diff --git "a/speaker_segmenter/pyannote-v3-pro/W32A32/SpeakerSegmenter.mlmodelc/model.mil" "b/speaker_segmenter/pyannote-v3-pro/W32A32/SpeakerSegmenter.mlmodelc/model.mil" new file mode 100644--- /dev/null +++ "b/speaker_segmenter/pyannote-v3-pro/W32A32/SpeakerSegmenter.mlmodelc/model.mil" @@ -0,0 +1,661 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3402.3.2"}, {"coremlc-version", "3402.4.1"}, {"coremltools-component-torch", "2.6.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.2"}})] +{ + func main(tensor input_1, tensor waveform) { + tensor cast_0_dtype_0 = const()[name = tensor("cast_0_dtype_0"), val = tensor("fp32")]; + tensor cast_1_dtype_0 = const()[name = tensor("cast_1_dtype_0"), val = tensor("fp32")]; + tensor model_sincnet_wav_norm1d_bias = const()[name = tensor("model_sincnet_wav_norm1d_bias"), val = tensor([0x1.73505ep-5])]; + tensor model_sincnet_wav_norm1d_weight = const()[name = tensor("model_sincnet_wav_norm1d_weight"), val = tensor([0x1.43f862p-7])]; + tensor model_sincnet_conv1d_0_weight = const()[name = tensor("model_sincnet_conv1d_0_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor model_sincnet_norm1d_0_bias = const()[name = tensor("model_sincnet_norm1d_0_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80448)))]; + tensor model_sincnet_norm1d_0_weight = const()[name = tensor("model_sincnet_norm1d_0_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80832)))]; + tensor model_sincnet_conv1d_1_bias = const()[name = tensor("model_sincnet_conv1d_1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81216)))]; + tensor model_sincnet_conv1d_1_weight = const()[name = tensor("model_sincnet_conv1d_1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81536)))]; + tensor model_sincnet_norm1d_1_bias = const()[name = tensor("model_sincnet_norm1d_1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177600)))]; + tensor model_sincnet_norm1d_1_weight = const()[name = tensor("model_sincnet_norm1d_1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177920)))]; + tensor model_sincnet_conv1d_2_bias = const()[name = tensor("model_sincnet_conv1d_2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178240)))]; + tensor model_sincnet_conv1d_2_weight = const()[name = tensor("model_sincnet_conv1d_2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178560)))]; + tensor model_sincnet_norm1d_2_bias = const()[name = tensor("model_sincnet_norm1d_2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(250624)))]; + tensor model_sincnet_norm1d_2_weight = const()[name = tensor("model_sincnet_norm1d_2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(250944)))]; + tensor model_linear_0_bias = const()[name = tensor("model_linear_0_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(251264)))]; + tensor model_linear_0_weight = const()[name = tensor("model_linear_0_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(251840)))]; + tensor model_linear_1_bias = const()[name = tensor("model_linear_1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(382976)))]; + tensor model_linear_1_weight = const()[name = tensor("model_linear_1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(383552)))]; + tensor model_classifier_bias = const()[name = tensor("model_classifier_bias"), val = tensor([0x1.6a54f8p+4, -0x1.0dc26cp+5, 0x1.97bfb8p+3, -0x1.525dp+6, 0x1.2ab916p+5, -0x1.35a3ep+6, -0x1.126ad8p-3])]; + tensor model_classifier_weight = const()[name = tensor("model_classifier_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(449152)))]; + tensor var_4 = const()[name = tensor("op_4"), val = tensor(0)]; + tensor sliding_windows_0_size_0 = const()[name = tensor("sliding_windows_0_size_0"), val = tensor(160000)]; + tensor sliding_windows_0_stride_0 = const()[name = tensor("sliding_windows_0_stride_0"), val = tensor(16000)]; + tensor cast_0 = cast(dtype = cast_0_dtype_0, x = waveform)[name = tensor("cast_20")]; + tensor sliding_windows_0 = sliding_windows(axis = var_4, size = sliding_windows_0_size_0, stride = sliding_windows_0_stride_0, x = cast_0)[name = tensor("sliding_windows_0")]; + tensor input_1_axes_0 = const()[name = tensor("input_1_axes_0"), val = tensor([1])]; + tensor sliding_window_waveform_type_fp32 = expand_dims(axes = input_1_axes_0, x = sliding_windows_0)[name = tensor("input_1")]; + tensor var_10 = const()[name = tensor("op_10"), val = tensor(-1)]; + tensor var_18 = const()[name = tensor("op_18"), val = tensor(0x1.4f8b58p-17)]; + tensor var_27 = const()[name = tensor("op_27"), val = tensor(0x1.47ae14p-7)]; + tensor input_3 = instance_norm(beta = model_sincnet_wav_norm1d_bias, epsilon = var_18, gamma = model_sincnet_wav_norm1d_weight, x = sliding_window_waveform_type_fp32)[name = tensor("input_3")]; + tensor outputs_pad_type_0 = const()[name = tensor("outputs_pad_type_0"), val = tensor("valid")]; + tensor outputs_strides_0 = const()[name = tensor("outputs_strides_0"), val = tensor([10])]; + tensor outputs_pad_0 = const()[name = tensor("outputs_pad_0"), val = tensor([0, 0])]; + tensor outputs_dilations_0 = const()[name = tensor("outputs_dilations_0"), val = tensor([1])]; + tensor outputs_groups_0 = const()[name = tensor("outputs_groups_0"), val = tensor(1)]; + tensor outputs = conv(dilations = outputs_dilations_0, groups = outputs_groups_0, pad = outputs_pad_0, pad_type = outputs_pad_type_0, strides = outputs_strides_0, weight = model_sincnet_conv1d_0_weight, x = input_3)[name = tensor("outputs")]; + tensor input_5 = abs(x = outputs)[name = tensor("input_5")]; + tensor var_58 = const()[name = tensor("op_58"), val = tensor([3])]; + tensor var_59 = const()[name = tensor("op_59"), val = tensor([3])]; + 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])]; + tensor input_7_ceil_mode_0 = const()[name = tensor("input_7_ceil_mode_0"), val = tensor(false)]; + tensor input_7 = max_pool(ceil_mode = input_7_ceil_mode_0, kernel_sizes = var_58, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = var_59, x = input_5)[name = tensor("input_7")]; + tensor input_9 = instance_norm(beta = model_sincnet_norm1d_0_bias, epsilon = var_18, gamma = model_sincnet_norm1d_0_weight, x = input_7)[name = tensor("input_9")]; + tensor input_11 = leaky_relu(alpha = var_27, x = input_9)[name = tensor("input_11")]; + 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])]; + tensor input_13_pad_0 = const()[name = tensor("input_13_pad_0"), val = tensor([0, 0])]; + tensor input_13_dilations_0 = const()[name = tensor("input_13_dilations_0"), val = tensor([1])]; + tensor input_13_groups_0 = const()[name = tensor("input_13_groups_0"), val = tensor(1)]; + tensor input_13 = conv(bias = model_sincnet_conv1d_1_bias, 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 = model_sincnet_conv1d_1_weight, x = input_11)[name = tensor("input_13")]; + tensor var_74 = const()[name = tensor("op_74"), val = tensor([3])]; + tensor var_75 = const()[name = tensor("op_75"), val = tensor([3])]; + tensor input_15_pad_type_0 = const()[name = tensor("input_15_pad_type_0"), val = tensor("custom")]; + tensor input_15_pad_0 = const()[name = tensor("input_15_pad_0"), val = tensor([0, 0])]; + tensor input_15_ceil_mode_0 = const()[name = tensor("input_15_ceil_mode_0"), val = tensor(false)]; + tensor input_15 = max_pool(ceil_mode = input_15_ceil_mode_0, kernel_sizes = var_74, pad = input_15_pad_0, pad_type = input_15_pad_type_0, strides = var_75, x = input_13)[name = tensor("input_15")]; + tensor input_17 = instance_norm(beta = model_sincnet_norm1d_1_bias, epsilon = var_18, gamma = model_sincnet_norm1d_1_weight, x = input_15)[name = tensor("input_17")]; + tensor input_19 = leaky_relu(alpha = var_27, x = input_17)[name = tensor("input_19")]; + 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])]; + tensor input_21_pad_0 = const()[name = tensor("input_21_pad_0"), val = tensor([0, 0])]; + tensor input_21_dilations_0 = const()[name = tensor("input_21_dilations_0"), val = tensor([1])]; + tensor input_21_groups_0 = const()[name = tensor("input_21_groups_0"), val = tensor(1)]; + tensor input_21 = conv(bias = model_sincnet_conv1d_2_bias, 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 = model_sincnet_conv1d_2_weight, x = input_19)[name = tensor("input_21")]; + tensor var_90 = const()[name = tensor("op_90"), val = tensor([3])]; + tensor var_91 = const()[name = tensor("op_91"), val = tensor([3])]; + tensor input_23_pad_type_0 = const()[name = tensor("input_23_pad_type_0"), val = tensor("custom")]; + tensor input_23_pad_0 = const()[name = tensor("input_23_pad_0"), val = tensor([0, 0])]; + tensor input_23_ceil_mode_0 = const()[name = tensor("input_23_ceil_mode_0"), val = tensor(false)]; + tensor input_23 = max_pool(ceil_mode = input_23_ceil_mode_0, kernel_sizes = var_90, pad = input_23_pad_0, pad_type = input_23_pad_type_0, strides = var_91, x = input_21)[name = tensor("input_23")]; + tensor input_25 = instance_norm(beta = model_sincnet_norm1d_2_bias, epsilon = var_18, gamma = model_sincnet_norm1d_2_weight, x = input_23)[name = tensor("input_25")]; + tensor x = leaky_relu(alpha = var_27, x = input_25)[name = tensor("x")]; + tensor transpose_2_perm_0 = const()[name = tensor("transpose_2_perm_0"), val = tensor([2, 0, 1])]; + tensor add_0 = const()[name = tensor("add_0"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(452800)))]; + tensor add_1 = const()[name = tensor("add_1"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(454912)))]; + tensor concat_4 = const()[name = tensor("concat_4"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(457024)))]; + tensor concat_5 = const()[name = tensor("concat_5"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(579968)))]; + tensor concat_6 = const()[name = tensor("concat_6"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(842176)))]; + tensor concat_7 = const()[name = tensor("concat_7"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(965120)))]; + tensor input_29_lstm_layer_0_lstm_h0_reshaped = const()[name = tensor("input_29_lstm_layer_0_lstm_h0_reshaped"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1227328)))]; + tensor input_29_lstm_layer_0_direction_0 = const()[name = tensor("input_29_lstm_layer_0_direction_0"), val = tensor("bidirectional")]; + tensor input_29_lstm_layer_0_output_sequence_0 = const()[name = tensor("input_29_lstm_layer_0_output_sequence_0"), val = tensor(true)]; + tensor input_29_lstm_layer_0_recurrent_activation_0 = const()[name = tensor("input_29_lstm_layer_0_recurrent_activation_0"), val = tensor("sigmoid")]; + tensor input_29_lstm_layer_0_cell_activation_0 = const()[name = tensor("input_29_lstm_layer_0_cell_activation_0"), val = tensor("tanh")]; + tensor input_29_lstm_layer_0_activation_0 = const()[name = tensor("input_29_lstm_layer_0_activation_0"), val = tensor("tanh")]; + tensor transpose_2 = transpose(perm = transpose_2_perm_0, x = x)[name = tensor("transpose_4")]; + tensor input_29_lstm_layer_0_0, tensor input_29_lstm_layer_0_1, tensor input_29_lstm_layer_0_2 = lstm(activation = input_29_lstm_layer_0_activation_0, bias = add_0, bias_back = add_1, cell_activation = input_29_lstm_layer_0_cell_activation_0, direction = input_29_lstm_layer_0_direction_0, initial_c = input_29_lstm_layer_0_lstm_h0_reshaped, initial_h = input_29_lstm_layer_0_lstm_h0_reshaped, output_sequence = input_29_lstm_layer_0_output_sequence_0, recurrent_activation = input_29_lstm_layer_0_recurrent_activation_0, weight_hh = concat_5, weight_hh_back = concat_7, weight_ih = concat_4, weight_ih_back = concat_6, x = transpose_2)[name = tensor("input_29_lstm_layer_0")]; + tensor add_2 = const()[name = tensor("add_2"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1248896)))]; + tensor add_3 = const()[name = tensor("add_3"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1251008)))]; + tensor concat_14 = const()[name = tensor("concat_14"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1253120)))]; + tensor concat_15 = const()[name = tensor("concat_15"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1777472)))]; + tensor concat_16 = const()[name = tensor("concat_16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2039680)))]; + tensor concat_17 = const()[name = tensor("concat_17"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2564032)))]; + tensor input_29_lstm_layer_1_direction_0 = const()[name = tensor("input_29_lstm_layer_1_direction_0"), val = tensor("bidirectional")]; + tensor input_29_lstm_layer_1_output_sequence_0 = const()[name = tensor("input_29_lstm_layer_1_output_sequence_0"), val = tensor(true)]; + tensor input_29_lstm_layer_1_recurrent_activation_0 = const()[name = tensor("input_29_lstm_layer_1_recurrent_activation_0"), val = tensor("sigmoid")]; + tensor input_29_lstm_layer_1_cell_activation_0 = const()[name = tensor("input_29_lstm_layer_1_cell_activation_0"), val = tensor("tanh")]; + tensor input_29_lstm_layer_1_activation_0 = const()[name = tensor("input_29_lstm_layer_1_activation_0"), val = tensor("tanh")]; + tensor input_29_lstm_layer_1_0, tensor input_29_lstm_layer_1_1, tensor input_29_lstm_layer_1_2 = lstm(activation = input_29_lstm_layer_1_activation_0, bias = add_2, bias_back = add_3, cell_activation = input_29_lstm_layer_1_cell_activation_0, direction = input_29_lstm_layer_1_direction_0, initial_c = input_29_lstm_layer_0_lstm_h0_reshaped, initial_h = input_29_lstm_layer_0_lstm_h0_reshaped, output_sequence = input_29_lstm_layer_1_output_sequence_0, recurrent_activation = input_29_lstm_layer_1_recurrent_activation_0, weight_hh = concat_15, weight_hh_back = concat_17, weight_ih = concat_14, weight_ih_back = concat_16, x = input_29_lstm_layer_0_0)[name = tensor("input_29_lstm_layer_1")]; + tensor add_4 = const()[name = tensor("add_4"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2826240)))]; + tensor add_5 = const()[name = tensor("add_5"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2828352)))]; + tensor concat_24 = const()[name = tensor("concat_24"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2830464)))]; + tensor concat_25 = const()[name = tensor("concat_25"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3354816)))]; + tensor concat_26 = const()[name = tensor("concat_26"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3617024)))]; + tensor concat_27 = const()[name = tensor("concat_27"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4141376)))]; + tensor input_29_lstm_layer_2_direction_0 = const()[name = tensor("input_29_lstm_layer_2_direction_0"), val = tensor("bidirectional")]; + tensor input_29_lstm_layer_2_output_sequence_0 = const()[name = tensor("input_29_lstm_layer_2_output_sequence_0"), val = tensor(true)]; + tensor input_29_lstm_layer_2_recurrent_activation_0 = const()[name = tensor("input_29_lstm_layer_2_recurrent_activation_0"), val = tensor("sigmoid")]; + tensor input_29_lstm_layer_2_cell_activation_0 = const()[name = tensor("input_29_lstm_layer_2_cell_activation_0"), val = tensor("tanh")]; + tensor input_29_lstm_layer_2_activation_0 = const()[name = tensor("input_29_lstm_layer_2_activation_0"), val = tensor("tanh")]; + tensor input_29_lstm_layer_2_0, tensor input_29_lstm_layer_2_1, tensor input_29_lstm_layer_2_2 = lstm(activation = input_29_lstm_layer_2_activation_0, bias = add_4, bias_back = add_5, cell_activation = input_29_lstm_layer_2_cell_activation_0, direction = input_29_lstm_layer_2_direction_0, initial_c = input_29_lstm_layer_0_lstm_h0_reshaped, initial_h = input_29_lstm_layer_0_lstm_h0_reshaped, output_sequence = input_29_lstm_layer_2_output_sequence_0, recurrent_activation = input_29_lstm_layer_2_recurrent_activation_0, weight_hh = concat_25, weight_hh_back = concat_27, weight_ih = concat_24, weight_ih_back = concat_26, x = input_29_lstm_layer_1_0)[name = tensor("input_29_lstm_layer_2")]; + tensor add_6 = const()[name = tensor("add_6"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4403584)))]; + tensor add_7 = const()[name = tensor("add_7"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4405696)))]; + tensor concat_34 = const()[name = tensor("concat_34"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4407808)))]; + tensor concat_35 = const()[name = tensor("concat_35"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4932160)))]; + tensor concat_36 = const()[name = tensor("concat_36"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5194368)))]; + tensor concat_37 = const()[name = tensor("concat_37"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5718720)))]; + tensor input_29_batch_first_direction_0 = const()[name = tensor("input_29_batch_first_direction_0"), val = tensor("bidirectional")]; + tensor input_29_batch_first_output_sequence_0 = const()[name = tensor("input_29_batch_first_output_sequence_0"), val = tensor(true)]; + tensor input_29_batch_first_recurrent_activation_0 = const()[name = tensor("input_29_batch_first_recurrent_activation_0"), val = tensor("sigmoid")]; + tensor input_29_batch_first_cell_activation_0 = const()[name = tensor("input_29_batch_first_cell_activation_0"), val = tensor("tanh")]; + tensor input_29_batch_first_activation_0 = const()[name = tensor("input_29_batch_first_activation_0"), val = tensor("tanh")]; + tensor input_29_batch_first_0, tensor input_29_batch_first_1, tensor input_29_batch_first_2 = lstm(activation = input_29_batch_first_activation_0, bias = add_6, bias_back = add_7, cell_activation = input_29_batch_first_cell_activation_0, direction = input_29_batch_first_direction_0, initial_c = input_29_lstm_layer_0_lstm_h0_reshaped, initial_h = input_29_lstm_layer_0_lstm_h0_reshaped, output_sequence = input_29_batch_first_output_sequence_0, recurrent_activation = input_29_batch_first_recurrent_activation_0, weight_hh = concat_35, weight_hh_back = concat_37, weight_ih = concat_34, weight_ih_back = concat_36, x = input_29_lstm_layer_2_0)[name = tensor("input_29_batch_first")]; + tensor input_29_perm_0 = const()[name = tensor("input_29_perm_0"), val = tensor([1, 0, 2])]; + tensor input_29 = transpose(perm = input_29_perm_0, x = input_29_batch_first_0)[name = tensor("transpose_3")]; + tensor input_31 = linear(bias = model_linear_0_bias, weight = model_linear_0_weight, x = input_29)[name = tensor("linear_0")]; + tensor input_33 = leaky_relu(alpha = var_27, x = input_31)[name = tensor("input_33")]; + tensor input_35 = linear(bias = model_linear_1_bias, weight = model_linear_1_weight, x = input_33)[name = tensor("linear_1")]; + tensor input_37 = leaky_relu(alpha = var_27, x = input_35)[name = tensor("input_37")]; + tensor classifier_output = linear(bias = model_classifier_bias, weight = model_classifier_weight, x = input_37)[name = tensor("linear_2")]; + tensor var_154_promoted = const()[name = tensor("op_154_promoted"), val = tensor(0x1.9p+5)]; + tensor cast_1 = cast(dtype = cast_1_dtype_0, x = input_1)[name = tensor("cast_19")]; + tensor var_155 = mul(x = cast_1, y = var_154_promoted)[name = tensor("op_155")]; + tensor input = sub(x = classifier_output, y = var_155)[name = tensor("input")]; + tensor powerset_softmax = softmax(axis = var_10, x = input)[name = tensor("powerset_softmax")]; + tensor powerset_epsilon_0 = const()[name = tensor("powerset_epsilon_0"), val = tensor(0x1p-149)]; + tensor powerset = log(epsilon = powerset_epsilon_0, x = powerset_softmax)[name = tensor("powerset")]; + tensor powerset_probs_1 = exp(x = powerset)[name = tensor("powerset_probs_1")]; + tensor transpose_0 = const()[name = tensor("transpose_0"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5980928)))]; + tensor speaker_probs_bias_0 = const()[name = tensor("speaker_probs_bias_0"), val = tensor([0x0p+0, 0x0p+0, 0x0p+0])]; + tensor speaker_probs_type_fp32 = linear(bias = speaker_probs_bias_0, weight = transpose_0, x = powerset_probs_1)[name = tensor("speaker_probs")]; + tensor var_163_axis_0 = const()[name = tensor("op_163_axis_0"), val = tensor(-1)]; + tensor var_163_keep_dims_0 = const()[name = tensor("op_163_keep_dims_0"), val = tensor(false)]; + tensor var_163 = reduce_argmax(axis = var_163_axis_0, keep_dims = var_163_keep_dims_0, x = powerset)[name = tensor("op_163")]; + tensor var_165_one_hot_vector_size_0 = const()[name = tensor("op_165_one_hot_vector_size_0"), val = tensor(7)]; + tensor var_165_axis_0 = const()[name = tensor("op_165_axis_0"), val = tensor(-1)]; + tensor var_165_on_value_0 = const()[name = tensor("op_165_on_value_0"), val = tensor(1)]; + tensor var_165_off_value_0 = const()[name = tensor("op_165_off_value_0"), val = tensor(0)]; + tensor var_165 = one_hot(axis = var_165_axis_0, indices = var_163, off_value = var_165_off_value_0, on_value = var_165_on_value_0, one_hot_vector_size = var_165_one_hot_vector_size_0)[name = tensor("op_165")]; + tensor cast_2_dtype_0 = const()[name = tensor("cast_2_dtype_0"), val = tensor("fp32")]; + tensor transpose_1 = const()[name = tensor("transpose_1"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5981120)))]; + tensor speaker_ids_bias_0 = const()[name = tensor("speaker_ids_bias_0"), val = tensor([0x0p+0, 0x0p+0, 0x0p+0])]; + tensor cast_2 = cast(dtype = cast_2_dtype_0, x = var_165)[name = tensor("cast_18")]; + tensor speaker_ids_type_fp32 = linear(bias = speaker_ids_bias_0, weight = transpose_1, x = cast_2)[name = tensor("speaker_ids")]; + tensor reduce_max_0_axes_0 = const()[name = tensor("reduce_max_0_axes_0"), val = tensor([-1])]; + tensor reduce_max_0_keep_dims_0 = const()[name = tensor("reduce_max_0_keep_dims_0"), val = tensor(false)]; + tensor reduce_max_0 = reduce_max(axes = reduce_max_0_axes_0, keep_dims = reduce_max_0_keep_dims_0, x = speaker_probs_type_fp32)[name = tensor("reduce_max_0")]; + tensor _aggregated_voice_activity = const()[name = tensor("_aggregated_voice_activity"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5981312)))]; + tensor var_206_begin_0 = const()[name = tensor("op_206_begin_0"), val = tensor([0, 0])]; + tensor var_206_end_0 = const()[name = tensor("op_206_end_0"), val = tensor([1, 589])]; + tensor var_206_end_mask_0 = const()[name = tensor("op_206_end_mask_0"), val = tensor([false, true])]; + tensor var_206_squeeze_mask_0 = const()[name = tensor("op_206_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_206 = slice_by_index(begin = var_206_begin_0, end = var_206_end_0, end_mask = var_206_end_mask_0, squeeze_mask = var_206_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_206")]; + tensor slice_by_index_0 = const()[name = tensor("slice_by_index_0"), val = tensor([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588])]; + tensor scatter_0_mode_0 = const()[name = tensor("scatter_0_mode_0"), val = tensor("update")]; + tensor scatter_0_axis_0 = const()[name = tensor("scatter_0_axis_0"), val = tensor(0)]; + tensor scatter_0 = scatter(axis = scatter_0_axis_0, data = _aggregated_voice_activity, indices = slice_by_index_0, mode = scatter_0_mode_0, updates = var_206)[name = tensor("scatter_0")]; + tensor var_221 = const()[name = tensor("op_221"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5988480)))]; + tensor scatter_1_mode_0 = const()[name = tensor("scatter_1_mode_0"), val = tensor("update")]; + tensor scatter_1_axis_0 = const()[name = tensor("scatter_1_axis_0"), val = tensor(0)]; + tensor scatter_1 = scatter(axis = scatter_1_axis_0, data = _aggregated_voice_activity, indices = slice_by_index_0, mode = scatter_1_mode_0, updates = var_221)[name = tensor("scatter_1")]; + tensor var_238_begin_0 = const()[name = tensor("op_238_begin_0"), val = tensor([58])]; + tensor var_238_end_0 = const()[name = tensor("op_238_end_0"), val = tensor([647])]; + tensor var_238_end_mask_0 = const()[name = tensor("op_238_end_mask_0"), val = tensor([false])]; + tensor var_238 = slice_by_index(begin = var_238_begin_0, end = var_238_end_0, end_mask = var_238_end_mask_0, x = scatter_0)[name = tensor("op_238")]; + tensor var_241_begin_0 = const()[name = tensor("op_241_begin_0"), val = tensor([1, 0])]; + tensor var_241_end_0 = const()[name = tensor("op_241_end_0"), val = tensor([2, 589])]; + tensor var_241_end_mask_0 = const()[name = tensor("op_241_end_mask_0"), val = tensor([false, true])]; + tensor var_241_squeeze_mask_0 = const()[name = tensor("op_241_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_241 = slice_by_index(begin = var_241_begin_0, end = var_241_end_0, end_mask = var_241_end_mask_0, squeeze_mask = var_241_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_241")]; + tensor var_243 = add(x = var_238, y = var_241)[name = tensor("op_243")]; + tensor slice_by_index_2 = const()[name = tensor("slice_by_index_2"), val = tensor([58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646])]; + tensor scatter_2_mode_0 = const()[name = tensor("scatter_2_mode_0"), val = tensor("update")]; + tensor scatter_2_axis_0 = const()[name = tensor("scatter_2_axis_0"), val = tensor(0)]; + tensor scatter_2 = scatter(axis = scatter_2_axis_0, data = scatter_0, indices = slice_by_index_2, mode = scatter_2_mode_0, updates = var_243)[name = tensor("scatter_2")]; + tensor var_253_begin_0 = const()[name = tensor("op_253_begin_0"), val = tensor([58])]; + tensor var_253_end_0 = const()[name = tensor("op_253_end_0"), val = tensor([647])]; + tensor var_253_end_mask_0 = const()[name = tensor("op_253_end_mask_0"), val = tensor([false])]; + tensor var_253 = slice_by_index(begin = var_253_begin_0, end = var_253_end_0, end_mask = var_253_end_mask_0, x = scatter_1)[name = tensor("op_253")]; + tensor var_254 = const()[name = tensor("op_254"), val = tensor(0x1p+0)]; + tensor var_256 = add(x = var_253, y = var_254)[name = tensor("op_256")]; + tensor scatter_3_mode_0 = const()[name = tensor("scatter_3_mode_0"), val = tensor("update")]; + tensor scatter_3_axis_0 = const()[name = tensor("scatter_3_axis_0"), val = tensor(0)]; + tensor scatter_3 = scatter(axis = scatter_3_axis_0, data = scatter_1, indices = slice_by_index_2, mode = scatter_3_mode_0, updates = var_256)[name = tensor("scatter_3")]; + tensor var_273_begin_0 = const()[name = tensor("op_273_begin_0"), val = tensor([117])]; + tensor var_273_end_0 = const()[name = tensor("op_273_end_0"), val = tensor([706])]; + tensor var_273_end_mask_0 = const()[name = tensor("op_273_end_mask_0"), val = tensor([false])]; + tensor var_273 = slice_by_index(begin = var_273_begin_0, end = var_273_end_0, end_mask = var_273_end_mask_0, x = scatter_2)[name = tensor("op_273")]; + tensor var_276_begin_0 = const()[name = tensor("op_276_begin_0"), val = tensor([2, 0])]; + tensor var_276_end_0 = const()[name = tensor("op_276_end_0"), val = tensor([3, 589])]; + tensor var_276_end_mask_0 = const()[name = tensor("op_276_end_mask_0"), val = tensor([false, true])]; + tensor var_276_squeeze_mask_0 = const()[name = tensor("op_276_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_276 = slice_by_index(begin = var_276_begin_0, end = var_276_end_0, end_mask = var_276_end_mask_0, squeeze_mask = var_276_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_276")]; + tensor var_278 = add(x = var_273, y = var_276)[name = tensor("op_278")]; + tensor slice_by_index_4 = const()[name = tensor("slice_by_index_4"), val = tensor([117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705])]; + tensor scatter_4_mode_0 = const()[name = tensor("scatter_4_mode_0"), val = tensor("update")]; + tensor scatter_4_axis_0 = const()[name = tensor("scatter_4_axis_0"), val = tensor(0)]; + tensor scatter_4 = scatter(axis = scatter_4_axis_0, data = scatter_2, indices = slice_by_index_4, mode = scatter_4_mode_0, updates = var_278)[name = tensor("scatter_4")]; + tensor var_288_begin_0 = const()[name = tensor("op_288_begin_0"), val = tensor([117])]; + tensor var_288_end_0 = const()[name = tensor("op_288_end_0"), val = tensor([706])]; + tensor var_288_end_mask_0 = const()[name = tensor("op_288_end_mask_0"), val = tensor([false])]; + tensor var_288 = slice_by_index(begin = var_288_begin_0, end = var_288_end_0, end_mask = var_288_end_mask_0, x = scatter_3)[name = tensor("op_288")]; + tensor var_289 = const()[name = tensor("op_289"), val = tensor(0x1p+0)]; + tensor var_291 = add(x = var_288, y = var_289)[name = tensor("op_291")]; + tensor scatter_5_mode_0 = const()[name = tensor("scatter_5_mode_0"), val = tensor("update")]; + tensor scatter_5_axis_0 = const()[name = tensor("scatter_5_axis_0"), val = tensor(0)]; + tensor scatter_5 = scatter(axis = scatter_5_axis_0, data = scatter_3, indices = slice_by_index_4, mode = scatter_5_mode_0, updates = var_291)[name = tensor("scatter_5")]; + tensor var_308_begin_0 = const()[name = tensor("op_308_begin_0"), val = tensor([176])]; + tensor var_308_end_0 = const()[name = tensor("op_308_end_0"), val = tensor([765])]; + tensor var_308_end_mask_0 = const()[name = tensor("op_308_end_mask_0"), val = tensor([false])]; + tensor var_308 = slice_by_index(begin = var_308_begin_0, end = var_308_end_0, end_mask = var_308_end_mask_0, x = scatter_4)[name = tensor("op_308")]; + tensor var_311_begin_0 = const()[name = tensor("op_311_begin_0"), val = tensor([3, 0])]; + tensor var_311_end_0 = const()[name = tensor("op_311_end_0"), val = tensor([4, 589])]; + tensor var_311_end_mask_0 = const()[name = tensor("op_311_end_mask_0"), val = tensor([false, true])]; + tensor var_311_squeeze_mask_0 = const()[name = tensor("op_311_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_311 = slice_by_index(begin = var_311_begin_0, end = var_311_end_0, end_mask = var_311_end_mask_0, squeeze_mask = var_311_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_311")]; + tensor var_313 = add(x = var_308, y = var_311)[name = tensor("op_313")]; + tensor slice_by_index_6 = const()[name = tensor("slice_by_index_6"), val = tensor([176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764])]; + tensor scatter_6_mode_0 = const()[name = tensor("scatter_6_mode_0"), val = tensor("update")]; + tensor scatter_6_axis_0 = const()[name = tensor("scatter_6_axis_0"), val = tensor(0)]; + tensor scatter_6 = scatter(axis = scatter_6_axis_0, data = scatter_4, indices = slice_by_index_6, mode = scatter_6_mode_0, updates = var_313)[name = tensor("scatter_6")]; + tensor var_323_begin_0 = const()[name = tensor("op_323_begin_0"), val = tensor([176])]; + tensor var_323_end_0 = const()[name = tensor("op_323_end_0"), val = tensor([765])]; + tensor var_323_end_mask_0 = const()[name = tensor("op_323_end_mask_0"), val = tensor([false])]; + tensor var_323 = slice_by_index(begin = var_323_begin_0, end = var_323_end_0, end_mask = var_323_end_mask_0, x = scatter_5)[name = tensor("op_323")]; + tensor var_324 = const()[name = tensor("op_324"), val = tensor(0x1p+0)]; + tensor var_326 = add(x = var_323, y = var_324)[name = tensor("op_326")]; + tensor scatter_7_mode_0 = const()[name = tensor("scatter_7_mode_0"), val = tensor("update")]; + tensor scatter_7_axis_0 = const()[name = tensor("scatter_7_axis_0"), val = tensor(0)]; + tensor scatter_7 = scatter(axis = scatter_7_axis_0, data = scatter_5, indices = slice_by_index_6, mode = scatter_7_mode_0, updates = var_326)[name = tensor("scatter_7")]; + tensor var_343_begin_0 = const()[name = tensor("op_343_begin_0"), val = tensor([235])]; + tensor var_343_end_0 = const()[name = tensor("op_343_end_0"), val = tensor([824])]; + tensor var_343_end_mask_0 = const()[name = tensor("op_343_end_mask_0"), val = tensor([false])]; + tensor var_343 = slice_by_index(begin = var_343_begin_0, end = var_343_end_0, end_mask = var_343_end_mask_0, x = scatter_6)[name = tensor("op_343")]; + tensor var_346_begin_0 = const()[name = tensor("op_346_begin_0"), val = tensor([4, 0])]; + tensor var_346_end_0 = const()[name = tensor("op_346_end_0"), val = tensor([5, 589])]; + tensor var_346_end_mask_0 = const()[name = tensor("op_346_end_mask_0"), val = tensor([false, true])]; + tensor var_346_squeeze_mask_0 = const()[name = tensor("op_346_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_346 = slice_by_index(begin = var_346_begin_0, end = var_346_end_0, end_mask = var_346_end_mask_0, squeeze_mask = var_346_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_346")]; + tensor var_348 = add(x = var_343, y = var_346)[name = tensor("op_348")]; + tensor slice_by_index_8 = const()[name = tensor("slice_by_index_8"), val = tensor([235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823])]; + tensor scatter_8_mode_0 = const()[name = tensor("scatter_8_mode_0"), val = tensor("update")]; + tensor scatter_8_axis_0 = const()[name = tensor("scatter_8_axis_0"), val = tensor(0)]; + tensor scatter_8 = scatter(axis = scatter_8_axis_0, data = scatter_6, indices = slice_by_index_8, mode = scatter_8_mode_0, updates = var_348)[name = tensor("scatter_8")]; + tensor var_358_begin_0 = const()[name = tensor("op_358_begin_0"), val = tensor([235])]; + tensor var_358_end_0 = const()[name = tensor("op_358_end_0"), val = tensor([824])]; + tensor var_358_end_mask_0 = const()[name = tensor("op_358_end_mask_0"), val = tensor([false])]; + tensor var_358 = slice_by_index(begin = var_358_begin_0, end = var_358_end_0, end_mask = var_358_end_mask_0, x = scatter_7)[name = tensor("op_358")]; + tensor var_359 = const()[name = tensor("op_359"), val = tensor(0x1p+0)]; + tensor var_361 = add(x = var_358, y = var_359)[name = tensor("op_361")]; + tensor scatter_9_mode_0 = const()[name = tensor("scatter_9_mode_0"), val = tensor("update")]; + tensor scatter_9_axis_0 = const()[name = tensor("scatter_9_axis_0"), val = tensor(0)]; + tensor scatter_9 = scatter(axis = scatter_9_axis_0, data = scatter_7, indices = slice_by_index_8, mode = scatter_9_mode_0, updates = var_361)[name = tensor("scatter_9")]; + tensor var_378_begin_0 = const()[name = tensor("op_378_begin_0"), val = tensor([294])]; + tensor var_378_end_0 = const()[name = tensor("op_378_end_0"), val = tensor([883])]; + tensor var_378_end_mask_0 = const()[name = tensor("op_378_end_mask_0"), val = tensor([false])]; + tensor var_378 = slice_by_index(begin = var_378_begin_0, end = var_378_end_0, end_mask = var_378_end_mask_0, x = scatter_8)[name = tensor("op_378")]; + tensor var_381_begin_0 = const()[name = tensor("op_381_begin_0"), val = tensor([5, 0])]; + tensor var_381_end_0 = const()[name = tensor("op_381_end_0"), val = tensor([6, 589])]; + tensor var_381_end_mask_0 = const()[name = tensor("op_381_end_mask_0"), val = tensor([false, true])]; + tensor var_381_squeeze_mask_0 = const()[name = tensor("op_381_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_381 = slice_by_index(begin = var_381_begin_0, end = var_381_end_0, end_mask = var_381_end_mask_0, squeeze_mask = var_381_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_381")]; + tensor var_383 = add(x = var_378, y = var_381)[name = tensor("op_383")]; + tensor slice_by_index_10 = const()[name = tensor("slice_by_index_10"), val = tensor([294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882])]; + tensor scatter_10_mode_0 = const()[name = tensor("scatter_10_mode_0"), val = tensor("update")]; + tensor scatter_10_axis_0 = const()[name = tensor("scatter_10_axis_0"), val = tensor(0)]; + tensor scatter_10 = scatter(axis = scatter_10_axis_0, data = scatter_8, indices = slice_by_index_10, mode = scatter_10_mode_0, updates = var_383)[name = tensor("scatter_10")]; + tensor var_393_begin_0 = const()[name = tensor("op_393_begin_0"), val = tensor([294])]; + tensor var_393_end_0 = const()[name = tensor("op_393_end_0"), val = tensor([883])]; + tensor var_393_end_mask_0 = const()[name = tensor("op_393_end_mask_0"), val = tensor([false])]; + tensor var_393 = slice_by_index(begin = var_393_begin_0, end = var_393_end_0, end_mask = var_393_end_mask_0, x = scatter_9)[name = tensor("op_393")]; + tensor var_394 = const()[name = tensor("op_394"), val = tensor(0x1p+0)]; + tensor var_396 = add(x = var_393, y = var_394)[name = tensor("op_396")]; + tensor scatter_11_mode_0 = const()[name = tensor("scatter_11_mode_0"), val = tensor("update")]; + tensor scatter_11_axis_0 = const()[name = tensor("scatter_11_axis_0"), val = tensor(0)]; + tensor scatter_11 = scatter(axis = scatter_11_axis_0, data = scatter_9, indices = slice_by_index_10, mode = scatter_11_mode_0, updates = var_396)[name = tensor("scatter_11")]; + tensor var_413_begin_0 = const()[name = tensor("op_413_begin_0"), val = tensor([353])]; + tensor var_413_end_0 = const()[name = tensor("op_413_end_0"), val = tensor([942])]; + tensor var_413_end_mask_0 = const()[name = tensor("op_413_end_mask_0"), val = tensor([false])]; + tensor var_413 = slice_by_index(begin = var_413_begin_0, end = var_413_end_0, end_mask = var_413_end_mask_0, x = scatter_10)[name = tensor("op_413")]; + tensor var_416_begin_0 = const()[name = tensor("op_416_begin_0"), val = tensor([6, 0])]; + tensor var_416_end_0 = const()[name = tensor("op_416_end_0"), val = tensor([7, 589])]; + tensor var_416_end_mask_0 = const()[name = tensor("op_416_end_mask_0"), val = tensor([false, true])]; + tensor var_416_squeeze_mask_0 = const()[name = tensor("op_416_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_416 = slice_by_index(begin = var_416_begin_0, end = var_416_end_0, end_mask = var_416_end_mask_0, squeeze_mask = var_416_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_416")]; + tensor var_418 = add(x = var_413, y = var_416)[name = tensor("op_418")]; + tensor slice_by_index_12 = const()[name = tensor("slice_by_index_12"), val = tensor([353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941])]; + tensor scatter_12_mode_0 = const()[name = tensor("scatter_12_mode_0"), val = tensor("update")]; + tensor scatter_12_axis_0 = const()[name = tensor("scatter_12_axis_0"), val = tensor(0)]; + tensor scatter_12 = scatter(axis = scatter_12_axis_0, data = scatter_10, indices = slice_by_index_12, mode = scatter_12_mode_0, updates = var_418)[name = tensor("scatter_12")]; + tensor var_428_begin_0 = const()[name = tensor("op_428_begin_0"), val = tensor([353])]; + tensor var_428_end_0 = const()[name = tensor("op_428_end_0"), val = tensor([942])]; + tensor var_428_end_mask_0 = const()[name = tensor("op_428_end_mask_0"), val = tensor([false])]; + tensor var_428 = slice_by_index(begin = var_428_begin_0, end = var_428_end_0, end_mask = var_428_end_mask_0, x = scatter_11)[name = tensor("op_428")]; + tensor var_429 = const()[name = tensor("op_429"), val = tensor(0x1p+0)]; + tensor var_431 = add(x = var_428, y = var_429)[name = tensor("op_431")]; + tensor scatter_13_mode_0 = const()[name = tensor("scatter_13_mode_0"), val = tensor("update")]; + tensor scatter_13_axis_0 = const()[name = tensor("scatter_13_axis_0"), val = tensor(0)]; + tensor scatter_13 = scatter(axis = scatter_13_axis_0, data = scatter_11, indices = slice_by_index_12, mode = scatter_13_mode_0, updates = var_431)[name = tensor("scatter_13")]; + tensor var_448_begin_0 = const()[name = tensor("op_448_begin_0"), val = tensor([412])]; + tensor var_448_end_0 = const()[name = tensor("op_448_end_0"), val = tensor([1001])]; + tensor var_448_end_mask_0 = const()[name = tensor("op_448_end_mask_0"), val = tensor([false])]; + tensor var_448 = slice_by_index(begin = var_448_begin_0, end = var_448_end_0, end_mask = var_448_end_mask_0, x = scatter_12)[name = tensor("op_448")]; + tensor var_451_begin_0 = const()[name = tensor("op_451_begin_0"), val = tensor([7, 0])]; + tensor var_451_end_0 = const()[name = tensor("op_451_end_0"), val = tensor([8, 589])]; + tensor var_451_end_mask_0 = const()[name = tensor("op_451_end_mask_0"), val = tensor([false, true])]; + tensor var_451_squeeze_mask_0 = const()[name = tensor("op_451_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_451 = slice_by_index(begin = var_451_begin_0, end = var_451_end_0, end_mask = var_451_end_mask_0, squeeze_mask = var_451_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_451")]; + tensor var_453 = add(x = var_448, y = var_451)[name = tensor("op_453")]; + tensor slice_by_index_14 = const()[name = tensor("slice_by_index_14"), val = tensor([412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000])]; + tensor scatter_14_mode_0 = const()[name = tensor("scatter_14_mode_0"), val = tensor("update")]; + tensor scatter_14_axis_0 = const()[name = tensor("scatter_14_axis_0"), val = tensor(0)]; + tensor scatter_14 = scatter(axis = scatter_14_axis_0, data = scatter_12, indices = slice_by_index_14, mode = scatter_14_mode_0, updates = var_453)[name = tensor("scatter_14")]; + tensor var_463_begin_0 = const()[name = tensor("op_463_begin_0"), val = tensor([412])]; + tensor var_463_end_0 = const()[name = tensor("op_463_end_0"), val = tensor([1001])]; + tensor var_463_end_mask_0 = const()[name = tensor("op_463_end_mask_0"), val = tensor([false])]; + tensor var_463 = slice_by_index(begin = var_463_begin_0, end = var_463_end_0, end_mask = var_463_end_mask_0, x = scatter_13)[name = tensor("op_463")]; + tensor var_464 = const()[name = tensor("op_464"), val = tensor(0x1p+0)]; + tensor var_466 = add(x = var_463, y = var_464)[name = tensor("op_466")]; + tensor scatter_15_mode_0 = const()[name = tensor("scatter_15_mode_0"), val = tensor("update")]; + tensor scatter_15_axis_0 = const()[name = tensor("scatter_15_axis_0"), val = tensor(0)]; + tensor scatter_15 = scatter(axis = scatter_15_axis_0, data = scatter_13, indices = slice_by_index_14, mode = scatter_15_mode_0, updates = var_466)[name = tensor("scatter_15")]; + tensor var_483_begin_0 = const()[name = tensor("op_483_begin_0"), val = tensor([471])]; + tensor var_483_end_0 = const()[name = tensor("op_483_end_0"), val = tensor([1060])]; + tensor var_483_end_mask_0 = const()[name = tensor("op_483_end_mask_0"), val = tensor([false])]; + tensor var_483 = slice_by_index(begin = var_483_begin_0, end = var_483_end_0, end_mask = var_483_end_mask_0, x = scatter_14)[name = tensor("op_483")]; + tensor var_486_begin_0 = const()[name = tensor("op_486_begin_0"), val = tensor([8, 0])]; + tensor var_486_end_0 = const()[name = tensor("op_486_end_0"), val = tensor([9, 589])]; + tensor var_486_end_mask_0 = const()[name = tensor("op_486_end_mask_0"), val = tensor([false, true])]; + tensor var_486_squeeze_mask_0 = const()[name = tensor("op_486_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_486 = slice_by_index(begin = var_486_begin_0, end = var_486_end_0, end_mask = var_486_end_mask_0, squeeze_mask = var_486_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_486")]; + tensor var_488 = add(x = var_483, y = var_486)[name = tensor("op_488")]; + tensor slice_by_index_16 = const()[name = tensor("slice_by_index_16"), val = tensor([471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059])]; + tensor scatter_16_mode_0 = const()[name = tensor("scatter_16_mode_0"), val = tensor("update")]; + tensor scatter_16_axis_0 = const()[name = tensor("scatter_16_axis_0"), val = tensor(0)]; + tensor scatter_16 = scatter(axis = scatter_16_axis_0, data = scatter_14, indices = slice_by_index_16, mode = scatter_16_mode_0, updates = var_488)[name = tensor("scatter_16")]; + tensor var_498_begin_0 = const()[name = tensor("op_498_begin_0"), val = tensor([471])]; + tensor var_498_end_0 = const()[name = tensor("op_498_end_0"), val = tensor([1060])]; + tensor var_498_end_mask_0 = const()[name = tensor("op_498_end_mask_0"), val = tensor([false])]; + tensor var_498 = slice_by_index(begin = var_498_begin_0, end = var_498_end_0, end_mask = var_498_end_mask_0, x = scatter_15)[name = tensor("op_498")]; + tensor var_499 = const()[name = tensor("op_499"), val = tensor(0x1p+0)]; + tensor var_501 = add(x = var_498, y = var_499)[name = tensor("op_501")]; + tensor scatter_17_mode_0 = const()[name = tensor("scatter_17_mode_0"), val = tensor("update")]; + tensor scatter_17_axis_0 = const()[name = tensor("scatter_17_axis_0"), val = tensor(0)]; + tensor scatter_17 = scatter(axis = scatter_17_axis_0, data = scatter_15, indices = slice_by_index_16, mode = scatter_17_mode_0, updates = var_501)[name = tensor("scatter_17")]; + tensor var_518_begin_0 = const()[name = tensor("op_518_begin_0"), val = tensor([530])]; + tensor var_518_end_0 = const()[name = tensor("op_518_end_0"), val = tensor([1119])]; + tensor var_518_end_mask_0 = const()[name = tensor("op_518_end_mask_0"), val = tensor([false])]; + tensor var_518 = slice_by_index(begin = var_518_begin_0, end = var_518_end_0, end_mask = var_518_end_mask_0, x = scatter_16)[name = tensor("op_518")]; + tensor var_521_begin_0 = const()[name = tensor("op_521_begin_0"), val = tensor([9, 0])]; + tensor var_521_end_0 = const()[name = tensor("op_521_end_0"), val = tensor([10, 589])]; + tensor var_521_end_mask_0 = const()[name = tensor("op_521_end_mask_0"), val = tensor([false, true])]; + tensor var_521_squeeze_mask_0 = const()[name = tensor("op_521_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_521 = slice_by_index(begin = var_521_begin_0, end = var_521_end_0, end_mask = var_521_end_mask_0, squeeze_mask = var_521_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_521")]; + tensor var_523 = add(x = var_518, y = var_521)[name = tensor("op_523")]; + tensor slice_by_index_18 = const()[name = tensor("slice_by_index_18"), val = tensor([530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118])]; + tensor scatter_18_mode_0 = const()[name = tensor("scatter_18_mode_0"), val = tensor("update")]; + tensor scatter_18_axis_0 = const()[name = tensor("scatter_18_axis_0"), val = tensor(0)]; + tensor scatter_18 = scatter(axis = scatter_18_axis_0, data = scatter_16, indices = slice_by_index_18, mode = scatter_18_mode_0, updates = var_523)[name = tensor("scatter_18")]; + tensor var_533_begin_0 = const()[name = tensor("op_533_begin_0"), val = tensor([530])]; + tensor var_533_end_0 = const()[name = tensor("op_533_end_0"), val = tensor([1119])]; + tensor var_533_end_mask_0 = const()[name = tensor("op_533_end_mask_0"), val = tensor([false])]; + tensor var_533 = slice_by_index(begin = var_533_begin_0, end = var_533_end_0, end_mask = var_533_end_mask_0, x = scatter_17)[name = tensor("op_533")]; + tensor var_534 = const()[name = tensor("op_534"), val = tensor(0x1p+0)]; + tensor var_536 = add(x = var_533, y = var_534)[name = tensor("op_536")]; + tensor scatter_19_mode_0 = const()[name = tensor("scatter_19_mode_0"), val = tensor("update")]; + tensor scatter_19_axis_0 = const()[name = tensor("scatter_19_axis_0"), val = tensor(0)]; + tensor scatter_19 = scatter(axis = scatter_19_axis_0, data = scatter_17, indices = slice_by_index_18, mode = scatter_19_mode_0, updates = var_536)[name = tensor("scatter_19")]; + tensor var_553_begin_0 = const()[name = tensor("op_553_begin_0"), val = tensor([589])]; + tensor var_553_end_0 = const()[name = tensor("op_553_end_0"), val = tensor([1178])]; + tensor var_553_end_mask_0 = const()[name = tensor("op_553_end_mask_0"), val = tensor([false])]; + tensor var_553 = slice_by_index(begin = var_553_begin_0, end = var_553_end_0, end_mask = var_553_end_mask_0, x = scatter_18)[name = tensor("op_553")]; + tensor var_556_begin_0 = const()[name = tensor("op_556_begin_0"), val = tensor([10, 0])]; + tensor var_556_end_0 = const()[name = tensor("op_556_end_0"), val = tensor([11, 589])]; + tensor var_556_end_mask_0 = const()[name = tensor("op_556_end_mask_0"), val = tensor([false, true])]; + tensor var_556_squeeze_mask_0 = const()[name = tensor("op_556_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_556 = slice_by_index(begin = var_556_begin_0, end = var_556_end_0, end_mask = var_556_end_mask_0, squeeze_mask = var_556_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_556")]; + tensor var_558 = add(x = var_553, y = var_556)[name = tensor("op_558")]; + tensor slice_by_index_20 = const()[name = tensor("slice_by_index_20"), val = tensor([589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177])]; + tensor scatter_20_mode_0 = const()[name = tensor("scatter_20_mode_0"), val = tensor("update")]; + tensor scatter_20_axis_0 = const()[name = tensor("scatter_20_axis_0"), val = tensor(0)]; + tensor scatter_20 = scatter(axis = scatter_20_axis_0, data = scatter_18, indices = slice_by_index_20, mode = scatter_20_mode_0, updates = var_558)[name = tensor("scatter_20")]; + tensor var_568_begin_0 = const()[name = tensor("op_568_begin_0"), val = tensor([589])]; + tensor var_568_end_0 = const()[name = tensor("op_568_end_0"), val = tensor([1178])]; + tensor var_568_end_mask_0 = const()[name = tensor("op_568_end_mask_0"), val = tensor([false])]; + tensor var_568 = slice_by_index(begin = var_568_begin_0, end = var_568_end_0, end_mask = var_568_end_mask_0, x = scatter_19)[name = tensor("op_568")]; + tensor var_569 = const()[name = tensor("op_569"), val = tensor(0x1p+0)]; + tensor var_571 = add(x = var_568, y = var_569)[name = tensor("op_571")]; + tensor scatter_21_mode_0 = const()[name = tensor("scatter_21_mode_0"), val = tensor("update")]; + tensor scatter_21_axis_0 = const()[name = tensor("scatter_21_axis_0"), val = tensor(0)]; + tensor scatter_21 = scatter(axis = scatter_21_axis_0, data = scatter_19, indices = slice_by_index_20, mode = scatter_21_mode_0, updates = var_571)[name = tensor("scatter_21")]; + tensor var_588_begin_0 = const()[name = tensor("op_588_begin_0"), val = tensor([647])]; + tensor var_588_end_0 = const()[name = tensor("op_588_end_0"), val = tensor([1236])]; + tensor var_588_end_mask_0 = const()[name = tensor("op_588_end_mask_0"), val = tensor([false])]; + tensor var_588 = slice_by_index(begin = var_588_begin_0, end = var_588_end_0, end_mask = var_588_end_mask_0, x = scatter_20)[name = tensor("op_588")]; + tensor var_591_begin_0 = const()[name = tensor("op_591_begin_0"), val = tensor([11, 0])]; + tensor var_591_end_0 = const()[name = tensor("op_591_end_0"), val = tensor([12, 589])]; + tensor var_591_end_mask_0 = const()[name = tensor("op_591_end_mask_0"), val = tensor([false, true])]; + tensor var_591_squeeze_mask_0 = const()[name = tensor("op_591_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_591 = slice_by_index(begin = var_591_begin_0, end = var_591_end_0, end_mask = var_591_end_mask_0, squeeze_mask = var_591_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_591")]; + tensor var_593 = add(x = var_588, y = var_591)[name = tensor("op_593")]; + tensor slice_by_index_22 = const()[name = tensor("slice_by_index_22"), val = tensor([647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235])]; + tensor scatter_22_mode_0 = const()[name = tensor("scatter_22_mode_0"), val = tensor("update")]; + tensor scatter_22_axis_0 = const()[name = tensor("scatter_22_axis_0"), val = tensor(0)]; + tensor scatter_22 = scatter(axis = scatter_22_axis_0, data = scatter_20, indices = slice_by_index_22, mode = scatter_22_mode_0, updates = var_593)[name = tensor("scatter_22")]; + tensor var_603_begin_0 = const()[name = tensor("op_603_begin_0"), val = tensor([647])]; + tensor var_603_end_0 = const()[name = tensor("op_603_end_0"), val = tensor([1236])]; + tensor var_603_end_mask_0 = const()[name = tensor("op_603_end_mask_0"), val = tensor([false])]; + tensor var_603 = slice_by_index(begin = var_603_begin_0, end = var_603_end_0, end_mask = var_603_end_mask_0, x = scatter_21)[name = tensor("op_603")]; + tensor var_604 = const()[name = tensor("op_604"), val = tensor(0x1p+0)]; + tensor var_606 = add(x = var_603, y = var_604)[name = tensor("op_606")]; + tensor scatter_23_mode_0 = const()[name = tensor("scatter_23_mode_0"), val = tensor("update")]; + tensor scatter_23_axis_0 = const()[name = tensor("scatter_23_axis_0"), val = tensor(0)]; + tensor scatter_23 = scatter(axis = scatter_23_axis_0, data = scatter_21, indices = slice_by_index_22, mode = scatter_23_mode_0, updates = var_606)[name = tensor("scatter_23")]; + tensor var_623_begin_0 = const()[name = tensor("op_623_begin_0"), val = tensor([706])]; + tensor var_623_end_0 = const()[name = tensor("op_623_end_0"), val = tensor([1295])]; + tensor var_623_end_mask_0 = const()[name = tensor("op_623_end_mask_0"), val = tensor([false])]; + tensor var_623 = slice_by_index(begin = var_623_begin_0, end = var_623_end_0, end_mask = var_623_end_mask_0, x = scatter_22)[name = tensor("op_623")]; + tensor var_626_begin_0 = const()[name = tensor("op_626_begin_0"), val = tensor([12, 0])]; + tensor var_626_end_0 = const()[name = tensor("op_626_end_0"), val = tensor([13, 589])]; + tensor var_626_end_mask_0 = const()[name = tensor("op_626_end_mask_0"), val = tensor([false, true])]; + tensor var_626_squeeze_mask_0 = const()[name = tensor("op_626_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_626 = slice_by_index(begin = var_626_begin_0, end = var_626_end_0, end_mask = var_626_end_mask_0, squeeze_mask = var_626_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_626")]; + tensor var_628 = add(x = var_623, y = var_626)[name = tensor("op_628")]; + tensor slice_by_index_24 = const()[name = tensor("slice_by_index_24"), val = tensor([706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294])]; + tensor scatter_24_mode_0 = const()[name = tensor("scatter_24_mode_0"), val = tensor("update")]; + tensor scatter_24_axis_0 = const()[name = tensor("scatter_24_axis_0"), val = tensor(0)]; + tensor scatter_24 = scatter(axis = scatter_24_axis_0, data = scatter_22, indices = slice_by_index_24, mode = scatter_24_mode_0, updates = var_628)[name = tensor("scatter_24")]; + tensor var_638_begin_0 = const()[name = tensor("op_638_begin_0"), val = tensor([706])]; + tensor var_638_end_0 = const()[name = tensor("op_638_end_0"), val = tensor([1295])]; + tensor var_638_end_mask_0 = const()[name = tensor("op_638_end_mask_0"), val = tensor([false])]; + tensor var_638 = slice_by_index(begin = var_638_begin_0, end = var_638_end_0, end_mask = var_638_end_mask_0, x = scatter_23)[name = tensor("op_638")]; + tensor var_639 = const()[name = tensor("op_639"), val = tensor(0x1p+0)]; + tensor var_641 = add(x = var_638, y = var_639)[name = tensor("op_641")]; + tensor scatter_25_mode_0 = const()[name = tensor("scatter_25_mode_0"), val = tensor("update")]; + tensor scatter_25_axis_0 = const()[name = tensor("scatter_25_axis_0"), val = tensor(0)]; + tensor scatter_25 = scatter(axis = scatter_25_axis_0, data = scatter_23, indices = slice_by_index_24, mode = scatter_25_mode_0, updates = var_641)[name = tensor("scatter_25")]; + tensor var_658_begin_0 = const()[name = tensor("op_658_begin_0"), val = tensor([765])]; + tensor var_658_end_0 = const()[name = tensor("op_658_end_0"), val = tensor([1354])]; + tensor var_658_end_mask_0 = const()[name = tensor("op_658_end_mask_0"), val = tensor([false])]; + tensor var_658 = slice_by_index(begin = var_658_begin_0, end = var_658_end_0, end_mask = var_658_end_mask_0, x = scatter_24)[name = tensor("op_658")]; + tensor var_661_begin_0 = const()[name = tensor("op_661_begin_0"), val = tensor([13, 0])]; + tensor var_661_end_0 = const()[name = tensor("op_661_end_0"), val = tensor([14, 589])]; + tensor var_661_end_mask_0 = const()[name = tensor("op_661_end_mask_0"), val = tensor([false, true])]; + tensor var_661_squeeze_mask_0 = const()[name = tensor("op_661_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_661 = slice_by_index(begin = var_661_begin_0, end = var_661_end_0, end_mask = var_661_end_mask_0, squeeze_mask = var_661_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_661")]; + tensor var_663 = add(x = var_658, y = var_661)[name = tensor("op_663")]; + tensor slice_by_index_26 = const()[name = tensor("slice_by_index_26"), val = tensor([765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353])]; + tensor scatter_26_mode_0 = const()[name = tensor("scatter_26_mode_0"), val = tensor("update")]; + tensor scatter_26_axis_0 = const()[name = tensor("scatter_26_axis_0"), val = tensor(0)]; + tensor scatter_26 = scatter(axis = scatter_26_axis_0, data = scatter_24, indices = slice_by_index_26, mode = scatter_26_mode_0, updates = var_663)[name = tensor("scatter_26")]; + tensor var_673_begin_0 = const()[name = tensor("op_673_begin_0"), val = tensor([765])]; + tensor var_673_end_0 = const()[name = tensor("op_673_end_0"), val = tensor([1354])]; + tensor var_673_end_mask_0 = const()[name = tensor("op_673_end_mask_0"), val = tensor([false])]; + tensor var_673 = slice_by_index(begin = var_673_begin_0, end = var_673_end_0, end_mask = var_673_end_mask_0, x = scatter_25)[name = tensor("op_673")]; + tensor var_674 = const()[name = tensor("op_674"), val = tensor(0x1p+0)]; + tensor var_676 = add(x = var_673, y = var_674)[name = tensor("op_676")]; + tensor scatter_27_mode_0 = const()[name = tensor("scatter_27_mode_0"), val = tensor("update")]; + tensor scatter_27_axis_0 = const()[name = tensor("scatter_27_axis_0"), val = tensor(0)]; + tensor scatter_27 = scatter(axis = scatter_27_axis_0, data = scatter_25, indices = slice_by_index_26, mode = scatter_27_mode_0, updates = var_676)[name = tensor("scatter_27")]; + tensor var_693_begin_0 = const()[name = tensor("op_693_begin_0"), val = tensor([824])]; + tensor var_693_end_0 = const()[name = tensor("op_693_end_0"), val = tensor([1413])]; + tensor var_693_end_mask_0 = const()[name = tensor("op_693_end_mask_0"), val = tensor([false])]; + tensor var_693 = slice_by_index(begin = var_693_begin_0, end = var_693_end_0, end_mask = var_693_end_mask_0, x = scatter_26)[name = tensor("op_693")]; + tensor var_696_begin_0 = const()[name = tensor("op_696_begin_0"), val = tensor([14, 0])]; + tensor var_696_end_0 = const()[name = tensor("op_696_end_0"), val = tensor([15, 589])]; + tensor var_696_end_mask_0 = const()[name = tensor("op_696_end_mask_0"), val = tensor([false, true])]; + tensor var_696_squeeze_mask_0 = const()[name = tensor("op_696_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_696 = slice_by_index(begin = var_696_begin_0, end = var_696_end_0, end_mask = var_696_end_mask_0, squeeze_mask = var_696_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_696")]; + tensor var_698 = add(x = var_693, y = var_696)[name = tensor("op_698")]; + tensor slice_by_index_28 = const()[name = tensor("slice_by_index_28"), val = tensor([824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1364, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1381, 1382, 1383, 1384, 1385, 1386, 1387, 1388, 1389, 1390, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1399, 1400, 1401, 1402, 1403, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412])]; + tensor scatter_28_mode_0 = const()[name = tensor("scatter_28_mode_0"), val = tensor("update")]; + tensor scatter_28_axis_0 = const()[name = tensor("scatter_28_axis_0"), val = tensor(0)]; + tensor scatter_28 = scatter(axis = scatter_28_axis_0, data = scatter_26, indices = slice_by_index_28, mode = scatter_28_mode_0, updates = var_698)[name = tensor("scatter_28")]; + tensor var_708_begin_0 = const()[name = tensor("op_708_begin_0"), val = tensor([824])]; + tensor var_708_end_0 = const()[name = tensor("op_708_end_0"), val = tensor([1413])]; + tensor var_708_end_mask_0 = const()[name = tensor("op_708_end_mask_0"), val = tensor([false])]; + tensor var_708 = slice_by_index(begin = var_708_begin_0, end = var_708_end_0, end_mask = var_708_end_mask_0, x = scatter_27)[name = tensor("op_708")]; + tensor var_709 = const()[name = tensor("op_709"), val = tensor(0x1p+0)]; + tensor var_711 = add(x = var_708, y = var_709)[name = tensor("op_711")]; + tensor scatter_29_mode_0 = const()[name = tensor("scatter_29_mode_0"), val = tensor("update")]; + tensor scatter_29_axis_0 = const()[name = tensor("scatter_29_axis_0"), val = tensor(0)]; + tensor scatter_29 = scatter(axis = scatter_29_axis_0, data = scatter_27, indices = slice_by_index_28, mode = scatter_29_mode_0, updates = var_711)[name = tensor("scatter_29")]; + tensor var_728_begin_0 = const()[name = tensor("op_728_begin_0"), val = tensor([883])]; + tensor var_728_end_0 = const()[name = tensor("op_728_end_0"), val = tensor([1472])]; + tensor var_728_end_mask_0 = const()[name = tensor("op_728_end_mask_0"), val = tensor([false])]; + tensor var_728 = slice_by_index(begin = var_728_begin_0, end = var_728_end_0, end_mask = var_728_end_mask_0, x = scatter_28)[name = tensor("op_728")]; + tensor var_731_begin_0 = const()[name = tensor("op_731_begin_0"), val = tensor([15, 0])]; + tensor var_731_end_0 = const()[name = tensor("op_731_end_0"), val = tensor([16, 589])]; + tensor var_731_end_mask_0 = const()[name = tensor("op_731_end_mask_0"), val = tensor([false, true])]; + tensor var_731_squeeze_mask_0 = const()[name = tensor("op_731_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_731 = slice_by_index(begin = var_731_begin_0, end = var_731_end_0, end_mask = var_731_end_mask_0, squeeze_mask = var_731_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_731")]; + tensor var_733 = add(x = var_728, y = var_731)[name = tensor("op_733")]; + tensor slice_by_index_30 = const()[name = tensor("slice_by_index_30"), val = tensor([883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1364, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1381, 1382, 1383, 1384, 1385, 1386, 1387, 1388, 1389, 1390, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1399, 1400, 1401, 1402, 1403, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426, 1427, 1428, 1429, 1430, 1431, 1432, 1433, 1434, 1435, 1436, 1437, 1438, 1439, 1440, 1441, 1442, 1443, 1444, 1445, 1446, 1447, 1448, 1449, 1450, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1459, 1460, 1461, 1462, 1463, 1464, 1465, 1466, 1467, 1468, 1469, 1470, 1471])]; + tensor scatter_30_mode_0 = const()[name = tensor("scatter_30_mode_0"), val = tensor("update")]; + tensor scatter_30_axis_0 = const()[name = tensor("scatter_30_axis_0"), val = tensor(0)]; + tensor scatter_30 = scatter(axis = scatter_30_axis_0, data = scatter_28, indices = slice_by_index_30, mode = scatter_30_mode_0, updates = var_733)[name = tensor("scatter_30")]; + tensor var_743_begin_0 = const()[name = tensor("op_743_begin_0"), val = tensor([883])]; + tensor var_743_end_0 = const()[name = tensor("op_743_end_0"), val = tensor([1472])]; + tensor var_743_end_mask_0 = const()[name = tensor("op_743_end_mask_0"), val = tensor([false])]; + tensor var_743 = slice_by_index(begin = var_743_begin_0, end = var_743_end_0, end_mask = var_743_end_mask_0, x = scatter_29)[name = tensor("op_743")]; + tensor var_744 = const()[name = tensor("op_744"), val = tensor(0x1p+0)]; + tensor var_746 = add(x = var_743, y = var_744)[name = tensor("op_746")]; + tensor scatter_31_mode_0 = const()[name = tensor("scatter_31_mode_0"), val = tensor("update")]; + tensor scatter_31_axis_0 = const()[name = tensor("scatter_31_axis_0"), val = tensor(0)]; + tensor scatter_31 = scatter(axis = scatter_31_axis_0, data = scatter_29, indices = slice_by_index_30, mode = scatter_31_mode_0, updates = var_746)[name = tensor("scatter_31")]; + tensor var_763_begin_0 = const()[name = tensor("op_763_begin_0"), val = tensor([942])]; + tensor var_763_end_0 = const()[name = tensor("op_763_end_0"), val = tensor([1531])]; + tensor var_763_end_mask_0 = const()[name = tensor("op_763_end_mask_0"), val = tensor([false])]; + tensor var_763 = slice_by_index(begin = var_763_begin_0, end = var_763_end_0, end_mask = var_763_end_mask_0, x = scatter_30)[name = tensor("op_763")]; + tensor var_766_begin_0 = const()[name = tensor("op_766_begin_0"), val = tensor([16, 0])]; + tensor var_766_end_0 = const()[name = tensor("op_766_end_0"), val = tensor([17, 589])]; + tensor var_766_end_mask_0 = const()[name = tensor("op_766_end_mask_0"), val = tensor([false, true])]; + tensor var_766_squeeze_mask_0 = const()[name = tensor("op_766_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_766 = slice_by_index(begin = var_766_begin_0, end = var_766_end_0, end_mask = var_766_end_mask_0, squeeze_mask = var_766_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_766")]; + tensor var_768 = add(x = var_763, y = var_766)[name = tensor("op_768")]; + tensor slice_by_index_32 = const()[name = tensor("slice_by_index_32"), val = tensor([942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1364, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1381, 1382, 1383, 1384, 1385, 1386, 1387, 1388, 1389, 1390, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1399, 1400, 1401, 1402, 1403, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426, 1427, 1428, 1429, 1430, 1431, 1432, 1433, 1434, 1435, 1436, 1437, 1438, 1439, 1440, 1441, 1442, 1443, 