_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88626944)))]; + tensor value_3_cast_fp16 = conv(bias = layers_0_encoder_attn_v_proj_bias_to_fp16, dilations = var_240, groups = var_103, pad = value_3_pad_0, pad_type = value_3_pad_type_0, strides = var_238, weight = layers_0_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_3_cast_fp16")]; + tensor var_244 = const()[name = tensor("op_244"), val = tensor([1, 12, 64, -1])]; + tensor var_245_cast_fp16 = reshape(shape = var_244, x = query_3_cast_fp16)[name = tensor("op_245_cast_fp16")]; + tensor var_246_to_fp16 = const()[name = tensor("op_246_to_fp16"), val = tensor(0x1p-3)]; + tensor var_247_cast_fp16 = mul(x = var_245_cast_fp16, y = var_246_to_fp16)[name = tensor("op_247_cast_fp16")]; + tensor var_248 = const()[name = tensor("op_248"), val = tensor([1, 12, 64, -1])]; + tensor var_249_cast_fp16 = reshape(shape = var_248, x = key_3_cast_fp16)[name = tensor("op_249_cast_fp16")]; + tensor mh_w_5_transpose_x_0 = const()[name = tensor("mh_w_5_transpose_x_0"), val = tensor(true)]; + tensor mh_w_5_transpose_y_0 = const()[name = tensor("mh_w_5_transpose_y_0"), val = tensor(false)]; + tensor mh_w_5_cast_fp16 = matmul(transpose_x = mh_w_5_transpose_x_0, transpose_y = mh_w_5_transpose_y_0, x = var_247_cast_fp16, y = var_249_cast_fp16)[name = tensor("mh_w_5_cast_fp16")]; + tensor obj_13_cast_fp16 = softmax(axis = var_96, x = mh_w_5_cast_fp16)[name = tensor("obj_13_cast_fp16")]; + tensor var_253 = const()[name = tensor("op_253"), val = tensor([1, 12, 64, -1])]; + tensor var_254_cast_fp16 = reshape(shape = var_253, x = value_3_cast_fp16)[name = tensor("op_254_cast_fp16")]; + tensor attn_3_transpose_x_0 = const()[name = tensor("attn_3_transpose_x_0"), val = tensor(false)]; + tensor attn_3_transpose_y_0 = const()[name = tensor("attn_3_transpose_y_0"), val = tensor(true)]; + tensor attn_3_cast_fp16 = matmul(transpose_x = attn_3_transpose_x_0, transpose_y = attn_3_transpose_y_0, x = var_254_cast_fp16, y = obj_13_cast_fp16)[name = tensor("attn_3_cast_fp16")]; + tensor var_257 = const()[name = tensor("op_257"), val = tensor([1, 768, 1, -1])]; + tensor input_3_cast_fp16 = reshape(shape = var_257, x = attn_3_cast_fp16)[name = tensor("input_3_cast_fp16")]; + tensor var_261 = const()[name = tensor("op_261"), val = tensor([1, 1])]; + tensor var_263 = const()[name = tensor("op_263"), val = tensor([1, 1])]; + tensor obj_11_pad_type_0 = const()[name = tensor("obj_11_pad_type_0"), val = tensor("custom")]; + tensor obj_11_pad_0 = const()[name = tensor("obj_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88628544)))]; + tensor layers_0_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_0_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89808256)))]; + tensor obj_11_cast_fp16 = conv(bias = layers_0_encoder_attn_o_proj_bias_to_fp16, dilations = var_263, groups = var_103, pad = obj_11_pad_0, pad_type = obj_11_pad_type_0, strides = var_261, weight = layers_0_encoder_attn_o_proj_weight_to_fp16, x = input_3_cast_fp16)[name = tensor("obj_11_cast_fp16")]; + tensor inputs_5_cast_fp16 = add(x = inputs_3_cast_fp16, y = obj_11_cast_fp16)[name = tensor("inputs_5_cast_fp16")]; + tensor var_269 = const()[name = tensor("op_269"), val = tensor([1])]; + tensor channels_mean_5_cast_fp16 = reduce_mean(axes = var_269, keep_dims = var_104, x = inputs_5_cast_fp16)[name = tensor("channels_mean_5_cast_fp16")]; + tensor zero_mean_5_cast_fp16 = sub(x = inputs_5_cast_fp16, y = channels_mean_5_cast_fp16)[name = tensor("zero_mean_5_cast_fp16")]; + tensor zero_mean_sq_5_cast_fp16 = mul(x = zero_mean_5_cast_fp16, y = zero_mean_5_cast_fp16)[name = tensor("zero_mean_sq_5_cast_fp16")]; + tensor var_273 = const()[name = tensor("op_273"), val = tensor([1])]; + tensor var_274_cast_fp16 = reduce_mean(axes = var_273, keep_dims = var_104, x = zero_mean_sq_5_cast_fp16)[name = tensor("op_274_cast_fp16")]; + tensor var_275_to_fp16 = const()[name = tensor("op_275_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_276_cast_fp16 = add(x = var_274_cast_fp16, y = var_275_to_fp16)[name = tensor("op_276_cast_fp16")]; + tensor denom_5_epsilon_0_to_fp16 = const()[name = tensor("denom_5_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_5_cast_fp16 = rsqrt(epsilon = denom_5_epsilon_0_to_fp16, x = var_276_cast_fp16)[name = tensor("denom_5_cast_fp16")]; + tensor out_5_cast_fp16 = mul(x = zero_mean_5_cast_fp16, y = denom_5_cast_fp16)[name = tensor("out_5_cast_fp16")]; + tensor input_5_gamma_0_to_fp16 = const()[name = tensor("input_5_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89809856)))]; + tensor input_5_beta_0_to_fp16 = const()[name = tensor("input_5_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89811456)))]; + tensor input_5_epsilon_0_to_fp16 = const()[name = tensor("input_5_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_5_cast_fp16 = batch_norm(beta = input_5_beta_0_to_fp16, epsilon = input_5_epsilon_0_to_fp16, gamma = input_5_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_5_cast_fp16)[name = tensor("input_5_cast_fp16")]; + tensor var_287 = const()[name = tensor("op_287"), val = tensor([1, 1])]; + tensor var_289 = const()[name = tensor("op_289"), val = tensor([1, 1])]; + tensor input_7_pad_type_0 = const()[name = tensor("input_7_pad_type_0"), val = tensor("custom")]; + tensor input_7_pad_0 = const()[name = tensor("input_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_fc1_weight_to_fp16 = const()[name = tensor("layers_0_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89813056)))]; + tensor layers_0_fc1_bias_to_fp16 = const()[name = tensor("layers_0_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94531712)))]; + tensor input_7_cast_fp16 = conv(bias = layers_0_fc1_bias_to_fp16, dilations = var_289, groups = var_103, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = var_287, weight = layers_0_fc1_weight_to_fp16, x = input_5_cast_fp16)[name = tensor("input_7_cast_fp16")]; + tensor input_9_mode_0 = const()[name = tensor("input_9_mode_0"), val = tensor("EXACT")]; + tensor input_9_cast_fp16 = gelu(mode = input_9_mode_0, x = input_7_cast_fp16)[name = tensor("input_9_cast_fp16")]; + tensor var_295 = const()[name = tensor("op_295"), val = tensor([1, 1])]; + tensor var_297 = const()[name = tensor("op_297"), val = tensor([1, 1])]; + tensor hidden_states_3_pad_type_0 = const()[name = tensor("hidden_states_3_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_3_pad_0 = const()[name = tensor("hidden_states_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_0_fc2_weight_to_fp16 = const()[name = tensor("layers_0_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94537920)))]; + tensor layers_0_fc2_bias_to_fp16 = const()[name = tensor("layers_0_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99256576)))]; + tensor hidden_states_3_cast_fp16 = conv(bias = layers_0_fc2_bias_to_fp16, dilations = var_297, groups = var_103, pad = hidden_states_3_pad_0, pad_type = hidden_states_3_pad_type_0, strides = var_295, weight = layers_0_fc2_weight_to_fp16, x = input_9_cast_fp16)[name = tensor("hidden_states_3_cast_fp16")]; + tensor inputs_7_cast_fp16 = add(x = inputs_5_cast_fp16, y = hidden_states_3_cast_fp16)[name = tensor("inputs_7_cast_fp16")]; + tensor var_310 = const()[name = tensor("op_310"), val = tensor(3)]; + tensor var_317 = const()[name = tensor("op_317"), val = tensor(1)]; + tensor var_318 = const()[name = tensor("op_318"), val = tensor(true)]; + tensor var_330 = const()[name = tensor("op_330"), val = tensor([1])]; + tensor channels_mean_7_cast_fp16 = reduce_mean(axes = var_330, keep_dims = var_318, x = inputs_7_cast_fp16)[name = tensor("channels_mean_7_cast_fp16")]; + tensor zero_mean_7_cast_fp16 = sub(x = inputs_7_cast_fp16, y = channels_mean_7_cast_fp16)[name = tensor("zero_mean_7_cast_fp16")]; + tensor zero_mean_sq_7_cast_fp16 = mul(x = zero_mean_7_cast_fp16, y = zero_mean_7_cast_fp16)[name = tensor("zero_mean_sq_7_cast_fp16")]; + tensor var_334 = const()[name = tensor("op_334"), val = tensor([1])]; + tensor var_335_cast_fp16 = reduce_mean(axes = var_334, keep_dims = var_318, x = zero_mean_sq_7_cast_fp16)[name = tensor("op_335_cast_fp16")]; + tensor var_336_to_fp16 = const()[name = tensor("op_336_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_337_cast_fp16 = add(x = var_335_cast_fp16, y = var_336_to_fp16)[name = tensor("op_337_cast_fp16")]; + tensor denom_7_epsilon_0_to_fp16 = const()[name = tensor("denom_7_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_7_cast_fp16 = rsqrt(epsilon = denom_7_epsilon_0_to_fp16, x = var_337_cast_fp16)[name = tensor("denom_7_cast_fp16")]; + tensor out_7_cast_fp16 = mul(x = zero_mean_7_cast_fp16, y = denom_7_cast_fp16)[name = tensor("out_7_cast_fp16")]; + tensor obj_15_gamma_0_to_fp16 = const()[name = tensor("obj_15_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99258176)))]; + tensor obj_15_beta_0_to_fp16 = const()[name = tensor("obj_15_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99259776)))]; + tensor obj_15_epsilon_0_to_fp16 = const()[name = tensor("obj_15_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_15_cast_fp16 = batch_norm(beta = obj_15_beta_0_to_fp16, epsilon = obj_15_epsilon_0_to_fp16, gamma = obj_15_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_7_cast_fp16)[name = tensor("obj_15_cast_fp16")]; + tensor var_352 = const()[name = tensor("op_352"), val = tensor([1, 1])]; + tensor var_354 = const()[name = tensor("op_354"), val = tensor([1, 1])]; + tensor query_5_pad_type_0 = const()[name = tensor("query_5_pad_type_0"), val = tensor("custom")]; + tensor query_5_pad_0 = const()[name = tensor("query_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99261376)))]; + tensor layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100441088)))]; + tensor query_5_cast_fp16 = conv(bias = layers_1_self_attn_q_proj_bias_to_fp16, dilations = var_354, groups = var_317, pad = query_5_pad_0, pad_type = query_5_pad_type_0, strides = var_352, weight = layers_1_self_attn_q_proj_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor("query_5_cast_fp16")]; + tensor var_358 = const()[name = tensor("op_358"), val = tensor([1, 1])]; + tensor var_360 = const()[name = tensor("op_360"), val = tensor([1, 1])]; + tensor current_key_3_pad_type_0 = const()[name = tensor("current_key_3_pad_type_0"), val = tensor("custom")]; + tensor current_key_3_pad_0 = const()[name = tensor("current_key_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100442688)))]; + tensor current_key_3_cast_fp16 = conv(dilations = var_360, groups = var_317, pad = current_key_3_pad_0, pad_type = current_key_3_pad_type_0, strides = var_358, weight = layers_1_self_attn_k_proj_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor("current_key_3_cast_fp16")]; + tensor var_365 = const()[name = tensor("op_365"), val = tensor([1, 1])]; + tensor var_367 = const()[name = tensor("op_367"), val = tensor([1, 1])]; + tensor current_value_3_pad_type_0 = const()[name = tensor("current_value_3_pad_type_0"), val = tensor("custom")]; + tensor current_value_3_pad_0 = const()[name = tensor("current_value_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101622400)))]; + tensor layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102802112)))]; + tensor current_value_3_cast_fp16 = conv(bias = layers_1_self_attn_v_proj_bias_to_fp16, dilations = var_367, groups = var_317, pad = current_value_3_pad_0, pad_type = current_value_3_pad_type_0, strides = var_365, weight = layers_1_self_attn_v_proj_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor("current_value_3_cast_fp16")]; + tensor var_374_cast_fp16 = mul(x = current_key_3_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_374_cast_fp16")]; + tensor var_376_cast_fp16 = mul(x = var_63_cast_fp16_1, y = var_161_cast_fp16)[name = tensor("op_376_cast_fp16")]; + tensor key_5_cast_fp16 = add(x = var_374_cast_fp16, y = var_376_cast_fp16)[name = tensor("key_5_cast_fp16")]; + tensor var_378_cast_fp16 = mul(x = current_value_3_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_378_cast_fp16")]; + tensor var_380_cast_fp16 = mul(x = var_78_cast_fp16_1, y = var_161_cast_fp16)[name = tensor("op_380_cast_fp16")]; + tensor value_5_cast_fp16 = add(x = var_378_cast_fp16, y = var_380_cast_fp16)[name = tensor("value_5_cast_fp16")]; + tensor var_383 = const()[name = tensor("op_383"), val = tensor([1, 12, 64, -1])]; + tensor var_384_cast_fp16 = reshape(shape = var_383, x = query_5_cast_fp16)[name = tensor("op_384_cast_fp16")]; + tensor var_385_to_fp16 = const()[name = tensor("op_385_to_fp16"), val = tensor(0x1p-3)]; + tensor var_386_cast_fp16 = mul(x = var_384_cast_fp16, y = var_385_to_fp16)[name = tensor("op_386_cast_fp16")]; + tensor var_387 = const()[name = tensor("op_387"), val = tensor([1, 12, 64, -1])]; + tensor var_388_cast_fp16 = reshape(shape = var_387, x = key_5_cast_fp16)[name = tensor("op_388_cast_fp16")]; + tensor mh_w_7_transpose_x_0 = const()[name = tensor("mh_w_7_transpose_x_0"), val = tensor(true)]; + tensor mh_w_7_transpose_y_0 = const()[name = tensor("mh_w_7_transpose_y_0"), val = tensor(false)]; + tensor mh_w_7_cast_fp16 = matmul(transpose_x = mh_w_7_transpose_x_0, transpose_y = mh_w_7_transpose_y_0, x = var_386_cast_fp16, y = var_388_cast_fp16)[name = tensor("mh_w_7_cast_fp16")]; + tensor mh_w_9_cast_fp16 = add(x = mh_w_7_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_9_cast_fp16")]; + tensor var_396_cast_fp16 = softmax(axis = var_310, x = mh_w_9_cast_fp16)[name = tensor("op_396_cast_fp16")]; + tensor var_397 = const()[name = tensor("op_397"), val = tensor([1, 12, 64, -1])]; + tensor var_398_cast_fp16 = reshape(shape = var_397, x = value_5_cast_fp16)[name = tensor("op_398_cast_fp16")]; + tensor attn_5_transpose_x_0 = const()[name = tensor("attn_5_transpose_x_0"), val = tensor(false)]; + tensor attn_5_transpose_y_0 = const()[name = tensor("attn_5_transpose_y_0"), val = tensor(true)]; + tensor attn_5_cast_fp16 = matmul(transpose_x = attn_5_transpose_x_0, transpose_y = attn_5_transpose_y_0, x = var_398_cast_fp16, y = var_396_cast_fp16)[name = tensor("attn_5_cast_fp16")]; + tensor var_401 = const()[name = tensor("op_401"), val = tensor([1, 768, 1, -1])]; + tensor input_11_cast_fp16 = reshape(shape = var_401, x = attn_5_cast_fp16)[name = tensor("input_11_cast_fp16")]; + tensor var_405 = const()[name = tensor("op_405"), val = tensor([1, 1])]; + tensor var_407 = const()[name = tensor("op_407"), val = tensor([1, 1])]; + tensor obj_21_pad_type_0 = const()[name = tensor("obj_21_pad_type_0"), val = tensor("custom")]; + tensor obj_21_pad_0 = const()[name = tensor("obj_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102803712)))]; + tensor layers_1_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103983424)))]; + tensor obj_21_cast_fp16 = conv(bias = layers_1_self_attn_o_proj_bias_to_fp16, dilations = var_407, groups = var_317, pad = obj_21_pad_0, pad_type = obj_21_pad_type_0, strides = var_405, weight = layers_1_self_attn_o_proj_weight_to_fp16, x = input_11_cast_fp16)[name = tensor("obj_21_cast_fp16")]; + tensor inputs_9_cast_fp16 = add(x = inputs_7_cast_fp16, y = obj_21_cast_fp16)[name = tensor("inputs_9_cast_fp16")]; + tensor var_417 = const()[name = tensor("op_417"), val = tensor([1])]; + tensor channels_mean_9_cast_fp16 = reduce_mean(axes = var_417, keep_dims = var_318, x = inputs_9_cast_fp16)[name = tensor("channels_mean_9_cast_fp16")]; + tensor zero_mean_9_cast_fp16 = sub(x = inputs_9_cast_fp16, y = channels_mean_9_cast_fp16)[name = tensor("zero_mean_9_cast_fp16")]; + tensor zero_mean_sq_9_cast_fp16 = mul(x = zero_mean_9_cast_fp16, y = zero_mean_9_cast_fp16)[name = tensor("zero_mean_sq_9_cast_fp16")]; + tensor var_421 = const()[name = tensor("op_421"), val = tensor([1])]; + tensor var_422_cast_fp16 = reduce_mean(axes = var_421, keep_dims = var_318, x = zero_mean_sq_9_cast_fp16)[name = tensor("op_422_cast_fp16")]; + tensor var_423_to_fp16 = const()[name = tensor("op_423_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_424_cast_fp16 = add(x = var_422_cast_fp16, y = var_423_to_fp16)[name = tensor("op_424_cast_fp16")]; + tensor denom_9_epsilon_0_to_fp16 = const()[name = tensor("denom_9_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_9_cast_fp16 = rsqrt(epsilon = denom_9_epsilon_0_to_fp16, x = var_424_cast_fp16)[name = tensor("denom_9_cast_fp16")]; + tensor out_9_cast_fp16 = mul(x = zero_mean_9_cast_fp16, y = denom_9_cast_fp16)[name = tensor("out_9_cast_fp16")]; + tensor obj_23_gamma_0_to_fp16 = const()[name = tensor("obj_23_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103985024)))]; + tensor obj_23_beta_0_to_fp16 = const()[name = tensor("obj_23_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103986624)))]; + tensor obj_23_epsilon_0_to_fp16 = const()[name = tensor("obj_23_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_23_cast_fp16 = batch_norm(beta = obj_23_beta_0_to_fp16, epsilon = obj_23_epsilon_0_to_fp16, gamma = obj_23_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_9_cast_fp16)[name = tensor("obj_23_cast_fp16")]; + tensor var_439 = const()[name = tensor("op_439"), val = tensor([1, 1])]; + tensor var_441 = const()[name = tensor("op_441"), val = tensor([1, 1])]; + tensor query_7_pad_type_0 = const()[name = tensor("query_7_pad_type_0"), val = tensor("custom")]; + tensor query_7_pad_0 = const()[name = tensor("query_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103988224)))]; + tensor layers_1_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_1_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(105167936)))]; + tensor query_7_cast_fp16 = conv(bias = layers_1_encoder_attn_q_proj_bias_to_fp16, dilations = var_441, groups = var_317, pad = query_7_pad_0, pad_type = query_7_pad_type_0, strides = var_439, weight = layers_1_encoder_attn_q_proj_weight_to_fp16, x = obj_23_cast_fp16)[name = tensor("query_7_cast_fp16")]; + tensor var_445 = const()[name = tensor("op_445"), val = tensor([1, 1])]; + tensor var_447 = const()[name = tensor("op_447"), val = tensor([1, 1])]; + tensor key_7_pad_type_0 = const()[name = tensor("key_7_pad_type_0"), val = tensor("custom")]; + tensor key_7_pad_0 = const()[name = tensor("key_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(105169536)))]; + tensor key_7_cast_fp16 = conv(dilations = var_447, groups = var_317, pad = key_7_pad_0, pad_type = key_7_pad_type_0, strides = var_445, weight = layers_1_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_7_cast_fp16")]; + tensor var_452 = const()[name = tensor("op_452"), val = tensor([1, 1])]; + tensor var_454 = const()[name = tensor("op_454"), val = tensor([1, 1])]; + tensor value_7_pad_type_0 = const()[name = tensor("value_7_pad_type_0"), val = tensor("custom")]; + tensor value_7_pad_0 = const()[name = tensor("value_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106349248)))]; + tensor layers_1_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_1_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107528960)))]; + tensor value_7_cast_fp16 = conv(bias = layers_1_encoder_attn_v_proj_bias_to_fp16, dilations = var_454, groups = var_317, pad = value_7_pad_0, pad_type = value_7_pad_type_0, strides = var_452, weight = layers_1_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_7_cast_fp16")]; + tensor var_458 = const()[name = tensor("op_458"), val = tensor([1, 12, 64, -1])]; + tensor var_459_cast_fp16 = reshape(shape = var_458, x = query_7_cast_fp16)[name = tensor("op_459_cast_fp16")]; + tensor var_460_to_fp16 = const()[name = tensor("op_460_to_fp16"), val = tensor(0x1p-3)]; + tensor var_461_cast_fp16 = mul(x = var_459_cast_fp16, y = var_460_to_fp16)[name = tensor("op_461_cast_fp16")]; + tensor var_462 = const()[name = tensor("op_462"), val = tensor([1, 12, 64, -1])]; + tensor var_463_cast_fp16 = reshape(shape = var_462, x = key_7_cast_fp16)[name = tensor("op_463_cast_fp16")]; + tensor mh_w_11_transpose_x_0 = const()[name = tensor("mh_w_11_transpose_x_0"), val = tensor(true)]; + tensor mh_w_11_transpose_y_0 = const()[name = tensor("mh_w_11_transpose_y_0"), val = tensor(false)]; + tensor mh_w_11_cast_fp16 = matmul(transpose_x = mh_w_11_transpose_x_0, transpose_y = mh_w_11_transpose_y_0, x = var_461_cast_fp16, y = var_463_cast_fp16)[name = tensor("mh_w_11_cast_fp16")]; + tensor obj_27_cast_fp16 = softmax(axis = var_310, x = mh_w_11_cast_fp16)[name = tensor("obj_27_cast_fp16")]; + tensor var_467 = const()[name = tensor("op_467"), val = tensor([1, 12, 64, -1])]; + tensor var_468_cast_fp16 = reshape(shape = var_467, x = value_7_cast_fp16)[name = tensor("op_468_cast_fp16")]; + tensor attn_7_transpose_x_0 = const()[name = tensor("attn_7_transpose_x_0"), val = tensor(false)]; + tensor attn_7_transpose_y_0 = const()[name = tensor("attn_7_transpose_y_0"), val = tensor(true)]; + tensor attn_7_cast_fp16 = matmul(transpose_x = attn_7_transpose_x_0, transpose_y = attn_7_transpose_y_0, x = var_468_cast_fp16, y = obj_27_cast_fp16)[name = tensor("attn_7_cast_fp16")]; + tensor var_471 = const()[name = tensor("op_471"), val = tensor([1, 768, 1, -1])]; + tensor input_13_cast_fp16 = reshape(shape = var_471, x = attn_7_cast_fp16)[name = tensor("input_13_cast_fp16")]; + tensor var_475 = const()[name = tensor("op_475"), val = tensor([1, 1])]; + tensor var_477 = const()[name = tensor("op_477"), val = tensor([1, 1])]; + tensor obj_25_pad_type_0 = const()[name = tensor("obj_25_pad_type_0"), val = tensor("custom")]; + tensor obj_25_pad_0 = const()[name = tensor("obj_25_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107530560)))]; + tensor layers_1_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_1_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108710272)))]; + tensor obj_25_cast_fp16 = conv(bias = layers_1_encoder_attn_o_proj_bias_to_fp16, dilations = var_477, groups = var_317, pad = obj_25_pad_0, pad_type = obj_25_pad_type_0, strides = var_475, weight = layers_1_encoder_attn_o_proj_weight_to_fp16, x = input_13_cast_fp16)[name = tensor("obj_25_cast_fp16")]; + tensor inputs_11_cast_fp16 = add(x = inputs_9_cast_fp16, y = obj_25_cast_fp16)[name = tensor("inputs_11_cast_fp16")]; + tensor var_483 = const()[name = tensor("op_483"), val = tensor([1])]; + tensor channels_mean_11_cast_fp16 = reduce_mean(axes = var_483, keep_dims = var_318, x = inputs_11_cast_fp16)[name = tensor("channels_mean_11_cast_fp16")]; + tensor zero_mean_11_cast_fp16 = sub(x = inputs_11_cast_fp16, y = channels_mean_11_cast_fp16)[name = tensor("zero_mean_11_cast_fp16")]; + tensor zero_mean_sq_11_cast_fp16 = mul(x = zero_mean_11_cast_fp16, y = zero_mean_11_cast_fp16)[name = tensor("zero_mean_sq_11_cast_fp16")]; + tensor var_487 = const()[name = tensor("op_487"), val = tensor([1])]; + tensor var_488_cast_fp16 = reduce_mean(axes = var_487, keep_dims = var_318, x = zero_mean_sq_11_cast_fp16)[name = tensor("op_488_cast_fp16")]; + tensor var_489_to_fp16 = const()[name = tensor("op_489_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_490_cast_fp16 = add(x = var_488_cast_fp16, y = var_489_to_fp16)[name = tensor("op_490_cast_fp16")]; + tensor denom_11_epsilon_0_to_fp16 = const()[name = tensor("denom_11_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_11_cast_fp16 = rsqrt(epsilon = denom_11_epsilon_0_to_fp16, x = var_490_cast_fp16)[name = tensor("denom_11_cast_fp16")]; + tensor out_11_cast_fp16 = mul(x = zero_mean_11_cast_fp16, y = denom_11_cast_fp16)[name = tensor("out_11_cast_fp16")]; + tensor input_15_gamma_0_to_fp16 = const()[name = tensor("input_15_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108711872)))]; + tensor input_15_beta_0_to_fp16 = const()[name = tensor("input_15_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108713472)))]; + tensor input_15_epsilon_0_to_fp16 = const()[name = tensor("input_15_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_15_cast_fp16 = batch_norm(beta = input_15_beta_0_to_fp16, epsilon = input_15_epsilon_0_to_fp16, gamma = input_15_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_11_cast_fp16)[name = tensor("input_15_cast_fp16")]; + tensor var_501 = const()[name = tensor("op_501"), val = tensor([1, 1])]; + tensor var_503 = const()[name = tensor("op_503"), val = tensor([1, 1])]; + tensor input_17_pad_type_0 = const()[name = tensor("input_17_pad_type_0"), val = tensor("custom")]; + tensor input_17_pad_0 = const()[name = tensor("input_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_fc1_weight_to_fp16 = const()[name = tensor("layers_1_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108715072)))]; + tensor layers_1_fc1_bias_to_fp16 = const()[name = tensor("layers_1_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113433728)))]; + tensor input_17_cast_fp16 = conv(bias = layers_1_fc1_bias_to_fp16, dilations = var_503, groups = var_317, pad = input_17_pad_0, pad_type = input_17_pad_type_0, strides = var_501, weight = layers_1_fc1_weight_to_fp16, x = input_15_cast_fp16)[name = tensor("input_17_cast_fp16")]; + tensor input_19_mode_0 = const()[name = tensor("input_19_mode_0"), val = tensor("EXACT")]; + tensor input_19_cast_fp16 = gelu(mode = input_19_mode_0, x = input_17_cast_fp16)[name = tensor("input_19_cast_fp16")]; + tensor var_509 = const()[name = tensor("op_509"), val = tensor([1, 1])]; + tensor var_511 = const()[name = tensor("op_511"), val = tensor([1, 1])]; + tensor hidden_states_5_pad_type_0 = const()[name = tensor("hidden_states_5_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_5_pad_0 = const()[name = tensor("hidden_states_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_1_fc2_weight_to_fp16 = const()[name = tensor("layers_1_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113439936)))]; + tensor layers_1_fc2_bias_to_fp16 = const()[name = tensor("layers_1_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118158592)))]; + tensor hidden_states_5_cast_fp16 = conv(bias = layers_1_fc2_bias_to_fp16, dilations = var_511, groups = var_317, pad = hidden_states_5_pad_0, pad_type = hidden_states_5_pad_type_0, strides = var_509, weight = layers_1_fc2_weight_to_fp16, x = input_19_cast_fp16)[name = tensor("hidden_states_5_cast_fp16")]; + tensor inputs_13_cast_fp16 = add(x = inputs_11_cast_fp16, y = hidden_states_5_cast_fp16)[name = tensor("inputs_13_cast_fp16")]; + tensor var_524 = const()[name = tensor("op_524"), val = tensor(3)]; + tensor var_531 = const()[name = tensor("op_531"), val = tensor(1)]; + tensor var_532 = const()[name = tensor("op_532"), val = tensor(true)]; + tensor var_544 = const()[name = tensor("op_544"), val = tensor([1])]; + tensor channels_mean_13_cast_fp16 = reduce_mean(axes = var_544, keep_dims = var_532, x = inputs_13_cast_fp16)[name = tensor("channels_mean_13_cast_fp16")]; + tensor zero_mean_13_cast_fp16 = sub(x = inputs_13_cast_fp16, y = channels_mean_13_cast_fp16)[name = tensor("zero_mean_13_cast_fp16")]; + tensor zero_mean_sq_13_cast_fp16 = mul(x = zero_mean_13_cast_fp16, y = zero_mean_13_cast_fp16)[name = tensor("zero_mean_sq_13_cast_fp16")]; + tensor var_548 = const()[name = tensor("op_548"), val = tensor([1])]; + tensor var_549_cast_fp16 = reduce_mean(axes = var_548, keep_dims = var_532, x = zero_mean_sq_13_cast_fp16)[name = tensor("op_549_cast_fp16")]; + tensor var_550_to_fp16 = const()[name = tensor("op_550_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_551_cast_fp16 = add(x = var_549_cast_fp16, y = var_550_to_fp16)[name = tensor("op_551_cast_fp16")]; + tensor denom_13_epsilon_0_to_fp16 = const()[name = tensor("denom_13_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_13_cast_fp16 = rsqrt(epsilon = denom_13_epsilon_0_to_fp16, x = var_551_cast_fp16)[name = tensor("denom_13_cast_fp16")]; + tensor out_13_cast_fp16 = mul(x = zero_mean_13_cast_fp16, y = denom_13_cast_fp16)[name = tensor("out_13_cast_fp16")]; + tensor obj_29_gamma_0_to_fp16 = const()[name = tensor("obj_29_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118160192)))]; + tensor obj_29_beta_0_to_fp16 = const()[name = tensor("obj_29_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118161792)))]; + tensor obj_29_epsilon_0_to_fp16 = const()[name = tensor("obj_29_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_29_cast_fp16 = batch_norm(beta = obj_29_beta_0_to_fp16, epsilon = obj_29_epsilon_0_to_fp16, gamma = obj_29_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_13_cast_fp16)[name = tensor("obj_29_cast_fp16")]; + tensor var_566 = const()[name = tensor("op_566"), val = tensor([1, 1])]; + tensor var_568 = const()[name = tensor("op_568"), val = tensor([1, 1])]; + tensor query_9_pad_type_0 = const()[name = tensor("query_9_pad_type_0"), val = tensor("custom")]; + tensor query_9_pad_0 = const()[name = tensor("query_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118163392)))]; + tensor layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119343104)))]; + tensor query_9_cast_fp16 = conv(bias = layers_2_self_attn_q_proj_bias_to_fp16, dilations = var_568, groups = var_531, pad = query_9_pad_0, pad_type = query_9_pad_type_0, strides = var_566, weight = layers_2_self_attn_q_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("query_9_cast_fp16")]; + tensor var_572 = const()[name = tensor("op_572"), val = tensor([1, 1])]; + tensor var_574 = const()[name = tensor("op_574"), val = tensor([1, 1])]; + tensor current_key_5_pad_type_0 = const()[name = tensor("current_key_5_pad_type_0"), val = tensor("custom")]; + tensor current_key_5_pad_0 = const()[name = tensor("current_key_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119344704)))]; + tensor current_key_5_cast_fp16 = conv(dilations = var_574, groups = var_531, pad = current_key_5_pad_0, pad_type = current_key_5_pad_type_0, strides = var_572, weight = layers_2_self_attn_k_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("current_key_5_cast_fp16")]; + tensor var_579 = const()[name = tensor("op_579"), val = tensor([1, 1])]; + tensor var_581 = const()[name = tensor("op_581"), val = tensor([1, 1])]; + tensor current_value_5_pad_type_0 = const()[name = tensor("current_value_5_pad_type_0"), val = tensor("custom")]; + tensor current_value_5_pad_0 = const()[name = tensor("current_value_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120524416)))]; + tensor layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121704128)))]; + tensor current_value_5_cast_fp16 = conv(bias = layers_2_self_attn_v_proj_bias_to_fp16, dilations = var_581, groups = var_531, pad = current_value_5_pad_0, pad_type = current_value_5_pad_type_0, strides = var_579, weight = layers_2_self_attn_v_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("current_value_5_cast_fp16")]; + tensor var_588_cast_fp16 = mul(x = current_key_5_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_588_cast_fp16")]; + tensor var_590_cast_fp16 = mul(x = var_63_cast_fp16_2, y = var_161_cast_fp16)[name = tensor("op_590_cast_fp16")]; + tensor key_9_cast_fp16 = add(x = var_588_cast_fp16, y = var_590_cast_fp16)[name = tensor("key_9_cast_fp16")]; + tensor var_592_cast_fp16 = mul(x = current_value_5_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_592_cast_fp16")]; + tensor var_594_cast_fp16 = mul(x = var_78_cast_fp16_2, y = var_161_cast_fp16)[name = tensor("op_594_cast_fp16")]; + tensor value_9_cast_fp16 = add(x = var_592_cast_fp16, y = var_594_cast_fp16)[name = tensor("value_9_cast_fp16")]; + tensor var_597 = const()[name = tensor("op_597"), val = tensor([1, 12, 64, -1])]; + tensor var_598_cast_fp16 = reshape(shape = var_597, x = query_9_cast_fp16)[name = tensor("op_598_cast_fp16")]; + tensor var_599_to_fp16 = const()[name = tensor("op_599_to_fp16"), val = tensor(0x1p-3)]; + tensor var_600_cast_fp16 = mul(x = var_598_cast_fp16, y = var_599_to_fp16)[name = tensor("op_600_cast_fp16")]; + tensor var_601 = const()[name = tensor("op_601"), val = tensor([1, 12, 64, -1])]; + tensor var_602_cast_fp16 = reshape(shape = var_601, x = key_9_cast_fp16)[name = tensor("op_602_cast_fp16")]; + tensor mh_w_13_transpose_x_0 = const()[name = tensor("mh_w_13_transpose_x_0"), val = tensor(true)]; + tensor mh_w_13_transpose_y_0 = const()[name = tensor("mh_w_13_transpose_y_0"), val = tensor(false)]; + tensor mh_w_13_cast_fp16 = matmul(transpose_x = mh_w_13_transpose_x_0, transpose_y = mh_w_13_transpose_y_0, x = var_600_cast_fp16, y = var_602_cast_fp16)[name = tensor("mh_w_13_cast_fp16")]; + tensor mh_w_15_cast_fp16 = add(x = mh_w_13_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_15_cast_fp16")]; + tensor var_610_cast_fp16 = softmax(axis = var_524, x = mh_w_15_cast_fp16)[name = tensor("op_610_cast_fp16")]; + tensor var_611 = const()[name = tensor("op_611"), val = tensor([1, 12, 64, -1])]; + tensor var_612_cast_fp16 = reshape(shape = var_611, x = value_9_cast_fp16)[name = tensor("op_612_cast_fp16")]; + tensor attn_9_transpose_x_0 = const()[name = tensor("attn_9_transpose_x_0"), val = tensor(false)]; + tensor attn_9_transpose_y_0 = const()[name = tensor("attn_9_transpose_y_0"), val = tensor(true)]; + tensor attn_9_cast_fp16 = matmul(transpose_x = attn_9_transpose_x_0, transpose_y = attn_9_transpose_y_0, x = var_612_cast_fp16, y = var_610_cast_fp16)[name = tensor("attn_9_cast_fp16")]; + tensor var_615 = const()[name = tensor("op_615"), val = tensor([1, 768, 1, -1])]; + tensor input_21_cast_fp16 = reshape(shape = var_615, x = attn_9_cast_fp16)[name = tensor("input_21_cast_fp16")]; + tensor var_619 = const()[name = tensor("op_619"), val = tensor([1, 1])]; + tensor var_621 = const()[name = tensor("op_621"), val = tensor([1, 1])]; + tensor obj_35_pad_type_0 = const()[name = tensor("obj_35_pad_type_0"), val = tensor("custom")]; + tensor obj_35_pad_0 = const()[name = tensor("obj_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121705728)))]; + tensor layers_2_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122885440)))]; + tensor obj_35_cast_fp16 = conv(bias = layers_2_self_attn_o_proj_bias_to_fp16, dilations = var_621, groups = var_531, pad = obj_35_pad_0, pad_type = obj_35_pad_type_0, strides = var_619, weight = layers_2_self_attn_o_proj_weight_to_fp16, x = input_21_cast_fp16)[name = tensor("obj_35_cast_fp16")]; + tensor inputs_15_cast_fp16 = add(x = inputs_13_cast_fp16, y = obj_35_cast_fp16)[name = tensor("inputs_15_cast_fp16")]; + tensor var_631 = const()[name = tensor("op_631"), val = tensor([1])]; + tensor channels_mean_15_cast_fp16 = reduce_mean(axes = var_631, keep_dims = var_532, x = inputs_15_cast_fp16)[name = tensor("channels_mean_15_cast_fp16")]; + tensor zero_mean_15_cast_fp16 = sub(x = inputs_15_cast_fp16, y = channels_mean_15_cast_fp16)[name = tensor("zero_mean_15_cast_fp16")]; + tensor zero_mean_sq_15_cast_fp16 = mul(x = zero_mean_15_cast_fp16, y = zero_mean_15_cast_fp16)[name = tensor("zero_mean_sq_15_cast_fp16")]; + tensor var_635 = const()[name = tensor("op_635"), val = tensor([1])]; + tensor var_636_cast_fp16 = reduce_mean(axes = var_635, keep_dims = var_532, x = zero_mean_sq_15_cast_fp16)[name = tensor("op_636_cast_fp16")]; + tensor var_637_to_fp16 = const()[name = tensor("op_637_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_638_cast_fp16 = add(x = var_636_cast_fp16, y = var_637_to_fp16)[name = tensor("op_638_cast_fp16")]; + tensor denom_15_epsilon_0_to_fp16 = const()[name = tensor("denom_15_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_15_cast_fp16 = rsqrt(epsilon = denom_15_epsilon_0_to_fp16, x = var_638_cast_fp16)[name = tensor("denom_15_cast_fp16")]; + tensor out_15_cast_fp16 = mul(x = zero_mean_15_cast_fp16, y = denom_15_cast_fp16)[name = tensor("out_15_cast_fp16")]; + tensor obj_37_gamma_0_to_fp16 = const()[name = tensor("obj_37_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122887040)))]; + tensor obj_37_beta_0_to_fp16 = const()[name = tensor("obj_37_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122888640)))]; + tensor obj_37_epsilon_0_to_fp16 = const()[name = tensor("obj_37_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_37_cast_fp16 = batch_norm(beta = obj_37_beta_0_to_fp16, epsilon = obj_37_epsilon_0_to_fp16, gamma = obj_37_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_15_cast_fp16)[name = tensor("obj_37_cast_fp16")]; + tensor var_653 = const()[name = tensor("op_653"), val = tensor([1, 1])]; + tensor var_655 = const()[name = tensor("op_655"), val = tensor([1, 1])]; + tensor query_11_pad_type_0 = const()[name = tensor("query_11_pad_type_0"), val = tensor("custom")]; + tensor query_11_pad_0 = const()[name = tensor("query_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122890240)))]; + tensor layers_2_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_2_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124069952)))]; + tensor query_11_cast_fp16 = conv(bias = layers_2_encoder_attn_q_proj_bias_to_fp16, dilations = var_655, groups = var_531, pad = query_11_pad_0, pad_type = query_11_pad_type_0, strides = var_653, weight = layers_2_encoder_attn_q_proj_weight_to_fp16, x = obj_37_cast_fp16)[name = tensor("query_11_cast_fp16")]; + tensor var_659 = const()[name = tensor("op_659"), val = tensor([1, 1])]; + tensor var_661 = const()[name = tensor("op_661"), val = tensor([1, 1])]; + tensor key_11_pad_type_0 = const()[name = tensor("key_11_pad_type_0"), val = tensor("custom")]; + tensor key_11_pad_0 = const()[name = tensor("key_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124071552)))]; + tensor key_11_cast_fp16 = conv(dilations = var_661, groups = var_531, pad = key_11_pad_0, pad_type = key_11_pad_type_0, strides = var_659, weight = layers_2_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_11_cast_fp16")]; + tensor var_666 = const()[name = tensor("op_666"), val = tensor([1, 1])]; + tensor var_668 = const()[name = tensor("op_668"), val = tensor([1, 1])]; + tensor value_11_pad_type_0 = const()[name = tensor("value_11_pad_type_0"), val = tensor("custom")]; + tensor value_11_pad_0 = const()[name = tensor("value_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125251264)))]; + tensor layers_2_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_2_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126430976)))]; + tensor value_11_cast_fp16 = conv(bias = layers_2_encoder_attn_v_proj_bias_to_fp16, dilations = var_668, groups = var_531, pad = value_11_pad_0, pad_type = value_11_pad_type_0, strides = var_666, weight = layers_2_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_11_cast_fp16")]; + tensor var_672 = const()[name = tensor("op_672"), val = tensor([1, 12, 64, -1])]; + tensor var_673_cast_fp16 = reshape(shape = var_672, x = query_11_cast_fp16)[name = tensor("op_673_cast_fp16")]; + tensor var_674_to_fp16 = const()[name = tensor("op_674_to_fp16"), val = tensor(0x1p-3)]; + tensor var_675_cast_fp16 = mul(x = var_673_cast_fp16, y = var_674_to_fp16)[name = tensor("op_675_cast_fp16")]; + tensor var_676 = const()[name = tensor("op_676"), val = tensor([1, 12, 64, -1])]; + tensor var_677_cast_fp16 = reshape(shape = var_676, x = key_11_cast_fp16)[name = tensor("op_677_cast_fp16")]; + tensor mh_w_17_transpose_x_0 = const()[name = tensor("mh_w_17_transpose_x_0"), val = tensor(true)]; + tensor mh_w_17_transpose_y_0 = const()[name = tensor("mh_w_17_transpose_y_0"), val = tensor(false)]; + tensor mh_w_17_cast_fp16 = matmul(transpose_x = mh_w_17_transpose_x_0, transpose_y = mh_w_17_transpose_y_0, x = var_675_cast_fp16, y = var_677_cast_fp16)[name = tensor("mh_w_17_cast_fp16")]; + tensor obj_41_cast_fp16 = softmax(axis = var_524, x = mh_w_17_cast_fp16)[name = tensor("obj_41_cast_fp16")]; + tensor var_681 = const()[name = tensor("op_681"), val = tensor([1, 12, 64, -1])]; + tensor var_682_cast_fp16 = reshape(shape = var_681, x = value_11_cast_fp16)[name = tensor("op_682_cast_fp16")]; + tensor attn_11_transpose_x_0 = const()[name = tensor("attn_11_transpose_x_0"), val = tensor(false)]; + tensor attn_11_transpose_y_0 = const()[name = tensor("attn_11_transpose_y_0"), val = tensor(true)]; + tensor attn_11_cast_fp16 = matmul(transpose_x = attn_11_transpose_x_0, transpose_y = attn_11_transpose_y_0, x = var_682_cast_fp16, y = obj_41_cast_fp16)[name = tensor("attn_11_cast_fp16")]; + tensor var_685 = const()[name = tensor("op_685"), val = tensor([1, 768, 1, -1])]; + tensor input_23_cast_fp16 = reshape(shape = var_685, x = attn_11_cast_fp16)[name = tensor("input_23_cast_fp16")]; + tensor var_689 = const()[name = tensor("op_689"), val = tensor([1, 1])]; + tensor var_691 = const()[name = tensor("op_691"), val = tensor([1, 1])]; + tensor obj_39_pad_type_0 = const()[name = tensor("obj_39_pad_type_0"), val = tensor("custom")]; + tensor obj_39_pad_0 = const()[name = tensor("obj_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126432576)))]; + tensor layers_2_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_2_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127612288)))]; + tensor obj_39_cast_fp16 = conv(bias = layers_2_encoder_attn_o_proj_bias_to_fp16, dilations = var_691, groups = var_531, pad = obj_39_pad_0, pad_type = obj_39_pad_type_0, strides = var_689, weight = layers_2_encoder_attn_o_proj_weight_to_fp16, x = input_23_cast_fp16)[name = tensor("obj_39_cast_fp16")]; + tensor inputs_17_cast_fp16 = add(x = inputs_15_cast_fp16, y = obj_39_cast_fp16)[name = tensor("inputs_17_cast_fp16")]; + tensor var_697 = const()[name = tensor("op_697"), val = tensor([1])]; + tensor channels_mean_17_cast_fp16 = reduce_mean(axes = var_697, keep_dims = var_532, x = inputs_17_cast_fp16)[name = tensor("channels_mean_17_cast_fp16")]; + tensor zero_mean_17_cast_fp16 = sub(x = inputs_17_cast_fp16, y = channels_mean_17_cast_fp16)[name = tensor("zero_mean_17_cast_fp16")]; + tensor zero_mean_sq_17_cast_fp16 = mul(x = zero_mean_17_cast_fp16, y = zero_mean_17_cast_fp16)[name = tensor("zero_mean_sq_17_cast_fp16")]; + tensor var_701 = const()[name = tensor("op_701"), val = tensor([1])]; + tensor var_702_cast_fp16 = reduce_mean(axes = var_701, keep_dims = var_532, x = zero_mean_sq_17_cast_fp16)[name = tensor("op_702_cast_fp16")]; + tensor var_703_to_fp16 = const()[name = tensor("op_703_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_704_cast_fp16 = add(x = var_702_cast_fp16, y = var_703_to_fp16)[name = tensor("op_704_cast_fp16")]; + tensor denom_17_epsilon_0_to_fp16 = const()[name = tensor("denom_17_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_17_cast_fp16 = rsqrt(epsilon = denom_17_epsilon_0_to_fp16, x = var_704_cast_fp16)[name = tensor("denom_17_cast_fp16")]; + tensor out_17_cast_fp16 = mul(x = zero_mean_17_cast_fp16, y = denom_17_cast_fp16)[name = tensor("out_17_cast_fp16")]; + tensor input_25_gamma_0_to_fp16 = const()[name = tensor("input_25_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127613888)))]; + tensor input_25_beta_0_to_fp16 = const()[name = tensor("input_25_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127615488)))]; + tensor input_25_epsilon_0_to_fp16 = const()[name = tensor("input_25_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_25_cast_fp16 = batch_norm(beta = input_25_beta_0_to_fp16, epsilon = input_25_epsilon_0_to_fp16, gamma = input_25_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_17_cast_fp16)[name = tensor("input_25_cast_fp16")]; + tensor var_715 = const()[name = tensor("op_715"), val = tensor([1, 1])]; + tensor var_717 = const()[name = tensor("op_717"), val = tensor([1, 1])]; + tensor input_27_pad_type_0 = const()[name = tensor("input_27_pad_type_0"), val = tensor("custom")]; + tensor input_27_pad_0 = const()[name = tensor("input_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_fc1_weight_to_fp16 = const()[name = tensor("layers_2_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127617088)))]; + tensor layers_2_fc1_bias_to_fp16 = const()[name = tensor("layers_2_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132335744)))]; + tensor input_27_cast_fp16 = conv(bias = layers_2_fc1_bias_to_fp16, dilations = var_717, groups = var_531, pad = input_27_pad_0, pad_type = input_27_pad_type_0, strides = var_715, weight = layers_2_fc1_weight_to_fp16, x = input_25_cast_fp16)[name = tensor("input_27_cast_fp16")]; + tensor input_29_mode_0 = const()[name = tensor("input_29_mode_0"), val = tensor("EXACT")]; + tensor input_29_cast_fp16 = gelu(mode = input_29_mode_0, x = input_27_cast_fp16)[name = tensor("input_29_cast_fp16")]; + tensor var_723 = const()[name = tensor("op_723"), val = tensor([1, 1])]; + tensor var_725 = const()[name = tensor("op_725"), val = tensor([1, 1])]; + tensor hidden_states_7_pad_type_0 = const()[name = tensor("hidden_states_7_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_7_pad_0 = const()[name = tensor("hidden_states_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_2_fc2_weight_to_fp16 = const()[name = tensor("layers_2_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132341952)))]; + tensor layers_2_fc2_bias_to_fp16 = const()[name = tensor("layers_2_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137060608)))]; + tensor hidden_states_7_cast_fp16 = conv(bias = layers_2_fc2_bias_to_fp16, dilations = var_725, groups = var_531, pad = hidden_states_7_pad_0, pad_type = hidden_states_7_pad_type_0, strides = var_723, weight = layers_2_fc2_weight_to_fp16, x = input_29_cast_fp16)[name = tensor("hidden_states_7_cast_fp16")]; + tensor inputs_19_cast_fp16 = add(x = inputs_17_cast_fp16, y = hidden_states_7_cast_fp16)[name = tensor("inputs_19_cast_fp16")]; + tensor var_738 = const()[name = tensor("op_738"), val = tensor(3)]; + tensor var_745 = const()[name = tensor("op_745"), val = tensor(1)]; + tensor var_746 = const()[name = tensor("op_746"), val = tensor(true)]; + tensor var_758 = const()[name = tensor("op_758"), val = tensor([1])]; + tensor channels_mean_19_cast_fp16 = reduce_mean(axes = var_758, keep_dims = var_746, x = inputs_19_cast_fp16)[name = tensor("channels_mean_19_cast_fp16")]; + tensor zero_mean_19_cast_fp16 = sub(x = inputs_19_cast_fp16, y = channels_mean_19_cast_fp16)[name = tensor("zero_mean_19_cast_fp16")]; + tensor zero_mean_sq_19_cast_fp16 = mul(x = zero_mean_19_cast_fp16, y = zero_mean_19_cast_fp16)[name = tensor("zero_mean_sq_19_cast_fp16")]; + tensor var_762 = const()[name = tensor("op_762"), val = tensor([1])]; + tensor var_763_cast_fp16 = reduce_mean(axes = var_762, keep_dims = var_746, x = zero_mean_sq_19_cast_fp16)[name = tensor("op_763_cast_fp16")]; + tensor var_764_to_fp16 = const()[name = tensor("op_764_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_765_cast_fp16 = add(x = var_763_cast_fp16, y = var_764_to_fp16)[name = tensor("op_765_cast_fp16")]; + tensor denom_19_epsilon_0_to_fp16 = const()[name = tensor("denom_19_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_19_cast_fp16 = rsqrt(epsilon = denom_19_epsilon_0_to_fp16, x = var_765_cast_fp16)[name = tensor("denom_19_cast_fp16")]; + tensor out_19_cast_fp16 = mul(x = zero_mean_19_cast_fp16, y = denom_19_cast_fp16)[name = tensor("out_19_cast_fp16")]; + tensor obj_43_gamma_0_to_fp16 = const()[name = tensor("obj_43_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137062208)))]; + tensor obj_43_beta_0_to_fp16 = const()[name = tensor("obj_43_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137063808)))]; + tensor obj_43_epsilon_0_to_fp16 = const()[name = tensor("obj_43_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_43_cast_fp16 = batch_norm(beta = obj_43_beta_0_to_fp16, epsilon = obj_43_epsilon_0_to_fp16, gamma = obj_43_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_19_cast_fp16)[name = tensor("obj_43_cast_fp16")]; + tensor var_780 = const()[name = tensor("op_780"), val = tensor([1, 1])]; + tensor var_782 = const()[name = tensor("op_782"), val = tensor([1, 1])]; + tensor query_13_pad_type_0 = const()[name = tensor("query_13_pad_type_0"), val = tensor("custom")]; + tensor query_13_pad_0 = const()[name = tensor("query_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137065408)))]; + tensor layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138245120)))]; + tensor query_13_cast_fp16 = conv(bias = layers_3_self_attn_q_proj_bias_to_fp16, dilations = var_782, groups = var_745, pad = query_13_pad_0, pad_type = query_13_pad_type_0, strides = var_780, weight = layers_3_self_attn_q_proj_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor("query_13_cast_fp16")]; + tensor var_786 = const()[name = tensor("op_786"), val = tensor([1, 1])]; + tensor var_788 = const()[name = tensor("op_788"), val = tensor([1, 1])]; + tensor current_key_7_pad_type_0 = const()[name = tensor("current_key_7_pad_type_0"), val = tensor("custom")]; + tensor current_key_7_pad_0 = const()[name = tensor("current_key_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138246720)))]; + tensor current_key_7_cast_fp16 = conv(dilations = var_788, groups = var_745, pad = current_key_7_pad_0, pad_type = current_key_7_pad_type_0, strides = var_786, weight = layers_3_self_attn_k_proj_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor("current_key_7_cast_fp16")]; + tensor var_793 = const()[name = tensor("op_793"), val = tensor([1, 1])]; + tensor var_795 = const()[name = tensor("op_795"), val = tensor([1, 1])]; + tensor current_value_7_pad_type_0 = const()[name = tensor("current_value_7_pad_type_0"), val = tensor("custom")]; + tensor current_value_7_pad_0 = const()[name = tensor("current_value_7_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139426432)))]; + tensor layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140606144)))]; + tensor current_value_7_cast_fp16 = conv(bias = layers_3_self_attn_v_proj_bias_to_fp16, dilations = var_795, groups = var_745, pad = current_value_7_pad_0, pad_type = current_value_7_pad_type_0, strides = var_793, weight = layers_3_self_attn_v_proj_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor("current_value_7_cast_fp16")]; + tensor var_802_cast_fp16 = mul(x = current_key_7_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_802_cast_fp16")]; + tensor var_804_cast_fp16 = mul(x = var_63_cast_fp16_3, y = var_161_cast_fp16)[name = tensor("op_804_cast_fp16")]; + tensor key_13_cast_fp16 = add(x = var_802_cast_fp16, y = var_804_cast_fp16)[name = tensor("key_13_cast_fp16")]; + tensor var_806_cast_fp16 = mul(x = current_value_7_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_806_cast_fp16")]; + tensor var_808_cast_fp16 = mul(x = var_78_cast_fp16_3, y = var_161_cast_fp16)[name = tensor("op_808_cast_fp16")]; + tensor value_13_cast_fp16 = add(x = var_806_cast_fp16, y = var_808_cast_fp16)[name = tensor("value_13_cast_fp16")]; + tensor var_811 = const()[name = tensor("op_811"), val = tensor([1, 12, 64, -1])]; + tensor var_812_cast_fp16 = reshape(shape = var_811, x = query_13_cast_fp16)[name = tensor("op_812_cast_fp16")]; + tensor var_813_to_fp16 = const()[name = tensor("op_813_to_fp16"), val = tensor(0x1p-3)]; + tensor var_814_cast_fp16 = mul(x = var_812_cast_fp16, y = var_813_to_fp16)[name = tensor("op_814_cast_fp16")]; + tensor var_815 = const()[name = tensor("op_815"), val = tensor([1, 12, 64, -1])]; + tensor var_816_cast_fp16 = reshape(shape = var_815, x = key_13_cast_fp16)[name = tensor("op_816_cast_fp16")]; + tensor mh_w_19_transpose_x_0 = const()[name = tensor("mh_w_19_transpose_x_0"), val = tensor(true)]; + tensor mh_w_19_transpose_y_0 = const()[name = tensor("mh_w_19_transpose_y_0"), val = tensor(false)]; + tensor mh_w_19_cast_fp16 = matmul(transpose_x = mh_w_19_transpose_x_0, transpose_y = mh_w_19_transpose_y_0, x = var_814_cast_fp16, y = var_816_cast_fp16)[name = tensor("mh_w_19_cast_fp16")]; + tensor mh_w_21_cast_fp16 = add(x = mh_w_19_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_21_cast_fp16")]; + tensor var_824_cast_fp16 = softmax(axis = var_738, x = mh_w_21_cast_fp16)[name = tensor("op_824_cast_fp16")]; + tensor var_825 = const()[name = tensor("op_825"), val = tensor([1, 12, 64, -1])]; + tensor var_826_cast_fp16 = reshape(shape = var_825, x = value_13_cast_fp16)[name = tensor("op_826_cast_fp16")]; + tensor attn_13_transpose_x_0 = const()[name = tensor("attn_13_transpose_x_0"), val = tensor(false)]; + tensor attn_13_transpose_y_0 = const()[name = tensor("attn_13_transpose_y_0"), val = tensor(true)]; + tensor attn_13_cast_fp16 = matmul(transpose_x = attn_13_transpose_x_0, transpose_y = attn_13_transpose_y_0, x = var_826_cast_fp16, y = var_824_cast_fp16)[name = tensor("attn_13_cast_fp16")]; + tensor var_829 = const()[name = tensor("op_829"), val = tensor([1, 768, 1, -1])]; + tensor input_31_cast_fp16 = reshape(shape = var_829, x = attn_13_cast_fp16)[name = tensor("input_31_cast_fp16")]; + tensor var_833 = const()[name = tensor("op_833"), val = tensor([1, 1])]; + tensor var_835 = const()[name = tensor("op_835"), val = tensor([1, 1])]; + tensor obj_49_pad_type_0 = const()[name = tensor("obj_49_pad_type_0"), val = tensor("custom")]; + tensor obj_49_pad_0 = const()[name = tensor("obj_49_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140607744)))]; + tensor layers_3_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141787456)))]; + tensor obj_49_cast_fp16 = conv(bias = layers_3_self_attn_o_proj_bias_to_fp16, dilations = var_835, groups = var_745, pad = obj_49_pad_0, pad_type = obj_49_pad_type_0, strides = var_833, weight = layers_3_self_attn_o_proj_weight_to_fp16, x = input_31_cast_fp16)[name = tensor("obj_49_cast_fp16")]; + tensor inputs_21_cast_fp16 = add(x = inputs_19_cast_fp16, y = obj_49_cast_fp16)[name = tensor("inputs_21_cast_fp16")]; + tensor var_845 = const()[name = tensor("op_845"), val = tensor([1])]; + tensor channels_mean_21_cast_fp16 = reduce_mean(axes = var_845, keep_dims = var_746, x = inputs_21_cast_fp16)[name = tensor("channels_mean_21_cast_fp16")]; + tensor zero_mean_21_cast_fp16 = sub(x = inputs_21_cast_fp16, y = channels_mean_21_cast_fp16)[name = tensor("zero_mean_21_cast_fp16")]; + tensor zero_mean_sq_21_cast_fp16 = mul(x = zero_mean_21_cast_fp16, y = zero_mean_21_cast_fp16)[name = tensor("zero_mean_sq_21_cast_fp16")]; + tensor var_849 = const()[name = tensor("op_849"), val = tensor([1])]; + tensor var_850_cast_fp16 = reduce_mean(axes = var_849, keep_dims = var_746, x = zero_mean_sq_21_cast_fp16)[name = tensor("op_850_cast_fp16")]; + tensor var_851_to_fp16 = const()[name = tensor("op_851_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_852_cast_fp16 = add(x = var_850_cast_fp16, y = var_851_to_fp16)[name = tensor("op_852_cast_fp16")]; + tensor denom_21_epsilon_0_to_fp16 = const()[name = tensor("denom_21_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_21_cast_fp16 = rsqrt(epsilon = denom_21_epsilon_0_to_fp16, x = var_852_cast_fp16)[name = tensor("denom_21_cast_fp16")]; + tensor out_21_cast_fp16 = mul(x = zero_mean_21_cast_fp16, y = denom_21_cast_fp16)[name = tensor("out_21_cast_fp16")]; + tensor obj_51_gamma_0_to_fp16 = const()[name = tensor("obj_51_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141789056)))]; + tensor obj_51_beta_0_to_fp16 = const()[name = tensor("obj_51_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141790656)))]; + tensor obj_51_epsilon_0_to_fp16 = const()[name = tensor("obj_51_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_51_cast_fp16 = batch_norm(beta = obj_51_beta_0_to_fp16, epsilon = obj_51_epsilon_0_to_fp16, gamma = obj_51_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_21_cast_fp16)[name = tensor("obj_51_cast_fp16")]; + tensor var_867 = const()[name = tensor("op_867"), val = tensor([1, 1])]; + tensor var_869 = const()[name = tensor("op_869"), val = tensor([1, 1])]; + tensor query_15_pad_type_0 = const()[name = tensor("query_15_pad_type_0"), val = tensor("custom")]; + tensor query_15_pad_0 = const()[name = tensor("query_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141792256)))]; + tensor layers_3_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_3_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142971968)))]; + tensor query_15_cast_fp16 = conv(bias = layers_3_encoder_attn_q_proj_bias_to_fp16, dilations = var_869, groups = var_745, pad = query_15_pad_0, pad_type = query_15_pad_type_0, strides = var_867, weight = layers_3_encoder_attn_q_proj_weight_to_fp16, x = obj_51_cast_fp16)[name = tensor("query_15_cast_fp16")]; + tensor var_873 = const()[name = tensor("op_873"), val = tensor([1, 1])]; + tensor var_875 = const()[name = tensor("op_875"), val = tensor([1, 1])]; + tensor key_15_pad_type_0 = const()[name = tensor("key_15_pad_type_0"), val = tensor("custom")]; + tensor key_15_pad_0 = const()[name = tensor("key_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142973568)))]; + tensor key_15_cast_fp16 = conv(dilations = var_875, groups = var_745, pad = key_15_pad_0, pad_type = key_15_pad_type_0, strides = var_873, weight = layers_3_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_15_cast_fp16")]; + tensor var_880 = const()[name = tensor("op_880"), val = tensor([1, 1])]; + tensor var_882 = const()[name = tensor("op_882"), val = tensor([1, 1])]; + tensor value_15_pad_type_0 = const()[name = tensor("value_15_pad_type_0"), val = tensor("custom")]; + tensor value_15_pad_0 = const()[name = tensor("value_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(144153280)))]; + tensor layers_3_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_3_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145332992)))]; + tensor value_15_cast_fp16 = conv(bias = layers_3_encoder_attn_v_proj_bias_to_fp16, dilations = var_882, groups = var_745, pad = value_15_pad_0, pad_type = value_15_pad_type_0, strides = var_880, weight = layers_3_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_15_cast_fp16")]; + tensor var_886 = const()[name = tensor("op_886"), val = tensor([1, 12, 64, -1])]; + tensor var_887_cast_fp16 = reshape(shape = var_886, x = query_15_cast_fp16)[name = tensor("op_887_cast_fp16")]; + tensor var_888_to_fp16 = const()[name = tensor("op_888_to_fp16"), val = tensor(0x1p-3)]; + tensor var_889_cast_fp16 = mul(x = var_887_cast_fp16, y = var_888_to_fp16)[name = tensor("op_889_cast_fp16")]; + tensor var_890 = const()[name = tensor("op_890"), val = tensor([1, 12, 64, -1])]; + tensor var_891_cast_fp16 = reshape(shape = var_890, x = key_15_cast_fp16)[name = tensor("op_891_cast_fp16")]; + tensor mh_w_23_transpose_x_0 = const()[name = tensor("mh_w_23_transpose_x_0"), val = tensor(true)]; + tensor mh_w_23_transpose_y_0 = const()[name = tensor("mh_w_23_transpose_y_0"), val = tensor(false)]; + tensor mh_w_23_cast_fp16 = matmul(transpose_x = mh_w_23_transpose_x_0, transpose_y = mh_w_23_transpose_y_0, x = var_889_cast_fp16, y = var_891_cast_fp16)[name = tensor("mh_w_23_cast_fp16")]; + tensor obj_55_cast_fp16 = softmax(axis = var_738, x = mh_w_23_cast_fp16)[name = tensor("obj_55_cast_fp16")]; + tensor var_895 = const()[name = tensor("op_895"), val = tensor([1, 12, 64, -1])]; + tensor var_896_cast_fp16 = reshape(shape = var_895, x = value_15_cast_fp16)[name = tensor("op_896_cast_fp16")]; + tensor attn_15_transpose_x_0 = const()[name = tensor("attn_15_transpose_x_0"), val = tensor(false)]; + tensor attn_15_transpose_y_0 = const()[name = tensor("attn_15_transpose_y_0"), val = tensor(true)]; + tensor attn_15_cast_fp16 = matmul(transpose_x = attn_15_transpose_x_0, transpose_y = attn_15_transpose_y_0, x = var_896_cast_fp16, y = obj_55_cast_fp16)[name = tensor("attn_15_cast_fp16")]; + tensor var_899 = const()[name = tensor("op_899"), val = tensor([1, 768, 1, -1])]; + tensor input_33_cast_fp16 = reshape(shape = var_899, x = attn_15_cast_fp16)[name = tensor("input_33_cast_fp16")]; + tensor var_903 = const()[name = tensor("op_903"), val = tensor([1, 1])]; + tensor var_905 = const()[name = tensor("op_905"), val = tensor([1, 1])]; + tensor obj_53_pad_type_0 = const()[name = tensor("obj_53_pad_type_0"), val = tensor("custom")]; + tensor obj_53_pad_0 = const()[name = tensor("obj_53_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145334592)))]; + tensor layers_3_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_3_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146514304)))]; + tensor obj_53_cast_fp16 = conv(bias = layers_3_encoder_attn_o_proj_bias_to_fp16, dilations = var_905, groups = var_745, pad = obj_53_pad_0, pad_type = obj_53_pad_type_0, strides = var_903, weight = layers_3_encoder_attn_o_proj_weight_to_fp16, x = input_33_cast_fp16)[name = tensor("obj_53_cast_fp16")]; + tensor