program(1.0) [buildInfo = dict, tensor>({{"coremlc-component-MIL", "5.25.0"}, {"coremlc-version", "1704.0.0.0.3"}, {"mldb_token", "mldb-7nwypqpa9o"}})] { func main(tensor audio, tensor cast_229_in_state, tensor input1_2_cast_in_state, tensor input_12_cast_elementwise_in_state, tensor input_13_cast_elementwise_in_state, tensor input_17_cast_in_state, tensor input_23_cast_elementwise_in_state, tensor input_27_cast_in_state, tensor input_33_cast_elementwise_in_state, tensor input_37_cast_in_state, tensor input_47_cast_in_state, tensor input_4_cast_in_state, tensor input_57_cast_in_state, tensor input_67_cast_in_state, tensor input_7_cast_in_state, tensor var_484_cast_elementwise_in_state) [FlexibleShapeInformation = tuple, dict, tensor>>, tuple, dict, list, ?>>>>((("DefaultShapes", {{"audio", [1, 4, 1920]}}), ("RangeDims", {{"audio", [[1, 1], [4, 4], [1920, 1920]]}}))), UserMetadata = dict, tensor>({{"iteration", "562569"}, {"taskid", "ubeyh3afn8"}})] { tensor var_3 = const()[name = tensor("op_3"), val = tensor(12)]; tensor var_4 = const()[name = tensor("op_4"), val = tensor(256)]; tensor var_12 = const()[name = tensor("op_12"), val = tensor(true)]; tensor var_16 = const()[name = tensor("op_16"), val = tensor(1)]; tensor var_26 = const()[name = tensor("op_26"), val = tensor([64])]; tensor var_28 = const()[name = tensor("op_28"), val = tensor([1])]; tensor input0_1_pad_type_0 = const()[name = tensor("input0_1_pad_type_0"), val = tensor("custom")]; tensor input0_1_pad_0 = const()[name = tensor("input0_1_pad_0"), val = tensor([64, 64])]; tensor audio_to_fp16_dtype_0 = const()[name = tensor("audio_to_fp16_dtype_0"), val = tensor("fp16")]; tensor stem_front_end_0_weight_to_fp16 = const()[name = tensor("stem_front_end_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; tensor cast_229 = cast(dtype = audio_to_fp16_dtype_0, x = audio); tensor cast_229_expanded = concat(axis = tensor(-1), interleave = tensor(false), values = (cast_229_in_state, cast_229)); tensor cast_229_out_state = slice_by_size(begin = tensor([0, 0, -64]), size = tensor([1, 4, 64]), x = cast_229_expanded); tensor input0_1_cast = conv(dilations = tensor([1]), groups = tensor(1), pad = tensor([0, 0]), pad_type = tensor("custom"), strides = tensor([64]), weight = stem_front_end_0_weight_to_fp16, x = cast_229_expanded); tensor var_31_cast = relu(x = input0_1_cast); tensor var_36 = const()[name = tensor("op_36"), val = tensor([1])]; tensor mean_y_4_cast = reduce_mean(axes = var_36, keep_dims = var_12, x = var_31_cast); tensor sub_0_cast = sub(x = var_31_cast, y = mean_y_4_cast); tensor square_0_cast = square(x = sub_0_cast); tensor reduce_mean_1_axes_0 = const()[name = tensor("reduce_mean_1_axes_0"), val = tensor([1])]; tensor reduce_mean_1_keep_dims_0 = const()[name = tensor("reduce_mean_1_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_1_cast = reduce_mean(axes = reduce_mean_1_axes_0, keep_dims = reduce_mean_1_keep_dims_0, x = square_0_cast); tensor sqrt_0_cast = sqrt(x = reduce_mean_1_cast); tensor mul_0_y_0_to_fp16 = const()[name = tensor("mul_0_y_0_to_fp16"), val = tensor(0x1.004p+0)]; tensor mul_0_cast = mul(x = sqrt_0_cast, y = mul_0_y_0_to_fp16); tensor var_40_to_fp16 = const()[name = tensor("op_40_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_4_cast = add(x = mul_0_cast, y = var_40_to_fp16); tensor stem_front_norm_norm_gamma_to_fp16 = const()[name = tensor("stem_front_norm_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(393344)))]; tensor var_43_cast = mul(x = stem_front_norm_norm_gamma_to_fp16, y = sub_0_cast); tensor var_44_cast = real_div(x = var_43_cast, y = std_y_4_cast); tensor stem_front_norm_norm_beta_to_fp16 = const()[name = tensor("stem_front_norm_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(394176)))]; tensor input_8_cast = add(x = var_44_cast, y = stem_front_norm_norm_beta_to_fp16); tensor var_47 = const()[name = tensor("op_47"), val = tensor([1])]; tensor var_49 = const()[name = tensor("op_49"), val = tensor([1])]; tensor input_12_pad_type_0 = const()[name = tensor("input_12_pad_type_0"), val = tensor("custom")]; tensor input_12_pad_0 = const()[name = tensor("input_12_pad_0"), val = tensor([0, 0])]; tensor stem_to_latent_weight_to_fp16 = const()[name = tensor("stem_to_latent_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(395008)))]; tensor input_12_cast = conv(dilations = var_49, groups = var_16, pad = input_12_pad_0, pad_type = input_12_pad_type_0, strides = var_47, weight = stem_to_latent_weight_to_fp16, x = input_8_cast); tensor var_68 = const()[name = tensor("op_68"), val = tensor([1])]; tensor var_70 = const()[name = tensor("op_70"), val = tensor([1])]; tensor input_5_pad_type_0 = const()[name = tensor("input_5_pad_type_0"), val = tensor("custom")]; tensor input_5_pad_0 = const()[name = tensor("input_5_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_0_tcn_0_weight_to_fp16 = const()[name = tensor("stem_sep_module_0_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(591680)))]; tensor input_5_cast = conv(dilations = var_70, groups = var_16, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = var_68, weight = stem_sep_module_0_tcn_0_weight_to_fp16, x = input_12_cast); tensor var_74_alpha_0_to_fp16 = const()[name = tensor("op_74_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(722816)))]; tensor var_74_cast = leaky_relu(alpha = tensor(0x1.06p-2), x = input_5_cast); tensor var_78 = const()[name = tensor("op_78"), val = tensor([1])]; tensor mean_y_3_cast = reduce_mean(axes = var_78, keep_dims = var_12, x = var_74_cast); tensor sub_1_cast = sub(x = var_74_cast, y = mean_y_3_cast); tensor square_1_cast = square(x = sub_1_cast); tensor reduce_mean_3_axes_0 = const()[name = tensor("reduce_mean_3_axes_0"), val = tensor([1])]; tensor reduce_mean_3_keep_dims_0 = const()[name = tensor("reduce_mean_3_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_3_cast = reduce_mean(axes = reduce_mean_3_axes_0, keep_dims = reduce_mean_3_keep_dims_0, x = square_1_cast); tensor sqrt_1_cast = sqrt(x = reduce_mean_3_cast); tensor mul_1_y_0_to_fp16 = const()[name = tensor("mul_1_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_1_cast = mul(x = sqrt_1_cast, y = mul_1_y_0_to_fp16); tensor var_82_to_fp16 = const()[name = tensor("op_82_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_3_cast = add(x = mul_1_cast, y = var_82_to_fp16); tensor stem_sep_module_0_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_0_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(723392)))]; tensor var_85_cast = mul(x = stem_sep_module_0_tcn_2_norm_gamma_to_fp16, y = sub_1_cast); tensor var_86_cast = real_div(x = var_85_cast, y = std_y_3_cast); tensor stem_sep_module_0_tcn_2_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_0_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(723968)))]; tensor input_7_cast = add(x = var_86_cast, y = stem_sep_module_0_tcn_2_norm_beta_to_fp16); tensor input_9_pad_0 = const()[name = tensor("input_9_pad_0"), val = tensor([0, 0, 0, 0, 1, 1])]; tensor input_9_mode_0 = const()[name = tensor("input_9_mode_0"), val = tensor("constant")]; tensor input_9_constant_val_0_to_fp16 = const()[name = tensor("input_9_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_9_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_7_cast_in_state, input_7_cast)); tensor input_7_cast_out_state = slice_by_size(begin = tensor([0, 0, -2]), size = tensor([1, 256, 2]), x = input_9_cast); tensor var_91 = const()[name = tensor("op_91"), val = tensor([1])]; tensor var_93 = const()[name = tensor("op_93"), val = tensor([1])]; tensor input_11_pad_type_0 = const()[name = tensor("input_11_pad_type_0"), val = tensor("custom")]; tensor input_11_pad_0 = const()[name = tensor("input_11_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_0_tcn_4_weight_to_fp16 = const()[name = tensor("stem_sep_module_0_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(724544)))]; tensor input_11_cast = conv(dilations = var_93, groups = var_4, pad = input_11_pad_0, pad_type = input_11_pad_type_0, strides = var_91, weight = stem_sep_module_0_tcn_4_weight_to_fp16, x = input_9_cast); tensor var_97_alpha_0_to_fp16 = const()[name = tensor("op_97_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(726144)))]; tensor var_97_cast = leaky_relu(alpha = tensor(-0x1.ff4p-4), x = input_11_cast); tensor var_101 = const()[name = tensor("op_101"), val = tensor([1])]; tensor mean_y_5_cast = reduce_mean(axes = var_101, keep_dims = var_12, x = var_97_cast); tensor sub_2_cast = sub(x = var_97_cast, y = mean_y_5_cast); tensor square_2_cast = square(x = sub_2_cast); tensor reduce_mean_5_axes_0 = const()[name = tensor("reduce_mean_5_axes_0"), val = tensor([1])]; tensor reduce_mean_5_keep_dims_0 = const()[name = tensor("reduce_mean_5_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_5_cast = reduce_mean(axes = reduce_mean_5_axes_0, keep_dims = reduce_mean_5_keep_dims_0, x = square_2_cast); tensor sqrt_2_cast = sqrt(x = reduce_mean_5_cast); tensor mul_2_y_0_to_fp16 = const()[name = tensor("mul_2_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_2_cast = mul(x = sqrt_2_cast, y = mul_2_y_0_to_fp16); tensor var_105_to_fp16 = const()[name = tensor("op_105_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_5_cast = add(x = mul_2_cast, y = var_105_to_fp16); tensor stem_sep_module_0_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_0_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(726720)))]; tensor var_108_cast = mul(x = stem_sep_module_0_tcn_6_norm_gamma_to_fp16, y = sub_2_cast); tensor var_109_cast = real_div(x = var_108_cast, y = std_y_5_cast); tensor stem_sep_module_0_tcn_6_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_0_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(727296)))]; tensor y_2_cast = add(x = var_109_cast, y = stem_sep_module_0_tcn_6_norm_beta_to_fp16); tensor input_12_cast_elementwise_expanded = concat(axis = tensor(-1), interleave = tensor(false), values = (input_12_cast_elementwise_in_state, input_12_cast)); tensor input_12_cast_elementwise_delayed = slice_by_size(begin = tensor([0, 0, 0]), size = tensor([1, 256, 30]), x = input_12_cast_elementwise_expanded); tensor input_12_cast_elementwise_out_state = slice_by_size(begin = tensor([0, 0, -1]), size = tensor([1, 256, 1]), x = input_12_cast_elementwise_expanded); tensor input_13_cast = add(x = input_12_cast_elementwise_delayed, y = y_2_cast); tensor var_120 = const()[name = tensor("op_120"), val = tensor([1])]; tensor var_122 = const()[name = tensor("op_122"), val = tensor([1])]; 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 stem_sep_module_1_tcn_0_weight_to_fp16 = const()[name = tensor("stem_sep_module_1_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(727872)))]; tensor input_15_cast = conv(dilations = var_122, groups = var_16, pad = input_15_pad_0, pad_type = input_15_pad_type_0, strides = var_120, weight = stem_sep_module_1_tcn_0_weight_to_fp16, x = input_13_cast); tensor var_126_alpha_0_to_fp16 = const()[name = tensor("op_126_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(859008)))]; tensor var_126_cast = leaky_relu(alpha = tensor(0x1.184p-1), x = input_15_cast); tensor var_130 = const()[name = tensor("op_130"), val = tensor([1])]; tensor mean_y_7_cast = reduce_mean(axes = var_130, keep_dims = var_12, x = var_126_cast); tensor sub_3_cast = sub(x = var_126_cast, y = mean_y_7_cast); tensor square_3_cast = square(x = sub_3_cast); tensor reduce_mean_7_axes_0 = const()[name = tensor("reduce_mean_7_axes_0"), val = tensor([1])]; tensor reduce_mean_7_keep_dims_0 = const()[name = tensor("reduce_mean_7_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_7_cast = reduce_mean(axes = reduce_mean_7_axes_0, keep_dims = reduce_mean_7_keep_dims_0, x = square_3_cast); tensor sqrt_3_cast = sqrt(x = reduce_mean_7_cast); tensor mul_3_y_0_to_fp16 = const()[name = tensor("mul_3_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_3_cast = mul(x = sqrt_3_cast, y = mul_3_y_0_to_fp16); tensor var_134_to_fp16 = const()[name = tensor("op_134_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_7_cast = add(x = mul_3_cast, y = var_134_to_fp16); tensor stem_sep_module_1_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_1_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(859584)))]; tensor var_137_cast = mul(x = stem_sep_module_1_tcn_2_norm_gamma_to_fp16, y = sub_3_cast); tensor var_138_cast = real_div(x = var_137_cast, y = std_y_7_cast); tensor stem_sep_module_1_tcn_2_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_1_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(860160)))]; tensor input_17_cast = add(x = var_138_cast, y = stem_sep_module_1_tcn_2_norm_beta_to_fp16); tensor input_19_pad_0 = const()[name = tensor("input_19_pad_0"), val = tensor([0, 0, 0, 0, 2, 2])]; tensor input_19_mode_0 = const()[name = tensor("input_19_mode_0"), val = tensor("constant")]; tensor input_19_constant_val_0_to_fp16 = const()[name = tensor("input_19_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_19_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_17_cast_in_state, input_17_cast)); tensor input_17_cast_out_state = slice_by_size(begin = tensor([0, 0, -4]), size = tensor([1, 256, 4]), x = input_19_cast); tensor var_143 = const()[name = tensor("op_143"), val = tensor([1])]; tensor var_145 = const()[name = tensor("op_145"), val = tensor([2])]; tensor input_21_pad_type_0 = const()[name = tensor("input_21_pad_type_0"), val = tensor("custom")]; tensor input_21_pad_0 = const()[name = tensor("input_21_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_1_tcn_4_weight_to_fp16 = const()[name = tensor("stem_sep_module_1_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(860736)))]; tensor input_21_cast = conv(dilations = var_145, groups = var_4, pad = input_21_pad_0, pad_type = input_21_pad_type_0, strides = var_143, weight = stem_sep_module_1_tcn_4_weight_to_fp16, x = input_19_cast); tensor var_149_alpha_0_to_fp16 = const()[name = tensor("op_149_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(862336)))]; tensor var_149_cast = leaky_relu(alpha = tensor(-0x1.718p-6), x = input_21_cast); tensor var_153 = const()[name = tensor("op_153"), val = tensor([1])]; tensor mean_y_9_cast = reduce_mean(axes = var_153, keep_dims = var_12, x = var_149_cast); tensor sub_4_cast = sub(x = var_149_cast, y = mean_y_9_cast); tensor square_4_cast = square(x = sub_4_cast); tensor reduce_mean_9_axes_0 = const()[name = tensor("reduce_mean_9_axes_0"), val = tensor([1])]; tensor reduce_mean_9_keep_dims_0 = const()[name = tensor("reduce_mean_9_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_9_cast = reduce_mean(axes = reduce_mean_9_axes_0, keep_dims = reduce_mean_9_keep_dims_0, x = square_4_cast); tensor sqrt_4_cast = sqrt(x = reduce_mean_9_cast); tensor mul_4_y_0_to_fp16 = const()[name = tensor("mul_4_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_4_cast = mul(x = sqrt_4_cast, y = mul_4_y_0_to_fp16); tensor var_157_to_fp16 = const()[name = tensor("op_157_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_9_cast = add(x = mul_4_cast, y = var_157_to_fp16); tensor stem_sep_module_1_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_1_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(862912)))]; tensor var_160_cast = mul(x = stem_sep_module_1_tcn_6_norm_gamma_to_fp16, y = sub_4_cast); tensor var_161_cast = real_div(x = var_160_cast, y = std_y_9_cast); tensor stem_sep_module_1_tcn_6_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_1_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(863488)))]; tensor y_4_cast = add(x = var_161_cast, y = stem_sep_module_1_tcn_6_norm_beta_to_fp16); tensor input_13_cast_elementwise_expanded = concat(axis = tensor(-1), interleave = tensor(false), values = (input_13_cast_elementwise_in_state, input_13_cast)); tensor input_13_cast_elementwise_delayed = slice_by_size(begin = tensor([0, 0, 0]), size = tensor([1, 256, 30]), x = input_13_cast_elementwise_expanded); tensor input_13_cast_elementwise_out_state = slice_by_size(begin = tensor([0, 0, -2]), size = tensor([1, 256, 2]), x = input_13_cast_elementwise_expanded); tensor input_23_cast = add(x = input_13_cast_elementwise_delayed, y = y_4_cast); tensor var_172 = const()[name = tensor("op_172"), val = tensor([1])]; tensor var_174 = const()[name = tensor("op_174"), val = tensor([1])]; tensor input_25_pad_type_0 = const()[name = tensor("input_25_pad_type_0"), val = tensor("custom")]; tensor input_25_pad_0 = const()[name = tensor("input_25_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_2_tcn_0_weight_to_fp16 = const()[name = tensor("stem_sep_module_2_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(864064)))]; tensor input_25_cast = conv(dilations = var_174, groups = var_16, pad = input_25_pad_0, pad_type = input_25_pad_type_0, strides = var_172, weight = stem_sep_module_2_tcn_0_weight_to_fp16, x = input_23_cast); tensor var_178_alpha_0_to_fp16 = const()[name = tensor("op_178_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(995200)))]; tensor var_178_cast = leaky_relu(alpha = tensor(-0x1.c04p-1), x = input_25_cast); tensor var_182 = const()[name = tensor("op_182"), val = tensor([1])]; tensor mean_y_11_cast = reduce_mean(axes = var_182, keep_dims = var_12, x = var_178_cast); tensor sub_5_cast = sub(x = var_178_cast, y = mean_y_11_cast); tensor square_5_cast = square(x = sub_5_cast); tensor reduce_mean_11_axes_0 = const()[name = tensor("reduce_mean_11_axes_0"), val = tensor([1])]; tensor reduce_mean_11_keep_dims_0 = const()[name = tensor("reduce_mean_11_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_11_cast = reduce_mean(axes = reduce_mean_11_axes_0, keep_dims = reduce_mean_11_keep_dims_0, x = square_5_cast); tensor sqrt_5_cast = sqrt(x = reduce_mean_11_cast); tensor mul_5_y_0_to_fp16 = const()[name = tensor("mul_5_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_5_cast = mul(x = sqrt_5_cast, y = mul_5_y_0_to_fp16); tensor var_186_to_fp16 = const()[name = tensor("op_186_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_11_cast = add(x = mul_5_cast, y = var_186_to_fp16); tensor stem_sep_module_2_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_2_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(995776)))]; tensor var_189_cast = mul(x = stem_sep_module_2_tcn_2_norm_gamma_to_fp16, y = sub_5_cast); tensor var_190_cast = real_div(x = var_189_cast, y = std_y_11_cast); tensor stem_sep_module_2_tcn_2_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_2_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(996352)))]; tensor input_27_cast = add(x = var_190_cast, y = stem_sep_module_2_tcn_2_norm_beta_to_fp16); tensor input_29_pad_0 = const()[name = tensor("input_29_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input_29_mode_0 = const()[name = tensor("input_29_mode_0"), val = tensor("constant")]; tensor input_29_constant_val_0_to_fp16 = const()[name = tensor("input_29_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_29_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_27_cast_in_state, input_27_cast)); tensor input_27_cast_out_state = slice_by_size(begin = tensor([0, 0, -8]), size = tensor([1, 256, 8]), x = input_29_cast); tensor var_195 = const()[name = tensor("op_195"), val = tensor([1])]; tensor var_197 = const()[name = tensor("op_197"), val = tensor([4])]; tensor input_31_pad_type_0 = const()[name = tensor("input_31_pad_type_0"), val = tensor("custom")]; tensor input_31_pad_0 = const()[name = tensor("input_31_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_2_tcn_4_weight_to_fp16 = const()[name = tensor("stem_sep_module_2_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(996928)))]; tensor input_31_cast = conv(dilations = var_197, groups = var_4, pad = input_31_pad_0, pad_type = input_31_pad_type_0, strides = var_195, weight = stem_sep_module_2_tcn_4_weight_to_fp16, x = input_29_cast); tensor var_201_alpha_0_to_fp16 = const()[name = tensor("op_201_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(998528)))]; tensor var_201_cast = leaky_relu(alpha = tensor(0x1.7b8p-2), x = input_31_cast); tensor var_205 = const()[name = tensor("op_205"), val = tensor([1])]; tensor mean_y_13_cast = reduce_mean(axes = var_205, keep_dims = var_12, x = var_201_cast); tensor sub_6_cast = sub(x = var_201_cast, y = mean_y_13_cast); tensor square_6_cast = square(x = sub_6_cast); tensor reduce_mean_13_axes_0 = const()[name = tensor("reduce_mean_13_axes_0"), val = tensor([1])]; tensor reduce_mean_13_keep_dims_0 = const()[name = tensor("reduce_mean_13_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_13_cast = reduce_mean(axes = reduce_mean_13_axes_0, keep_dims = reduce_mean_13_keep_dims_0, x = square_6_cast); tensor sqrt_6_cast = sqrt(x = reduce_mean_13_cast); tensor mul_6_y_0_to_fp16 = const()[name = tensor("mul_6_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_6_cast = mul(x = sqrt_6_cast, y = mul_6_y_0_to_fp16); tensor var_209_to_fp16 = const()[name = tensor("op_209_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_13_cast = add(x = mul_6_cast, y = var_209_to_fp16); tensor stem_sep_module_2_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_2_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(999104)))]; tensor var_212_cast = mul(x = stem_sep_module_2_tcn_6_norm_gamma_to_fp16, y = sub_6_cast); tensor var_213_cast = real_div(x = var_212_cast, y = std_y_13_cast); tensor stem_sep_module_2_tcn_6_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_2_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(999680)))]; tensor y_6_cast = add(x = var_213_cast, y = stem_sep_module_2_tcn_6_norm_beta_to_fp16); tensor input_23_cast_elementwise_expanded = concat(axis = tensor(-1), interleave = tensor(false), values = (input_23_cast_elementwise_in_state, input_23_cast)); tensor input_23_cast_elementwise_delayed = slice_by_size(begin = tensor([0, 0, 0]), size = tensor([1, 256, 30]), x = input_23_cast_elementwise_expanded); tensor input_23_cast_elementwise_out_state = slice_by_size(begin = tensor([0, 0, -4]), size = tensor([1, 256, 4]), x = input_23_cast_elementwise_expanded); tensor input_33_cast = add(x = input_23_cast_elementwise_delayed, y = y_6_cast); tensor var_224 = const()[name = tensor("op_224"), val = tensor([1])]; tensor var_226 = const()[name = tensor("op_226"), val = tensor([1])]; tensor input_35_pad_type_0 = const()[name = tensor("input_35_pad_type_0"), val = tensor("custom")]; tensor input_35_pad_0 = const()[name = tensor("input_35_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_3_tcn_0_weight_to_fp16 = const()[name = tensor("stem_sep_module_3_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1000256)))]; tensor input_35_cast = conv(dilations = var_226, groups = var_16, pad = input_35_pad_0, pad_type = input_35_pad_type_0, strides = var_224, weight = stem_sep_module_3_tcn_0_weight_to_fp16, x = input_33_cast); tensor var_230_alpha_0_to_fp16 = const()[name = tensor("op_230_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1131392)))]; tensor var_230_cast = leaky_relu(alpha = tensor(0x1.c98p-2), x = input_35_cast); tensor var_234 = const()[name = tensor("op_234"), val = tensor([1])]; tensor mean_y_15_cast = reduce_mean(axes = var_234, keep_dims = var_12, x = var_230_cast); tensor sub_7_cast = sub(x = var_230_cast, y = mean_y_15_cast); tensor square_7_cast = square(x = sub_7_cast); tensor reduce_mean_15_axes_0 = const()[name = tensor("reduce_mean_15_axes_0"), val = tensor([1])]; tensor reduce_mean_15_keep_dims_0 = const()[name = tensor("reduce_mean_15_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_15_cast = reduce_mean(axes = reduce_mean_15_axes_0, keep_dims = reduce_mean_15_keep_dims_0, x = square_7_cast); tensor sqrt_7_cast = sqrt(x = reduce_mean_15_cast); tensor mul_7_y_0_to_fp16 = const()[name = tensor("mul_7_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_7_cast = mul(x = sqrt_7_cast, y = mul_7_y_0_to_fp16); tensor var_238_to_fp16 = const()[name = tensor("op_238_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_15_cast = add(x = mul_7_cast, y = var_238_to_fp16); tensor stem_sep_module_3_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_3_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1131968)))]; tensor var_241_cast = mul(x = stem_sep_module_3_tcn_2_norm_gamma_to_fp16, y = sub_7_cast); tensor var_242_cast = real_div(x = var_241_cast, y = std_y_15_cast); tensor stem_sep_module_3_tcn_2_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_3_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1132544)))]; tensor input_37_cast = add(x = var_242_cast, y = stem_sep_module_3_tcn_2_norm_beta_to_fp16); tensor input_39_pad_0 = const()[name = tensor("input_39_pad_0"), val = tensor([0, 0, 0, 0, 8, 8])]; tensor input_39_mode_0 = const()[name = tensor("input_39_mode_0"), val = tensor("constant")]; tensor input_39_constant_val_0_to_fp16 = const()[name = tensor("input_39_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_39_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_37_cast_in_state, input_37_cast)); tensor input_37_cast_out_state = slice_by_size(begin = tensor([0, 0, -16]), size = tensor([1, 256, 16]), x = input_39_cast); tensor var_247 = const()[name = tensor("op_247"), val = tensor([1])]; tensor var_249 = const()[name = tensor("op_249"), val = tensor([8])]; tensor input_41_pad_type_0 = const()[name = tensor("input_41_pad_type_0"), val = tensor("custom")]; tensor input_41_pad_0 = const()[name = tensor("input_41_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_3_tcn_4_weight_to_fp16 = const()[name = tensor("stem_sep_module_3_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1133120)))]; tensor input_41_cast = conv(dilations = var_249, groups = var_4, pad = input_41_pad_0, pad_type = input_41_pad_type_0, strides = var_247, weight = stem_sep_module_3_tcn_4_weight_to_fp16, x = input_39_cast); tensor var_253_alpha_0_to_fp16 = const()[name = tensor("op_253_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1134720)))]; tensor var_253_cast = leaky_relu(alpha = tensor(0x1.d38p-2), x = input_41_cast); tensor var_257 = const()[name = tensor("op_257"), val = tensor([1])]; tensor mean_y_17_cast = reduce_mean(axes = var_257, keep_dims = var_12, x = var_253_cast); tensor sub_8_cast = sub(x = var_253_cast, y = mean_y_17_cast); tensor square_8_cast = square(x = sub_8_cast); tensor reduce_mean_17_axes_0 = const()[name = tensor("reduce_mean_17_axes_0"), val = tensor([1])]; tensor reduce_mean_17_keep_dims_0 = const()[name = tensor("reduce_mean_17_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_17_cast = reduce_mean(axes = reduce_mean_17_axes_0, keep_dims = reduce_mean_17_keep_dims_0, x = square_8_cast); tensor sqrt_8_cast = sqrt(x = reduce_mean_17_cast); tensor mul_8_y_0_to_fp16 = const()[name = tensor("mul_8_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_8_cast = mul(x = sqrt_8_cast, y = mul_8_y_0_to_fp16); tensor var_261_to_fp16 = const()[name = tensor("op_261_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_17_cast = add(x = mul_8_cast, y = var_261_to_fp16); tensor stem_sep_module_3_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_3_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1135296)))]; tensor var_264_cast = mul(x = stem_sep_module_3_tcn_6_norm_gamma_to_fp16, y = sub_8_cast); tensor var_265_cast = real_div(x = var_264_cast, y = std_y_17_cast); tensor stem_sep_module_3_tcn_6_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_3_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1135872)))]; tensor y_8_cast = add(x = var_265_cast, y = stem_sep_module_3_tcn_6_norm_beta_to_fp16); tensor input_33_cast_elementwise_expanded = concat(axis = tensor(-1), interleave = tensor(false), values = (input_33_cast_elementwise_in_state, input_33_cast)); tensor input_33_cast_elementwise_delayed = slice_by_size(begin = tensor([0, 0, 0]), size = tensor([1, 256, 30]), x = input_33_cast_elementwise_expanded); tensor input_33_cast_elementwise_out_state = slice_by_size(begin = tensor([0, 0, -8]), size = tensor([1, 256, 8]), x = input_33_cast_elementwise_expanded); tensor input_43_cast = add(x = input_33_cast_elementwise_delayed, y = y_8_cast); tensor var_276 = const()[name = tensor("op_276"), val = tensor([1])]; tensor var_278 = const()[name = tensor("op_278"), val = tensor([1])]; tensor input_45_pad_type_0 = const()[name = tensor("input_45_pad_type_0"), val = tensor("custom")]; tensor input_45_pad_0 = const()[name = tensor("input_45_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_4_tcn_0_weight_to_fp16 = const()[name = tensor("stem_sep_module_4_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1136448)))]; tensor input_45_cast = conv(dilations = var_278, groups = var_16, pad = input_45_pad_0, pad_type = input_45_pad_type_0, strides = var_276, weight = stem_sep_module_4_tcn_0_weight_to_fp16, x = input_43_cast); tensor var_282_alpha_0_to_fp16 = const()[name = tensor("op_282_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1267584)))]; tensor var_282_cast = leaky_relu(alpha = tensor(0x1.978p+1), x = input_45_cast); tensor var_286 = const()[name = tensor("op_286"), val = tensor([1])]; tensor mean_y_19_cast = reduce_mean(axes = var_286, keep_dims = var_12, x = var_282_cast); tensor sub_9_cast = sub(x = var_282_cast, y = mean_y_19_cast); tensor square_9_cast = square(x = sub_9_cast); tensor reduce_mean_19_axes_0 = const()[name = tensor("reduce_mean_19_axes_0"), val = tensor([1])]; tensor reduce_mean_19_keep_dims_0 = const()[name = tensor("reduce_mean_19_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_19_cast = reduce_mean(axes = reduce_mean_19_axes_0, keep_dims = reduce_mean_19_keep_dims_0, x = square_9_cast); tensor sqrt_9_cast = sqrt(x = reduce_mean_19_cast); tensor mul_9_y_0_to_fp16 = const()[name = tensor("mul_9_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_9_cast = mul(x = sqrt_9_cast, y = mul_9_y_0_to_fp16); tensor var_290_to_fp16 = const()[name = tensor("op_290_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_19_cast = add(x = mul_9_cast, y = var_290_to_fp16); tensor stem_sep_module_4_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_4_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1268160)))]; tensor var_293_cast = mul(x = stem_sep_module_4_tcn_2_norm_gamma_to_fp16, y = sub_9_cast); tensor var_294_cast = real_div(x = var_293_cast, y = std_y_19_cast); tensor stem_sep_module_4_tcn_2_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_4_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1268736)))]; tensor input_47_cast = add(x = var_294_cast, y = stem_sep_module_4_tcn_2_norm_beta_to_fp16); tensor input_49_pad_0 = const()[name = tensor("input_49_pad_0"), val = tensor([0, 0, 0, 0, 