1444, 1445, 1446, 1447, 1448, 1449, 1450, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1459, 1460, 1461, 1462, 1463, 1464, 1465, 1466, 1467, 1468, 1469, 1470, 1471, 1472, 1473, 1474, 1475, 1476, 1477, 1478, 1479, 1480, 1481, 1482, 1483, 1484, 1485, 1486, 1487, 1488, 1489, 1490, 1491, 1492, 1493, 1494, 1495, 1496, 1497, 1498, 1499, 1500, 1501, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1515, 1516, 1517, 1518, 1519, 1520, 1521, 1522, 1523, 1524, 1525, 1526, 1527, 1528, 1529, 1530])]; + tensor scatter_32_mode_0 = const()[name = tensor("scatter_32_mode_0"), val = tensor("update")]; + tensor scatter_32_axis_0 = const()[name = tensor("scatter_32_axis_0"), val = tensor(0)]; + tensor scatter_32 = scatter(axis = scatter_32_axis_0, data = scatter_30, indices = slice_by_index_32, mode = scatter_32_mode_0, updates = var_768)[name = tensor("scatter_32")]; + tensor var_778_begin_0 = const()[name = tensor("op_778_begin_0"), val = tensor([942])]; + tensor var_778_end_0 = const()[name = tensor("op_778_end_0"), val = tensor([1531])]; + tensor var_778_end_mask_0 = const()[name = tensor("op_778_end_mask_0"), val = tensor([false])]; + tensor var_778 = slice_by_index(begin = var_778_begin_0, end = var_778_end_0, end_mask = var_778_end_mask_0, x = scatter_31)[name = tensor("op_778")]; + tensor var_779 = const()[name = tensor("op_779"), val = tensor(0x1p+0)]; + tensor var_781 = add(x = var_778, y = var_779)[name = tensor("op_781")]; + tensor scatter_33_mode_0 = const()[name = tensor("scatter_33_mode_0"), val = tensor("update")]; + tensor scatter_33_axis_0 = const()[name = tensor("scatter_33_axis_0"), val = tensor(0)]; + tensor scatter_33 = scatter(axis = scatter_33_axis_0, data = scatter_31, indices = slice_by_index_32, mode = scatter_33_mode_0, updates = var_781)[name = tensor("scatter_33")]; + tensor var_798_begin_0 = const()[name = tensor("op_798_begin_0"), val = tensor([1001])]; + tensor var_798_end_0 = const()[name = tensor("op_798_end_0"), val = tensor([1590])]; + tensor var_798_end_mask_0 = const()[name = tensor("op_798_end_mask_0"), val = tensor([false])]; + tensor var_798 = slice_by_index(begin = var_798_begin_0, end = var_798_end_0, end_mask = var_798_end_mask_0, x = scatter_32)[name = tensor("op_798")]; + tensor var_801_begin_0 = const()[name = tensor("op_801_begin_0"), val = tensor([17, 0])]; + tensor var_801_end_0 = const()[name = tensor("op_801_end_0"), val = tensor([18, 589])]; + tensor var_801_end_mask_0 = const()[name = tensor("op_801_end_mask_0"), val = tensor([false, true])]; + tensor var_801_squeeze_mask_0 = const()[name = tensor("op_801_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_801 = slice_by_index(begin = var_801_begin_0, end = var_801_end_0, end_mask = var_801_end_mask_0, squeeze_mask = var_801_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_801")]; + tensor var_803 = add(x = var_798, y = var_801)[name = tensor("op_803")]; + tensor slice_by_index_34 = const()[name = tensor("slice_by_index_34"), val = tensor([1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1364, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1381, 1382, 1383, 1384, 1385, 1386, 1387, 1388, 1389, 1390, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1399, 1400, 1401, 1402, 1403, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426, 1427, 1428, 1429, 1430, 1431, 1432, 1433, 1434, 1435, 1436, 1437, 1438, 1439, 1440, 1441, 1442, 1443, 1444, 1445, 1446, 1447, 1448, 1449, 1450, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1459, 1460, 1461, 1462, 1463, 1464, 1465, 1466, 1467, 1468, 1469, 1470, 1471, 1472, 1473, 1474, 1475, 1476, 1477, 1478, 1479, 1480, 1481, 1482, 1483, 1484, 1485, 1486, 1487, 1488, 1489, 1490, 1491, 1492, 1493, 1494, 1495, 1496, 1497, 1498, 1499, 1500, 1501, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1515, 1516, 1517, 1518, 1519, 1520, 1521, 1522, 1523, 1524, 1525, 1526, 1527, 1528, 1529, 1530, 1531, 1532, 1533, 1534, 1535, 1536, 1537, 1538, 1539, 1540, 1541, 1542, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1551, 1552, 1553, 1554, 1555, 1556, 1557, 1558, 1559, 1560, 1561, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1572, 1573, 1574, 1575, 1576, 1577, 1578, 1579, 1580, 1581, 1582, 1583, 1584, 1585, 1586, 1587, 1588, 1589])]; + tensor scatter_34_mode_0 = const()[name = tensor("scatter_34_mode_0"), val = tensor("update")]; + tensor scatter_34_axis_0 = const()[name = tensor("scatter_34_axis_0"), val = tensor(0)]; + tensor scatter_34 = scatter(axis = scatter_34_axis_0, data = scatter_32, indices = slice_by_index_34, mode = scatter_34_mode_0, updates = var_803)[name = tensor("scatter_34")]; + tensor var_813_begin_0 = const()[name = tensor("op_813_begin_0"), val = tensor([1001])]; + tensor var_813_end_0 = const()[name = tensor("op_813_end_0"), val = tensor([1590])]; + tensor var_813_end_mask_0 = const()[name = tensor("op_813_end_mask_0"), val = tensor([false])]; + tensor var_813 = slice_by_index(begin = var_813_begin_0, end = var_813_end_0, end_mask = var_813_end_mask_0, x = scatter_33)[name = tensor("op_813")]; + tensor var_814 = const()[name = tensor("op_814"), val = tensor(0x1p+0)]; + tensor var_816 = add(x = var_813, y = var_814)[name = tensor("op_816")]; + tensor scatter_35_mode_0 = const()[name = tensor("scatter_35_mode_0"), val = tensor("update")]; + tensor scatter_35_axis_0 = const()[name = tensor("scatter_35_axis_0"), val = tensor(0)]; + tensor scatter_35 = scatter(axis = scatter_35_axis_0, data = scatter_33, indices = slice_by_index_34, mode = scatter_35_mode_0, updates = var_816)[name = tensor("scatter_35")]; + tensor var_833_begin_0 = const()[name = tensor("op_833_begin_0"), val = tensor([1060])]; + tensor var_833_end_0 = const()[name = tensor("op_833_end_0"), val = tensor([1649])]; + tensor var_833_end_mask_0 = const()[name = tensor("op_833_end_mask_0"), val = tensor([false])]; + tensor var_833 = slice_by_index(begin = var_833_begin_0, end = var_833_end_0, end_mask = var_833_end_mask_0, x = scatter_34)[name = tensor("op_833")]; + tensor var_836_begin_0 = const()[name = tensor("op_836_begin_0"), val = tensor([18, 0])]; + tensor var_836_end_0 = const()[name = tensor("op_836_end_0"), val = tensor([19, 589])]; + tensor var_836_end_mask_0 = const()[name = tensor("op_836_end_mask_0"), val = tensor([false, true])]; + tensor var_836_squeeze_mask_0 = const()[name = tensor("op_836_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_836 = slice_by_index(begin = var_836_begin_0, end = var_836_end_0, end_mask = var_836_end_mask_0, squeeze_mask = var_836_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_836")]; + tensor var_838 = add(x = var_833, y = var_836)[name = tensor("op_838")]; + tensor slice_by_index_36 = const()[name = tensor("slice_by_index_36"), val = tensor([1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1364, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1381, 1382, 1383, 1384, 1385, 1386, 1387, 1388, 1389, 1390, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1399, 1400, 1401, 1402, 1403, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426, 1427, 1428, 1429, 1430, 1431, 1432, 1433, 1434, 1435, 1436, 1437, 1438, 1439, 1440, 1441, 1442, 1443, 1444, 1445, 1446, 1447, 1448, 1449, 1450, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1459, 1460, 1461, 1462, 1463, 1464, 1465, 1466, 1467, 1468, 1469, 1470, 1471, 1472, 1473, 1474, 1475, 1476, 1477, 1478, 1479, 1480, 1481, 1482, 1483, 1484, 1485, 1486, 1487, 1488, 1489, 1490, 1491, 1492, 1493, 1494, 1495, 1496, 1497, 1498, 1499, 1500, 1501, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1515, 1516, 1517, 1518, 1519, 1520, 1521, 1522, 1523, 1524, 1525, 1526, 1527, 1528, 1529, 1530, 1531, 1532, 1533, 1534, 1535, 1536, 1537, 1538, 1539, 1540, 1541, 1542, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1551, 1552, 1553, 1554, 1555, 1556, 1557, 1558, 1559, 1560, 1561, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1572, 1573, 1574, 1575, 1576, 1577, 1578, 1579, 1580, 1581, 1582, 1583, 1584, 1585, 1586, 1587, 1588, 1589, 1590, 1591, 1592, 1593, 1594, 1595, 1596, 1597, 1598, 1599, 1600, 1601, 1602, 1603, 1604, 1605, 1606, 1607, 1608, 1609, 1610, 1611, 1612, 1613, 1614, 1615, 1616, 1617, 1618, 1619, 1620, 1621, 1622, 1623, 1624, 1625, 1626, 1627, 1628, 1629, 1630, 1631, 1632, 1633, 1634, 1635, 1636, 1637, 1638, 1639, 1640, 1641, 1642, 1643, 1644, 1645, 1646, 1647, 1648])]; + tensor scatter_36_mode_0 = const()[name = tensor("scatter_36_mode_0"), val = tensor("update")]; + tensor scatter_36_axis_0 = const()[name = tensor("scatter_36_axis_0"), val = tensor(0)]; + tensor scatter_36 = scatter(axis = scatter_36_axis_0, data = scatter_34, indices = slice_by_index_36, mode = scatter_36_mode_0, updates = var_838)[name = tensor("scatter_36")]; + tensor var_848_begin_0 = const()[name = tensor("op_848_begin_0"), val = tensor([1060])]; + tensor var_848_end_0 = const()[name = tensor("op_848_end_0"), val = tensor([1649])]; + tensor var_848_end_mask_0 = const()[name = tensor("op_848_end_mask_0"), val = tensor([false])]; + tensor var_848 = slice_by_index(begin = var_848_begin_0, end = var_848_end_0, end_mask = var_848_end_mask_0, x = scatter_35)[name = tensor("op_848")]; + tensor var_849 = const()[name = tensor("op_849"), val = tensor(0x1p+0)]; + tensor var_851 = add(x = var_848, y = var_849)[name = tensor("op_851")]; + tensor scatter_37_mode_0 = const()[name = tensor("scatter_37_mode_0"), val = tensor("update")]; + tensor scatter_37_axis_0 = const()[name = tensor("scatter_37_axis_0"), val = tensor(0)]; + tensor scatter_37 = scatter(axis = scatter_37_axis_0, data = scatter_35, indices = slice_by_index_36, mode = scatter_37_mode_0, updates = var_851)[name = tensor("scatter_37")]; + tensor var_868_begin_0 = const()[name = tensor("op_868_begin_0"), val = tensor([1119])]; + tensor var_868_end_0 = const()[name = tensor("op_868_end_0"), val = tensor([1708])]; + tensor var_868_end_mask_0 = const()[name = tensor("op_868_end_mask_0"), val = tensor([false])]; + tensor var_868 = slice_by_index(begin = var_868_begin_0, end = var_868_end_0, end_mask = var_868_end_mask_0, x = scatter_36)[name = tensor("op_868")]; + tensor var_871_begin_0 = const()[name = tensor("op_871_begin_0"), val = tensor([19, 0])]; + tensor var_871_end_0 = const()[name = tensor("op_871_end_0"), val = tensor([20, 589])]; + tensor var_871_end_mask_0 = const()[name = tensor("op_871_end_mask_0"), val = tensor([false, true])]; + tensor var_871_squeeze_mask_0 = const()[name = tensor("op_871_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_871 = slice_by_index(begin = var_871_begin_0, end = var_871_end_0, end_mask = var_871_end_mask_0, squeeze_mask = var_871_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_871")]; + tensor var_873 = add(x = var_868, y = var_871)[name = tensor("op_873")]; + tensor slice_by_index_38 = const()[name = tensor("slice_by_index_38"), val = tensor([1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1364, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1381, 1382, 1383, 1384, 1385, 1386, 1387, 1388, 1389, 1390, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1399, 1400, 1401, 1402, 1403, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426, 1427, 1428, 1429, 1430, 1431, 1432, 1433, 1434, 1435, 1436, 1437, 1438, 1439, 1440, 1441, 1442, 1443, 1444, 1445, 1446, 1447, 1448, 1449, 1450, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1459, 1460, 1461, 1462, 1463, 1464, 1465, 1466, 1467, 1468, 1469, 1470, 1471, 1472, 1473, 1474, 1475, 1476, 1477, 1478, 1479, 1480, 1481, 1482, 1483, 1484, 1485, 1486, 1487, 1488, 1489, 1490, 1491, 1492, 1493, 1494, 1495, 1496, 1497, 1498, 1499, 1500, 1501, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1515, 1516, 1517, 1518, 1519, 1520, 1521, 1522, 1523, 1524, 1525, 1526, 1527, 1528, 1529, 1530, 1531, 1532, 1533, 1534, 1535, 1536, 1537, 1538, 1539, 1540, 1541, 1542, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1551, 1552, 1553, 1554, 1555, 1556, 1557, 1558, 1559, 1560, 1561, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1572, 1573, 1574, 1575, 1576, 1577, 1578, 1579, 1580, 1581, 1582, 1583, 1584, 1585, 1586, 1587, 1588, 1589, 1590, 1591, 1592, 1593, 1594, 1595, 1596, 1597, 1598, 1599, 1600, 1601, 1602, 1603, 1604, 1605, 1606, 1607, 1608, 1609, 1610, 1611, 1612, 1613, 1614, 1615, 1616, 1617, 1618, 1619, 1620, 1621, 1622, 1623, 1624, 1625, 1626, 1627, 1628, 1629, 1630, 1631, 1632, 1633, 1634, 1635, 1636, 1637, 1638, 1639, 1640, 1641, 1642, 1643, 1644, 1645, 1646, 1647, 1648, 1649, 1650, 1651, 1652, 1653, 1654, 1655, 1656, 1657, 1658, 1659, 1660, 1661, 1662, 1663, 1664, 1665, 1666, 1667, 1668, 1669, 1670, 1671, 1672, 1673, 1674, 1675, 1676, 1677, 1678, 1679, 1680, 1681, 1682, 1683, 1684, 1685, 1686, 1687, 1688, 1689, 1690, 1691, 1692, 1693, 1694, 1695, 1696, 1697, 1698, 1699, 1700, 1701, 1702, 1703, 1704, 1705, 1706, 1707])]; + tensor scatter_38_mode_0 = const()[name = tensor("scatter_38_mode_0"), val = tensor("update")]; + tensor scatter_38_axis_0 = const()[name = tensor("scatter_38_axis_0"), val = tensor(0)]; + tensor scatter_38 = scatter(axis = scatter_38_axis_0, data = scatter_36, indices = slice_by_index_38, mode = scatter_38_mode_0, updates = var_873)[name = tensor("scatter_38")]; + tensor var_883_begin_0 = const()[name = tensor("op_883_begin_0"), val = tensor([1119])]; + tensor var_883_end_0 = const()[name = tensor("op_883_end_0"), val = tensor([1708])]; + tensor var_883_end_mask_0 = const()[name = tensor("op_883_end_mask_0"), val = tensor([false])]; + tensor var_883 = slice_by_index(begin = var_883_begin_0, end = var_883_end_0, end_mask = var_883_end_mask_0, x = scatter_37)[name = tensor("op_883")]; + tensor var_884 = const()[name = tensor("op_884"), val = tensor(0x1p+0)]; + tensor var_886 = add(x = var_883, y = var_884)[name = tensor("op_886")]; + tensor scatter_39_mode_0 = const()[name = tensor("scatter_39_mode_0"), val = tensor("update")]; + tensor scatter_39_axis_0 = const()[name = tensor("scatter_39_axis_0"), val = tensor(0)]; + tensor scatter_39 = scatter(axis = scatter_39_axis_0, data = scatter_37, indices = slice_by_index_38, mode = scatter_39_mode_0, updates = var_886)[name = tensor("scatter_39")]; + tensor var_903_begin_0 = const()[name = tensor("op_903_begin_0"), val = tensor([1178])]; + tensor var_903_end_0 = const()[name = tensor("op_903_end_0"), val = tensor([1])]; + tensor var_903_end_mask_0 = const()[name = tensor("op_903_end_mask_0"), val = tensor([true])]; + tensor var_903 = slice_by_index(begin = var_903_begin_0, end = var_903_end_0, end_mask = var_903_end_mask_0, x = scatter_38)[name = tensor("op_903")]; + tensor var_906_begin_0 = const()[name = tensor("op_906_begin_0"), val = tensor([20, 0])]; + tensor var_906_end_0 = const()[name = tensor("op_906_end_0"), val = tensor([21, 589])]; + tensor var_906_end_mask_0 = const()[name = tensor("op_906_end_mask_0"), val = tensor([false, true])]; + tensor var_906_squeeze_mask_0 = const()[name = tensor("op_906_squeeze_mask_0"), val = tensor([true, false])]; + tensor var_906 = slice_by_index(begin = var_906_begin_0, end = var_906_end_0, end_mask = var_906_end_mask_0, squeeze_mask = var_906_squeeze_mask_0, x = reduce_max_0)[name = tensor("op_906")]; + tensor var_908 = add(x = var_903, y = var_906)[name = tensor("op_908")]; + tensor slice_by_index_40 = const()[name = tensor("slice_by_index_40"), val = tensor([1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1364, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1381, 1382, 1383, 1384, 1385, 1386, 1387, 1388, 1389, 1390, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1399, 1400, 1401, 1402, 1403, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426, 1427, 1428, 1429, 1430, 1431, 1432, 1433, 1434, 1435, 1436, 1437, 1438, 1439, 1440, 1441, 1442, 1443, 1444, 1445, 1446, 1447, 1448, 1449, 1450, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1459, 1460, 1461, 1462, 1463, 1464, 1465, 1466, 1467, 1468, 1469, 1470, 1471, 1472, 1473, 1474, 1475, 1476, 1477, 1478, 1479, 1480, 1481, 1482, 1483, 1484, 1485, 1486, 1487, 1488, 1489, 1490, 1491, 1492, 1493, 1494, 1495, 1496, 1497, 1498, 1499, 1500, 1501, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1515, 1516, 1517, 1518, 1519, 1520, 1521, 1522, 1523, 1524, 1525, 1526, 1527, 1528, 1529, 1530, 1531, 1532, 1533, 1534, 1535, 1536, 1537, 1538, 1539, 1540, 1541, 1542, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1551, 1552, 1553, 1554, 1555, 1556, 1557, 1558, 1559, 1560, 1561, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1572, 1573, 1574, 1575, 1576, 1577, 1578, 1579, 1580, 1581, 1582, 1583, 1584, 1585, 1586, 1587, 1588, 1589, 1590, 1591, 1592, 1593, 1594, 1595, 1596, 1597, 1598, 1599, 1600, 1601, 1602, 1603, 1604, 1605, 1606, 1607, 1608, 1609, 1610, 1611, 1612, 1613, 1614, 1615, 1616, 1617, 1618, 1619, 1620, 1621, 1622, 1623, 1624, 1625, 1626, 1627, 1628, 1629, 1630, 1631, 1632, 1633, 1634, 1635, 1636, 1637, 1638, 1639, 1640, 1641, 1642, 1643, 1644, 1645, 1646, 1647, 1648, 1649, 1650, 1651, 1652, 1653, 1654, 1655, 1656, 1657, 1658, 1659, 1660, 1661, 1662, 1663, 1664, 1665, 1666, 1667, 1668, 1669, 1670, 1671, 1672, 1673, 1674, 1675, 1676, 1677, 1678, 1679, 1680, 1681, 1682, 1683, 1684, 1685, 1686, 1687, 1688, 1689, 1690, 1691, 1692, 1693, 1694, 1695, 1696, 1697, 1698, 1699, 1700, 1701, 1702, 1703, 1704, 1705, 1706, 1707, 1708, 1709, 1710, 1711, 1712, 1713, 1714, 1715, 1716, 1717, 1718, 1719, 1720, 1721, 1722, 1723, 1724, 1725, 1726, 1727, 1728, 1729, 1730, 1731, 1732, 1733, 1734, 1735, 1736, 1737, 1738, 1739, 1740, 1741, 1742, 1743, 1744, 1745, 1746, 1747, 1748, 1749, 1750, 1751, 1752, 1753, 1754, 1755, 1756, 1757, 1758, 1759, 1760, 1761, 1762, 1763, 1764, 1765, 1766])]; + tensor scatter_40_mode_0 = const()[name = tensor("scatter_40_mode_0"), val = tensor("update")]; + tensor scatter_40_axis_0 = const()[name = tensor("scatter_40_axis_0"), val = tensor(0)]; + tensor scatter_40 = scatter(axis = scatter_40_axis_0, data = scatter_38, indices = slice_by_index_40, mode = scatter_40_mode_0, updates = var_908)[name = tensor("scatter_40")]; + tensor var_918_begin_0 = const()[name = tensor("op_918_begin_0"), val = tensor([1178])]; + tensor var_918_end_0 = const()[name = tensor("op_918_end_0"), val = tensor([1])]; + tensor var_918_end_mask_0 = const()[name = tensor("op_918_end_mask_0"), val = tensor([true])]; + tensor var_918 = slice_by_index(begin = var_918_begin_0, end = var_918_end_0, end_mask = var_918_end_mask_0, x = scatter_39)[name = tensor("op_918")]; + tensor var_919 = const()[name = tensor("op_919"), val = tensor(0x1p+0)]; + tensor var_921 = add(x = var_918, y = var_919)[name = tensor("op_921")]; + tensor scatter_41_mode_0 = const()[name = tensor("scatter_41_mode_0"), val = tensor("update")]; + tensor scatter_41_axis_0 = const()[name = tensor("scatter_41_axis_0"), val = tensor(0)]; + tensor scatter_41 = scatter(axis = scatter_41_axis_0, data = scatter_39, indices = slice_by_index_40, mode = scatter_41_mode_0, updates = var_921)[name = tensor("scatter_41")]; + tensor voice_activity_type_fp32 = real_div(x = scatter_40, y = scatter_41)[name = tensor("op_928")]; + tensor var_933_axes_0 = const()[name = tensor("op_933_axes_0"), val = tensor([1])]; + tensor var_933_keep_dims_0 = const()[name = tensor("op_933_keep_dims_0"), val = tensor(false)]; + tensor speaker_activity_type_fp32 = reduce_sum(axes = var_933_axes_0, keep_dims = var_933_keep_dims_0, x = speaker_ids_type_fp32)[name = tensor("op_933")]; + tensor var_938_axes_0 = const()[name = tensor("op_938_axes_0"), val = tensor([2])]; + tensor var_938_keep_dims_0 = const()[name = tensor("op_938_keep_dims_0"), val = tensor(false)]; + tensor var_938 = reduce_sum(axes = var_938_axes_0, keep_dims = var_938_keep_dims_0, x = speaker_ids_type_fp32)[name = tensor("op_938")]; + tensor var_939 = const()[name = tensor("op_939"), val = tensor(0x1p+0)]; + tensor var_940 = greater(x = var_938, y = var_939)[name = tensor("op_940")]; + tensor cast_6_dtype_0 = const()[name = tensor("cast_6_dtype_0"), val = tensor("fp16")]; + tensor cast_7_dtype_0 = const()[name = tensor("cast_7_dtype_0"), val = tensor("fp16")]; + tensor cast_8_dtype_0 = const()[name = tensor("cast_8_dtype_0"), val = tensor("fp16")]; + tensor cast_9_dtype_0 = const()[name = tensor("cast_9_dtype_0"), val = tensor("fp16")]; + tensor cast_10_dtype_0 = const()[name = tensor("cast_10_dtype_0"), val = tensor("fp16")]; + tensor cast_11_dtype_0 = const()[name = tensor("cast_11_dtype_0"), val = tensor("fp16")]; + tensor sliding_window_waveform = cast(dtype = cast_11_dtype_0, x = sliding_window_waveform_type_fp32)[name = tensor("cast_12")]; + tensor voice_activity = cast(dtype = cast_10_dtype_0, x = voice_activity_type_fp32)[name = tensor("cast_13")]; + tensor overlapped_speaker_activity = cast(dtype = cast_9_dtype_0, x = var_940)[name = tensor("cast_14")]; + tensor speaker_activity = cast(dtype = cast_8_dtype_0, x = speaker_activity_type_fp32)[name = tensor("cast_15")]; + tensor speaker_ids = cast(dtype = cast_7_dtype_0, x = speaker_ids_type_fp32)[name = tensor("cast_16")]; + tensor speaker_probs = cast(dtype = cast_6_dtype_0, x = speaker_probs_type_fp32)[name = tensor("cast_17")]; + } -> (speaker_probs, speaker_ids, speaker_activity, overlapped_speaker_activity, voice_activity, sliding_window_waveform); +} \ No newline at end of file