inputs_23_cast_fp16 = add(x = inputs_21_cast_fp16, y = obj_53_cast_fp16)[name = tensor("inputs_23_cast_fp16")]; + tensor var_911 = const()[name = tensor("op_911"), val = tensor([1])]; + tensor channels_mean_23_cast_fp16 = reduce_mean(axes = var_911, keep_dims = var_746, x = inputs_23_cast_fp16)[name = tensor("channels_mean_23_cast_fp16")]; + tensor zero_mean_23_cast_fp16 = sub(x = inputs_23_cast_fp16, y = channels_mean_23_cast_fp16)[name = tensor("zero_mean_23_cast_fp16")]; + tensor zero_mean_sq_23_cast_fp16 = mul(x = zero_mean_23_cast_fp16, y = zero_mean_23_cast_fp16)[name = tensor("zero_mean_sq_23_cast_fp16")]; + tensor var_915 = const()[name = tensor("op_915"), val = tensor([1])]; + tensor var_916_cast_fp16 = reduce_mean(axes = var_915, keep_dims = var_746, x = zero_mean_sq_23_cast_fp16)[name = tensor("op_916_cast_fp16")]; + tensor var_917_to_fp16 = const()[name = tensor("op_917_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_918_cast_fp16 = add(x = var_916_cast_fp16, y = var_917_to_fp16)[name = tensor("op_918_cast_fp16")]; + tensor denom_23_epsilon_0_to_fp16 = const()[name = tensor("denom_23_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_23_cast_fp16 = rsqrt(epsilon = denom_23_epsilon_0_to_fp16, x = var_918_cast_fp16)[name = tensor("denom_23_cast_fp16")]; + tensor out_23_cast_fp16 = mul(x = zero_mean_23_cast_fp16, y = denom_23_cast_fp16)[name = tensor("out_23_cast_fp16")]; + tensor input_35_gamma_0_to_fp16 = const()[name = tensor("input_35_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146515904)))]; + tensor input_35_beta_0_to_fp16 = const()[name = tensor("input_35_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146517504)))]; + tensor input_35_epsilon_0_to_fp16 = const()[name = tensor("input_35_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_35_cast_fp16 = batch_norm(beta = input_35_beta_0_to_fp16, epsilon = input_35_epsilon_0_to_fp16, gamma = input_35_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_23_cast_fp16)[name = tensor("input_35_cast_fp16")]; + tensor var_929 = const()[name = tensor("op_929"), val = tensor([1, 1])]; + tensor var_931 = const()[name = tensor("op_931"), val = tensor([1, 1])]; + tensor input_37_pad_type_0 = const()[name = tensor("input_37_pad_type_0"), val = tensor("custom")]; + tensor input_37_pad_0 = const()[name = tensor("input_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_fc1_weight_to_fp16 = const()[name = tensor("layers_3_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146519104)))]; + tensor layers_3_fc1_bias_to_fp16 = const()[name = tensor("layers_3_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151237760)))]; + tensor input_37_cast_fp16 = conv(bias = layers_3_fc1_bias_to_fp16, dilations = var_931, groups = var_745, pad = input_37_pad_0, pad_type = input_37_pad_type_0, strides = var_929, weight = layers_3_fc1_weight_to_fp16, x = input_35_cast_fp16)[name = tensor("input_37_cast_fp16")]; + tensor input_39_mode_0 = const()[name = tensor("input_39_mode_0"), val = tensor("EXACT")]; + tensor input_39_cast_fp16 = gelu(mode = input_39_mode_0, x = input_37_cast_fp16)[name = tensor("input_39_cast_fp16")]; + tensor var_937 = const()[name = tensor("op_937"), val = tensor([1, 1])]; + tensor var_939 = const()[name = tensor("op_939"), val = tensor([1, 1])]; + tensor hidden_states_9_pad_type_0 = const()[name = tensor("hidden_states_9_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_9_pad_0 = const()[name = tensor("hidden_states_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_3_fc2_weight_to_fp16 = const()[name = tensor("layers_3_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151243968)))]; + tensor layers_3_fc2_bias_to_fp16 = const()[name = tensor("layers_3_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155962624)))]; + tensor hidden_states_9_cast_fp16 = conv(bias = layers_3_fc2_bias_to_fp16, dilations = var_939, groups = var_745, pad = hidden_states_9_pad_0, pad_type = hidden_states_9_pad_type_0, strides = var_937, weight = layers_3_fc2_weight_to_fp16, x = input_39_cast_fp16)[name = tensor("hidden_states_9_cast_fp16")]; + tensor inputs_25_cast_fp16 = add(x = inputs_23_cast_fp16, y = hidden_states_9_cast_fp16)[name = tensor("inputs_25_cast_fp16")]; + tensor var_952 = const()[name = tensor("op_952"), val = tensor(3)]; + tensor var_959 = const()[name = tensor("op_959"), val = tensor(1)]; + tensor var_960 = const()[name = tensor("op_960"), val = tensor(true)]; + tensor var_972 = const()[name = tensor("op_972"), val = tensor([1])]; + tensor channels_mean_25_cast_fp16 = reduce_mean(axes = var_972, keep_dims = var_960, x = inputs_25_cast_fp16)[name = tensor("channels_mean_25_cast_fp16")]; + tensor zero_mean_25_cast_fp16 = sub(x = inputs_25_cast_fp16, y = channels_mean_25_cast_fp16)[name = tensor("zero_mean_25_cast_fp16")]; + tensor zero_mean_sq_25_cast_fp16 = mul(x = zero_mean_25_cast_fp16, y = zero_mean_25_cast_fp16)[name = tensor("zero_mean_sq_25_cast_fp16")]; + tensor var_976 = const()[name = tensor("op_976"), val = tensor([1])]; + tensor var_977_cast_fp16 = reduce_mean(axes = var_976, keep_dims = var_960, x = zero_mean_sq_25_cast_fp16)[name = tensor("op_977_cast_fp16")]; + tensor var_978_to_fp16 = const()[name = tensor("op_978_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_979_cast_fp16 = add(x = var_977_cast_fp16, y = var_978_to_fp16)[name = tensor("op_979_cast_fp16")]; + tensor denom_25_epsilon_0_to_fp16 = const()[name = tensor("denom_25_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_25_cast_fp16 = rsqrt(epsilon = denom_25_epsilon_0_to_fp16, x = var_979_cast_fp16)[name = tensor("denom_25_cast_fp16")]; + tensor out_25_cast_fp16 = mul(x = zero_mean_25_cast_fp16, y = denom_25_cast_fp16)[name = tensor("out_25_cast_fp16")]; + tensor obj_57_gamma_0_to_fp16 = const()[name = tensor("obj_57_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155964224)))]; + tensor obj_57_beta_0_to_fp16 = const()[name = tensor("obj_57_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155965824)))]; + tensor obj_57_epsilon_0_to_fp16 = const()[name = tensor("obj_57_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_57_cast_fp16 = batch_norm(beta = obj_57_beta_0_to_fp16, epsilon = obj_57_epsilon_0_to_fp16, gamma = obj_57_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_25_cast_fp16)[name = tensor("obj_57_cast_fp16")]; + tensor var_994 = const()[name = tensor("op_994"), val = tensor([1, 1])]; + tensor var_996 = const()[name = tensor("op_996"), val = tensor([1, 1])]; + tensor query_17_pad_type_0 = const()[name = tensor("query_17_pad_type_0"), val = tensor("custom")]; + tensor query_17_pad_0 = const()[name = tensor("query_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155967424)))]; + tensor layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(157147136)))]; + tensor query_17_cast_fp16 = conv(bias = layers_4_self_attn_q_proj_bias_to_fp16, dilations = var_996, groups = var_959, pad = query_17_pad_0, pad_type = query_17_pad_type_0, strides = var_994, weight = layers_4_self_attn_q_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("query_17_cast_fp16")]; + tensor var_1000 = const()[name = tensor("op_1000"), val = tensor([1, 1])]; + tensor var_1002 = const()[name = tensor("op_1002"), val = tensor([1, 1])]; + tensor current_key_9_pad_type_0 = const()[name = tensor("current_key_9_pad_type_0"), val = tensor("custom")]; + tensor current_key_9_pad_0 = const()[name = tensor("current_key_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(157148736)))]; + tensor current_key_9_cast_fp16 = conv(dilations = var_1002, groups = var_959, pad = current_key_9_pad_0, pad_type = current_key_9_pad_type_0, strides = var_1000, weight = layers_4_self_attn_k_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("current_key_9_cast_fp16")]; + tensor var_1007 = const()[name = tensor("op_1007"), val = tensor([1, 1])]; + tensor var_1009 = const()[name = tensor("op_1009"), val = tensor([1, 1])]; + tensor current_value_9_pad_type_0 = const()[name = tensor("current_value_9_pad_type_0"), val = tensor("custom")]; + tensor current_value_9_pad_0 = const()[name = tensor("current_value_9_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158328448)))]; + tensor layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159508160)))]; + tensor current_value_9_cast_fp16 = conv(bias = layers_4_self_attn_v_proj_bias_to_fp16, dilations = var_1009, groups = var_959, pad = current_value_9_pad_0, pad_type = current_value_9_pad_type_0, strides = var_1007, weight = layers_4_self_attn_v_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("current_value_9_cast_fp16")]; + tensor var_1016_cast_fp16 = mul(x = current_key_9_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1016_cast_fp16")]; + tensor var_1018_cast_fp16 = mul(x = var_63_cast_fp16_4, y = var_161_cast_fp16)[name = tensor("op_1018_cast_fp16")]; + tensor key_17_cast_fp16 = add(x = var_1016_cast_fp16, y = var_1018_cast_fp16)[name = tensor("key_17_cast_fp16")]; + tensor var_1020_cast_fp16 = mul(x = current_value_9_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1020_cast_fp16")]; + tensor var_1022_cast_fp16 = mul(x = var_78_cast_fp16_4, y = var_161_cast_fp16)[name = tensor("op_1022_cast_fp16")]; + tensor value_17_cast_fp16 = add(x = var_1020_cast_fp16, y = var_1022_cast_fp16)[name = tensor("value_17_cast_fp16")]; + tensor var_1025 = const()[name = tensor("op_1025"), val = tensor([1, 12, 64, -1])]; + tensor var_1026_cast_fp16 = reshape(shape = var_1025, x = query_17_cast_fp16)[name = tensor("op_1026_cast_fp16")]; + tensor var_1027_to_fp16 = const()[name = tensor("op_1027_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1028_cast_fp16 = mul(x = var_1026_cast_fp16, y = var_1027_to_fp16)[name = tensor("op_1028_cast_fp16")]; + tensor var_1029 = const()[name = tensor("op_1029"), val = tensor([1, 12, 64, -1])]; + tensor var_1030_cast_fp16 = reshape(shape = var_1029, x = key_17_cast_fp16)[name = tensor("op_1030_cast_fp16")]; + tensor mh_w_25_transpose_x_0 = const()[name = tensor("mh_w_25_transpose_x_0"), val = tensor(true)]; + tensor mh_w_25_transpose_y_0 = const()[name = tensor("mh_w_25_transpose_y_0"), val = tensor(false)]; + tensor mh_w_25_cast_fp16 = matmul(transpose_x = mh_w_25_transpose_x_0, transpose_y = mh_w_25_transpose_y_0, x = var_1028_cast_fp16, y = var_1030_cast_fp16)[name = tensor("mh_w_25_cast_fp16")]; + tensor mh_w_27_cast_fp16 = add(x = mh_w_25_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_27_cast_fp16")]; + tensor var_1038_cast_fp16 = softmax(axis = var_952, x = mh_w_27_cast_fp16)[name = tensor("op_1038_cast_fp16")]; + tensor var_1039 = const()[name = tensor("op_1039"), val = tensor([1, 12, 64, -1])]; + tensor var_1040_cast_fp16 = reshape(shape = var_1039, x = value_17_cast_fp16)[name = tensor("op_1040_cast_fp16")]; + tensor attn_17_transpose_x_0 = const()[name = tensor("attn_17_transpose_x_0"), val = tensor(false)]; + tensor attn_17_transpose_y_0 = const()[name = tensor("attn_17_transpose_y_0"), val = tensor(true)]; + tensor attn_17_cast_fp16 = matmul(transpose_x = attn_17_transpose_x_0, transpose_y = attn_17_transpose_y_0, x = var_1040_cast_fp16, y = var_1038_cast_fp16)[name = tensor("attn_17_cast_fp16")]; + tensor var_1043 = const()[name = tensor("op_1043"), val = tensor([1, 768, 1, -1])]; + tensor input_41_cast_fp16 = reshape(shape = var_1043, x = attn_17_cast_fp16)[name = tensor("input_41_cast_fp16")]; + tensor var_1047 = const()[name = tensor("op_1047"), val = tensor([1, 1])]; + tensor var_1049 = const()[name = tensor("op_1049"), val = tensor([1, 1])]; + tensor obj_63_pad_type_0 = const()[name = tensor("obj_63_pad_type_0"), val = tensor("custom")]; + tensor obj_63_pad_0 = const()[name = tensor("obj_63_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159509760)))]; + tensor layers_4_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160689472)))]; + tensor obj_63_cast_fp16 = conv(bias = layers_4_self_attn_o_proj_bias_to_fp16, dilations = var_1049, groups = var_959, pad = obj_63_pad_0, pad_type = obj_63_pad_type_0, strides = var_1047, weight = layers_4_self_attn_o_proj_weight_to_fp16, x = input_41_cast_fp16)[name = tensor("obj_63_cast_fp16")]; + tensor inputs_27_cast_fp16 = add(x = inputs_25_cast_fp16, y = obj_63_cast_fp16)[name = tensor("inputs_27_cast_fp16")]; + tensor var_1059 = const()[name = tensor("op_1059"), val = tensor([1])]; + tensor channels_mean_27_cast_fp16 = reduce_mean(axes = var_1059, keep_dims = var_960, x = inputs_27_cast_fp16)[name = tensor("channels_mean_27_cast_fp16")]; + tensor zero_mean_27_cast_fp16 = sub(x = inputs_27_cast_fp16, y = channels_mean_27_cast_fp16)[name = tensor("zero_mean_27_cast_fp16")]; + tensor zero_mean_sq_27_cast_fp16 = mul(x = zero_mean_27_cast_fp16, y = zero_mean_27_cast_fp16)[name = tensor("zero_mean_sq_27_cast_fp16")]; + tensor var_1063 = const()[name = tensor("op_1063"), val = tensor([1])]; + tensor var_1064_cast_fp16 = reduce_mean(axes = var_1063, keep_dims = var_960, x = zero_mean_sq_27_cast_fp16)[name = tensor("op_1064_cast_fp16")]; + tensor var_1065_to_fp16 = const()[name = tensor("op_1065_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1066_cast_fp16 = add(x = var_1064_cast_fp16, y = var_1065_to_fp16)[name = tensor("op_1066_cast_fp16")]; + tensor denom_27_epsilon_0_to_fp16 = const()[name = tensor("denom_27_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_27_cast_fp16 = rsqrt(epsilon = denom_27_epsilon_0_to_fp16, x = var_1066_cast_fp16)[name = tensor("denom_27_cast_fp16")]; + tensor out_27_cast_fp16 = mul(x = zero_mean_27_cast_fp16, y = denom_27_cast_fp16)[name = tensor("out_27_cast_fp16")]; + tensor obj_65_gamma_0_to_fp16 = const()[name = tensor("obj_65_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160691072)))]; + tensor obj_65_beta_0_to_fp16 = const()[name = tensor("obj_65_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160692672)))]; + tensor obj_65_epsilon_0_to_fp16 = const()[name = tensor("obj_65_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_65_cast_fp16 = batch_norm(beta = obj_65_beta_0_to_fp16, epsilon = obj_65_epsilon_0_to_fp16, gamma = obj_65_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_27_cast_fp16)[name = tensor("obj_65_cast_fp16")]; + tensor var_1081 = const()[name = tensor("op_1081"), val = tensor([1, 1])]; + tensor var_1083 = const()[name = tensor("op_1083"), val = tensor([1, 1])]; + tensor query_19_pad_type_0 = const()[name = tensor("query_19_pad_type_0"), val = tensor("custom")]; + tensor query_19_pad_0 = const()[name = tensor("query_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160694272)))]; + tensor layers_4_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_4_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161873984)))]; + tensor query_19_cast_fp16 = conv(bias = layers_4_encoder_attn_q_proj_bias_to_fp16, dilations = var_1083, groups = var_959, pad = query_19_pad_0, pad_type = query_19_pad_type_0, strides = var_1081, weight = layers_4_encoder_attn_q_proj_weight_to_fp16, x = obj_65_cast_fp16)[name = tensor("query_19_cast_fp16")]; + tensor var_1087 = const()[name = tensor("op_1087"), val = tensor([1, 1])]; + tensor var_1089 = const()[name = tensor("op_1089"), val = tensor([1, 1])]; + tensor key_19_pad_type_0 = const()[name = tensor("key_19_pad_type_0"), val = tensor("custom")]; + tensor key_19_pad_0 = const()[name = tensor("key_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161875584)))]; + tensor key_19_cast_fp16 = conv(dilations = var_1089, groups = var_959, pad = key_19_pad_0, pad_type = key_19_pad_type_0, strides = var_1087, weight = layers_4_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_19_cast_fp16")]; + tensor var_1094 = const()[name = tensor("op_1094"), val = tensor([1, 1])]; + tensor var_1096 = const()[name = tensor("op_1096"), val = tensor([1, 1])]; + tensor value_19_pad_type_0 = const()[name = tensor("value_19_pad_type_0"), val = tensor("custom")]; + tensor value_19_pad_0 = const()[name = tensor("value_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(163055296)))]; + tensor layers_4_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_4_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164235008)))]; + tensor value_19_cast_fp16 = conv(bias = layers_4_encoder_attn_v_proj_bias_to_fp16, dilations = var_1096, groups = var_959, pad = value_19_pad_0, pad_type = value_19_pad_type_0, strides = var_1094, weight = layers_4_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_19_cast_fp16")]; + tensor var_1100 = const()[name = tensor("op_1100"), val = tensor([1, 12, 64, -1])]; + tensor var_1101_cast_fp16 = reshape(shape = var_1100, x = query_19_cast_fp16)[name = tensor("op_1101_cast_fp16")]; + tensor var_1102_to_fp16 = const()[name = tensor("op_1102_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1103_cast_fp16 = mul(x = var_1101_cast_fp16, y = var_1102_to_fp16)[name = tensor("op_1103_cast_fp16")]; + tensor var_1104 = const()[name = tensor("op_1104"), val = tensor([1, 12, 64, -1])]; + tensor var_1105_cast_fp16 = reshape(shape = var_1104, x = key_19_cast_fp16)[name = tensor("op_1105_cast_fp16")]; + tensor mh_w_29_transpose_x_0 = const()[name = tensor("mh_w_29_transpose_x_0"), val = tensor(true)]; + tensor mh_w_29_transpose_y_0 = const()[name = tensor("mh_w_29_transpose_y_0"), val = tensor(false)]; + tensor mh_w_29_cast_fp16 = matmul(transpose_x = mh_w_29_transpose_x_0, transpose_y = mh_w_29_transpose_y_0, x = var_1103_cast_fp16, y = var_1105_cast_fp16)[name = tensor("mh_w_29_cast_fp16")]; + tensor obj_69_cast_fp16 = softmax(axis = var_952, x = mh_w_29_cast_fp16)[name = tensor("obj_69_cast_fp16")]; + tensor var_1109 = const()[name = tensor("op_1109"), val = tensor([1, 12, 64, -1])]; + tensor var_1110_cast_fp16 = reshape(shape = var_1109, x = value_19_cast_fp16)[name = tensor("op_1110_cast_fp16")]; + tensor attn_19_transpose_x_0 = const()[name = tensor("attn_19_transpose_x_0"), val = tensor(false)]; + tensor attn_19_transpose_y_0 = const()[name = tensor("attn_19_transpose_y_0"), val = tensor(true)]; + tensor attn_19_cast_fp16 = matmul(transpose_x = attn_19_transpose_x_0, transpose_y = attn_19_transpose_y_0, x = var_1110_cast_fp16, y = obj_69_cast_fp16)[name = tensor("attn_19_cast_fp16")]; + tensor var_1113 = const()[name = tensor("op_1113"), val = tensor([1, 768, 1, -1])]; + tensor input_43_cast_fp16 = reshape(shape = var_1113, x = attn_19_cast_fp16)[name = tensor("input_43_cast_fp16")]; + tensor var_1117 = const()[name = tensor("op_1117"), val = tensor([1, 1])]; + tensor var_1119 = const()[name = tensor("op_1119"), val = tensor([1, 1])]; + tensor obj_67_pad_type_0 = const()[name = tensor("obj_67_pad_type_0"), val = tensor("custom")]; + tensor obj_67_pad_0 = const()[name = tensor("obj_67_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164236608)))]; + tensor layers_4_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_4_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165416320)))]; + tensor obj_67_cast_fp16 = conv(bias = layers_4_encoder_attn_o_proj_bias_to_fp16, dilations = var_1119, groups = var_959, pad = obj_67_pad_0, pad_type = obj_67_pad_type_0, strides = var_1117, weight = layers_4_encoder_attn_o_proj_weight_to_fp16, x = input_43_cast_fp16)[name = tensor("obj_67_cast_fp16")]; + tensor inputs_29_cast_fp16 = add(x = inputs_27_cast_fp16, y = obj_67_cast_fp16)[name = tensor("inputs_29_cast_fp16")]; + tensor var_1125 = const()[name = tensor("op_1125"), val = tensor([1])]; + tensor channels_mean_29_cast_fp16 = reduce_mean(axes = var_1125, keep_dims = var_960, x = inputs_29_cast_fp16)[name = tensor("channels_mean_29_cast_fp16")]; + tensor zero_mean_29_cast_fp16 = sub(x = inputs_29_cast_fp16, y = channels_mean_29_cast_fp16)[name = tensor("zero_mean_29_cast_fp16")]; + tensor zero_mean_sq_29_cast_fp16 = mul(x = zero_mean_29_cast_fp16, y = zero_mean_29_cast_fp16)[name = tensor("zero_mean_sq_29_cast_fp16")]; + tensor var_1129 = const()[name = tensor("op_1129"), val = tensor([1])]; + tensor var_1130_cast_fp16 = reduce_mean(axes = var_1129, keep_dims = var_960, x = zero_mean_sq_29_cast_fp16)[name = tensor("op_1130_cast_fp16")]; + tensor var_1131_to_fp16 = const()[name = tensor("op_1131_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1132_cast_fp16 = add(x = var_1130_cast_fp16, y = var_1131_to_fp16)[name = tensor("op_1132_cast_fp16")]; + tensor denom_29_epsilon_0_to_fp16 = const()[name = tensor("denom_29_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_29_cast_fp16 = rsqrt(epsilon = denom_29_epsilon_0_to_fp16, x = var_1132_cast_fp16)[name = tensor("denom_29_cast_fp16")]; + tensor out_29_cast_fp16 = mul(x = zero_mean_29_cast_fp16, y = denom_29_cast_fp16)[name = tensor("out_29_cast_fp16")]; + tensor input_45_gamma_0_to_fp16 = const()[name = tensor("input_45_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165417920)))]; + tensor input_45_beta_0_to_fp16 = const()[name = tensor("input_45_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165419520)))]; + tensor input_45_epsilon_0_to_fp16 = const()[name = tensor("input_45_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_45_cast_fp16 = batch_norm(beta = input_45_beta_0_to_fp16, epsilon = input_45_epsilon_0_to_fp16, gamma = input_45_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_29_cast_fp16)[name = tensor("input_45_cast_fp16")]; + tensor var_1143 = const()[name = tensor("op_1143"), val = tensor([1, 1])]; + tensor var_1145 = const()[name = tensor("op_1145"), val = tensor([1, 1])]; + tensor input_47_pad_type_0 = const()[name = tensor("input_47_pad_type_0"), val = tensor("custom")]; + tensor input_47_pad_0 = const()[name = tensor("input_47_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_fc1_weight_to_fp16 = const()[name = tensor("layers_4_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165421120)))]; + tensor layers_4_fc1_bias_to_fp16 = const()[name = tensor("layers_4_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170139776)))]; + tensor input_47_cast_fp16 = conv(bias = layers_4_fc1_bias_to_fp16, dilations = var_1145, groups = var_959, pad = input_47_pad_0, pad_type = input_47_pad_type_0, strides = var_1143, weight = layers_4_fc1_weight_to_fp16, x = input_45_cast_fp16)[name = tensor("input_47_cast_fp16")]; + tensor input_49_mode_0 = const()[name = tensor("input_49_mode_0"), val = tensor("EXACT")]; + tensor input_49_cast_fp16 = gelu(mode = input_49_mode_0, x = input_47_cast_fp16)[name = tensor("input_49_cast_fp16")]; + tensor var_1151 = const()[name = tensor("op_1151"), val = tensor([1, 1])]; + tensor var_1153 = const()[name = tensor("op_1153"), val = tensor([1, 1])]; + tensor hidden_states_11_pad_type_0 = const()[name = tensor("hidden_states_11_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_11_pad_0 = const()[name = tensor("hidden_states_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_4_fc2_weight_to_fp16 = const()[name = tensor("layers_4_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170145984)))]; + tensor layers_4_fc2_bias_to_fp16 = const()[name = tensor("layers_4_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174864640)))]; + tensor hidden_states_11_cast_fp16 = conv(bias = layers_4_fc2_bias_to_fp16, dilations = var_1153, groups = var_959, pad = hidden_states_11_pad_0, pad_type = hidden_states_11_pad_type_0, strides = var_1151, weight = layers_4_fc2_weight_to_fp16, x = input_49_cast_fp16)[name = tensor("hidden_states_11_cast_fp16")]; + tensor inputs_31_cast_fp16 = add(x = inputs_29_cast_fp16, y = hidden_states_11_cast_fp16)[name = tensor("inputs_31_cast_fp16")]; + tensor var_1166 = const()[name = tensor("op_1166"), val = tensor(3)]; + tensor var_1173 = const()[name = tensor("op_1173"), val = tensor(1)]; + tensor var_1174 = const()[name = tensor("op_1174"), val = tensor(true)]; + tensor var_1186 = const()[name = tensor("op_1186"), val = tensor([1])]; + tensor channels_mean_31_cast_fp16 = reduce_mean(axes = var_1186, keep_dims = var_1174, x = inputs_31_cast_fp16)[name = tensor("channels_mean_31_cast_fp16")]; + tensor zero_mean_31_cast_fp16 = sub(x = inputs_31_cast_fp16, y = channels_mean_31_cast_fp16)[name = tensor("zero_mean_31_cast_fp16")]; + tensor zero_mean_sq_31_cast_fp16 = mul(x = zero_mean_31_cast_fp16, y = zero_mean_31_cast_fp16)[name = tensor("zero_mean_sq_31_cast_fp16")]; + tensor var_1190 = const()[name = tensor("op_1190"), val = tensor([1])]; + tensor var_1191_cast_fp16 = reduce_mean(axes = var_1190, keep_dims = var_1174, x = zero_mean_sq_31_cast_fp16)[name = tensor("op_1191_cast_fp16")]; + tensor var_1192_to_fp16 = const()[name = tensor("op_1192_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1193_cast_fp16 = add(x = var_1191_cast_fp16, y = var_1192_to_fp16)[name = tensor("op_1193_cast_fp16")]; + tensor denom_31_epsilon_0_to_fp16 = const()[name = tensor("denom_31_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_31_cast_fp16 = rsqrt(epsilon = denom_31_epsilon_0_to_fp16, x = var_1193_cast_fp16)[name = tensor("denom_31_cast_fp16")]; + tensor out_31_cast_fp16 = mul(x = zero_mean_31_cast_fp16, y = denom_31_cast_fp16)[name = tensor("out_31_cast_fp16")]; + tensor obj_71_gamma_0_to_fp16 = const()[name = tensor("obj_71_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174866240)))]; + tensor obj_71_beta_0_to_fp16 = const()[name = tensor("obj_71_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174867840)))]; + tensor obj_71_epsilon_0_to_fp16 = const()[name = tensor("obj_71_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_71_cast_fp16 = batch_norm(beta = obj_71_beta_0_to_fp16, epsilon = obj_71_epsilon_0_to_fp16, gamma = obj_71_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_31_cast_fp16)[name = tensor("obj_71_cast_fp16")]; + tensor var_1208 = const()[name = tensor("op_1208"), val = tensor([1, 1])]; + tensor var_1210 = const()[name = tensor("op_1210"), val = tensor([1, 1])]; + tensor query_21_pad_type_0 = const()[name = tensor("query_21_pad_type_0"), val = tensor("custom")]; + tensor query_21_pad_0 = const()[name = tensor("query_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174869440)))]; + tensor layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176049152)))]; + tensor query_21_cast_fp16 = conv(bias = layers_5_self_attn_q_proj_bias_to_fp16, dilations = var_1210, groups = var_1173, pad = query_21_pad_0, pad_type = query_21_pad_type_0, strides = var_1208, weight = layers_5_self_attn_q_proj_weight_to_fp16, x = obj_71_cast_fp16)[name = tensor("query_21_cast_fp16")]; + tensor var_1214 = const()[name = tensor("op_1214"), val = tensor([1, 1])]; + tensor var_1216 = const()[name = tensor("op_1216"), val = tensor([1, 1])]; + tensor current_key_11_pad_type_0 = const()[name = tensor("current_key_11_pad_type_0"), val = tensor("custom")]; + tensor current_key_11_pad_0 = const()[name = tensor("current_key_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176050752)))]; + tensor current_key_11_cast_fp16 = conv(dilations = var_1216, groups = var_1173, pad = current_key_11_pad_0, pad_type = current_key_11_pad_type_0, strides = var_1214, weight = layers_5_self_attn_k_proj_weight_to_fp16, x = obj_71_cast_fp16)[name = tensor("current_key_11_cast_fp16")]; + tensor var_1221 = const()[name = tensor("op_1221"), val = tensor([1, 1])]; + tensor var_1223 = const()[name = tensor("op_1223"), val = tensor([1, 1])]; + tensor current_value_11_pad_type_0 = const()[name = tensor("current_value_11_pad_type_0"), val = tensor("custom")]; + tensor current_value_11_pad_0 = const()[name = tensor("current_value_11_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177230464)))]; + tensor layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178410176)))]; + tensor current_value_11_cast_fp16 = conv(bias = layers_5_self_attn_v_proj_bias_to_fp16, dilations = var_1223, groups = var_1173, pad = current_value_11_pad_0, pad_type = current_value_11_pad_type_0, strides = var_1221, weight = layers_5_self_attn_v_proj_weight_to_fp16, x = obj_71_cast_fp16)[name = tensor("current_value_11_cast_fp16")]; + tensor var_1230_cast_fp16 = mul(x = current_key_11_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1230_cast_fp16")]; + tensor var_1232_cast_fp16 = mul(x = var_63_cast_fp16_5, y = var_161_cast_fp16)[name = tensor("op_1232_cast_fp16")]; + tensor key_21_cast_fp16 = add(x = var_1230_cast_fp16, y = var_1232_cast_fp16)[name = tensor("key_21_cast_fp16")]; + tensor var_1234_cast_fp16 = mul(x = current_value_11_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1234_cast_fp16")]; + tensor var_1236_cast_fp16 = mul(x = var_78_cast_fp16_5, y = var_161_cast_fp16)[name = tensor("op_1236_cast_fp16")]; + tensor value_21_cast_fp16 = add(x = var_1234_cast_fp16, y = var_1236_cast_fp16)[name = tensor("value_21_cast_fp16")]; + tensor var_1239 = const()[name = tensor("op_1239"), val = tensor([1, 12, 64, -1])]; + tensor var_1240_cast_fp16 = reshape(shape = var_1239, x = query_21_cast_fp16)[name = tensor("op_1240_cast_fp16")]; + tensor var_1241_to_fp16 = const()[name = tensor("op_1241_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1242_cast_fp16 = mul(x = var_1240_cast_fp16, y = var_1241_to_fp16)[name = tensor("op_1242_cast_fp16")]; + tensor var_1243 = const()[name = tensor("op_1243"), val = tensor([1, 12, 64, -1])]; + tensor var_1244_cast_fp16 = reshape(shape = var_1243, x = key_21_cast_fp16)[name = tensor("op_1244_cast_fp16")]; + tensor mh_w_31_transpose_x_0 = const()[name = tensor("mh_w_31_transpose_x_0"), val = tensor(true)]; + tensor mh_w_31_transpose_y_0 = const()[name = tensor("mh_w_31_transpose_y_0"), val = tensor(false)]; + tensor mh_w_31_cast_fp16 = matmul(transpose_x = mh_w_31_transpose_x_0, transpose_y = mh_w_31_transpose_y_0, x = var_1242_cast_fp16, y = var_1244_cast_fp16)[name = tensor("mh_w_31_cast_fp16")]; + tensor mh_w_33_cast_fp16 = add(x = mh_w_31_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_33_cast_fp16")]; + tensor var_1252_cast_fp16 = softmax(axis = var_1166, x = mh_w_33_cast_fp16)[name = tensor("op_1252_cast_fp16")]; + tensor var_1253 = const()[name = tensor("op_1253"), val = tensor([1, 12, 64, -1])]; + tensor var_1254_cast_fp16 = reshape(shape = var_1253, x = value_21_cast_fp16)[name = tensor("op_1254_cast_fp16")]; + tensor attn_21_transpose_x_0 = const()[name = tensor("attn_21_transpose_x_0"), val = tensor(false)]; + tensor attn_21_transpose_y_0 = const()[name = tensor("attn_21_transpose_y_0"), val = tensor(true)]; + tensor attn_21_cast_fp16 = matmul(transpose_x = attn_21_transpose_x_0, transpose_y = attn_21_transpose_y_0, x = var_1254_cast_fp16, y = var_1252_cast_fp16)[name = tensor("attn_21_cast_fp16")]; + tensor var_1257 = const()[name = tensor("op_1257"), val = tensor([1, 768, 1, -1])]; + tensor input_51_cast_fp16 = reshape(shape = var_1257, x = attn_21_cast_fp16)[name = tensor("input_51_cast_fp16")]; + tensor var_1261 = const()[name = tensor("op_1261"), val = tensor([1, 1])]; + tensor var_1263 = const()[name = tensor("op_1263"), val = tensor([1, 1])]; + tensor obj_77_pad_type_0 = const()[name = tensor("obj_77_pad_type_0"), val = tensor("custom")]; + tensor obj_77_pad_0 = const()[name = tensor("obj_77_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178411776)))]; + tensor layers_5_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179591488)))]; + tensor obj_77_cast_fp16 = conv(bias = layers_5_self_attn_o_proj_bias_to_fp16, dilations = var_1263, groups = var_1173, pad = obj_77_pad_0, pad_type = obj_77_pad_type_0, strides = var_1261, weight = layers_5_self_attn_o_proj_weight_to_fp16, x = input_51_cast_fp16)[name = tensor("obj_77_cast_fp16")]; + tensor inputs_33_cast_fp16 = add(x = inputs_31_cast_fp16, y = obj_77_cast_fp16)[name = tensor("inputs_33_cast_fp16")]; + tensor var_1273 = const()[name = tensor("op_1273"), val = tensor([1])]; + tensor channels_mean_33_cast_fp16 = reduce_mean(axes = var_1273, keep_dims = var_1174, x = inputs_33_cast_fp16)[name = tensor("channels_mean_33_cast_fp16")]; + tensor zero_mean_33_cast_fp16 = sub(x = inputs_33_cast_fp16, y = channels_mean_33_cast_fp16)[name = tensor("zero_mean_33_cast_fp16")]; + tensor zero_mean_sq_33_cast_fp16 = mul(x = zero_mean_33_cast_fp16, y = zero_mean_33_cast_fp16)[name = tensor("zero_mean_sq_33_cast_fp16")]; + tensor var_1277 = const()[name = tensor("op_1277"), val = tensor([1])]; + tensor var_1278_cast_fp16 = reduce_mean(axes = var_1277, keep_dims = var_1174, x = zero_mean_sq_33_cast_fp16)[name = tensor("op_1278_cast_fp16")]; + tensor var_1279_to_fp16 = const()[name = tensor("op_1279_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1280_cast_fp16 = add(x = var_1278_cast_fp16, y = var_1279_to_fp16)[name = tensor("op_1280_cast_fp16")]; + tensor denom_33_epsilon_0_to_fp16 = const()[name = tensor("denom_33_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_33_cast_fp16 = rsqrt(epsilon = denom_33_epsilon_0_to_fp16, x = var_1280_cast_fp16)[name = tensor("denom_33_cast_fp16")]; + tensor out_33_cast_fp16 = mul(x = zero_mean_33_cast_fp16, y = denom_33_cast_fp16)[name = tensor("out_33_cast_fp16")]; + tensor obj_79_gamma_0_to_fp16 = const()[name = tensor("obj_79_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179593088)))]; + tensor obj_79_beta_0_to_fp16 = const()[name = tensor("obj_79_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179594688)))]; + tensor obj_79_epsilon_0_to_fp16 = const()[name = tensor("obj_79_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_79_cast_fp16 = batch_norm(beta = obj_79_beta_0_to_fp16, epsilon = obj_79_epsilon_0_to_fp16, gamma = obj_79_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_33_cast_fp16)[name = tensor("obj_79_cast_fp16")]; + tensor var_1295 = const()[name = tensor("op_1295"), val = tensor([1, 1])]; + tensor var_1297 = const()[name = tensor("op_1297"), val = tensor([1, 1])]; + tensor query_23_pad_type_0 = const()[name = tensor("query_23_pad_type_0"), val = tensor("custom")]; + tensor query_23_pad_0 = const()[name = tensor("query_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179596288)))]; + tensor layers_5_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_5_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180776000)))]; + tensor query_23_cast_fp16 = conv(bias = layers_5_encoder_attn_q_proj_bias_to_fp16, dilations = var_1297, groups = var_1173, pad = query_23_pad_0, pad_type = query_23_pad_type_0, strides = var_1295, weight = layers_5_encoder_attn_q_proj_weight_to_fp16, x = obj_79_cast_fp16)[name = tensor("query_23_cast_fp16")]; + tensor var_1301 = const()[name = tensor("op_1301"), val = tensor([1, 1])]; + tensor var_1303 = const()[name = tensor("op_1303"), val = tensor([1, 1])]; + tensor key_23_pad_type_0 = const()[name = tensor("key_23_pad_type_0"), val = tensor("custom")]; + tensor key_23_pad_0 = const()[name = tensor("key_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180777600)))]; + tensor key_23_cast_fp16 = conv(dilations = var_1303, groups = var_1173, pad = key_23_pad_0, pad_type = key_23_pad_type_0, strides = var_1301, weight = layers_5_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_23_cast_fp16")]; + tensor var_1308 = const()[name = tensor("op_1308"), val = tensor([1, 1])]; + tensor var_1310 = const()[name = tensor("op_1310"), val = tensor([1, 1])]; + tensor value_23_pad_type_0 = const()[name = tensor("value_23_pad_type_0"), val = tensor("custom")]; + tensor value_23_pad_0 = const()[name = tensor("value_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(181957312)))]; + tensor layers_5_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_5_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183137024)))]; + tensor value_23_cast_fp16 = conv(bias = layers_5_encoder_attn_v_proj_bias_to_fp16, dilations = var_1310, groups = var_1173, pad = value_23_pad_0, pad_type = value_23_pad_type_0, strides = var_1308, weight = layers_5_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_23_cast_fp16")]; + tensor var_1314 = const()[name = tensor("op_1314"), val = tensor([1, 12, 64, -1])]; + tensor var_1315_cast_fp16 = reshape(shape = var_1314, x = query_23_cast_fp16)[name = tensor("op_1315_cast_fp16")]; + tensor var_1316_to_fp16 = const()[name = tensor("op_1316_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1317_cast_fp16 = mul(x = var_1315_cast_fp16, y = var_1316_to_fp16)[name = tensor("op_1317_cast_fp16")]; + tensor var_1318 = const()[name = tensor("op_1318"), val = tensor([1, 12, 64, -1])]; + tensor var_1319_cast_fp16 = reshape(shape = var_1318, x = key_23_cast_fp16)[name = tensor("op_1319_cast_fp16")]; + tensor mh_w_35_transpose_x_0 = const()[name = tensor("mh_w_35_transpose_x_0"), val = tensor(true)]; + tensor mh_w_35_transpose_y_0 = const()[name = tensor("mh_w_35_transpose_y_0"), val = tensor(false)]; + tensor mh_w_35_cast_fp16 = matmul(transpose_x = mh_w_35_transpose_x_0, transpose_y = mh_w_35_transpose_y_0, x = var_1317_cast_fp16, y = var_1319_cast_fp16)[name = tensor("mh_w_35_cast_fp16")]; + tensor obj_83_cast_fp16 = softmax(axis = var_1166, x = mh_w_35_cast_fp16)[name = tensor("obj_83_cast_fp16")]; + tensor var_1323 = const()[name = tensor("op_1323"), val = tensor([1, 12, 64, -1])]; + tensor var_1324_cast_fp16 = reshape(shape = var_1323, x = value_23_cast_fp16)[name = tensor("op_1324_cast_fp16")]; + tensor attn_23_transpose_x_0 = const()[name = tensor("attn_23_transpose_x_0"), val = tensor(false)]; + tensor attn_23_transpose_y_0 = const()[name = tensor("attn_23_transpose_y_0"), val = tensor(true)]; + tensor attn_23_cast_fp16 = matmul(transpose_x = attn_23_transpose_x_0, transpose_y = attn_23_transpose_y_0, x = var_1324_cast_fp16, y = obj_83_cast_fp16)[name = tensor("attn_23_cast_fp16")]; + tensor var_1327 = const()[name = tensor("op_1327"), val = tensor([1, 768, 1, -1])]; + tensor input_53_cast_fp16 = reshape(shape = var_1327, x = attn_23_cast_fp16)[name = tensor("input_53_cast_fp16")]; + tensor var_1331 = const()[name = tensor("op_1331"), val = tensor([1, 1])]; + tensor var_1333 = const()[name = tensor("op_1333"), val = tensor([1, 1])]; + tensor obj_81_pad_type_0 = const()[name = tensor("obj_81_pad_type_0"), val = tensor("custom")]; + tensor obj_81_pad_0 = const()[name = tensor("obj_81_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183138624)))]; + tensor layers_5_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_5_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184318336)))]; + tensor obj_81_cast_fp16 = conv(bias = layers_5_encoder_attn_o_proj_bias_to_fp16, dilations = var_1333, groups = var_1173, pad = obj_81_pad_0, pad_type = obj_81_pad_type_0, strides = var_1331, weight = layers_5_encoder_attn_o_proj_weight_to_fp16, x = input_53_cast_fp16)[name = tensor("obj_81_cast_fp16")]; + tensor inputs_35_cast_fp16 = add(x = inputs_33_cast_fp16, y = obj_81_cast_fp16)[name = tensor("inputs_35_cast_fp16")]; + tensor var_1342 = const()[name = tensor("op_1342"), val = tensor([1])]; + tensor channels_mean_35_cast_fp16 = reduce_mean(axes = var_1342, keep_dims = var_1174, x = inputs_35_cast_fp16)[name = tensor("channels_mean_35_cast_fp16")]; + tensor zero_mean_35_cast_fp16 = sub(x = inputs_35_cast_fp16, y = channels_mean_35_cast_fp16)[name = tensor("zero_mean_35_cast_fp16")]; + tensor zero_mean_sq_35_cast_fp16 = mul(x = zero_mean_35_cast_fp16, y = zero_mean_35_cast_fp16)[name = tensor("zero_mean_sq_35_cast_fp16")]; + tensor var_1346 = const()[name = tensor("op_1346"), val = tensor([1])]; + tensor var_1347_cast_fp16 = reduce_mean(axes = var_1346, keep_dims = var_1174, x = zero_mean_sq_35_cast_fp16)[name = tensor("op_1347_cast_fp16")]; + tensor var_1348_to_fp16 = const()[name = tensor("op_1348_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1349_cast_fp16 = add(x = var_1347_cast_fp16, y = var_1348_to_fp16)[name = tensor("op_1349_cast_fp16")]; + tensor denom_35_epsilon_0_to_fp16 = const()[name = tensor("denom_35_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_35_cast_fp16 = rsqrt(epsilon = denom_35_epsilon_0_to_fp16, x = var_1349_cast_fp16)[name = tensor("denom_35_cast_fp16")]; + tensor out_35_cast_fp16 = mul(x = zero_mean_35_cast_fp16, y = denom_35_cast_fp16)[name = tensor("out_35_cast_fp16")]; + tensor input_55_gamma_0_to_fp16 = const()[name = tensor("input_55_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184319936)))]; + tensor input_55_beta_0_to_fp16 = const()[name = tensor("input_55_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184321536)))]; + tensor input_55_epsilon_0_to_fp16 = const()[name = tensor("input_55_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_55_cast_fp16 = batch_norm(beta = input_55_beta_0_to_fp16, epsilon = input_55_epsilon_0_to_fp16, gamma = input_55_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_35_cast_fp16)[name = tensor("input_55_cast_fp16")]; + tensor var_1360 = const()[name = tensor("op_1360"), val = tensor([1, 1])]; + tensor var_1362 = const()[name = tensor("op_1362"), val = tensor([1, 1])]; + tensor input_57_pad_type_0 = const()[name = tensor("input_57_pad_type_0"), val = tensor("custom")]; + tensor input_57_pad_0 = const()[name = tensor("input_57_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_fc1_weight_to_fp16 = const()[name = tensor("layers_5_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184323136)))]; + tensor layers_5_fc1_bias_to_fp16 = const()[name = tensor("layers_5_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189041792)))]; + tensor input_57_cast_fp16 = conv(bias = layers_5_fc1_bias_to_fp16, dilations = var_1362, groups = var_1173, pad = input_57_pad_0, pad_type = input_57_pad_type_0, strides = var_1360, weight = layers_5_fc1_weight_to_fp16, x = input_55_cast_fp16)[name = tensor("input_57_cast_fp16")]; + tensor input_59_mode_0 = const()[name = tensor("input_59_mode_0"), val = tensor("EXACT")]; + tensor input_59_cast_fp16 = gelu(mode = input_59_mode_0, x = input_57_cast_fp16)[name = tensor("input_59_cast_fp16")]; + tensor var_1368 = const()[name = tensor("op_1368"), val = tensor([1, 1])]; + tensor var_1370 = const()[name = tensor("op_1370"), val = tensor([1, 1])]; + tensor hidden_states_13_pad_type_0 = const()[name = tensor("hidden_states_13_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_13_pad_0 = const()[name = tensor("hidden_states_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_5_fc2_weight_to_fp16 = const()[name = tensor("layers_5_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189048000)))]; + tensor layers_5_fc2_bias_to_fp16 = const()[name = tensor("layers_5_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(193766656)))]; + tensor hidden_states_13_cast_fp16 = conv(bias = layers_5_fc2_bias_to_fp16, dilations = var_1370, groups = var_1173, pad = hidden_states_13_pad_0, pad_type = hidden_states_13_pad_type_0, strides = var_1368, weight = layers_5_fc2_weight_to_fp16, x = input_59_cast_fp16)[name = tensor("hidden_states_13_cast_fp16")]; + tensor inputs_37_cast_fp16 = add(x = inputs_35_cast_fp16, y = hidden_states_13_cast_fp16)[name = tensor("inputs_37_cast_fp16")]; + tensor var_1384 = const()[name = tensor("op_1384"), val = tensor(3)]; + tensor var_1391 = const()[name = tensor("op_1391"), val = tensor(1)]; + tensor var_1392 = const()[name = tensor("op_1392"), val = tensor(true)]; + tensor var_1404 = const()[name = tensor("op_1404"), val = tensor([1])]; + tensor channels_mean_37_cast_fp16 = reduce_mean(axes = var_1404, keep_dims = var_1392, x = inputs_37_cast_fp16)[name = tensor("channels_mean_37_cast_fp16")]; + tensor zero_mean_37_cast_fp16 = sub(x = inputs_37_cast_fp16, y = channels_mean_37_cast_fp16)[name = tensor("zero_mean_37_cast_fp16")]; + tensor zero_mean_sq_37_cast_fp16 = mul(x = zero_mean_37_cast_fp16, y = zero_mean_37_cast_fp16)[name = tensor("zero_mean_sq_37_cast_fp16")]; + tensor var_1408 = const()[name = tensor("op_1408"), val = tensor([1])]; + tensor var_1409_cast_fp16 = reduce_mean(axes = var_1408, keep_dims = var_1392, x = zero_mean_sq_37_cast_fp16)[name = tensor("op_1409_cast_fp16")]; + tensor var_1410_to_fp16 = const()[name = tensor("op_1410_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1411_cast_fp16 = add(x = var_1409_cast_fp16, y = var_1410_to_fp16)[name = tensor("op_1411_cast_fp16")]; + tensor denom_37_epsilon_0_to_fp16 = const()[name = tensor("denom_37_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_37_cast_fp16 = rsqrt(epsilon = denom_37_epsilon_0_to_fp16, x = var_1411_cast_fp16)[name = tensor("denom_37_cast_fp16")]; + tensor out_37_cast_fp16 = mul(x = zero_mean_37_cast_fp16, y = denom_37_cast_fp16)[name = tensor("out_37_cast_fp16")]; + tensor obj_85_gamma_0_to_fp16 = const()[name = tensor("obj_85_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(193768256)))]; + tensor obj_85_beta_0_to_fp16 = const()[name = tensor("obj_85_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(193769856)))]; + tensor obj_85_epsilon_0_to_fp16 = const()[name = tensor("obj_85_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_85_cast_fp16 = batch_norm(beta = obj_85_beta_0_to_fp16, epsilon = obj_85_epsilon_0_to_fp16, gamma = obj_85_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_37_cast_fp16)[name = tensor("obj_85_cast_fp16")]; + tensor var_1426 = const()[name = tensor("op_1426"), val = tensor([1, 1])]; + tensor var_1428 = const()[name = tensor("op_1428"), val = tensor([1, 1])]; + tensor query_25_pad_type_0 = const()[name = tensor("query_25_pad_type_0"), val = tensor("custom")]; + tensor query_25_pad_0 = const()[name = tensor("query_25_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(193771456)))]; + tensor layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(194951168)))]; + tensor query_25_cast_fp16 = conv(bias = layers_6_self_attn_q_proj_bias_to_fp16, dilations = var_1428, groups = var_1391, pad = query_25_pad_0, pad_type = query_25_pad_type_0, strides = var_1426, weight = layers_6_self_attn_q_proj_weight_to_fp16, x = obj_85_cast_fp16)[name = tensor("query_25_cast_fp16")]; + tensor var_1432 = const()[name = tensor("op_1432"), val = tensor([1, 1])]; + tensor var_1434 = const()[name = tensor("op_1434"), val = tensor([1, 1])]; + tensor current_key_13_pad_type_0 = const()[name = tensor("current_key_13_pad_type_0"), val = tensor("custom")]; + tensor current_key_13_pad_0 = const()[name = tensor("current_key_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(194952768)))]; + tensor current_key_13_cast_fp16 = conv(dilations = var_1434, groups = var_1391, pad = current_key_13_pad_0, pad_type = current_key_13_pad_type_0, strides = var_1432, weight = layers_6_self_attn_k_proj_weight_to_fp16, x = obj_85_cast_fp16)[name = tensor("current_key_13_cast_fp16")]; + tensor var_1439 = const()[name = tensor("op_1439"), val = tensor([1, 1])]; + tensor var_1441 = const()[name = tensor("op_1441"), val = tensor([1, 1])]; + tensor current_value_13_pad_type_0 = const()[name = tensor("current_value_13_pad_type_0"), val = tensor("custom")]; + tensor current_value_13_pad_0 = const()[name = tensor("current_value_13_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(196132480)))]; + tensor layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197312192)))]; + tensor current_value_13_cast_fp16 = conv(bias = layers_6_self_attn_v_proj_bias_to_fp16, dilations = var_1441, groups = var_1391, pad = current_value_13_pad_0, pad_type = current_value_13_pad_type_0, strides = var_1439, weight = layers_6_self_attn_v_proj_weight_to_fp16, x = obj_85_cast_fp16)[name = tensor("current_value_13_cast_fp16")]; + tensor var_1448_cast_fp16 = mul(x = current_key_13_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1448_cast_fp16")]; + tensor var_1450_cast_fp16 = mul(x = var_63_cast_fp16_6, y = var_161_cast_fp16)[name = tensor("op_1450_cast_fp16")]; + tensor key_25_cast_fp16 = add(x = var_1448_cast_fp16, y = var_1450_cast_fp16)[name = tensor("key_25_cast_fp16")]; + tensor var_1452_cast_fp16 = mul(x = current_value_13_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1452_cast_fp16")]; + tensor var_1454_cast_fp16 = mul(x = var_78_cast_fp16_6, y = var_161_cast_fp16)[name = tensor("op_1454_cast_fp16")]; + tensor value_25_cast_fp16 = add(x = var_1452_cast_fp16, y = var_1454_cast_fp16)[name = tensor("value_25_cast_fp16")]; + tensor var_1457 = const()[name = tensor("op_1457"), val = tensor([1, 12, 64, -1])]; + tensor var_1458_cast_fp16 = reshape(shape = var_1457, x = query_25_cast_fp16)[name = tensor("op_1458_cast_fp16")]; + tensor var_1459_to_fp16 = const()[name = tensor("op_1459_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1460_cast_fp16 = mul(x = var_1458_cast_fp16, y = var_1459_to_fp16)[name = tensor("op_1460_cast_fp16")]; + tensor var_1461 = const()[name = tensor("op_1461"), val = tensor([1, 12, 64, -1])]; + tensor var_1462_cast_fp16 = reshape(shape = var_1461, x = key_25_cast_fp16)[name = tensor("op_1462_cast_fp16")]; + tensor mh_w_37_transpose_x_0 = const()[name = tensor("mh_w_37_transpose_x_0"), val = tensor(true)]; + tensor mh_w_37_transpose_y_0 = const()[name = tensor("mh_w_37_transpose_y_0"), val = tensor(false)]; + tensor mh_w_37_cast_fp16 = matmul(transpose_x = mh_w_37_transpose_x_0, transpose_y = mh_w_37_transpose_y_0, x = var_1460_cast_fp16, y = var_1462_cast_fp16)[name = tensor("mh_w_37_cast_fp16")]; + tensor mh_w_39_cast_fp16 = add(x = mh_w_37_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_39_cast_fp16")]; + tensor var_1470_cast_fp16 = softmax(axis = var_1384, x = mh_w_39_cast_fp16)[name = tensor("op_1470_cast_fp16")]; + tensor var_1471 = const()[name = tensor("op_1471"), val = tensor([1, 12, 64, -1])]; + tensor var_1472_cast_fp16 = reshape(shape = var_1471, x = value_25_cast_fp16)[name = tensor("op_1472_cast_fp16")]; + tensor attn_25_transpose_x_0 = const()[name = tensor("attn_25_transpose_x_0"), val = tensor(false)]; + tensor attn_25_transpose_y_0 = const()[name = tensor("attn_25_transpose_y_0"), val = tensor(true)]; + tensor attn_25_cast_fp16 = matmul(transpose_x = attn_25_transpose_x_0, transpose_y = attn_25_transpose_y_0, x = var_1472_cast_fp16, y = var_1470_cast_fp16)[name = tensor("attn_25_cast_fp16")]; + tensor var_1475 = const()[name = tensor("op_1475"), val = tensor([1, 768, 1, -1])]; + tensor input_61_cast_fp16 = reshape(shape = var_1475, x = attn_25_cast_fp16)[name = tensor("input_61_cast_fp16")]; + tensor var_1479 = const()[name = tensor("op_1479"), val = tensor([1, 1])]; + tensor var_1481 = const()[name = tensor("op_1481"), val = tensor([1, 1])]; + tensor obj_91_pad_type_0 = const()[name = tensor("obj_91_pad_type_0"), val = tensor("custom")]; + tensor obj_91_pad_0 = const()[name = tensor("obj_91_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197313792)))]; + tensor layers_6_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198493504)))]; + tensor obj_91_cast_fp16 = conv(bias = layers_6_self_attn_o_proj_bias_to_fp16, dilations = var_1481, groups = var_1391, pad = obj_91_pad_0, pad_type = obj_91_pad_type_0, strides = var_1479, weight = layers_6_self_attn_o_proj_weight_to_fp16, x = input_61_cast_fp16)[name = tensor("obj_91_cast_fp16")]; + tensor inputs_39_cast_fp16 = add(x = inputs_37_cast_fp16, y = obj_91_cast_fp16)[name = tensor("inputs_39_cast_fp16")]; + tensor var_1491 = const()[name = tensor("op_1491"), val = tensor([1])]; + tensor channels_mean_39_cast_fp16 = reduce_mean(axes = var_1491, keep_dims = var_1392, x = inputs_39_cast_fp16)[name = tensor("channels_mean_39_cast_fp16")]; + tensor zero_mean_39_cast_fp16 = sub(x = inputs_39_cast_fp16, y = channels_mean_39_cast_fp16)[name = tensor("zero_mean_39_cast_fp16")]; + tensor zero_mean_sq_39_cast_fp16 = mul(x = zero_mean_39_cast_fp16, y = zero_mean_39_cast_fp16)[name = tensor("zero_mean_sq_39_cast_fp16")]; + tensor var_1495 = const()[name = tensor("op_1495"), val = tensor([1])]; + tensor var_1496_cast_fp16 = reduce_mean(axes = var_1495, keep_dims = var_1392, x = zero_mean_sq_39_cast_fp16)[name = tensor("op_1496_cast_fp16")]; + tensor var_1497_to_fp16 = const()[name = tensor("op_1497_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1498_cast_fp16 = add(x = var_1496_cast_fp16, y = var_1497_to_fp16)[name = tensor("op_1498_cast_fp16")]; + tensor denom_39_epsilon_0_to_fp16 = const()[name = tensor("denom_39_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_39_cast_fp16 = rsqrt(epsilon = denom_39_epsilon_0_to_fp16, x = var_1498_cast_fp16)[name = tensor("denom_39_cast_fp16")]; + tensor out_39_cast_fp16 = mul(x = zero_mean_39_cast_fp16, y = denom_39_cast_fp16)[name = tensor("out_39_cast_fp16")]; + tensor obj_93_gamma_0_to_fp16 = const()[name = tensor("obj_93_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198495104)))]; + tensor obj_93_beta_0_to_fp16 = const()[name = tensor("obj_93_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198496704)))]; + tensor obj_93_epsilon_0_to_fp16 = const()[name = tensor("obj_93_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_93_cast_fp16 = batch_norm(beta = obj_93_beta_0_to_fp16, epsilon = obj_93_epsilon_0_to_fp16, gamma = obj_93_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_39_cast_fp16)[name = tensor("obj_93_cast_fp16")]; + tensor var_1513 = const()[name = tensor("op_1513"), val = tensor([1, 1])]; + tensor var_1515 = const()[name = tensor("op_1515"), val = tensor([1, 1])]; + tensor query_27_pad_type_0 = const()[name = tensor("query_27_pad_type_0"), val = tensor("custom")]; + tensor query_27_pad_0 = const()[name = tensor("query_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_6_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198498304)))]; + tensor layers_6_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_6_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199678016)))]; + tensor query_27_cast_fp16 = conv(bias = layers_6_encoder_attn_q_proj_bias_to_fp16, dilations = var_1515, groups = var_1391, pad = query_27_pad_0, pad_type = query_27_pad_type_0, strides = var_1513, weight = layers_6_encoder_attn_q_proj_weight_to_fp16, x = obj_93_cast_fp16)[name = tensor("query_27_cast_fp16")]; + tensor var_1519 = const()[name = tensor("op_1519"), val = tensor([1, 1])]; + tensor var_1521 = const()[name = tensor("op_1521"), val = tensor([1, 1])]; + tensor key_27_pad_type_0 = const()[name = tensor("key_27_pad_type_0"), val = tensor("custom")]; + tensor key_27_pad_0 = const()[name = tensor("key_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_6_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199679616)))]; + tensor key_27_cast_fp16 = conv(dilations = var_1521, groups = var_1391, pad = key_27_pad_0, pad_type = key_27_pad_type_0, strides = var_1519, weight = layers_6_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_27_cast_fp16")]; + tensor var_1526 = const()[name = tensor("op_1526"), val = tensor([1, 1])]; + tensor var_1528 = const()[name = tensor("op_1528"), val = tensor([1, 1])]; + tensor value_27_pad_type_0 = const()[name = tensor("value_27_pad_type_0"), val = tensor("custom")]; + tensor value_27_pad_0 = const()[name = tensor("value_27_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_6_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200859328)))]; + tensor layers_6_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_6_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202039040)))]; + tensor value_27_cast_fp16 = conv(bias = layers_6_encoder_attn_v_proj_bias_to_fp16, dilations = var_1528, groups = var_1391, pad = value_27_pad_0, pad_type = value_27_pad_type_0, strides = var_1526, weight = layers_6_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_27_cast_fp16")]; + tensor var_1532 = const()[name = tensor("op_1532"), val = tensor([1, 12, 64, -1])]; + tensor var_1533_cast_fp16 = reshape(shape = var_1532, x = query_27_cast_fp16)[name = tensor("op_1533_cast_fp16")]; + tensor var_1534_to_fp16 = const()[name = tensor("op_1534_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1535_cast_fp16 = mul(x = var_1533_cast_fp16, y = var_1534_to_fp16)[name = tensor("op_1535_cast_fp16")]; + tensor var_1536 = const()[name = tensor("op_1536"), val = tensor([1, 12, 64, -1])]; + tensor var_1537_cast_fp16 = reshape(shape = var_1536, x = key_27_cast_fp16)[name = tensor("op_1537_cast_fp16")]; + tensor mh_w_41_transpose_x_0 = const()[name = tensor("mh_w_41_transpose_x_0"), val = tensor(true)]; + tensor mh_w_41_transpose_y_0 = const()[name = tensor("mh_w_41_transpose_y_0"), val = tensor(false)]; + tensor mh_w_41_cast_fp16 = matmul(transpose_x = mh_w_41_transpose_x_0, transpose_y = mh_w_41_transpose_y_0, x = var_1535_cast_fp16, y = var_1537_cast_fp16)[name = tensor("mh_w_41_cast_fp16")]; + tensor obj_97_cast_fp16 = softmax(axis = var_1384, x = mh_w_41_cast_fp16)[name = tensor("obj_97_cast_fp16")]; + tensor var_1541 = const()[name = tensor("op_1541"), val = tensor([1, 12, 64, -1])]; + tensor var_1542_cast_fp16 = reshape(shape = var_1541, x = value_27_cast_fp16)[name = tensor("op_1542_cast_fp16")]; + tensor attn_27_transpose_x_0 = const()[name = tensor("attn_27_transpose_x_0"), val = tensor(false)]; + tensor attn_27_transpose_y_0 = const()[name = tensor("attn_27_transpose_y_0"), val = tensor(true)]; + tensor attn_27_cast_fp16 = matmul(transpose_x = attn_27_transpose_x_0, transpose_y = attn_27_transpose_y_0, x = var_1542_cast_fp16, y = obj_97_cast_fp16)[name = tensor("attn_27_cast_fp16")]; + tensor var_1545 = const()[name = tensor("op_1545"), val = tensor([1, 768, 1, -1])]; + tensor input_63_cast_fp16 = reshape(shape = var_1545, x = attn_27_cast_fp16)[name = tensor("input_63_cast_fp16")]; + tensor var_1549 = const()[name = tensor("op_1549"), val = tensor([1, 1])]; + tensor var_1551 = const()[name = tensor("op_1551"), val = tensor([1, 1])]; + tensor obj_95_pad_type_0 = const()[name = tensor("obj_95_pad_type_0"), val = tensor("custom")]; + tensor obj_95_pad_0 = const()[name = tensor("obj_95_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_6_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202040640)))]; + tensor layers_6_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_6_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203220352)))]; + tensor obj_95_cast_fp16 = conv(bias = layers_6_encoder_attn_o_proj_bias_to_fp16, dilations = var_1551, groups = var_1391, pad = obj_95_pad_0, pad_type = obj_95_pad_type_0, strides = var_1549, weight = layers_6_encoder_attn_o_proj_weight_to_fp16, x = input_63_cast_fp16)[name = tensor("obj_95_cast_fp16")]; + tensor inputs_41_cast_fp16 = add(x = inputs_39_cast_fp16, y = obj_95_cast_fp16)[name = tensor("inputs_41_cast_fp16")]; + tensor var_1557 = const()[name = tensor("op_1557"), val = tensor([1])]; + tensor channels_mean_41_cast_fp16 = reduce_mean(axes = var_1557, keep_dims = var_1392, x = inputs_41_cast_fp16)[name = tensor("channels_mean_41_cast_fp16")]; + tensor zero_mean_41_cast_fp16 = sub(x = inputs_41_cast_fp16, y = channels_mean_41_cast_fp16)[name = tensor("zero_mean_41_cast_fp16")]; + tensor zero_mean_sq_41_cast_fp16 = mul(x = zero_mean_41_cast_fp16, y = zero_mean_41_cast_fp16)[name = tensor("zero_mean_sq_41_cast_fp16")]; + tensor var_1561 = const()[name = tensor("op_1561"), val = tensor([1])]; + tensor var_1562_cast_fp16 = reduce_mean(axes = var_1561, keep_dims = var_1392, x = zero_mean_sq_41_cast_fp16)[name = tensor("op_1562_cast_fp16")]; + tensor var_1563_to_fp16 = const()[name = tensor("op_1563_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1564_cast_fp16 = add(x = var_1562_cast_fp16, y = var_1563_to_fp16)[name = tensor("op_1564_cast_fp16")]; + tensor denom_41_epsilon_0_to_fp16 = const()[name = tensor("denom_41_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_41_cast_fp16 = rsqrt(epsilon = denom_41_epsilon_0_to_fp16, x = var_1564_cast_fp16)[name = tensor("denom_41_cast_fp16")]; + tensor out_41_cast_fp16 = mul(x = zero_mean_41_cast_fp16, y = denom_41_cast_fp16)[name = tensor("out_41_cast_fp16")]; + tensor input_65_gamma_0_to_fp16 = const()[name = tensor("input_65_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203221952)))]; + tensor input_65_beta_0_to_fp16 = const()[name = tensor("input_65_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203223552)))]; + tensor input_65_epsilon_0_to_fp16 = const()[name = tensor("input_65_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_65_cast_fp16 = batch_norm(beta = input_65_beta_0_to_fp16, epsilon = input_65_epsilon_0_to_fp16, gamma = input_65_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_41_cast_fp16)[name = tensor("input_65_cast_fp16")]; + tensor var_1575 = const()[name = tensor("op_1575"), val = tensor([1, 1])]; + tensor var_1577 = const()[name = tensor("op_1577"), val = tensor([1, 1])]; + tensor input_67_pad_type_0 = const()[name = tensor("input_67_pad_type_0"), val = tensor("custom")]; + tensor input_67_pad_0 = const()[name = tensor("input_67_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_fc1_weight_to_fp16 = const()[name = tensor("layers_6_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203225152)))]; + tensor layers_6_fc1_bias_to_fp16 = const()[name = tensor("layers_6_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(207943808)))]; + tensor input_67_cast_fp16 = conv(bias = layers_6_fc1_bias_to_fp16, dilations = var_1577, groups = var_1391, pad = input_67_pad_0, pad_type = input_67_pad_type_0, strides = var_1575, weight = layers_6_fc1_weight_to_fp16, x = input_65_cast_fp16)[name = tensor("input_67_cast_fp16")]; + tensor input_69_mode_0 = const()[name = tensor("input_69_mode_0"), val = tensor("EXACT")]; + tensor input_69_cast_fp16 = gelu(mode = input_69_mode_0, x = input_67_cast_fp16)[name = tensor("input_69_cast_fp16")]; + tensor var_1583 = const()[name = tensor("op_1583"), val = tensor([1, 1])]; + tensor var_1585 = const()[name = tensor("op_1585"), val = tensor([1, 1])]; + tensor hidden_states_15_pad_type_0 = const()[name = tensor("hidden_states_15_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_15_pad_0 = const()[name = tensor("hidden_states_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_6_fc2_weight_to_fp16 = const()[name = tensor("layers_6_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(207950016)))]; + tensor layers_6_fc2_bias_to_fp16 = const()[name = tensor("layers_6_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(212668672)))]; + tensor hidden_states_15_cast_fp16 = conv(bias = layers_6_fc2_bias_to_fp16, dilations = var_1585, groups = var_1391, pad = hidden_states_15_pad_0, pad_type = hidden_states_15_pad_type_0, strides = var_1583, weight = layers_6_fc2_weight_to_fp16, x = input_69_cast_fp16)[name = tensor("hidden_states_15_cast_fp16")]; + tensor inputs_43_cast_fp16 = add(x = inputs_41_cast_fp16, y = hidden_states_15_cast_fp16)[name = tensor("inputs_43_cast_fp16")]; + tensor var_1598 = const()[name = tensor("op_1598"), val = tensor(3)]; + tensor var_1605 = const()[name = tensor("op_1605"), val = tensor(1)]; + tensor var_1606 = const()[name = tensor("op_1606"), val = tensor(true)]; + tensor var_1618 = const()[name = tensor("op_1618"), val = tensor([1])]; + tensor channels_mean_43_cast_fp16 = reduce_mean(axes = var_1618, keep_dims = var_1606, x = inputs_43_cast_fp16)[name = tensor("channels_mean_43_cast_fp16")]; + tensor zero_mean_43_cast_fp16 = sub(x = inputs_43_cast_fp16, y = channels_mean_43_cast_fp16)[name = tensor("zero_mean_43_cast_fp16")]; + tensor zero_mean_sq_43_cast_fp16 = mul(x = zero_mean_43_cast_fp16, y = zero_mean_43_cast_fp16)[name = tensor("zero_mean_sq_43_cast_fp16")]; + tensor var_1622 = const()[name = tensor("op_1622"), val = tensor([1])]; + tensor var_1623_cast_fp16 = reduce_mean(axes = var_1622, keep_dims = var_1606, x = zero_mean_sq_43_cast_fp16)[name = tensor("op_1623_cast_fp16")]; + tensor var_1624_to_fp16 = const()[name = tensor("op_1624_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1625_cast_fp16 = add(x = var_1623_cast_fp16, y = var_1624_to_fp16)[name = tensor("op_1625_cast_fp16")]; + tensor denom_43_epsilon_0_to_fp16 = const()[name = tensor("denom_43_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_43_cast_fp16 = rsqrt(epsilon = denom_43_epsilon_0_to_fp16, x = var_1625_cast_fp16)[name = tensor("denom_43_cast_fp16")]; + tensor out_43_cast_fp16 = mul(x = zero_mean_43_cast_fp16, y = denom_43_cast_fp16)[name = tensor("out_43_cast_fp16")]; + tensor obj_99_gamma_0_to_fp16 = const()[name = tensor("obj_99_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(212670272)))]; + tensor obj_99_beta_0_to_fp16 = const()[name = tensor("obj_99_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(212671872)))]; + tensor obj_99_epsilon_0_to_fp16 = const()[name = tensor("obj_99_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_99_cast_fp16 = batch_norm(beta = obj_99_beta_0_to_fp16, epsilon = obj_99_epsilon_0_to_fp16, gamma = obj_99_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_43_cast_fp16)[name = tensor("obj_99_cast_fp16")]; + tensor var_1640 = const()[name = tensor("op_1640"), val = tensor([1, 1])]; + tensor var_1642 = const()[name = tensor("op_1642"), val = tensor([1, 1])]; + tensor query_29_pad_type_0 = const()[name = tensor("query_29_pad_type_0"), val = tensor("custom")]; + tensor query_29_pad_0 = const()[name = tensor("query_29_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(212673472)))]; + tensor layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(213853184)))]; + tensor query_29_cast_fp16 = conv(bias = layers_7_self_attn_q_proj_bias_to_fp16, dilations = var_1642, groups = var_1605, pad = query_29_pad_0, pad_type = query_29_pad_type_0, strides = var_1640, weight = layers_7_self_attn_q_proj_weight_to_fp16, x = obj_99_cast_fp16)[name = tensor("query_29_cast_fp16")]; + tensor var_1646 = const()[name = tensor("op_1646"), val = tensor([1, 1])]; + tensor var_1648 = const()[name = tensor("op_1648"), val = tensor([1, 1])]; + tensor current_key_15_pad_type_0 = const()[name = tensor("current_key_15_pad_type_0"), val = tensor("custom")]; + tensor current_key_15_pad_0 = const()[name = tensor("current_key_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(213854784)))]; + tensor current_key_15_cast_fp16 = conv(dilations = var_1648, groups = var_1605, pad = current_key_15_pad_0, pad_type = current_key_15_pad_type_0, strides = var_1646, weight = layers_7_self_attn_k_proj_weight_to_fp16, x = obj_99_cast_fp16)[name = tensor("current_key_15_cast_fp16")]; + tensor var_1653 = const()[name = tensor("op_1653"), val = tensor([1, 1])]; + tensor var_1655 = const()[name = tensor("op_1655"), val = tensor([1, 1])]; + tensor current_value_15_pad_type_0 = const()[name = tensor("current_value_15_pad_type_0"), val = tensor("custom")]; + tensor current_value_15_pad_0 = const()[name = tensor("current_value_15_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215034496)))]; + tensor layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216214208)))]; + tensor current_value_15_cast_fp16 = conv(bias = layers_7_self_attn_v_proj_bias_to_fp16, dilations = var_1655, groups = var_1605, pad = current_value_15_pad_0, pad_type = current_value_15_pad_type_0, strides = var_1653, weight = layers_7_self_attn_v_proj_weight_to_fp16, x = obj_99_cast_fp16)[name = tensor("current_value_15_cast_fp16")]; + tensor var_1662_cast_fp16 = mul(x = current_key_15_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1662_cast_fp16")]; + tensor var_1664_cast_fp16 = mul(x = var_63_cast_fp16_7, y = var_161_cast_fp16)[name = tensor("op_1664_cast_fp16")]; + tensor key_29_cast_fp16 = add(x = var_1662_cast_fp16, y = var_1664_cast_fp16)[name = tensor("key_29_cast_fp16")]; + tensor var_1666_cast_fp16 = mul(x = current_value_15_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1666_cast_fp16")]; + tensor var_1668_cast_fp16 = mul(x = var_78_cast_fp16_7, y = var_161_cast_fp16)[name = tensor("op_1668_cast_fp16")]; + tensor value_29_cast_fp16 = add(x = var_1666_cast_fp16, y = var_1668_cast_fp16)[name = tensor("value_29_cast_fp16")]; + tensor var_1671 = const()[name = tensor("op_1671"), val = tensor([1, 12, 64, -1])]; + tensor var_1672_cast_fp16 = reshape(shape = var_1671, x = query_29_cast_fp16)[name = tensor("op_1672_cast_fp16")]; + tensor var_1673_to_fp16 = const()[name = tensor("op_1673_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1674_cast_fp16 = mul(x = var_1672_cast_fp16, y = var_1673_to_fp16)[name = tensor("op_1674_cast_fp16")]; + tensor var_1675 = const()[name = tensor("op_1675"), val = tensor([1, 12, 64, -1])]; + tensor var_1676_cast_fp16 = reshape(shape = var_1675, x = key_29_cast_fp16)[name = tensor("op_1676_cast_fp16")]; + tensor mh_w_43_transpose_x_0 = const()[name = tensor("mh_w_43_transpose_x_0"), val = tensor(true)]; + tensor mh_w_43_transpose_y_0 = const()[name = tensor("mh_w_43_transpose_y_0"), val = tensor(false)]; + tensor mh_w_43_cast_fp16 = matmul(transpose_x = mh_w_43_transpose_x_0, transpose_y = mh_w_43_transpose_y_0, x = var_1674_cast_fp16, y = var_1676_cast_fp16)[name = tensor("mh_w_43_cast_fp16")]; + tensor mh_w_45_cast_fp16 = add(x = mh_w_43_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_45_cast_fp16")]; + tensor var_1684_cast_fp16 = softmax(axis = var_1598, x = mh_w_45_cast_fp16)[name = tensor("op_1684_cast_fp16")]; + tensor var_1685 = const()[name = tensor("op_1685"), val = tensor([1, 12, 64, -1])]; + tensor var_1686_cast_fp16 = reshape(shape = var_1685, x = value_29_cast_fp16)[name = tensor("op_1686_cast_fp16")]; + tensor attn_29_transpose_x_0 = const()[name = tensor("attn_29_transpose_x_0"), val = tensor(false)]; + tensor attn_29_transpose_y_0 = const()[name = tensor("attn_29_transpose_y_0"), val = tensor(true)]; + tensor attn_29_cast_fp16 = matmul(transpose_x = attn_29_transpose_x_0, transpose_y = attn_29_transpose_y_0, x = var_1686_cast_fp16, y = var_1684_cast_fp16)[name = tensor("attn_29_cast_fp16")]; + tensor var_1689 = const()[name = tensor("op_1689"), val = tensor([1, 768, 1, -1])]; + tensor input_71_cast_fp16 = reshape(shape = var_1689, x = attn_29_cast_fp16)[name = tensor("input_71_cast_fp16")]; + tensor var_1693 = const()[name = tensor("op_1693"), val = tensor([1, 1])]; + tensor var_1695 = const()[name = tensor("op_1695"), val = tensor([1, 1])]; + tensor obj_105_pad_type_0 = const()[name = tensor("obj_105_pad_type_0"), val = tensor("custom")]; + tensor obj_105_pad_0 = const()[name = tensor("obj_105_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216215808)))]; + tensor layers_7_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217395520)))]; + tensor obj_105_cast_fp16 = conv(bias = layers_7_self_attn_o_proj_bias_to_fp16, dilations = var_1695, groups = var_1605, pad = obj_105_pad_0, pad_type = obj_105_pad_type_0, strides = var_1693, weight = layers_7_self_attn_o_proj_weight_to_fp16, x = input_71_cast_fp16)[name = tensor("obj_105_cast_fp16")]; + tensor inputs_45_cast_fp16 = add(x = inputs_43_cast_fp16, y = obj_105_cast_fp16)[name = tensor("inputs_45_cast_fp16")]; + tensor var_1705 = const()[name = tensor("op_1705"), val = tensor([1])]; + tensor channels_mean_45_cast_fp16 = reduce_mean(axes = var_1705, keep_dims = var_1606, x = inputs_45_cast_fp16)[name = tensor("channels_mean_45_cast_fp16")]; + tensor zero_mean_45_cast_fp16 = sub(x = inputs_45_cast_fp16, y = channels_mean_45_cast_fp16)[name = tensor("zero_mean_45_cast_fp16")]; + tensor zero_mean_sq_45_cast_fp16 = mul(x = zero_mean_45_cast_fp16, y = zero_mean_45_cast_fp16)[name = tensor("zero_mean_sq_45_cast_fp16")]; + tensor var_1709 = const()[name = tensor("op_1709"), val = tensor([1])]; + tensor var_1710_cast_fp16 = reduce_mean(axes = var_1709, keep_dims = var_1606, x = zero_mean_sq_45_cast_fp16)[name = tensor("op_1710_cast_fp16")]; + tensor var_1711_to_fp16 = const()[name = tensor("op_1711_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1712_cast_fp16 = add(x = var_1710_cast_fp16, y = var_1711_to_fp16)[name = tensor("op_1712_cast_fp16")]; + tensor denom_45_epsilon_0_to_fp16 = const()[name = tensor("denom_45_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_45_cast_fp16 = rsqrt(epsilon = denom_45_epsilon_0_to_fp16, x = var_1712_cast_fp16)[name = tensor("denom_45_cast_fp16")]; + tensor out_45_cast_fp16 = mul(x = zero_mean_45_cast_fp16, y = denom_45_cast_fp16)[name = tensor("out_45_cast_fp16")]; + tensor obj_107_gamma_0_to_fp16 = const()[name = tensor("obj_107_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217397120)))]; + tensor obj_107_beta_0_to_fp16 = const()[name = tensor("obj_107_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217398720)))]; + tensor obj_107_epsilon_0_to_fp16 = const()[name = tensor("obj_107_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_107_cast_fp16 = batch_norm(beta = obj_107_beta_0_to_fp16, epsilon = obj_107_epsilon_0_to_fp16, gamma = obj_107_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_45_cast_fp16)[name = tensor("obj_107_cast_fp16")]; + tensor var_1727 = const()[name = tensor("op_1727"), val = tensor([1, 1])]; + tensor var_1729 = const()[name = tensor("op_1729"), val = tensor([1, 1])]; + tensor query_31_pad_type_0 = const()[name = tensor("query_31_pad_type_0"), val = tensor("custom")]; + tensor query_31_pad_0 = const()[name = tensor("query_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_7_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217400320)))]; + tensor layers_7_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_7_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(218580032)))]; + tensor query_31_cast_fp16 = conv(bias = layers_7_encoder_attn_q_proj_bias_to_fp16, dilations = var_1729, groups = var_1605, pad = query_31_pad_0, pad_type = query_31_pad_type_0, strides = var_1727, weight = layers_7_encoder_attn_q_proj_weight_to_fp16, x = obj_107_cast_fp16)[name = tensor("query_31_cast_fp16")]; + tensor var_1733 = const()[name = tensor("op_1733"), val = tensor([1, 1])]; + tensor var_1735 = const()[name = tensor("op_1735"), val = tensor([1, 1])]; + tensor key_31_pad_type_0 = const()[name = tensor("key_31_pad_type_0"), val = tensor("custom")]; + tensor key_31_pad_0 = const()[name = tensor("key_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_7_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(218581632)))]; + tensor key_31_cast_fp16 = conv(dilations = var_1735, groups = var_1605, pad = key_31_pad_0, pad_type = key_31_pad_type_0, strides = var_1733, weight = layers_7_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_31_cast_fp16")]; + tensor var_1740 = const()[name = tensor("op_1740"), val = tensor([1, 1])]; + tensor var_1742 = const()[name = tensor("op_1742"), val = tensor([1, 1])]; + tensor value_31_pad_type_0 = const()[name = tensor("value_31_pad_type_0"), val = tensor("custom")]; + tensor value_31_pad_0 = const()[name = tensor("value_31_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_7_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(219761344)))]; + tensor layers_7_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_7_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(220941056)))]; + tensor value_31_cast_fp16 = conv(bias = layers_7_encoder_attn_v_proj_bias_to_fp16, dilations = var_1742, groups = var_1605, pad = value_31_pad_0, pad_type = value_31_pad_type_0, strides = var_1740, weight = layers_7_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_31_cast_fp16")]; + tensor var_1746 = const()[name = tensor("op_1746"), val = tensor([1, 12, 64, -1])]; + tensor var_1747_cast_fp16 = reshape(shape = var_1746, x = query_31_cast_fp16)[name = tensor("op_1747_cast_fp16")]; + tensor var_1748_to_fp16 = const()[name = tensor("op_1748_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1749_cast_fp16 = mul(x = var_1747_cast_fp16, y = var_1748_to_fp16)[name = tensor("op_1749_cast_fp16")]; + tensor var_1750 = const()[name = tensor("op_1750"), val = tensor([1, 12, 64, -1])]; + tensor var_1751_cast_fp16 = reshape(shape = var_1750, x = key_31_cast_fp16)[name = tensor("op_1751_cast_fp16")]; + tensor mh_w_47_transpose_x_0 = const()[name = tensor("mh_w_47_transpose_x_0"), val = tensor(true)]; + tensor mh_w_47_transpose_y_0 = const()[name = tensor("mh_w_47_transpose_y_0"), val = tensor(false)]; + tensor mh_w_47_cast_fp16 = matmul(transpose_x = mh_w_47_transpose_x_0, transpose_y = mh_w_47_transpose_y_0, x = var_1749_cast_fp16, y = var_1751_cast_fp16)[name = tensor("mh_w_47_cast_fp16")]; + tensor obj_111_cast_fp16 = softmax(axis = var_1598, x = mh_w_47_cast_fp16)[name = tensor("obj_111_cast_fp16")]; + tensor var_1755 = const()[name = tensor("op_1755"), val = tensor([1, 12, 64, -1])]; + tensor var_1756_cast_fp16 = reshape(shape = var_1755, x = value_31_cast_fp16)[name = tensor("op_1756_cast_fp16")]; + tensor attn_31_transpose_x_0 = const()[name = tensor("attn_31_transpose_x_0"), val = tensor(false)]; + tensor attn_31_transpose_y_0 = const()[name = tensor("attn_31_transpose_y_0"), val = tensor(true)]; + tensor attn_31_cast_fp16 = matmul(transpose_x = attn_31_transpose_x_0, transpose_y = attn_31_transpose_y_0, x = var_1756_cast_fp16, y = obj_111_cast_fp16)[name = tensor("attn_31_cast_fp16")]; + tensor var_1759 = const()[name = tensor("op_1759"), val = tensor([1, 768, 1, -1])]; + tensor input_73_cast_fp16 = reshape(shape = var_1759, x = attn_31_cast_fp16)[name = tensor("input_73_cast_fp16")]; + tensor var_1763 = const()[name = tensor("op_1763"), val = tensor([1, 1])]; + tensor var_1765 = const()[name = tensor("op_1765"), val = tensor([1, 1])]; + tensor obj_109_pad_type_0 = const()[name = tensor("obj_109_pad_type_0"), val = tensor("custom")]; + tensor obj_109_pad_0 = const()[name = tensor("obj_109_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_7_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(220942656)))]; + tensor layers_7_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_7_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222122368)))]; + tensor obj_109_cast_fp16 = conv(bias = layers_7_encoder_attn_o_proj_bias_to_fp16, dilations = var_1765, groups = var_1605, pad = obj_109_pad_0, pad_type = obj_109_pad_type_0, strides = var_1763, weight = layers_7_encoder_attn_o_proj_weight_to_fp16, x = input_73_cast_fp16)[name = tensor("obj_109_cast_fp16")]; + tensor inputs_47_cast_fp16 = add(x = inputs_45_cast_fp16, y = obj_109_cast_fp16)[name = tensor("inputs_47_cast_fp16")]; + tensor var_1771 = const()[name = tensor("op_1771"), val = tensor([1])]; + tensor channels_mean_47_cast_fp16 = reduce_mean(axes = var_1771, keep_dims = var_1606, x = inputs_47_cast_fp16)[name = tensor("channels_mean_47_cast_fp16")]; + tensor zero_mean_47_cast_fp16 = sub(x = inputs_47_cast_fp16, y = channels_mean_47_cast_fp16)[name = tensor("zero_mean_47_cast_fp16")]; + tensor zero_mean_sq_47_cast_fp16 = mul(x = zero_mean_47_cast_fp16, y = zero_mean_47_cast_fp16)[name = tensor("zero_mean_sq_47_cast_fp16")]; + tensor var_1775 = const()[name = tensor("op_1775"), val = tensor([1])]; + tensor var_1776_cast_fp16 = reduce_mean(axes = var_1775, keep_dims = var_1606, x = zero_mean_sq_47_cast_fp16)[name = tensor("op_1776_cast_fp16")]; + tensor var_1777_to_fp16 = const()[name = tensor("op_1777_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1778_cast_fp16 = add(x = var_1776_cast_fp16, y = var_1777_to_fp16)[name = tensor("op_1778_cast_fp16")]; + tensor denom_47_epsilon_0_to_fp16 = const()[name = tensor("denom_47_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_47_cast_fp16 = rsqrt(epsilon = denom_47_epsilon_0_to_fp16, x = var_1778_cast_fp16)[name = tensor("denom_47_cast_fp16")]; + tensor out_47_cast_fp16 = mul(x = zero_mean_47_cast_fp16, y = denom_47_cast_fp16)[name = tensor("out_47_cast_fp16")]; + tensor input_75_gamma_0_to_fp16 = const()[name = tensor("input_75_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222123968)))]; + tensor input_75_beta_0_to_fp16 = const()[name = tensor("input_75_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222125568)))]; + tensor input_75_epsilon_0_to_fp16 = const()[name = tensor("input_75_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_75_cast_fp16 = batch_norm(beta = input_75_beta_0_to_fp16, epsilon = input_75_epsilon_0_to_fp16, gamma = input_75_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_47_cast_fp16)[name = tensor("input_75_cast_fp16")]; + tensor var_1789 = const()[name = tensor("op_1789"), val = tensor([1, 1])]; + tensor var_1791 = const()[name = tensor("op_1791"), val = tensor([1, 1])]; + tensor input_77_pad_type_0 = const()[name = tensor("input_77_pad_type_0"), val = tensor("custom")]; + tensor input_77_pad_0 = const()[name = tensor("input_77_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_fc1_weight_to_fp16 = const()[name = tensor("layers_7_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222127168)))]; + tensor layers_7_fc1_bias_to_fp16 = const()[name = tensor("layers_7_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(226845824)))]; + tensor input_77_cast_fp16 = conv(bias = layers_7_fc1_bias_to_fp16, dilations = var_1791, groups = var_1605, pad = input_77_pad_0, pad_type = input_77_pad_type_0, strides = var_1789, weight = layers_7_fc1_weight_to_fp16, x = input_75_cast_fp16)[name = tensor("input_77_cast_fp16")]; + tensor input_79_mode_0 = const()[name = tensor("input_79_mode_0"), val = tensor("EXACT")]; + tensor input_79_cast_fp16 = gelu(mode = input_79_mode_0, x = input_77_cast_fp16)[name = tensor("input_79_cast_fp16")]; + tensor var_1797 = const()[name = tensor("op_1797"), val = tensor([1, 1])]; + tensor var_1799 = const()[name = tensor("op_1799"), val = tensor([1, 1])]; + tensor hidden_states_17_pad_type_0 = const()[name = tensor("hidden_states_17_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_17_pad_0 = const()[name = tensor("hidden_states_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_7_fc2_weight_to_fp16 = const()[name = tensor("layers_7_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(226852032)))]; + tensor layers_7_fc2_bias_to_fp16 = const()[name = tensor("layers_7_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231570688)))]; + tensor hidden_states_17_cast_fp16 = conv(bias = layers_7_fc2_bias_to_fp16, dilations = var_1799, groups = var_1605, pad = hidden_states_17_pad_0, pad_type = hidden_states_17_pad_type_0, strides = var_1797, weight = layers_7_fc2_weight_to_fp16, x = input_79_cast_fp16)[name = tensor("hidden_states_17_cast_fp16")]; + tensor inputs_49_cast_fp16 = add(x = inputs_47_cast_fp16, y = hidden_states_17_cast_fp16)[name = tensor("inputs_49_cast_fp16")]; + tensor var_1812 = const()[name = tensor("op_1812"), val = tensor(3)]; + tensor var_1819 = const()[name = tensor("op_1819"), val = tensor(1)]; + tensor var_1820 = const()[name = tensor("op_1820"), val = tensor(true)]; + tensor var_1832 = const()[name = tensor("op_1832"), val = tensor([1])]; + tensor channels_mean_49_cast_fp16 = reduce_mean(axes = var_1832, keep_dims = var_1820, x = inputs_49_cast_fp16)[name = tensor("channels_mean_49_cast_fp16")]; + tensor zero_mean_49_cast_fp16 = sub(x = inputs_49_cast_fp16, y = channels_mean_49_cast_fp16)[name = tensor("zero_mean_49_cast_fp16")]; + tensor zero_mean_sq_49_cast_fp16 = mul(x = zero_mean_49_cast_fp16, y = zero_mean_49_cast_fp16)[name = tensor("zero_mean_sq_49_cast_fp16")]; + tensor var_1836 = const()[name = tensor("op_1836"), val = tensor([1])]; + tensor var_1837_cast_fp16 = reduce_mean(axes = var_1836, keep_dims = var_1820, x = zero_mean_sq_49_cast_fp16)[name = tensor("op_1837_cast_fp16")]; + tensor var_1838_to_fp16 = const()[name = tensor("op_1838_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1839_cast_fp16 = add(x = var_1837_cast_fp16, y = var_1838_to_fp16)[name = tensor("op_1839_cast_fp16")]; + tensor denom_49_epsilon_0_to_fp16 = const()[name = tensor("denom_49_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_49_cast_fp16 = rsqrt(epsilon = denom_49_epsilon_0_to_fp16, x = var_1839_cast_fp16)[name = tensor("denom_49_cast_fp16")]; + tensor out_49_cast_fp16 = mul(x = zero_mean_49_cast_fp16, y = denom_49_cast_fp16)[name = tensor("out_49_cast_fp16")]; + tensor obj_113_gamma_0_to_fp16 = const()[name = tensor("obj_113_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231572288)))]; + tensor obj_113_beta_0_to_fp16 = const()[name = tensor("obj_113_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231573888)))]; + tensor obj_113_epsilon_0_to_fp16 = const()[name = tensor("obj_113_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_113_cast_fp16 = batch_norm(beta = obj_113_beta_0_to_fp16, epsilon = obj_113_epsilon_0_to_fp16, gamma = obj_113_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_49_cast_fp16)[name = tensor("obj_113_cast_fp16")]; + tensor var_1854 = const()[name = tensor("op_1854"), val = tensor([1, 1])]; + tensor var_1856 = const()[name = tensor("op_1856"), val = tensor([1, 1])]; + tensor query_33_pad_type_0 = const()[name = tensor("query_33_pad_type_0"), val = tensor("custom")]; + tensor query_33_pad_0 = const()[name = tensor("query_33_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231575488)))]; + tensor layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(232755200)))]; + tensor query_33_cast_fp16 = conv(bias = layers_8_self_attn_q_proj_bias_to_fp16, dilations = var_1856, groups = var_1819, pad = query_33_pad_0, pad_type = query_33_pad_type_0, strides = var_1854, weight = layers_8_self_attn_q_proj_weight_to_fp16, x = obj_113_cast_fp16)[name = tensor("query_33_cast_fp16")]; + tensor var_1860 = const()[name = tensor("op_1860"), val = tensor([1, 1])]; + tensor var_1862 = const()[name = tensor("op_1862"), val = tensor([1, 1])]; + tensor current_key_17_pad_type_0 = const()[name = tensor("current_key_17_pad_type_0"), val = tensor("custom")]; + tensor current_key_17_pad_0 = const()[name = tensor("current_key_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(232756800)))]; + tensor current_key_17_cast_fp16 = conv(dilations = var_1862, groups = var_1819, pad = current_key_17_pad_0, pad_type = current_key_17_pad_type_0, strides = var_1860, weight = layers_8_self_attn_k_proj_weight_to_fp16, x = obj_113_cast_fp16)[name = tensor("current_key_17_cast_fp16")]; + tensor var_1867 = const()[name = tensor("op_1867"), val = tensor([1, 1])]; + tensor var_1869 = const()[name = tensor("op_1869"), val = tensor([1, 1])]; + tensor current_value_17_pad_type_0 = const()[name = tensor("current_value_17_pad_type_0"), val = tensor("custom")]; + tensor current_value_17_pad_0 = const()[name = tensor("current_value_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233936512)))]; + tensor layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235116224)))]; + tensor current_value_17_cast_fp16 = conv(bias = layers_8_self_attn_v_proj_bias_to_fp16, dilations = var_1869, groups = var_1819, pad = current_value_17_pad_0, pad_type = current_value_17_pad_type_0, strides = var_1867, weight = layers_8_self_attn_v_proj_weight_to_fp16, x = obj_113_cast_fp16)[name = tensor("current_value_17_cast_fp16")]; + tensor var_1876_cast_fp16 = mul(x = current_key_17_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1876_cast_fp16")]; + tensor var_1878_cast_fp16 = mul(x = var_63_cast_fp16_8, y = var_161_cast_fp16)[name = tensor("op_1878_cast_fp16")]; + tensor key_33_cast_fp16 = add(x = var_1876_cast_fp16, y = var_1878_cast_fp16)[name = tensor("key_33_cast_fp16")]; + tensor var_1880_cast_fp16 = mul(x = current_value_17_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1880_cast_fp16")]; + tensor var_1882_cast_fp16 = mul(x = var_78_cast_fp16_8, y = var_161_cast_fp16)[name = tensor("op_1882_cast_fp16")]; + tensor value_33_cast_fp16 = add(x = var_1880_cast_fp16, y = var_1882_cast_fp16)[name = tensor("value_33_cast_fp16")]; + tensor var_1885 = const()[name = tensor("op_1885"), val = tensor([1, 12, 64, -1])]; + tensor var_1886_cast_fp16 = reshape(shape = var_1885, x = query_33_cast_fp16)[name = tensor("op_1886_cast_fp16")]; + tensor var_1887_to_fp16 = const()[name = tensor("op_1887_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1888_cast_fp16 = mul(x = var_1886_cast_fp16, y = var_1887_to_fp16)[name = tensor("op_1888_cast_fp16")]; + tensor var_1889 = const()[name = tensor("op_1889"), val = tensor([1, 12, 64, -1])]; + tensor var_1890_cast_fp16 = reshape(shape = var_1889, x = key_33_cast_fp16)[name = tensor("op_1890_cast_fp16")]; + tensor mh_w_49_transpose_x_0 = const()[name = tensor("mh_w_49_transpose_x_0"), val = tensor(true)]; + tensor mh_w_49_transpose_y_0 = const()[name = tensor("mh_w_49_transpose_y_0"), val = tensor(false)]; + tensor mh_w_49_cast_fp16 = matmul(transpose_x = mh_w_49_transpose_x_0, transpose_y = mh_w_49_transpose_y_0, x = var_1888_cast_fp16, y = var_1890_cast_fp16)[name = tensor("mh_w_49_cast_fp16")]; + tensor mh_w_51_cast_fp16 = add(x = mh_w_49_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_51_cast_fp16")]; + tensor var_1898_cast_fp16 = softmax(axis = var_1812, x = mh_w_51_cast_fp16)[name = tensor("op_1898_cast_fp16")]; + tensor var_1899 = const()[name = tensor("op_1899"), val = tensor([1, 12, 64, -1])]; + tensor var_1900_cast_fp16 = reshape(shape = var_1899, x = value_33_cast_fp16)[name = tensor("op_1900_cast_fp16")]; + tensor attn_33_transpose_x_0 = const()[name = tensor("attn_33_transpose_x_0"), val = tensor(false)]; + tensor attn_33_transpose_y_0 = const()[name = tensor("attn_33_transpose_y_0"), val = tensor(true)]; + tensor attn_33_cast_fp16 = matmul(transpose_x = attn_33_transpose_x_0, transpose_y = attn_33_transpose_y_0, x = var_1900_cast_fp16, y = var_1898_cast_fp16)[name = tensor("attn_33_cast_fp16")]; + tensor var_1903 = const()[name = tensor("op_1903"), val = tensor([1, 768, 1, -1])]; + tensor input_81_cast_fp16 = reshape(shape = var_1903, x = attn_33_cast_fp16)[name = tensor("input_81_cast_fp16")]; + tensor var_1907 = const()[name = tensor("op_1907"), val = tensor([1, 1])]; + tensor var_1909 = const()[name = tensor("op_1909"), val = tensor([1, 1])]; + tensor obj_119_pad_type_0 = const()[name = tensor("obj_119_pad_type_0"), val = tensor("custom")]; + tensor obj_119_pad_0 = const()[name = tensor("obj_119_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235117824)))]; + tensor layers_8_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236297536)))]; + tensor obj_119_cast_fp16 = conv(bias = layers_8_self_attn_o_proj_bias_to_fp16, dilations = var_1909, groups = var_1819, pad = obj_119_pad_0, pad_type = obj_119_pad_type_0, strides = var_1907, weight = layers_8_self_attn_o_proj_weight_to_fp16, x = input_81_cast_fp16)[name = tensor("obj_119_cast_fp16")]; + tensor inputs_51_cast_fp16 = add(x = inputs_49_cast_fp16, y = obj_119_cast_fp16)[name = tensor("inputs_51_cast_fp16")]; + tensor var_1919 = const()[name = tensor("op_1919"), val = tensor([1])]; + tensor channels_mean_51_cast_fp16 = reduce_mean(axes = var_1919, keep_dims = var_1820, x = inputs_51_cast_fp16)[name = tensor("channels_mean_51_cast_fp16")]; + tensor zero_mean_51_cast_fp16 = sub(x = inputs_51_cast_fp16, y = channels_mean_51_cast_fp16)[name = tensor("zero_mean_51_cast_fp16")]; + tensor zero_mean_sq_51_cast_fp16 = mul(x = zero_mean_51_cast_fp16, y = zero_mean_51_cast_fp16)[name = tensor("zero_mean_sq_51_cast_fp16")]; + tensor var_1923 = const()[name = tensor("op_1923"), val = tensor([1])]; + tensor var_1924_cast_fp16 = reduce_mean(axes = var_1923, keep_dims = var_1820, x = zero_mean_sq_51_cast_fp16)[name = tensor("op_1924_cast_fp16")]; + tensor var_1925_to_fp16 = const()[name = tensor("op_1925_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1926_cast_fp16 = add(x = var_1924_cast_fp16, y = var_1925_to_fp16)[name = tensor("op_1926_cast_fp16")]; + tensor denom_51_epsilon_0_to_fp16 = const()[name = tensor("denom_51_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_51_cast_fp16 = rsqrt(epsilon = denom_51_epsilon_0_to_fp16, x = var_1926_cast_fp16)[name = tensor("denom_51_cast_fp16")]; + tensor out_51_cast_fp16 = mul(x = zero_mean_51_cast_fp16, y = denom_51_cast_fp16)[name = tensor("out_51_cast_fp16")]; + tensor obj_121_gamma_0_to_fp16 = const()[name = tensor("obj_121_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236299136)))]; + tensor obj_121_beta_0_to_fp16 = const()[name = tensor("obj_121_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236300736)))]; + tensor obj_121_epsilon_0_to_fp16 = const()[name = tensor("obj_121_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_121_cast_fp16 = batch_norm(beta = obj_121_beta_0_to_fp16, epsilon = obj_121_epsilon_0_to_fp16, gamma = obj_121_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_51_cast_fp16)[name = tensor("obj_121_cast_fp16")]; + tensor var_1941 = const()[name = tensor("op_1941"), val = tensor([1, 1])]; + tensor var_1943 = const()[name = tensor("op_1943"), val = tensor([1, 1])]; + tensor query_35_pad_type_0 = const()[name = tensor("query_35_pad_type_0"), val = tensor("custom")]; + tensor query_35_pad_0 = const()[name = tensor("query_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_8_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236302336)))]; + tensor layers_8_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_8_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(237482048)))]; + tensor query_35_cast_fp16 = conv(bias = layers_8_encoder_attn_q_proj_bias_to_fp16, dilations = var_1943, groups = var_1819, pad = query_35_pad_0, pad_type = query_35_pad_type_0, strides = var_1941, weight = layers_8_encoder_attn_q_proj_weight_to_fp16, x = obj_121_cast_fp16)[name = tensor("query_35_cast_fp16")]; + tensor var_1947 = const()[name = tensor("op_1947"), val = tensor([1, 1])]; + tensor var_1949 = const()[name = tensor("op_1949"), val = tensor([1, 1])]; + tensor key_35_pad_type_0 = const()[name = tensor("key_35_pad_type_0"), val = tensor("custom")]; + tensor key_35_pad_0 = const()[name = tensor("key_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_8_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(237483648)))]; + tensor key_35_cast_fp16 = conv(dilations = var_1949, groups = var_1819, pad = key_35_pad_0, pad_type = key_35_pad_type_0, strides = var_1947, weight = layers_8_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_35_cast_fp16")]; + tensor var_1954 = const()[name = tensor("op_1954"), val = tensor([1, 1])]; + tensor var_1956 = const()[name = tensor("op_1956"), val = tensor([1, 1])]; + tensor value_35_pad_type_0 = const()[name = tensor("value_35_pad_type_0"), val = tensor("custom")]; + tensor value_35_pad_0 = const()[name = tensor("value_35_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_8_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(238663360)))]; + tensor layers_8_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_8_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(239843072)))]; + tensor value_35_cast_fp16 = conv(bias = layers_8_encoder_attn_v_proj_bias_to_fp16, dilations = var_1956, groups = var_1819, pad = value_35_pad_0, pad_type = value_35_pad_type_0, strides = var_1954, weight = layers_8_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_35_cast_fp16")]; + tensor var_1960 = const()[name = tensor("op_1960"), val = tensor([1, 12, 64, -1])]; + tensor var_1961_cast_fp16 = reshape(shape = var_1960, x = query_35_cast_fp16)[name = tensor("op_1961_cast_fp16")]; + tensor var_1962_to_fp16 = const()[name = tensor("op_1962_to_fp16"), val = tensor(0x1p-3)]; + tensor var_1963_cast_fp16 = mul(x = var_1961_cast_fp16, y = var_1962_to_fp16)[name = tensor("op_1963_cast_fp16")]; + tensor var_1964 = const()[name = tensor("op_1964"), val = tensor([1, 12, 64, -1])]; + tensor var_1965_cast_fp16 = reshape(shape = var_1964, x = key_35_cast_fp16)[name = tensor("op_1965_cast_fp16")]; + tensor mh_w_53_transpose_x_0 = const()[name = tensor("mh_w_53_transpose_x_0"), val = tensor(true)]; + tensor mh_w_53_transpose_y_0 = const()[name = tensor("mh_w_53_transpose_y_0"), val = tensor(false)]; + tensor mh_w_53_cast_fp16 = matmul(transpose_x = mh_w_53_transpose_x_0, transpose_y = mh_w_53_transpose_y_0, x = var_1963_cast_fp16, y = var_1965_cast_fp16)[name = tensor("mh_w_53_cast_fp16")]; + tensor obj_125_cast_fp16 = softmax(axis = var_1812, x = mh_w_53_cast_fp16)[name = tensor("obj_125_cast_fp16")]; + tensor var_1969 = const()[name = tensor("op_1969"), val = tensor([1, 12, 64, -1])]; + tensor var_1970_cast_fp16 = reshape(shape = var_1969, x = value_35_cast_fp16)[name = tensor("op_1970_cast_fp16")]; + tensor attn_35_transpose_x_0 = const()[name = tensor("attn_35_transpose_x_0"), val = tensor(false)]; + tensor attn_35_transpose_y_0 = const()[name = tensor("attn_35_transpose_y_0"), val = tensor(true)]; + tensor attn_35_cast_fp16 = matmul(transpose_x = attn_35_transpose_x_0, transpose_y = attn_35_transpose_y_0, x = var_1970_cast_fp16, y = obj_125_cast_fp16)[name = tensor("attn_35_cast_fp16")]; + tensor var_1973 = const()[name = tensor("op_1973"), val = tensor([1, 768, 1, -1])]; + tensor input_83_cast_fp16 = reshape(shape = var_1973, x = attn_35_cast_fp16)[name = tensor("input_83_cast_fp16")]; + tensor var_1977 = const()[name = tensor("op_1977"), val = tensor([1, 1])]; + tensor var_1979 = const()[name = tensor("op_1979"), val = tensor([1, 1])]; + tensor obj_123_pad_type_0 = const()[name = tensor("obj_123_pad_type_0"), val = tensor("custom")]; + tensor obj_123_pad_0 = const()[name = tensor("obj_123_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_8_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(239844672)))]; + tensor layers_8_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_8_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241024384)))]; + tensor obj_123_cast_fp16 = conv(bias = layers_8_encoder_attn_o_proj_bias_to_fp16, dilations = var_1979, groups = var_1819, pad = obj_123_pad_0, pad_type = obj_123_pad_type_0, strides = var_1977, weight = layers_8_encoder_attn_o_proj_weight_to_fp16, x = input_83_cast_fp16)[name = tensor("obj_123_cast_fp16")]; + tensor inputs_53_cast_fp16 = add(x = inputs_51_cast_fp16, y = obj_123_cast_fp16)[name = tensor("inputs_53_cast_fp16")]; + tensor var_1988 = const()[name = tensor("op_1988"), val = tensor([1])]; + tensor channels_mean_53_cast_fp16 = reduce_mean(axes = var_1988, keep_dims = var_1820, x = inputs_53_cast_fp16)[name = tensor("channels_mean_53_cast_fp16")]; + tensor zero_mean_53_cast_fp16 = sub(x = inputs_53_cast_fp16, y = channels_mean_53_cast_fp16)[name = tensor("zero_mean_53_cast_fp16")]; + tensor zero_mean_sq_53_cast_fp16 = mul(x = zero_mean_53_cast_fp16, y = zero_mean_53_cast_fp16)[name = tensor("zero_mean_sq_53_cast_fp16")]; + tensor var_1992 = const()[name = tensor("op_1992"), val = tensor([1])]; + tensor var_1993_cast_fp16 = reduce_mean(axes = var_1992, keep_dims = var_1820, x = zero_mean_sq_53_cast_fp16)[name = tensor("op_1993_cast_fp16")]; + tensor var_1994_to_fp16 = const()[name = tensor("op_1994_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_1995_cast_fp16 = add(x = var_1993_cast_fp16, y = var_1994_to_fp16)[name = tensor("op_1995_cast_fp16")]; + tensor denom_53_epsilon_0_to_fp16 = const()[name = tensor("denom_53_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_53_cast_fp16 = rsqrt(epsilon = denom_53_epsilon_0_to_fp16, x = var_1995_cast_fp16)[name = tensor("denom_53_cast_fp16")]; + tensor out_53_cast_fp16 = mul(x = zero_mean_53_cast_fp16, y = denom_53_cast_fp16)[name = tensor("out_53_cast_fp16")]; + tensor input_85_gamma_0_to_fp16 = const()[name = tensor("input_85_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241025984)))]; + tensor input_85_beta_0_to_fp16 = const()[name = tensor("input_85_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241027584)))]; + tensor input_85_epsilon_0_to_fp16 = const()[name = tensor("input_85_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_85_cast_fp16 = batch_norm(beta = input_85_beta_0_to_fp16, epsilon = input_85_epsilon_0_to_fp16, gamma = input_85_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_53_cast_fp16)[name = tensor("input_85_cast_fp16")]; + tensor var_2006 = const()[name = tensor("op_2006"), val = tensor([1, 1])]; + tensor var_2008 = const()[name = tensor("op_2008"), val = tensor([1, 1])]; + tensor input_87_pad_type_0 = const()[name = tensor("input_87_pad_type_0"), val = tensor("custom")]; + tensor input_87_pad_0 = const()[name = tensor("input_87_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_fc1_weight_to_fp16 = const()[name = tensor("layers_8_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241029184)))]; + tensor layers_8_fc1_bias_to_fp16 = const()[name = tensor("layers_8_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(245747840)))]; + tensor input_87_cast_fp16 = conv(bias = layers_8_fc1_bias_to_fp16, dilations = var_2008, groups = var_1819, pad = input_87_pad_0, pad_type = input_87_pad_type_0, strides = var_2006, weight = layers_8_fc1_weight_to_fp16, x = input_85_cast_fp16)[name = tensor("input_87_cast_fp16")]; + tensor input_89_mode_0 = const()[name = tensor("input_89_mode_0"), val = tensor("EXACT")]; + tensor input_89_cast_fp16 = gelu(mode = input_89_mode_0, x = input_87_cast_fp16)[name = tensor("input_89_cast_fp16")]; + tensor var_2014 = const()[name = tensor("op_2014"), val = tensor([1, 1])]; + tensor var_2016 = const()[name = tensor("op_2016"), val = tensor([1, 1])]; + tensor hidden_states_19_pad_type_0 = const()[name = tensor("hidden_states_19_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_19_pad_0 = const()[name = tensor("hidden_states_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_8_fc2_weight_to_fp16 = const()[name = tensor("layers_8_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(245754048)))]; + tensor layers_8_fc2_bias_to_fp16 = const()[name = tensor("layers_8_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(250472704)))]; + tensor hidden_states_19_cast_fp16 = conv(bias = layers_8_fc2_bias_to_fp16, dilations = var_2016, groups = var_1819, pad = hidden_states_19_pad_0, pad_type = hidden_states_19_pad_type_0, strides = var_2014, weight = layers_8_fc2_weight_to_fp16, x = input_89_cast_fp16)[name = tensor("hidden_states_19_cast_fp16")]; + tensor inputs_55_cast_fp16 = add(x = inputs_53_cast_fp16, y = hidden_states_19_cast_fp16)[name = tensor("inputs_55_cast_fp16")]; + tensor var_2030 = const()[name = tensor("op_2030"), val = tensor(3)]; + tensor var_2037 = const()[name = tensor("op_2037"), val = tensor(1)]; + tensor var_2038 = const()[name = tensor("op_2038"), val = tensor(true)]; + tensor var_2050 = const()[name = tensor("op_2050"), val = tensor([1])]; + tensor channels_mean_55_cast_fp16 = reduce_mean(axes = var_2050, keep_dims = var_2038, x = inputs_55_cast_fp16)[name = tensor("channels_mean_55_cast_fp16")]; + tensor zero_mean_55_cast_fp16 = sub(x = inputs_55_cast_fp16, y = channels_mean_55_cast_fp16)[name = tensor("zero_mean_55_cast_fp16")]; + tensor zero_mean_sq_55_cast_fp16 = mul(x = zero_mean_55_cast_fp16, y = zero_mean_55_cast_fp16)[name = tensor("zero_mean_sq_55_cast_fp16")]; + tensor var_2054 = const()[name = tensor("op_2054"), val = tensor([1])]; + tensor var_2055_cast_fp16 = reduce_mean(axes = var_2054, keep_dims = var_2038, x = zero_mean_sq_55_cast_fp16)[name = tensor("op_2055_cast_fp16")]; + tensor var_2056_to_fp16 = const()[name = tensor("op_2056_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2057_cast_fp16 = add(x = var_2055_cast_fp16, y = var_2056_to_fp16)[name = tensor("op_2057_cast_fp16")]; + tensor denom_55_epsilon_0_to_fp16 = const()[name = tensor("denom_55_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_55_cast_fp16 = rsqrt(epsilon = denom_55_epsilon_0_to_fp16, x = var_2057_cast_fp16)[name = tensor("denom_55_cast_fp16")]; + tensor out_55_cast_fp16 = mul(x = zero_mean_55_cast_fp16, y = denom_55_cast_fp16)[name = tensor("out_55_cast_fp16")]; + tensor obj_127_gamma_0_to_fp16 = const()[name = tensor("obj_127_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(250474304)))]; + tensor obj_127_beta_0_to_fp16 = const()[name = tensor("obj_127_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(250475904)))]; + tensor obj_127_epsilon_0_to_fp16 = const()[name = tensor("obj_127_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_127_cast_fp16 = batch_norm(beta = obj_127_beta_0_to_fp16, epsilon = obj_127_epsilon_0_to_fp16, gamma = obj_127_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_55_cast_fp16)[name = tensor("obj_127_cast_fp16")]; + tensor var_2072 = const()[name = tensor("op_2072"), val = tensor([1, 1])]; + tensor var_2074 = const()[name = tensor("op_2074"), val = tensor([1, 1])]; + tensor query_37_pad_type_0 = const()[name = tensor("query_37_pad_type_0"), val = tensor("custom")]; + tensor query_37_pad_0 = const()[name = tensor("query_37_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(250477504)))]; + tensor layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(251657216)))]; + tensor query_37_cast_fp16 = conv(bias = layers_9_self_attn_q_proj_bias_to_fp16, dilations = var_2074, groups = var_2037, pad = query_37_pad_0, pad_type = query_37_pad_type_0, strides = var_2072, weight = layers_9_self_attn_q_proj_weight_to_fp16, x = obj_127_cast_fp16)[name = tensor("query_37_cast_fp16")]; + tensor var_2078 = const()[name = tensor("op_2078"), val = tensor([1, 1])]; + tensor var_2080 = const()[name = tensor("op_2080"), val = tensor([1, 1])]; + tensor current_key_19_pad_type_0 = const()[name = tensor("current_key_19_pad_type_0"), val = tensor("custom")]; + tensor current_key_19_pad_0 = const()[name = tensor("current_key_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(251658816)))]; + tensor current_key_19_cast_fp16 = conv(dilations = var_2080, groups = var_2037, pad = current_key_19_pad_0, pad_type = current_key_19_pad_type_0, strides = var_2078, weight = layers_9_self_attn_k_proj_weight_to_fp16, x = obj_127_cast_fp16)[name = tensor("current_key_19_cast_fp16")]; + tensor var_2085 = const()[name = tensor("op_2085"), val = tensor([1, 1])]; + tensor var_2087 = const()[name = tensor("op_2087"), val = tensor([1, 1])]; + tensor current_value_19_pad_type_0 = const()[name = tensor("current_value_19_pad_type_0"), val = tensor("custom")]; + tensor current_value_19_pad_0 = const()[name = tensor("current_value_19_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252838528)))]; + tensor layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254018240)))]; + tensor current_value_19_cast_fp16 = conv(bias = layers_9_self_attn_v_proj_bias_to_fp16, dilations = var_2087, groups = var_2037, pad = current_value_19_pad_0, pad_type = current_value_19_pad_type_0, strides = var_2085, weight = layers_9_self_attn_v_proj_weight_to_fp16, x = obj_127_cast_fp16)[name = tensor("current_value_19_cast_fp16")]; + tensor var_2094_cast_fp16 = mul(x = current_key_19_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_2094_cast_fp16")]; + tensor var_2096_cast_fp16 = mul(x = var_63_cast_fp16_9, y = var_161_cast_fp16)[name = tensor("op_2096_cast_fp16")]; + tensor key_37_cast_fp16 = add(x = var_2094_cast_fp16, y = var_2096_cast_fp16)[name = tensor("key_37_cast_fp16")]; + tensor var_2098_cast_fp16 = mul(x = current_value_19_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_2098_cast_fp16")]; + tensor var_2100_cast_fp16 = mul(x = var_78_cast_fp16_9, y = var_161_cast_fp16)[name = tensor("op_2100_cast_fp16")]; + tensor value_37_cast_fp16 = add(x = var_2098_cast_fp16, y = var_2100_cast_fp16)[name = tensor("value_37_cast_fp16")]; + tensor var_2103 = const()[name = tensor("op_2103"), val = tensor([1, 12, 64, -1])]; + tensor var_2104_cast_fp16 = reshape(shape = var_2103, x = query_37_cast_fp16)[name = tensor("op_2104_cast_fp16")]; + tensor var_2105_to_fp16 = const()[name = tensor("op_2105_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2106_cast_fp16 = mul(x = var_2104_cast_fp16, y = var_2105_to_fp16)[name = tensor("op_2106_cast_fp16")]; + tensor var_2107 = const()[name = tensor("op_2107"), val = tensor([1, 12, 64, -1])]; + tensor var_2108_cast_fp16 = reshape(shape = var_2107, x = key_37_cast_fp16)[name = tensor("op_2108_cast_fp16")]; + tensor mh_w_55_transpose_x_0 = const()[name = tensor("mh_w_55_transpose_x_0"), val = tensor(true)]; + tensor mh_w_55_transpose_y_0 = const()[name = tensor("mh_w_55_transpose_y_0"), val = tensor(false)]; + tensor mh_w_55_cast_fp16 = matmul(transpose_x = mh_w_55_transpose_x_0, transpose_y = mh_w_55_transpose_y_0, x = var_2106_cast_fp16, y = var_2108_cast_fp16)[name = tensor("mh_w_55_cast_fp16")]; + tensor mh_w_57_cast_fp16 = add(x = mh_w_55_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_57_cast_fp16")]; + tensor var_2116_cast_fp16 = softmax(axis = var_2030, x = mh_w_57_cast_fp16)[name = tensor("op_2116_cast_fp16")]; + tensor var_2117 = const()[name = tensor("op_2117"), val = tensor([1, 12, 64, -1])]; + tensor var_2118_cast_fp16 = reshape(shape = var_2117, x = value_37_cast_fp16)[name = tensor("op_2118_cast_fp16")]; + tensor attn_37_transpose_x_0 = const()[name = tensor("attn_37_transpose_x_0"), val = tensor(false)]; + tensor attn_37_transpose_y_0 = const()[name = tensor("attn_37_transpose_y_0"), val = tensor(true)]; + tensor attn_37_cast_fp16 = matmul(transpose_x = attn_37_transpose_x_0, transpose_y = attn_37_transpose_y_0, x = var_2118_cast_fp16, y = var_2116_cast_fp16)[name = tensor("attn_37_cast_fp16")]; + tensor var_2121 = const()[name = tensor("op_2121"), val = tensor([1, 768, 1, -1])]; + tensor input_91_cast_fp16 = reshape(shape = var_2121, x = attn_37_cast_fp16)[name = tensor("input_91_cast_fp16")]; + tensor var_2125 = const()[name = tensor("op_2125"), val = tensor([1, 1])]; + tensor var_2127 = const()[name = tensor("op_2127"), val = tensor([1, 1])]; + tensor obj_133_pad_type_0 = const()[name = tensor("obj_133_pad_type_0"), val = tensor("custom")]; + tensor obj_133_pad_0 = const()[name = tensor("obj_133_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254019840)))]; + tensor layers_9_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255199552)))]; + tensor obj_133_cast_fp16 = conv(bias = layers_9_self_attn_o_proj_bias_to_fp16, dilations = var_2127, groups = var_2037, pad = obj_133_pad_0, pad_type = obj_133_pad_type_0, strides = var_2125, weight = layers_9_self_attn_o_proj_weight_to_fp16, x = input_91_cast_fp16)[name = tensor("obj_133_cast_fp16")]; + tensor inputs_57_cast_fp16 = add(x = inputs_55_cast_fp16, y = obj_133_cast_fp16)[name = tensor("inputs_57_cast_fp16")]; + tensor var_2137 = const()[name = tensor("op_2137"), val = tensor([1])]; + tensor channels_mean_57_cast_fp16 = reduce_mean(axes = var_2137, keep_dims = var_2038, x = inputs_57_cast_fp16)[name = tensor("channels_mean_57_cast_fp16")]; + tensor zero_mean_57_cast_fp16 = sub(x = inputs_57_cast_fp16, y = channels_mean_57_cast_fp16)[name = tensor("zero_mean_57_cast_fp16")]; + tensor zero_mean_sq_57_cast_fp16 = mul(x = zero_mean_57_cast_fp16, y = zero_mean_57_cast_fp16)[name = tensor("zero_mean_sq_57_cast_fp16")]; + tensor var_2141 = const()[name = tensor("op_2141"), val = tensor([1])]; + tensor var_2142_cast_fp16 = reduce_mean(axes = var_2141, keep_dims = var_2038, x = zero_mean_sq_57_cast_fp16)[name = tensor("op_2142_cast_fp16")]; + tensor var_2143_to_fp16 = const()[name = tensor("op_2143_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2144_cast_fp16 = add(x = var_2142_cast_fp16, y = var_2143_to_fp16)[name = tensor("op_2144_cast_fp16")]; + tensor denom_57_epsilon_0_to_fp16 = const()[name = tensor("denom_57_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_57_cast_fp16 = rsqrt(epsilon = denom_57_epsilon_0_to_fp16, x = var_2144_cast_fp16)[name = tensor("denom_57_cast_fp16")]; + tensor out_57_cast_fp16 = mul(x = zero_mean_57_cast_fp16, y = denom_57_cast_fp16)[name = tensor("out_57_cast_fp16")]; + tensor obj_135_gamma_0_to_fp16 = const()[name = tensor("obj_135_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255201152)))]; + tensor obj_135_beta_0_to_fp16 = const()[name = tensor("obj_135_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255202752)))]; + tensor obj_135_epsilon_0_to_fp16 = const()[name = tensor("obj_135_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_135_cast_fp16 = batch_norm(beta = obj_135_beta_0_to_fp16, epsilon = obj_135_epsilon_0_to_fp16, gamma = obj_135_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_57_cast_fp16)[name = tensor("obj_135_cast_fp16")]; + tensor var_2159 = const()[name = tensor("op_2159"), val = tensor([1, 1])]; + tensor var_2161 = const()[name = tensor("op_2161"), val = tensor([1, 1])]; + tensor query_39_pad_type_0 = const()[name = tensor("query_39_pad_type_0"), val = tensor("custom")]; + tensor query_39_pad_0 = const()[name = tensor("query_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_9_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255204352)))]; + tensor layers_9_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_9_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(256384064)))]; + tensor query_39_cast_fp16 = conv(bias = layers_9_encoder_attn_q_proj_bias_to_fp16, dilations = var_2161, groups = var_2037, pad = query_39_pad_0, pad_type = query_39_pad_type_0, strides = var_2159, weight = layers_9_encoder_attn_q_proj_weight_to_fp16, x = obj_135_cast_fp16)[name = tensor("query_39_cast_fp16")]; + tensor var_2165 = const()[name = tensor("op_2165"), val = tensor([1, 1])]; + tensor var_2167 = const()[name = tensor("op_2167"), val = tensor([1, 1])]; + tensor key_39_pad_type_0 = const()[name = tensor("key_39_pad_type_0"), val = tensor("custom")]; + tensor key_39_pad_0 = const()[name = tensor("key_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_9_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(256385664)))]; + tensor key_39_cast_fp16 = conv(dilations = var_2167, groups = var_2037, pad = key_39_pad_0, pad_type = key_39_pad_type_0, strides = var_2165, weight = layers_9_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_39_cast_fp16")]; + tensor var_2172 = const()[name = tensor("op_2172"), val = tensor([1, 1])]; + tensor var_2174 = const()[name = tensor("op_2174"), val = tensor([1, 1])]; + tensor value_39_pad_type_0 = const()[name = tensor("value_39_pad_type_0"), val = tensor("custom")]; + tensor value_39_pad_0 = const()[name = tensor("value_39_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_9_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(257565376)))]; + tensor layers_9_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_9_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(258745088)))]; + tensor value_39_cast_fp16 = conv(bias = layers_9_encoder_attn_v_proj_bias_to_fp16, dilations = var_2174, groups = var_2037, pad = value_39_pad_0, pad_type = value_39_pad_type_0, strides = var_2172, weight = layers_9_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_39_cast_fp16")]; + tensor var_2178 = const()[name = tensor("op_2178"), val = tensor([1, 12, 64, -1])]; + tensor var_2179_cast_fp16 = reshape(shape = var_2178, x = query_39_cast_fp16)[name = tensor("op_2179_cast_fp16")]; + tensor var_2180_to_fp16 = const()[name = tensor("op_2180_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2181_cast_fp16 = mul(x = var_2179_cast_fp16, y = var_2180_to_fp16)[name = tensor("op_2181_cast_fp16")]; + tensor var_2182 = const()[name = tensor("op_2182"), val = tensor([1, 12, 64, -1])]; + tensor var_2183_cast_fp16 = reshape(shape = var_2182, x = key_39_cast_fp16)[name = tensor("op_2183_cast_fp16")]; + tensor mh_w_59_transpose_x_0 = const()[name = tensor("mh_w_59_transpose_x_0"), val = tensor(true)]; + tensor mh_w_59_transpose_y_0 = const()[name = tensor("mh_w_59_transpose_y_0"), val = tensor(false)]; + tensor mh_w_59_cast_fp16 = matmul(transpose_x = mh_w_59_transpose_x_0, transpose_y = mh_w_59_transpose_y_0, x = var_2181_cast_fp16, y = var_2183_cast_fp16)[name = tensor("mh_w_59_cast_fp16")]; + tensor obj_139_cast_fp16 = softmax(axis = var_2030, x = mh_w_59_cast_fp16)[name = tensor("obj_139_cast_fp16")]; + tensor var_2187 = const()[name = tensor("op_2187"), val = tensor([1, 12, 64, -1])]; + tensor var_2188_cast_fp16 = reshape(shape = var_2187, x = value_39_cast_fp16)[name = tensor("op_2188_cast_fp16")]; + tensor attn_39_transpose_x_0 = const()[name = tensor("attn_39_transpose_x_0"), val = tensor(false)]; + tensor attn_39_transpose_y_0 = const()[name = tensor("attn_39_transpose_y_0"), val = tensor(true)]; + tensor attn_39_cast_fp16 = matmul(transpose_x = attn_39_transpose_x_0, transpose_y = attn_39_transpose_y_0, x = var_2188_cast_fp16, y = obj_139_cast_fp16)[name = tensor("attn_39_cast_fp16")]; + tensor var_2191 = const()[name = tensor("op_2191"), val = tensor([1, 768, 1, -1])]; + tensor input_93_cast_fp16 = reshape(shape = var_2191, x = attn_39_cast_fp16)[name = tensor("input_93_cast_fp16")]; + tensor var_2195 = const()[name = tensor("op_2195"), val = tensor([1, 1])]; + tensor var_2197 = const()[name = tensor("op_2197"), val = tensor([1, 1])]; + tensor obj_137_pad_type_0 = const()[name = tensor("obj_137_pad_type_0"), val = tensor("custom")]; + tensor obj_137_pad_0 = const()[name = tensor("obj_137_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_9_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(258746688)))]; + tensor layers_9_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_9_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259926400)))]; + tensor obj_137_cast_fp16 = conv(bias = layers_9_encoder_attn_o_proj_bias_to_fp16, dilations = var_2197, groups = var_2037, pad = obj_137_pad_0, pad_type = obj_137_pad_type_0, strides = var_2195, weight = layers_9_encoder_attn_o_proj_weight_to_fp16, x = input_93_cast_fp16)[name = tensor("obj_137_cast_fp16")]; + tensor inputs_59_cast_fp16 = add(x = inputs_57_cast_fp16, y = obj_137_cast_fp16)[name = tensor("inputs_59_cast_fp16")]; + tensor var_2206 = const()[name = tensor("op_2206"), val = tensor([1])]; + tensor channels_mean_59_cast_fp16 = reduce_mean(axes = var_2206, keep_dims = var_2038, x = inputs_59_cast_fp16)[name = tensor("channels_mean_59_cast_fp16")]; + tensor zero_mean_59_cast_fp16 = sub(x = inputs_59_cast_fp16, y = channels_mean_59_cast_fp16)[name = tensor("zero_mean_59_cast_fp16")]; + tensor zero_mean_sq_59_cast_fp16 = mul(x = zero_mean_59_cast_fp16, y = zero_mean_59_cast_fp16)[name = tensor("zero_mean_sq_59_cast_fp16")]; + tensor var_2210 = const()[name = tensor("op_2210"), val = tensor([1])]; + tensor var_2211_cast_fp16 = reduce_mean(axes = var_2210, keep_dims = var_2038, x = zero_mean_sq_59_cast_fp16)[name = tensor("op_2211_cast_fp16")]; + tensor var_2212_to_fp16 = const()[name = tensor("op_2212_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2213_cast_fp16 = add(x = var_2211_cast_fp16, y = var_2212_to_fp16)[name = tensor("op_2213_cast_fp16")]; + tensor denom_59_epsilon_0_to_fp16 = const()[name = tensor("denom_59_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_59_cast_fp16 = rsqrt(epsilon = denom_59_epsilon_0_to_fp16, x = var_2213_cast_fp16)[name = tensor("denom_59_cast_fp16")]; + tensor out_59_cast_fp16 = mul(x = zero_mean_59_cast_fp16, y = denom_59_cast_fp16)[name = tensor("out_59_cast_fp16")]; + tensor input_95_gamma_0_to_fp16 = const()[name = tensor("input_95_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259928000)))]; + tensor input_95_beta_0_to_fp16 = const()[name = tensor("input_95_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259929600)))]; + tensor input_95_epsilon_0_to_fp16 = const()[name = tensor("input_95_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_95_cast_fp16 = batch_norm(beta = input_95_beta_0_to_fp16, epsilon = input_95_epsilon_0_to_fp16, gamma = input_95_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_59_cast_fp16)[name = tensor("input_95_cast_fp16")]; + tensor var_2224 = const()[name = tensor("op_2224"), val = tensor([1, 1])]; + tensor var_2226 = const()[name = tensor("op_2226"), val = tensor([1, 1])]; + tensor input_97_pad_type_0 = const()[name = tensor("input_97_pad_type_0"), val = tensor("custom")]; + tensor input_97_pad_0 = const()[name = tensor("input_97_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_fc1_weight_to_fp16 = const()[name = tensor("layers_9_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259931200)))]; + tensor layers_9_fc1_bias_to_fp16 = const()[name = tensor("layers_9_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264649856)))]; + tensor input_97_cast_fp16 = conv(bias = layers_9_fc1_bias_to_fp16, dilations = var_2226, groups = var_2037, pad = input_97_pad_0, pad_type = input_97_pad_type_0, strides = var_2224, weight = layers_9_fc1_weight_to_fp16, x = input_95_cast_fp16)[name = tensor("input_97_cast_fp16")]; + tensor input_99_mode_0 = const()[name = tensor("input_99_mode_0"), val = tensor("EXACT")]; + tensor input_99_cast_fp16 = gelu(mode = input_99_mode_0, x = input_97_cast_fp16)[name = tensor("input_99_cast_fp16")]; + tensor var_2232 = const()[name = tensor("op_2232"), val = tensor([1, 1])]; + tensor var_2234 = const()[name = tensor("op_2234"), val = tensor([1, 1])]; + tensor hidden_states_21_pad_type_0 = const()[name = tensor("hidden_states_21_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_21_pad_0 = const()[name = tensor("hidden_states_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_9_fc2_weight_to_fp16 = const()[name = tensor("layers_9_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264656064)))]; + tensor layers_9_fc2_bias_to_fp16 = const()[name = tensor("layers_9_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269374720)))]; + tensor hidden_states_21_cast_fp16 = conv(bias = layers_9_fc2_bias_to_fp16, dilations = var_2234, groups = var_2037, pad = hidden_states_21_pad_0, pad_type = hidden_states_21_pad_type_0, strides = var_2232, weight = layers_9_fc2_weight_to_fp16, x = input_99_cast_fp16)[name = tensor("hidden_states_21_cast_fp16")]; + tensor inputs_61_cast_fp16 = add(x = inputs_59_cast_fp16, y = hidden_states_21_cast_fp16)[name = tensor("inputs_61_cast_fp16")]; + tensor var_2248 = const()[name = tensor("op_2248"), val = tensor(3)]; + tensor var_2255 = const()[name = tensor("op_2255"), val = tensor(1)]; + tensor var_2256 = const()[name = tensor("op_2256"), val = tensor(true)]; + tensor var_2268 = const()[name = tensor("op_2268"), val = tensor([1])]; + tensor channels_mean_61_cast_fp16 = reduce_mean(axes = var_2268, keep_dims = var_2256, x = inputs_61_cast_fp16)[name = tensor("channels_mean_61_cast_fp16")]; + tensor zero_mean_61_cast_fp16 = sub(x = inputs_61_cast_fp16, y = channels_mean_61_cast_fp16)[name = tensor("zero_mean_61_cast_fp16")]; + tensor zero_mean_sq_61_cast_fp16 = mul(x = zero_mean_61_cast_fp16, y = zero_mean_61_cast_fp16)[name = tensor("zero_mean_sq_61_cast_fp16")]; + tensor var_2272 = const()[name = tensor("op_2272"), val = tensor([1])]; + tensor var_2273_cast_fp16 = reduce_mean(axes = var_2272, keep_dims = var_2256, x = zero_mean_sq_61_cast_fp16)[name = tensor("op_2273_cast_fp16")]; + tensor var_2274_to_fp16 = const()[name = tensor("op_2274_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2275_cast_fp16 = add(x = var_2273_cast_fp16, y = var_2274_to_fp16)[name = tensor("op_2275_cast_fp16")]; + tensor denom_61_epsilon_0_to_fp16 = const()[name = tensor("denom_61_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_61_cast_fp16 = rsqrt(epsilon = denom_61_epsilon_0_to_fp16, x = var_2275_cast_fp16)[name = tensor("denom_61_cast_fp16")]; + tensor out_61_cast_fp16 = mul(x = zero_mean_61_cast_fp16, y = denom_61_cast_fp16)[name = tensor("out_61_cast_fp16")]; + tensor obj_141_gamma_0_to_fp16 = const()[name = tensor("obj_141_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269376320)))]; + tensor obj_141_beta_0_to_fp16 = const()[name = tensor("obj_141_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269377920)))]; + tensor obj_141_epsilon_0_to_fp16 = const()[name = tensor("obj_141_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_141_cast_fp16 = batch_norm(beta = obj_141_beta_0_to_fp16, epsilon = obj_141_epsilon_0_to_fp16, gamma = obj_141_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_61_cast_fp16)[name = tensor("obj_141_cast_fp16")]; + tensor var_2290 = const()[name = tensor("op_2290"), val = tensor([1, 1])]; + tensor var_2292 = const()[name = tensor("op_2292"), val = tensor([1, 1])]; + tensor query_41_pad_type_0 = const()[name = tensor("query_41_pad_type_0"), val = tensor("custom")]; + tensor query_41_pad_0 = const()[name = tensor("query_41_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269379520)))]; + tensor layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(270559232)))]; + tensor query_41_cast_fp16 = conv(bias = layers_10_self_attn_q_proj_bias_to_fp16, dilations = var_2292, groups = var_2255, pad = query_41_pad_0, pad_type = query_41_pad_type_0, strides = var_2290, weight = layers_10_self_attn_q_proj_weight_to_fp16, x = obj_141_cast_fp16)[name = tensor("query_41_cast_fp16")]; + tensor var_2296 = const()[name = tensor("op_2296"), val = tensor([1, 1])]; + tensor var_2298 = const()[name = tensor("op_2298"), val = tensor([1, 1])]; + tensor current_key_21_pad_type_0 = const()[name = tensor("current_key_21_pad_type_0"), val = tensor("custom")]; + tensor current_key_21_pad_0 = const()[name = tensor("current_key_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(270560832)))]; + tensor current_key_21_cast_fp16 = conv(dilations = var_2298, groups = var_2255, pad = current_key_21_pad_0, pad_type = current_key_21_pad_type_0, strides = var_2296, weight = layers_10_self_attn_k_proj_weight_to_fp16, x = obj_141_cast_fp16)[name = tensor("current_key_21_cast_fp16")]; + tensor var_2303 = const()[name = tensor("op_2303"), val = tensor([1, 1])]; + tensor var_2305 = const()[name = tensor("op_2305"), val = tensor([1, 1])]; + tensor current_value_21_pad_type_0 = const()[name = tensor("current_value_21_pad_type_0"), val = tensor("custom")]; + tensor current_value_21_pad_0 = const()[name = tensor("current_value_21_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271740544)))]; + tensor layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272920256)))]; + tensor current_value_21_cast_fp16 = conv(bias = layers_10_self_attn_v_proj_bias_to_fp16, dilations = var_2305, groups = var_2255, pad = current_value_21_pad_0, pad_type = current_value_21_pad_type_0, strides = var_2303, weight = layers_10_self_attn_v_proj_weight_to_fp16, x = obj_141_cast_fp16)[name = tensor("current_value_21_cast_fp16")]; + tensor var_2312_cast_fp16 = mul(x = current_key_21_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_2312_cast_fp16")]; + tensor var_2314_cast_fp16 = mul(x = var_63_cast_fp16_10, y = var_161_cast_fp16)[name = tensor("op_2314_cast_fp16")]; + tensor key_41_cast_fp16 = add(x = var_2312_cast_fp16, y = var_2314_cast_fp16)[name = tensor("key_41_cast_fp16")]; + tensor var_2316_cast_fp16 = mul(x = current_value_21_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_2316_cast_fp16")]; + tensor var_2318_cast_fp16 = mul(x = var_78_cast_fp16_10, y = var_161_cast_fp16)[name = tensor("op_2318_cast_fp16")]; + tensor value_41_cast_fp16 = add(x = var_2316_cast_fp16, y = var_2318_cast_fp16)[name = tensor("value_41_cast_fp16")]; + tensor var_2321 = const()[name = tensor("op_2321"), val = tensor([1, 12, 64, -1])]; + tensor var_2322_cast_fp16 = reshape(shape = var_2321, x = query_41_cast_fp16)[name = tensor("op_2322_cast_fp16")]; + tensor var_2323_to_fp16 = const()[name = tensor("op_2323_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2324_cast_fp16 = mul(x = var_2322_cast_fp16, y = var_2323_to_fp16)[name = tensor("op_2324_cast_fp16")]; + tensor var_2325 = const()[name = tensor("op_2325"), val = tensor([1, 12, 64, -1])]; + tensor var_2326_cast_fp16 = reshape(shape = var_2325, x = key_41_cast_fp16)[name = tensor("op_2326_cast_fp16")]; + tensor mh_w_61_transpose_x_0 = const()[name = tensor("mh_w_61_transpose_x_0"), val = tensor(true)]; + tensor mh_w_61_transpose_y_0 = const()[name = tensor("mh_w_61_transpose_y_0"), val = tensor(false)]; + tensor mh_w_61_cast_fp16 = matmul(transpose_x = mh_w_61_transpose_x_0, transpose_y = mh_w_61_transpose_y_0, x = var_2324_cast_fp16, y = var_2326_cast_fp16)[name = tensor("mh_w_61_cast_fp16")]; + tensor mh_w_63_cast_fp16 = add(x = mh_w_61_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_63_cast_fp16")]; + tensor var_2334_cast_fp16 = softmax(axis = var_2248, x = mh_w_63_cast_fp16)[name = tensor("op_2334_cast_fp16")]; + tensor var_2335 = const()[name = tensor("op_2335"), val = tensor([1, 12, 64, -1])]; + tensor var_2336_cast_fp16 = reshape(shape = var_2335, x = value_41_cast_fp16)[name = tensor("op_2336_cast_fp16")]; + tensor attn_41_transpose_x_0 = const()[name = tensor("attn_41_transpose_x_0"), val = tensor(false)]; + tensor attn_41_transpose_y_0 = const()[name = tensor("attn_41_transpose_y_0"), val = tensor(true)]; + tensor attn_41_cast_fp16 = matmul(transpose_x = attn_41_transpose_x_0, transpose_y = attn_41_transpose_y_0, x = var_2336_cast_fp16, y = var_2334_cast_fp16)[name = tensor("attn_41_cast_fp16")]; + tensor var_2339 = const()[name = tensor("op_2339"), val = tensor([1, 768, 1, -1])]; + tensor input_101_cast_fp16 = reshape(shape = var_2339, x = attn_41_cast_fp16)[name = tensor("input_101_cast_fp16")]; + tensor var_2343 = const()[name = tensor("op_2343"), val = tensor([1, 1])]; + tensor var_2345 = const()[name = tensor("op_2345"), val = tensor([1, 1])]; + tensor obj_147_pad_type_0 = const()[name = tensor("obj_147_pad_type_0"), val = tensor("custom")]; + tensor obj_147_pad_0 = const()[name = tensor("obj_147_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272921856)))]; + tensor layers_10_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274101568)))]; + tensor obj_147_cast_fp16 = conv(bias = layers_10_self_attn_o_proj_bias_to_fp16, dilations = var_2345, groups = var_2255, pad = obj_147_pad_0, pad_type = obj_147_pad_type_0, strides = var_2343, weight = layers_10_self_attn_o_proj_weight_to_fp16, x = input_101_cast_fp16)[name = tensor("obj_147_cast_fp16")]; + tensor inputs_63_cast_fp16 = add(x = inputs_61_cast_fp16, y = obj_147_cast_fp16)[name = tensor("inputs_63_cast_fp16")]; + tensor var_2355 = const()[name = tensor("op_2355"), val = tensor([1])]; + tensor channels_mean_63_cast_fp16 = reduce_mean(axes = var_2355, keep_dims = var_2256, x = inputs_63_cast_fp16)[name = tensor("channels_mean_63_cast_fp16")]; + tensor zero_mean_63_cast_fp16 = sub(x = inputs_63_cast_fp16, y = channels_mean_63_cast_fp16)[name = tensor("zero_mean_63_cast_fp16")]; + tensor zero_mean_sq_63_cast_fp16 = mul(x = zero_mean_63_cast_fp16, y = zero_mean_63_cast_fp16)[name = tensor("zero_mean_sq_63_cast_fp16")]; + tensor var_2359 = const()[name = tensor("op_2359"), val = tensor([1])]; + tensor var_2360_cast_fp16 = reduce_mean(axes = var_2359, keep_dims = var_2256, x = zero_mean_sq_63_cast_fp16)[name = tensor("op_2360_cast_fp16")]; + tensor var_2361_to_fp16 = const()[name = tensor("op_2361_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2362_cast_fp16 = add(x = var_2360_cast_fp16, y = var_2361_to_fp16)[name = tensor("op_2362_cast_fp16")]; + tensor denom_63_epsilon_0_to_fp16 = const()[name = tensor("denom_63_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_63_cast_fp16 = rsqrt(epsilon = denom_63_epsilon_0_to_fp16, x = var_2362_cast_fp16)[name = tensor("denom_63_cast_fp16")]; + tensor out_63_cast_fp16 = mul(x = zero_mean_63_cast_fp16, y = denom_63_cast_fp16)[name = tensor("out_63_cast_fp16")]; + tensor obj_149_gamma_0_to_fp16 = const()[name = tensor("obj_149_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274103168)))]; + tensor obj_149_beta_0_to_fp16 = const()[name = tensor("obj_149_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274104768)))]; + tensor obj_149_epsilon_0_to_fp16 = const()[name = tensor("obj_149_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_149_cast_fp16 = batch_norm(beta = obj_149_beta_0_to_fp16, epsilon = obj_149_epsilon_0_to_fp16, gamma = obj_149_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_63_cast_fp16)[name = tensor("obj_149_cast_fp16")]; + tensor var_2377 = const()[name = tensor("op_2377"), val = tensor([1, 1])]; + tensor var_2379 = const()[name = tensor("op_2379"), val = tensor([1, 1])]; + tensor query_43_pad_type_0 = const()[name = tensor("query_43_pad_type_0"), val = tensor("custom")]; + tensor query_43_pad_0 = const()[name = tensor("query_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_10_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274106368)))]; + tensor layers_10_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_10_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(275286080)))]; + tensor query_43_cast_fp16 = conv(bias = layers_10_encoder_attn_q_proj_bias_to_fp16, dilations = var_2379, groups = var_2255, pad = query_43_pad_0, pad_type = query_43_pad_type_0, strides = var_2377, weight = layers_10_encoder_attn_q_proj_weight_to_fp16, x = obj_149_cast_fp16)[name = tensor("query_43_cast_fp16")]; + tensor var_2383 = const()[name = tensor("op_2383"), val = tensor([1, 1])]; + tensor var_2385 = const()[name = tensor("op_2385"), val = tensor([1, 1])]; + tensor key_43_pad_type_0 = const()[name = tensor("key_43_pad_type_0"), val = tensor("custom")]; + tensor key_43_pad_0 = const()[name = tensor("key_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_10_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(275287680)))]; + tensor key_43_cast_fp16 = conv(dilations = var_2385, groups = var_2255, pad = key_43_pad_0, pad_type = key_43_pad_type_0, strides = var_2383, weight = layers_10_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_43_cast_fp16")]; + tensor var_2390 = const()[name = tensor("op_2390"), val = tensor([1, 1])]; + tensor var_2392 = const()[name = tensor("op_2392"), val = tensor([1, 1])]; + tensor value_43_pad_type_0 = const()[name = tensor("value_43_pad_type_0"), val = tensor("custom")]; + tensor value_43_pad_0 = const()[name = tensor("value_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_10_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(276467392)))]; + tensor layers_10_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_10_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(277647104)))]; + tensor value_43_cast_fp16 = conv(bias = layers_10_encoder_attn_v_proj_bias_to_fp16, dilations = var_2392, groups = var_2255, pad = value_43_pad_0, pad_type = value_43_pad_type_0, strides = var_2390, weight = layers_10_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_43_cast_fp16")]; + tensor var_2396 = const()[name = tensor("op_2396"), val = tensor([1, 12, 64, -1])]; + tensor var_2397_cast_fp16 = reshape(shape = var_2396, x = query_43_cast_fp16)[name = tensor("op_2397_cast_fp16")]; + tensor var_2398_to_fp16 = const()[name = tensor("op_2398_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2399_cast_fp16 = mul(x = var_2397_cast_fp16, y = var_2398_to_fp16)[name = tensor("op_2399_cast_fp16")]; + tensor var_2400 = const()[name = tensor("op_2400"), val = tensor([1, 12, 64, -1])]; + tensor var_2401_cast_fp16 = reshape(shape = var_2400, x = key_43_cast_fp16)[name = tensor("op_2401_cast_fp16")]; + tensor mh_w_65_transpose_x_0 = const()[name = tensor("mh_w_65_transpose_x_0"), val = tensor(true)]; + tensor mh_w_65_transpose_y_0 = const()[name = tensor("mh_w_65_transpose_y_0"), val = tensor(false)]; + tensor mh_w_65_cast_fp16 = matmul(transpose_x = mh_w_65_transpose_x_0, transpose_y = mh_w_65_transpose_y_0, x = var_2399_cast_fp16, y = var_2401_cast_fp16)[name = tensor("mh_w_65_cast_fp16")]; + tensor obj_153_cast_fp16 = softmax(axis = var_2248, x = mh_w_65_cast_fp16)[name = tensor("obj_153_cast_fp16")]; + tensor var_2405 = const()[name = tensor("op_2405"), val = tensor([1, 12, 64, -1])]; + tensor var_2406_cast_fp16 = reshape(shape = var_2405, x = value_43_cast_fp16)[name = tensor("op_2406_cast_fp16")]; + tensor attn_43_transpose_x_0 = const()[name = tensor("attn_43_transpose_x_0"), val = tensor(false)]; + tensor attn_43_transpose_y_0 = const()[name = tensor("attn_43_transpose_y_0"), val = tensor(true)]; + tensor attn_43_cast_fp16 = matmul(transpose_x = attn_43_transpose_x_0, transpose_y = attn_43_transpose_y_0, x = var_2406_cast_fp16, y = obj_153_cast_fp16)[name = tensor("attn_43_cast_fp16")]; + tensor var_2409 = const()[name = tensor("op_2409"), val = tensor([1, 768, 1, -1])]; + tensor input_103_cast_fp16 = reshape(shape = var_2409, x = attn_43_cast_fp16)[name = tensor("input_103_cast_fp16")]; + tensor var_2413 = const()[name = tensor("op_2413"), val = tensor([1, 1])]; + tensor var_2415 = const()[name = tensor("op_2415"), val = tensor([1, 1])]; + tensor obj_151_pad_type_0 = const()[name = tensor("obj_151_pad_type_0"), val = tensor("custom")]; + tensor obj_151_pad_0 = const()[name = tensor("obj_151_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_10_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(277648704)))]; + tensor layers_10_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_10_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278828416)))]; + tensor obj_151_cast_fp16 = conv(bias = layers_10_encoder_attn_o_proj_bias_to_fp16, dilations = var_2415, groups = var_2255, pad = obj_151_pad_0, pad_type = obj_151_pad_type_0, strides = var_2413, weight = layers_10_encoder_attn_o_proj_weight_to_fp16, x = input_103_cast_fp16)[name = tensor("obj_151_cast_fp16")]; + tensor inputs_65_cast_fp16 = add(x = inputs_63_cast_fp16, y = obj_151_cast_fp16)[name = tensor("inputs_65_cast_fp16")]; + tensor var_2424 = const()[name = tensor("op_2424"), val = tensor([1])]; + tensor channels_mean_65_cast_fp16 = reduce_mean(axes = var_2424, keep_dims = var_2256, x = inputs_65_cast_fp16)[name = tensor("channels_mean_65_cast_fp16")]; + tensor zero_mean_65_cast_fp16 = sub(x = inputs_65_cast_fp16, y = channels_mean_65_cast_fp16)[name = tensor("zero_mean_65_cast_fp16")]; + tensor zero_mean_sq_65_cast_fp16 = mul(x = zero_mean_65_cast_fp16, y = zero_mean_65_cast_fp16)[name = tensor("zero_mean_sq_65_cast_fp16")]; + tensor var_2428 = const()[name = tensor("op_2428"), val = tensor([1])]; + tensor var_2429_cast_fp16 = reduce_mean(axes = var_2428, keep_dims = var_2256, x = zero_mean_sq_65_cast_fp16)[name = tensor("op_2429_cast_fp16")]; + tensor var_2430_to_fp16 = const()[name = tensor("op_2430_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2431_cast_fp16 = add(x = var_2429_cast_fp16, y = var_2430_to_fp16)[name = tensor("op_2431_cast_fp16")]; + tensor denom_65_epsilon_0_to_fp16 = const()[name = tensor("denom_65_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_65_cast_fp16 = rsqrt(epsilon = denom_65_epsilon_0_to_fp16, x = var_2431_cast_fp16)[name = tensor("denom_65_cast_fp16")]; + tensor out_65_cast_fp16 = mul(x = zero_mean_65_cast_fp16, y = denom_65_cast_fp16)[name = tensor("out_65_cast_fp16")]; + tensor input_105_gamma_0_to_fp16 = const()[name = tensor("input_105_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278830016)))]; + tensor input_105_beta_0_to_fp16 = const()[name = tensor("input_105_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278831616)))]; + tensor input_105_epsilon_0_to_fp16 = const()[name = tensor("input_105_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_105_cast_fp16 = batch_norm(beta = input_105_beta_0_to_fp16, epsilon = input_105_epsilon_0_to_fp16, gamma = input_105_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_65_cast_fp16)[name = tensor("input_105_cast_fp16")]; + tensor var_2442 = const()[name = tensor("op_2442"), val = tensor([1, 1])]; + tensor var_2444 = const()[name = tensor("op_2444"), val = tensor([1, 1])]; + tensor input_107_pad_type_0 = const()[name = tensor("input_107_pad_type_0"), val = tensor("custom")]; + tensor input_107_pad_0 = const()[name = tensor("input_107_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_fc1_weight_to_fp16 = const()[name = tensor("layers_10_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278833216)))]; + tensor layers_10_fc1_bias_to_fp16 = const()[name = tensor("layers_10_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(283551872)))]; + tensor input_107_cast_fp16 = conv(bias = layers_10_fc1_bias_to_fp16, dilations = var_2444, groups = var_2255, pad = input_107_pad_0, pad_type = input_107_pad_type_0, strides = var_2442, weight = layers_10_fc1_weight_to_fp16, x = input_105_cast_fp16)[name = tensor("input_107_cast_fp16")]; + tensor input_109_mode_0 = const()[name = tensor("input_109_mode_0"), val = tensor("EXACT")]; + tensor input_109_cast_fp16 = gelu(mode = input_109_mode_0, x = input_107_cast_fp16)[name = tensor("input_109_cast_fp16")]; + tensor var_2450 = const()[name = tensor("op_2450"), val = tensor([1, 1])]; + tensor var_2452 = const()[name = tensor("op_2452"), val = tensor([1, 1])]; + tensor hidden_states_23_pad_type_0 = const()[name = tensor("hidden_states_23_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_23_pad_0 = const()[name = tensor("hidden_states_23_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_10_fc2_weight_to_fp16 = const()[name = tensor("layers_10_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(283558080)))]; + tensor layers_10_fc2_bias_to_fp16 = const()[name = tensor("layers_10_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(288276736)))]; + tensor hidden_states_23_cast_fp16 = conv(bias = layers_10_fc2_bias_to_fp16, dilations = var_2452, groups = var_2255, pad = hidden_states_23_pad_0, pad_type = hidden_states_23_pad_type_0, strides = var_2450, weight = layers_10_fc2_weight_to_fp16, x = input_109_cast_fp16)[name = tensor("hidden_states_23_cast_fp16")]; + tensor inputs_67_cast_fp16 = add(x = inputs_65_cast_fp16, y = hidden_states_23_cast_fp16)[name = tensor("inputs_67_cast_fp16")]; + tensor var_2466 = const()[name = tensor("op_2466"), val = tensor(3)]; + tensor var_2473 = const()[name = tensor("op_2473"), val = tensor(1)]; + tensor var_2474 = const()[name = tensor("op_2474"), val = tensor(true)]; + tensor var_2486 = const()[name = tensor("op_2486"), val = tensor([1])]; + tensor channels_mean_67_cast_fp16 = reduce_mean(axes = var_2486, keep_dims = var_2474, x = inputs_67_cast_fp16)[name = tensor("channels_mean_67_cast_fp16")]; + tensor zero_mean_67_cast_fp16 = sub(x = inputs_67_cast_fp16, y = channels_mean_67_cast_fp16)[name = tensor("zero_mean_67_cast_fp16")]; + tensor zero_mean_sq_67_cast_fp16 = mul(x = zero_mean_67_cast_fp16, y = zero_mean_67_cast_fp16)[name = tensor("zero_mean_sq_67_cast_fp16")]; + tensor var_2490 = const()[name = tensor("op_2490"), val = tensor([1])]; + tensor var_2491_cast_fp16 = reduce_mean(axes = var_2490, keep_dims = var_2474, x = zero_mean_sq_67_cast_fp16)[name = tensor("op_2491_cast_fp16")]; + tensor var_2492_to_fp16 = const()[name = tensor("op_2492_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2493_cast_fp16 = add(x = var_2491_cast_fp16, y = var_2492_to_fp16)[name = tensor("op_2493_cast_fp16")]; + tensor denom_67_epsilon_0_to_fp16 = const()[name = tensor("denom_67_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_67_cast_fp16 = rsqrt(epsilon = denom_67_epsilon_0_to_fp16, x = var_2493_cast_fp16)[name = tensor("denom_67_cast_fp16")]; + tensor out_67_cast_fp16 = mul(x = zero_mean_67_cast_fp16, y = denom_67_cast_fp16)[name = tensor("out_67_cast_fp16")]; + tensor obj_155_gamma_0_to_fp16 = const()[name = tensor("obj_155_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(288278336)))]; + tensor obj_155_beta_0_to_fp16 = const()[name = tensor("obj_155_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(288279936)))]; + tensor obj_155_epsilon_0_to_fp16 = const()[name = tensor("obj_155_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_155_cast_fp16 = batch_norm(beta = obj_155_beta_0_to_fp16, epsilon = obj_155_epsilon_0_to_fp16, gamma = obj_155_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_67_cast_fp16)[name = tensor("obj_155_cast_fp16")]; + tensor var_2508 = const()[name = tensor("op_2508"), val = tensor([1, 1])]; + tensor var_2510 = const()[name = tensor("op_2510"), val = tensor([1, 1])]; + tensor query_45_pad_type_0 = const()[name = tensor("query_45_pad_type_0"), val = tensor("custom")]; + tensor query_45_pad_0 = const()[name = tensor("query_45_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(288281536)))]; + tensor layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289461248)))]; + tensor query_45_cast_fp16 = conv(bias = layers_11_self_attn_q_proj_bias_to_fp16, dilations = var_2510, groups = var_2473, pad = query_45_pad_0, pad_type = query_45_pad_type_0, strides = var_2508, weight = layers_11_self_attn_q_proj_weight_to_fp16, x = obj_155_cast_fp16)[name = tensor("query_45_cast_fp16")]; + tensor var_2514 = const()[name = tensor("op_2514"), val = tensor([1, 1])]; + tensor var_2516 = const()[name = tensor("op_2516"), val = tensor([1, 1])]; + tensor current_key_pad_type_0 = const()[name = tensor("current_key_pad_type_0"), val = tensor("custom")]; + tensor current_key_pad_0 = const()[name = tensor("current_key_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289462848)))]; + tensor current_key_cast_fp16 = conv(dilations = var_2516, groups = var_2473, pad = current_key_pad_0, pad_type = current_key_pad_type_0, strides = var_2514, weight = layers_11_self_attn_k_proj_weight_to_fp16, x = obj_155_cast_fp16)[name = tensor("current_key_cast_fp16")]; + tensor var_2521 = const()[name = tensor("op_2521"), val = tensor([1, 1])]; + tensor var_2523 = const()[name = tensor("op_2523"), val = tensor([1, 1])]; + tensor current_value_pad_type_0 = const()[name = tensor("current_value_pad_type_0"), val = tensor("custom")]; + tensor current_value_pad_0 = const()[name = tensor("current_value_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290642560)))]; + tensor layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291822272)))]; + tensor current_value_cast_fp16 = conv(bias = layers_11_self_attn_v_proj_bias_to_fp16, dilations = var_2523, groups = var_2473, pad = current_value_pad_0, pad_type = current_value_pad_type_0, strides = var_2521, weight = layers_11_self_attn_v_proj_weight_to_fp16, x = obj_155_cast_fp16)[name = tensor("current_value_cast_fp16")]; + tensor var_2530_cast_fp16 = mul(x = current_key_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_2530_cast_fp16")]; + tensor var_2532_cast_fp16 = mul(x = var_63_cast_fp16_11, y = var_161_cast_fp16)[name = tensor("op_2532_cast_fp16")]; + tensor key_45_cast_fp16 = add(x = var_2530_cast_fp16, y = var_2532_cast_fp16)[name = tensor("key_45_cast_fp16")]; + tensor var_2534_cast_fp16 = mul(x = current_value_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_2534_cast_fp16")]; + tensor var_2536_cast_fp16 = mul(x = var_78_cast_fp16_11, y = var_161_cast_fp16)[name = tensor("op_2536_cast_fp16")]; + tensor value_45_cast_fp16 = add(x = var_2534_cast_fp16, y = var_2536_cast_fp16)[name = tensor("value_45_cast_fp16")]; + tensor var_2539 = const()[name = tensor("op_2539"), val = tensor([1, 12, 64, -1])]; + tensor var_2540_cast_fp16 = reshape(shape = var_2539, x = query_45_cast_fp16)[name = tensor("op_2540_cast_fp16")]; + tensor var_2541_to_fp16 = const()[name = tensor("op_2541_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2542_cast_fp16 = mul(x = var_2540_cast_fp16, y = var_2541_to_fp16)[name = tensor("op_2542_cast_fp16")]; + tensor var_2543 = const()[name = tensor("op_2543"), val = tensor([1, 12, 64, -1])]; + tensor var_2544_cast_fp16 = reshape(shape = var_2543, x = key_45_cast_fp16)[name = tensor("op_2544_cast_fp16")]; + tensor mh_w_67_transpose_x_0 = const()[name = tensor("mh_w_67_transpose_x_0"), val = tensor(true)]; + tensor mh_w_67_transpose_y_0 = const()[name = tensor("mh_w_67_transpose_y_0"), val = tensor(false)]; + tensor mh_w_67_cast_fp16 = matmul(transpose_x = mh_w_67_transpose_x_0, transpose_y = mh_w_67_transpose_y_0, x = var_2542_cast_fp16, y = var_2544_cast_fp16)[name = tensor("mh_w_67_cast_fp16")]; + tensor mh_w_69_cast_fp16 = add(x = mh_w_67_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_69_cast_fp16")]; + tensor var_2552_cast_fp16 = softmax(axis = var_2466, x = mh_w_69_cast_fp16)[name = tensor("op_2552_cast_fp16")]; + tensor var_2553 = const()[name = tensor("op_2553"), val = tensor([1, 12, 64, -1])]; + tensor var_2554_cast_fp16 = reshape(shape = var_2553, x = value_45_cast_fp16)[name = tensor("op_2554_cast_fp16")]; + tensor attn_45_transpose_x_0 = const()[name = tensor("attn_45_transpose_x_0"), val = tensor(false)]; + tensor attn_45_transpose_y_0 = const()[name = tensor("attn_45_transpose_y_0"), val = tensor(true)]; + tensor attn_45_cast_fp16 = matmul(transpose_x = attn_45_transpose_x_0, transpose_y = attn_45_transpose_y_0, x = var_2554_cast_fp16, y = var_2552_cast_fp16)[name = tensor("attn_45_cast_fp16")]; + tensor var_2557 = const()[name = tensor("op_2557"), val = tensor([1, 768, 1, -1])]; + tensor input_111_cast_fp16 = reshape(shape = var_2557, x = attn_45_cast_fp16)[name = tensor("input_111_cast_fp16")]; + tensor var_2561 = const()[name = tensor("op_2561"), val = tensor([1, 1])]; + tensor var_2563 = const()[name = tensor("op_2563"), val = tensor([1, 1])]; + tensor obj_161_pad_type_0 = const()[name = tensor("obj_161_pad_type_0"), val = tensor("custom")]; + tensor obj_161_pad_0 = const()[name = tensor("obj_161_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291823872)))]; + tensor layers_11_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293003584)))]; + tensor obj_161_cast_fp16 = conv(bias = layers_11_self_attn_o_proj_bias_to_fp16, dilations = var_2563, groups = var_2473, pad = obj_161_pad_0, pad_type = obj_161_pad_type_0, strides = var_2561, weight = layers_11_self_attn_o_proj_weight_to_fp16, x = input_111_cast_fp16)[name = tensor("obj_161_cast_fp16")]; + tensor inputs_69_cast_fp16 = add(x = inputs_67_cast_fp16, y = obj_161_cast_fp16)[name = tensor("inputs_69_cast_fp16")]; + tensor var_2573 = const()[name = tensor("op_2573"), val = tensor([1])]; + tensor channels_mean_69_cast_fp16 = reduce_mean(axes = var_2573, keep_dims = var_2474, x = inputs_69_cast_fp16)[name = tensor("channels_mean_69_cast_fp16")]; + tensor zero_mean_69_cast_fp16 = sub(x = inputs_69_cast_fp16, y = channels_mean_69_cast_fp16)[name = tensor("zero_mean_69_cast_fp16")]; + tensor zero_mean_sq_69_cast_fp16 = mul(x = zero_mean_69_cast_fp16, y = zero_mean_69_cast_fp16)[name = tensor("zero_mean_sq_69_cast_fp16")]; + tensor var_2577 = const()[name = tensor("op_2577"), val = tensor([1])]; + tensor var_2578_cast_fp16 = reduce_mean(axes = var_2577, keep_dims = var_2474, x = zero_mean_sq_69_cast_fp16)[name = tensor("op_2578_cast_fp16")]; + tensor var_2579_to_fp16 = const()[name = tensor("op_2579_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2580_cast_fp16 = add(x = var_2578_cast_fp16, y = var_2579_to_fp16)[name = tensor("op_2580_cast_fp16")]; + tensor denom_69_epsilon_0_to_fp16 = const()[name = tensor("denom_69_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_69_cast_fp16 = rsqrt(epsilon = denom_69_epsilon_0_to_fp16, x = var_2580_cast_fp16)[name = tensor("denom_69_cast_fp16")]; + tensor out_69_cast_fp16 = mul(x = zero_mean_69_cast_fp16, y = denom_69_cast_fp16)[name = tensor("out_69_cast_fp16")]; + tensor obj_163_gamma_0_to_fp16 = const()[name = tensor("obj_163_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293005184)))]; + tensor obj_163_beta_0_to_fp16 = const()[name = tensor("obj_163_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293006784)))]; + tensor obj_163_epsilon_0_to_fp16 = const()[name = tensor("obj_163_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor obj_163_cast_fp16 = batch_norm(beta = obj_163_beta_0_to_fp16, epsilon = obj_163_epsilon_0_to_fp16, gamma = obj_163_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_69_cast_fp16)[name = tensor("obj_163_cast_fp16")]; + tensor var_2595 = const()[name = tensor("op_2595"), val = tensor([1, 1])]; + tensor var_2597 = const()[name = tensor("op_2597"), val = tensor([1, 1])]; + tensor query_pad_type_0 = const()[name = tensor("query_pad_type_0"), val = tensor("custom")]; + tensor query_pad_0 = const()[name = tensor("query_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_11_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293008384)))]; + tensor layers_11_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_11_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(294188096)))]; + tensor query_cast_fp16 = conv(bias = layers_11_encoder_attn_q_proj_bias_to_fp16, dilations = var_2597, groups = var_2473, pad = query_pad_0, pad_type = query_pad_type_0, strides = var_2595, weight = layers_11_encoder_attn_q_proj_weight_to_fp16, x = obj_163_cast_fp16)[name = tensor("query_cast_fp16")]; + tensor var_2601 = const()[name = tensor("op_2601"), val = tensor([1, 1])]; + tensor var_2603 = const()[name = tensor("op_2603"), val = tensor([1, 1])]; + tensor key_pad_type_0 = const()[name = tensor("key_pad_type_0"), val = tensor("custom")]; + tensor key_pad_0 = const()[name = tensor("key_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_11_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(294189696)))]; + tensor key_cast_fp16 = conv(dilations = var_2603, groups = var_2473, pad = key_pad_0, pad_type = key_pad_type_0, strides = var_2601, weight = layers_11_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_cast_fp16")]; + tensor var_2608 = const()[name = tensor("op_2608"), val = tensor([1, 1])]; + tensor var_2610 = const()[name = tensor("op_2610"), val = tensor([1, 1])]; + tensor value_pad_type_0 = const()[name = tensor("value_pad_type_0"), val = tensor("custom")]; + tensor value_pad_0 = const()[name = tensor("value_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_11_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(295369408)))]; + tensor layers_11_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_11_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(296549120)))]; + tensor value_cast_fp16 = conv(bias = layers_11_encoder_attn_v_proj_bias_to_fp16, dilations = var_2610, groups = var_2473, pad = value_pad_0, pad_type = value_pad_type_0, strides = var_2608, weight = layers_11_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_cast_fp16")]; + tensor var_2614 = const()[name = tensor("op_2614"), val = tensor([1, 12, 64, -1])]; + tensor var_2615_cast_fp16 = reshape(shape = var_2614, x = query_cast_fp16)[name = tensor("op_2615_cast_fp16")]; + tensor var_2616_to_fp16 = const()[name = tensor("op_2616_to_fp16"), val = tensor(0x1p-3)]; + tensor var_2617_cast_fp16 = mul(x = var_2615_cast_fp16, y = var_2616_to_fp16)[name = tensor("op_2617_cast_fp16")]; + tensor var_2618 = const()[name = tensor("op_2618"), val = tensor([1, 12, 64, -1])]; + tensor var_2619_cast_fp16 = reshape(shape = var_2618, x = key_cast_fp16)[name = tensor("op_2619_cast_fp16")]; + tensor mh_w_transpose_x_0 = const()[name = tensor("mh_w_transpose_x_0"), val = tensor(true)]; + tensor mh_w_transpose_y_0 = const()[name = tensor("mh_w_transpose_y_0"), val = tensor(false)]; + tensor mh_w_cast_fp16 = matmul(transpose_x = mh_w_transpose_x_0, transpose_y = mh_w_transpose_y_0, x = var_2617_cast_fp16, y = var_2619_cast_fp16)[name = tensor("mh_w_cast_fp16")]; + tensor obj_167_cast_fp16 = softmax(axis = var_2466, x = mh_w_cast_fp16)[name = tensor("obj_167_cast_fp16")]; + tensor var_2623 = const()[name = tensor("op_2623"), val = tensor([1, 12, 64, -1])]; + tensor var_2624_cast_fp16 = reshape(shape = var_2623, x = value_cast_fp16)[name = tensor("op_2624_cast_fp16")]; + tensor attn_transpose_x_0 = const()[name = tensor("attn_transpose_x_0"), val = tensor(false)]; + tensor attn_transpose_y_0 = const()[name = tensor("attn_transpose_y_0"), val = tensor(true)]; + tensor attn_cast_fp16 = matmul(transpose_x = attn_transpose_x_0, transpose_y = attn_transpose_y_0, x = var_2624_cast_fp16, y = obj_167_cast_fp16)[name = tensor("attn_cast_fp16")]; + tensor var_2627 = const()[name = tensor("op_2627"), val = tensor([1, 768, 1, -1])]; + tensor input_113_cast_fp16 = reshape(shape = var_2627, x = attn_cast_fp16)[name = tensor("input_113_cast_fp16")]; + tensor var_2631 = const()[name = tensor("op_2631"), val = tensor([1, 1])]; + tensor var_2633 = const()[name = tensor("op_2633"), val = tensor([1, 1])]; + tensor obj_165_pad_type_0 = const()[name = tensor("obj_165_pad_type_0"), val = tensor("custom")]; + tensor obj_165_pad_0 = const()[name = tensor("obj_165_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_11_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(296550720)))]; + tensor layers_11_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_11_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297730432)))]; + tensor obj_165_cast_fp16 = conv(bias = layers_11_encoder_attn_o_proj_bias_to_fp16, dilations = var_2633, groups = var_2473, pad = obj_165_pad_0, pad_type = obj_165_pad_type_0, strides = var_2631, weight = layers_11_encoder_attn_o_proj_weight_to_fp16, x = input_113_cast_fp16)[name = tensor("obj_165_cast_fp16")]; + tensor inputs_71_cast_fp16 = add(x = inputs_69_cast_fp16, y = obj_165_cast_fp16)[name = tensor("inputs_71_cast_fp16")]; + tensor var_2639 = const()[name = tensor("op_2639"), val = tensor([1])]; + tensor channels_mean_71_cast_fp16 = reduce_mean(axes = var_2639, keep_dims = var_2474, x = inputs_71_cast_fp16)[name = tensor("channels_mean_71_cast_fp16")]; + tensor zero_mean_71_cast_fp16 = sub(x = inputs_71_cast_fp16, y = channels_mean_71_cast_fp16)[name = tensor("zero_mean_71_cast_fp16")]; + tensor zero_mean_sq_71_cast_fp16 = mul(x = zero_mean_71_cast_fp16, y = zero_mean_71_cast_fp16)[name = tensor("zero_mean_sq_71_cast_fp16")]; + tensor var_2643 = const()[name = tensor("op_2643"), val = tensor([1])]; + tensor var_2644_cast_fp16 = reduce_mean(axes = var_2643, keep_dims = var_2474, x = zero_mean_sq_71_cast_fp16)[name = tensor("op_2644_cast_fp16")]; + tensor var_2645_to_fp16 = const()[name = tensor("op_2645_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2646_cast_fp16 = add(x = var_2644_cast_fp16, y = var_2645_to_fp16)[name = tensor("op_2646_cast_fp16")]; + tensor denom_71_epsilon_0_to_fp16 = const()[name = tensor("denom_71_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_71_cast_fp16 = rsqrt(epsilon = denom_71_epsilon_0_to_fp16, x = var_2646_cast_fp16)[name = tensor("denom_71_cast_fp16")]; + tensor out_71_cast_fp16 = mul(x = zero_mean_71_cast_fp16, y = denom_71_cast_fp16)[name = tensor("out_71_cast_fp16")]; + tensor input_115_gamma_0_to_fp16 = const()[name = tensor("input_115_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297732032)))]; + tensor input_115_beta_0_to_fp16 = const()[name = tensor("input_115_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297733632)))]; + tensor input_115_epsilon_0_to_fp16 = const()[name = tensor("input_115_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor input_115_cast_fp16 = batch_norm(beta = input_115_beta_0_to_fp16, epsilon = input_115_epsilon_0_to_fp16, gamma = input_115_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_71_cast_fp16)[name = tensor("input_115_cast_fp16")]; + tensor var_2657 = const()[name = tensor("op_2657"), val = tensor([1, 1])]; + tensor var_2659 = const()[name = tensor("op_2659"), val = tensor([1, 1])]; + tensor input_117_pad_type_0 = const()[name = tensor("input_117_pad_type_0"), val = tensor("custom")]; + tensor input_117_pad_0 = const()[name = tensor("input_117_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_fc1_weight_to_fp16 = const()[name = tensor("layers_11_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297735232)))]; + tensor layers_11_fc1_bias_to_fp16 = const()[name = tensor("layers_11_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(302453888)))]; + tensor input_117_cast_fp16 = conv(bias = layers_11_fc1_bias_to_fp16, dilations = var_2659, groups = var_2473, pad = input_117_pad_0, pad_type = input_117_pad_type_0, strides = var_2657, weight = layers_11_fc1_weight_to_fp16, x = input_115_cast_fp16)[name = tensor("input_117_cast_fp16")]; + tensor input_mode_0 = const()[name = tensor("input_mode_0"), val = tensor("EXACT")]; + tensor input_cast_fp16 = gelu(mode = input_mode_0, x = input_117_cast_fp16)[name = tensor("input_cast_fp16")]; + tensor var_2665 = const()[name = tensor("op_2665"), val = tensor([1, 1])]; + tensor var_2667 = const()[name = tensor("op_2667"), val = tensor([1, 1])]; + tensor hidden_states_25_pad_type_0 = const()[name = tensor("hidden_states_25_pad_type_0"), val = tensor("custom")]; + tensor hidden_states_25_pad_0 = const()[name = tensor("hidden_states_25_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor layers_11_fc2_weight_to_fp16 = const()[name = tensor("layers_11_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(302460096)))]; + tensor layers_11_fc2_bias_to_fp16 = const()[name = tensor("layers_11_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307178752)))]; + tensor hidden_states_25_cast_fp16 = conv(bias = layers_11_fc2_bias_to_fp16, dilations = var_2667, groups = var_2473, pad = hidden_states_25_pad_0, pad_type = hidden_states_25_pad_type_0, strides = var_2665, weight = layers_11_fc2_weight_to_fp16, x = input_cast_fp16)[name = tensor("hidden_states_25_cast_fp16")]; + tensor inputs_cast_fp16 = add(x = inputs_71_cast_fp16, y = hidden_states_25_cast_fp16)[name = tensor("inputs_cast_fp16")]; + tensor var_2677 = const()[name = tensor("op_2677"), val = tensor(true)]; + tensor var_2681 = const()[name = tensor("op_2681"), val = tensor([1])]; + tensor channels_mean_cast_fp16 = reduce_mean(axes = var_2681, keep_dims = var_2677, x = inputs_cast_fp16)[name = tensor("channels_mean_cast_fp16")]; + tensor zero_mean_cast_fp16 = sub(x = inputs_cast_fp16, y = channels_mean_cast_fp16)[name = tensor("zero_mean_cast_fp16")]; + tensor zero_mean_sq_cast_fp16 = mul(x = zero_mean_cast_fp16, y = zero_mean_cast_fp16)[name = tensor("zero_mean_sq_cast_fp16")]; + tensor var_2685 = const()[name = tensor("op_2685"), val = tensor([1])]; + tensor var_2686_cast_fp16 = reduce_mean(axes = var_2685, keep_dims = var_2677, x = zero_mean_sq_cast_fp16)[name = tensor("op_2686_cast_fp16")]; + tensor var_2687_to_fp16 = const()[name = tensor("op_2687_to_fp16"), val = tensor(0x1.5p-17)]; + tensor var_2688_cast_fp16 = add(x = var_2686_cast_fp16, y = var_2687_to_fp16)[name = tensor("op_2688_cast_fp16")]; + tensor denom_epsilon_0_to_fp16 = const()[name = tensor("denom_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; + tensor denom_cast_fp16 = rsqrt(epsilon = denom_epsilon_0_to_fp16, x = var_2688_cast_fp16)[name = tensor("denom_cast_fp16")]; + tensor out_cast_fp16 = mul(x = zero_mean_cast_fp16, y = denom_cast_fp16)[name = tensor("out_cast_fp16")]; + tensor hidden_states_gamma_0_to_fp16 = const()[name = tensor("hidden_states_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307180352)))]; + tensor hidden_states_beta_0_to_fp16 = const()[name = tensor("hidden_states_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307181952)))]; + tensor hidden_states_epsilon_0_to_fp16 = const()[name = tensor("hidden_states_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; + tensor hidden_states_cast_fp16 = batch_norm(beta = hidden_states_beta_0_to_fp16, epsilon = hidden_states_epsilon_0_to_fp16, gamma = hidden_states_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_cast_fp16)[name = tensor("hidden_states_cast_fp16")]; + tensor var_2698_axes_0 = const()[name = tensor("op_2698_axes_0"), val = tensor([2])]; + tensor var_2698_cast_fp16 = squeeze(axes = var_2698_axes_0, x = hidden_states_cast_fp16)[name = tensor("op_2698_cast_fp16")]; + tensor var_2701_perm_0 = const()[name = tensor("op_2701_perm_0"), val = tensor([0, 2, 1])]; + tensor linear_0_bias_0_to_fp16 = const()[name = tensor("linear_0_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307183552)))]; + tensor transpose_0 = transpose(perm = var_2701_perm_0, x = var_2698_cast_fp16)[name = tensor("transpose_0")]; + tensor logits = linear(bias = linear_0_bias_0_to_fp16, weight = embed_tokens_weight_to_fp16, x = transpose_0)[name = tensor("linear_0_cast_fp16")]; + tensor var_2705 = const()[name = tensor("op_2705"), val = tensor(1)]; + tensor obj_171_interleave_0 = const()[name = tensor("obj_171_interleave_0"), val = tensor(false)]; + tensor key_cache_updates = concat(axis = var_2705, interleave = obj_171_interleave_0, values = (current_key_1_cast_fp16, current_key_3_cast_fp16, current_key_5_cast_fp16, current_key_7_cast_fp16, current_key_9_cast_fp16, current_key_11_cast_fp16, current_key_13_cast_fp16, current_key_15_cast_fp16, current_key_17_cast_fp16, current_key_19_cast_fp16, current_key_21_cast_fp16, current_key_cast_fp16))[name = tensor("obj_171_cast_fp16")]; + tensor var_2708 = const()[name = tensor("op_2708"), val = tensor(1)]; + tensor obj_173_interleave_0 = const()[name = tensor("obj_173_interleave_0"), val = tensor(false)]; + tensor value_cache_updates = concat(axis = var_2708, interleave = obj_173_interleave_0, values = (current_value_1_cast_fp16, current_value_3_cast_fp16, current_value_5_cast_fp16, current_value_7_cast_fp16, current_value_9_cast_fp16, current_value_11_cast_fp16, current_value_13_cast_fp16, current_value_15_cast_fp16, current_value_17_cast_fp16, current_value_19_cast_fp16, current_value_21_cast_fp16, current_value_cast_fp16))[name = tensor("obj_173_cast_fp16")]; + tensor var_2719_begin_0 = const()[name = tensor("op_2719_begin_0"), val = tensor([0, 3, 0, 0])]; + tensor var_2719_end_0 = const()[name = tensor("op_2719_end_0"), val = tensor([1, 4, 1, 1500])]; + tensor var_2719_end_mask_0 = const()[name = tensor("op_2719_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2719_cast_fp16 = slice_by_index(begin = var_2719_begin_0, end = var_2719_end_0, end_mask = var_2719_end_mask_0, x = obj_83_cast_fp16)[name = tensor("op_2719_cast_fp16")]; + tensor var_2722_begin_0 = const()[name = tensor("op_2722_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2722_end_0 = const()[name = tensor("op_2722_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_2722_end_mask_0 = const()[name = tensor("op_2722_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_2722_squeeze_mask_0 = const()[name = tensor("op_2722_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_2722_cast_fp16 = slice_by_index(begin = var_2722_begin_0, end = var_2722_end_0, end_mask = var_2722_end_mask_0, squeeze_mask = var_2722_squeeze_mask_0, x = var_2719_cast_fp16)[name = tensor("op_2722_cast_fp16")]; + tensor var_2737_begin_0 = const()[name = tensor("op_2737_begin_0"), val = tensor([0, 9, 0, 0])]; + tensor var_2737_end_0 = const()[name = tensor("op_2737_end_0"), val = tensor([1, 10, 1, 1500])]; + tensor var_2737_end_mask_0 = const()[name = tensor("op_2737_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2737_cast_fp16 = slice_by_index(begin = var_2737_begin_0, end = var_2737_end_0, end_mask = var_2737_end_mask_0, x = obj_83_cast_fp16)[name = tensor("op_2737_cast_fp16")]; + tensor var_2740_begin_0 = const()[name = tensor("op_2740_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2740_end_0 = const()[name = tensor("op_2740_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_2740_end_mask_0 = const()[name = tensor("op_2740_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_2740_squeeze_mask_0 = const()[name = tensor("op_2740_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_2740_cast_fp16 = slice_by_index(begin = var_2740_begin_0, end = var_2740_end_0, end_mask = var_2740_end_mask_0, squeeze_mask = var_2740_squeeze_mask_0, x = var_2737_cast_fp16)[name = tensor("op_2740_cast_fp16")]; + tensor var_2755_begin_0 = const()[name = tensor("op_2755_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2755_end_0 = const()[name = tensor("op_2755_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_2755_end_mask_0 = const()[name = tensor("op_2755_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2755_cast_fp16 = slice_by_index(begin = var_2755_begin_0, end = var_2755_end_0, end_mask = var_2755_end_mask_0, x = obj_125_cast_fp16)[name = tensor("op_2755_cast_fp16")]; + tensor var_2758_begin_0 = const()[name = tensor("op_2758_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2758_end_0 = const()[name = tensor("op_2758_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_2758_end_mask_0 = const()[name = tensor("op_2758_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_2758_squeeze_mask_0 = const()[name = tensor("op_2758_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_2758_cast_fp16 = slice_by_index(begin = var_2758_begin_0, end = var_2758_end_0, end_mask = var_2758_end_mask_0, squeeze_mask = var_2758_squeeze_mask_0, x = var_2755_cast_fp16)[name = tensor("op_2758_cast_fp16")]; + tensor var_2773_begin_0 = const()[name = tensor("op_2773_begin_0"), val = tensor([0, 4, 0, 0])]; + tensor var_2773_end_0 = const()[name = tensor("op_2773_end_0"), val = tensor([1, 5, 1, 1500])]; + tensor var_2773_end_mask_0 = const()[name = tensor("op_2773_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2773_cast_fp16 = slice_by_index(begin = var_2773_begin_0, end = var_2773_end_0, end_mask = var_2773_end_mask_0, x = obj_125_cast_fp16)[name = tensor("op_2773_cast_fp16")]; + tensor var_2776_begin_0 = const()[name = tensor("op_2776_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2776_end_0 = const()[name = tensor("op_2776_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_2776_end_mask_0 = const()[name = tensor("op_2776_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_2776_squeeze_mask_0 = const()[name = tensor("op_2776_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_2776_cast_fp16 = slice_by_index(begin = var_2776_begin_0, end = var_2776_end_0, end_mask = var_2776_end_mask_0, squeeze_mask = var_2776_squeeze_mask_0, x = var_2773_cast_fp16)[name = tensor("op_2776_cast_fp16")]; + tensor var_2791_begin_0 = const()[name = tensor("op_2791_begin_0"), val = tensor([0, 7, 0, 0])]; + tensor var_2791_end_0 = const()[name = tensor("op_2791_end_0"), val = tensor([1, 8, 1, 1500])]; + tensor var_2791_end_mask_0 = const()[name = tensor("op_2791_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2791_cast_fp16 = slice_by_index(begin = var_2791_begin_0, end = var_2791_end_0, end_mask = var_2791_end_mask_0, x = obj_125_cast_fp16)[name = tensor("op_2791_cast_fp16")]; + tensor var_2794_begin_0 = const()[name = tensor("op_2794_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2794_end_0 = const()[name = tensor("op_2794_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_2794_end_mask_0 = const()[name = tensor("op_2794_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_2794_squeeze_mask_0 = const()[name = tensor("op_2794_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_2794_cast_fp16 = slice_by_index(begin = var_2794_begin_0, end = var_2794_end_0, end_mask = var_2794_end_mask_0, squeeze_mask = var_2794_squeeze_mask_0, x = var_2791_cast_fp16)[name = tensor("op_2794_cast_fp16")]; + tensor var_2809_begin_0 = const()[name = tensor("op_2809_begin_0"), val = tensor([0, 8, 0, 0])]; + tensor var_2809_end_0 = const()[name = tensor("op_2809_end_0"), val = tensor([1, 9, 1, 1500])]; + tensor var_2809_end_mask_0 = const()[name = tensor("op_2809_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2809_cast_fp16 = slice_by_index(begin = var_2809_begin_0, end = var_2809_end_0, end_mask = var_2809_end_mask_0, x = obj_125_cast_fp16)[name = tensor("op_2809_cast_fp16")]; + tensor var_2812_begin_0 = const()[name = tensor("op_2812_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2812_end_0 = const()[name = tensor("op_2812_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_2812_end_mask_0 = const()[name = tensor("op_2812_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_2812_squeeze_mask_0 = const()[name = tensor("op_2812_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_2812_cast_fp16 = slice_by_index(begin = var_2812_begin_0, end = var_2812_end_0, end_mask = var_2812_end_mask_0, squeeze_mask = var_2812_squeeze_mask_0, x = var_2809_cast_fp16)[name = tensor("op_2812_cast_fp16")]; + tensor var_2827_begin_0 = const()[name = tensor("op_2827_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2827_end_0 = const()[name = tensor("op_2827_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_2827_end_mask_0 = const()[name = tensor("op_2827_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2827_cast_fp16 = slice_by_index(begin = var_2827_begin_0, end = var_2827_end_0, end_mask = var_2827_end_mask_0, x = obj_139_cast_fp16)[name = tensor("op_2827_cast_fp16")]; + tensor var_2830_begin_0 = const()[name = tensor("op_2830_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2830_end_0 = const()[name = tensor("op_2830_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_2830_end_mask_0 = const()[name = tensor("op_2830_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_2830_squeeze_mask_0 = const()[name = tensor("op_2830_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_2830_cast_fp16 = slice_by_index(begin = var_2830_begin_0, end = var_2830_end_0, end_mask = var_2830_end_mask_0, squeeze_mask = var_2830_squeeze_mask_0, x = var_2827_cast_fp16)[name = tensor("op_2830_cast_fp16")]; + tensor var_2845_begin_0 = const()[name = tensor("op_2845_begin_0"), val = tensor([0, 7, 0, 0])]; + tensor var_2845_end_0 = const()[name = tensor("op_2845_end_0"), val = tensor([1, 8, 1, 1500])]; + tensor var_2845_end_mask_0 = const()[name = tensor("op_2845_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2845_cast_fp16 = slice_by_index(begin = var_2845_begin_0, end = var_2845_end_0, end_mask = var_2845_end_mask_0, x = obj_139_cast_fp16)[name = tensor("op_2845_cast_fp16")]; + tensor var_2848_begin_0 = const()[name = tensor("op_2848_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2848_end_0 = const()[name = tensor("op_2848_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_2848_end_mask_0 = const()[name = tensor("op_2848_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_2848_squeeze_mask_0 = const()[name = tensor("op_2848_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_2848_cast_fp16 = slice_by_index(begin = var_2848_begin_0, end = var_2848_end_0, end_mask = var_2848_end_mask_0, squeeze_mask = var_2848_squeeze_mask_0, x = var_2845_cast_fp16)[name = tensor("op_2848_cast_fp16")]; + tensor var_2863_begin_0 = const()[name = tensor("op_2863_begin_0"), val = tensor([0, 9, 0, 0])]; + tensor var_2863_end_0 = const()[name = tensor("op_2863_end_0"), val = tensor([1, 10, 1, 1500])]; + tensor var_2863_end_mask_0 = const()[name = tensor("op_2863_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2863_cast_fp16 = slice_by_index(begin = var_2863_begin_0, end = var_2863_end_0, end_mask = var_2863_end_mask_0, x = obj_139_cast_fp16)[name = tensor("op_2863_cast_fp16")]; + tensor var_2866_begin_0 = const()[name = tensor("op_2866_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2866_end_0 = const()[name = tensor("op_2866_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_2866_end_mask_0 = const()[name = tensor("op_2866_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_2866_squeeze_mask_0 = const()[name = tensor("op_2866_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_2866_cast_fp16 = slice_by_index(begin = var_2866_begin_0, end = var_2866_end_0, end_mask = var_2866_end_mask_0, squeeze_mask = var_2866_squeeze_mask_0, x = var_2863_cast_fp16)[name = tensor("op_2866_cast_fp16")]; + tensor var_2881_begin_0 = const()[name = tensor("op_2881_begin_0"), val = tensor([0, 5, 0, 0])]; + tensor var_2881_end_0 = const()[name = tensor("op_2881_end_0"), val = tensor([1, 6, 1, 1500])]; + tensor var_2881_end_mask_0 = const()[name = tensor("op_2881_end_mask_0"), val = tensor([true, false, true, true])]; + tensor var_2881_cast_fp16 = slice_by_index(begin = var_2881_begin_0, end = var_2881_end_0, end_mask = var_2881_end_mask_0, x = obj_153_cast_fp16)[name = tensor("op_2881_cast_fp16")]; + tensor var_2884_begin_0 = const()[name = tensor("op_2884_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_2884_end_0 = const()[name = tensor("op_2884_end_0"), val = tensor([1, 1, 1, 1500])]; + tensor var_2884_end_mask_0 = const()[name = tensor("op_2884_end_mask_0"), val = tensor([true, true, false, true])]; + tensor var_2884_squeeze_mask_0 = const()[name = tensor("op_2884_squeeze_mask_0"), val = tensor([false, false, true, false])]; + tensor var_2884_cast_fp16 = slice_by_index(begin = var_2884_begin_0, end = var_2884_end_0, end_mask = var_2884_end_mask_0, squeeze_mask = var_2884_squeeze_mask_0, x = var_2881_cast_fp16)[name = tensor("op_2884_cast_fp16")]; + tensor var_2891 = const()[name = tensor("op_2891"), val = tensor(1)]; + tensor var_2892_interleave_0 = const()[name = tensor("op_2892_interleave_0"), val = tensor(false)]; + tensor var_2892_cast_fp16 = concat(axis = var_2891, interleave = var_2892_interleave_0, values = (var_2722_cast_fp16, var_2740_cast_fp16, var_2758_cast_fp16, var_2776_cast_fp16, var_2794_cast_fp16, var_2812_cast_fp16, var_2830_cast_fp16, var_2848_cast_fp16, var_2866_cast_fp16, var_2884_cast_fp16))[name = tensor("op_2892_cast_fp16")]; + tensor var_2894 = const()[name = tensor("op_2894"), val = tensor([1])]; + tensor var_2895 = const()[name = tensor("op_2895"), val = tensor(false)]; + tensor alignment_heads_weights = reduce_mean(axes = var_2894, keep_dims = var_2895, x = var_2892_cast_fp16)[name = tensor("obj_cast_fp16")]; + } -> (logits, key_cache_updates, value_cache_updates, alignment_heads_weights); +} \ No newline at end of file diff --git a/openai_whisper-small/TextDecoder.mlmodelc/model.mlmodel b/openai_whisper-small/TextDecoder.mlmodelc/model.mlmodel new file mode 100644 index 0000000000000000000000000000000000000000..3200504bad9d1d06bf4223e5c695bea0257696e5 --- /dev/null +++ b/openai_whisper-small/TextDecoder.mlmodelc/model.mlmodel @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7ea861c6dfdd866ed0f2e7fe0c3df7459daa44481cb25236e03698dd6d259391 +size 313629 diff --git a/openai_whisper-small/TextDecoder.mlmodelc/weights/weight.bin b/openai_whisper-small/TextDecoder.mlmodelc/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..f06c9ac384fec32001d96a53bd48156581906005 --- /dev/null +++ b/openai_whisper-small/TextDecoder.mlmodelc/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bfea8044a8f38e8d33f56585b1e75ce023d3845e2a945e20480bd7e16558016e +size 307287346 diff --git a/openai_whisper-small/config.json b/openai_whisper-small/config.json new file mode 100644 index 0000000000000000000000000000000000000000..9dee569cf0c20925208ec84fecbb95e873f8bf24 --- /dev/null +++ b/openai_whisper-small/config.json @@ -0,0 +1 @@ +{"_name_or_path": "openai/whisper-small", "activation_dropout": 0.0, "activation_function": "gelu", "architectures": ["WhisperForConditionalGeneration"], "attention_dropout": 0.0, "begin_suppress_tokens": [220, 50257], "bos_token_id": 50257, "d_model": 768, "decoder_attention_heads": 12, "decoder_ffn_dim": 3072, "decoder_layerdrop": 0.0, "decoder_layers": 12, "decoder_start_token_id": 50258, "dropout": 0.0, "encoder_attention_heads": 12, "encoder_ffn_dim": 3072, "encoder_layerdrop": 0.0, "encoder_layers": 12, "eos_token_id": 50257, "forced_decoder_ids": [[1, 50259], [2, 50359], [3, 50363]], "init_std": 0.02, "is_encoder_decoder": true, "max_length": 448, "max_source_positions": 1500, "max_target_positions": 448, "model_type": "whisper", "num_hidden_layers": 12, "num_mel_bins": 80, "pad_token_id": 50257, "scale_embedding": false, "suppress_tokens": [1, 2, 7, 8, 9, 10, 14, 25, 26, 27, 28, 29, 31, 58, 59, 60, 61, 62, 63, 90, 91, 92, 93, 359, 503, 522, 542, 873, 893, 902, 918, 922, 931, 1350, 1853, 1982, 2460, 2627, 3246, 3253, 3268, 3536, 3846, 3961, 4183, 4667, 6585, 6647, 7273, 9061, 9383, 10428, 10929, 11938, 12033, 12331, 12562, 13793, 14157, 14635, 15265, 15618, 16553, 16604, 18362, 18956, 20075, 21675, 22520, 26130, 26161, 26435, 28279, 29464, 31650, 32302, 32470, 36865, 42863, 47425, 49870, 50254, 50258, 50360, 50361, 50362], "torch_dtype": "float32", "transformers_version": "4.27.0.dev0", "use_cache": true, "vocab_size": 51865} \ No newline at end of file diff --git a/openai_whisper-small/generation_config.json b/openai_whisper-small/generation_config.json new file mode 100644 index 0000000000000000000000000000000000000000..cdd26273f9cd1ab8ecda49f5b8c033134c61cb4a --- /dev/null +++ b/openai_whisper-small/generation_config.json @@ -0,0 +1 @@ +{"alignment_heads": [[5, 3], [5, 9], [8, 0], [8, 4], [8, 7], [8, 8], [9, 0], [9, 7], [9, 9], [10, 5]], "begin_suppress_tokens": [220, 50257], "bos_token_id": 50257, "decoder_start_token_id": 50258, "eos_token_id": 50257, "forced_decoder_ids": [[1, null], [2, 50359]], "is_multilingual": true, "lang_to_id": {"<|af|>": 50327, "<|am|>": 50334, "<|ar|>": 50272, "<|as|>": 50350, "<|az|>": 50304, "<|ba|>": 50355, "<|be|>": 50330, "<|bg|>": 50292, "<|bn|>": 50302, "<|bo|>": 50347, "<|br|>": 50309, "<|bs|>": 50315, "<|ca|>": 50270, "<|cs|>": 50283, "<|cy|>": 50297, "<|da|>": 50285, "<|de|>": 50261, "<|el|>": 50281, "<|en|>": 50259, "<|es|>": 50262, "<|et|>": 50307, "<|eu|>": 50310, "<|fa|>": 50300, "<|fi|>": 50277, "<|fo|>": 50338, "<|fr|>": 50265, "<|gl|>": 50319, "<|gu|>": 50333, "<|haw|>": 50352, "<|ha|>": 50354, "<|he|>": 50279, 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