32, 0])]; tensor input_49_mode_0 = const()[name = tensor("input_49_mode_0"), val = tensor("constant")]; tensor input_49_constant_val_0_to_fp16 = const()[name = tensor("input_49_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_49_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_47_cast_in_state, input_47_cast)); tensor input_47_cast_out_state = slice_by_size(begin = tensor([0, 0, -32]), size = tensor([1, 256, 32]), x = input_49_cast); tensor var_299 = const()[name = tensor("op_299"), val = tensor([1])]; tensor var_301 = const()[name = tensor("op_301"), val = tensor([16])]; tensor input_51_pad_type_0 = const()[name = tensor("input_51_pad_type_0"), val = tensor("custom")]; tensor input_51_pad_0 = const()[name = tensor("input_51_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_4_tcn_4_weight_to_fp16 = const()[name = tensor("stem_sep_module_4_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1269312)))]; tensor input_51_cast = conv(dilations = var_301, groups = var_4, pad = input_51_pad_0, pad_type = input_51_pad_type_0, strides = var_299, weight = stem_sep_module_4_tcn_4_weight_to_fp16, x = input_49_cast); tensor var_305_alpha_0_to_fp16 = const()[name = tensor("op_305_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1270912)))]; tensor var_305_cast = leaky_relu(alpha = tensor(-0x1.754p-1), x = input_51_cast); tensor var_309 = const()[name = tensor("op_309"), val = tensor([1])]; tensor mean_y_21_cast = reduce_mean(axes = var_309, keep_dims = var_12, x = var_305_cast); tensor sub_10_cast = sub(x = var_305_cast, y = mean_y_21_cast); tensor square_10_cast = square(x = sub_10_cast); tensor reduce_mean_21_axes_0 = const()[name = tensor("reduce_mean_21_axes_0"), val = tensor([1])]; tensor reduce_mean_21_keep_dims_0 = const()[name = tensor("reduce_mean_21_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_21_cast = reduce_mean(axes = reduce_mean_21_axes_0, keep_dims = reduce_mean_21_keep_dims_0, x = square_10_cast); tensor sqrt_10_cast = sqrt(x = reduce_mean_21_cast); tensor mul_10_y_0_to_fp16 = const()[name = tensor("mul_10_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_10_cast = mul(x = sqrt_10_cast, y = mul_10_y_0_to_fp16); tensor var_313_to_fp16 = const()[name = tensor("op_313_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_21_cast = add(x = mul_10_cast, y = var_313_to_fp16); tensor stem_sep_module_4_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_4_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1271488)))]; tensor var_316_cast = mul(x = stem_sep_module_4_tcn_6_norm_gamma_to_fp16, y = sub_10_cast); tensor var_317_cast = real_div(x = var_316_cast, y = std_y_21_cast); tensor stem_sep_module_4_tcn_6_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_4_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1272064)))]; tensor y_10_cast = add(x = var_317_cast, y = stem_sep_module_4_tcn_6_norm_beta_to_fp16); tensor input_53_cast = add(x = input_43_cast, y = y_10_cast); tensor var_328 = const()[name = tensor("op_328"), val = tensor([1])]; tensor var_330 = const()[name = tensor("op_330"), val = tensor([1])]; tensor input_55_pad_type_0 = const()[name = tensor("input_55_pad_type_0"), val = tensor("custom")]; tensor input_55_pad_0 = const()[name = tensor("input_55_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_5_tcn_0_weight_to_fp16 = const()[name = tensor("stem_sep_module_5_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1272640)))]; tensor input_55_cast = conv(dilations = var_330, groups = var_16, pad = input_55_pad_0, pad_type = input_55_pad_type_0, strides = var_328, weight = stem_sep_module_5_tcn_0_weight_to_fp16, x = input_53_cast); tensor var_334_alpha_0_to_fp16 = const()[name = tensor("op_334_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1403776)))]; tensor var_334_cast = leaky_relu(alpha = tensor(0x1.444p-2), x = input_55_cast); tensor var_338 = const()[name = tensor("op_338"), val = tensor([1])]; tensor mean_y_23_cast = reduce_mean(axes = var_338, keep_dims = var_12, x = var_334_cast); tensor sub_11_cast = sub(x = var_334_cast, y = mean_y_23_cast); tensor square_11_cast = square(x = sub_11_cast); tensor reduce_mean_23_axes_0 = const()[name = tensor("reduce_mean_23_axes_0"), val = tensor([1])]; tensor reduce_mean_23_keep_dims_0 = const()[name = tensor("reduce_mean_23_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_23_cast = reduce_mean(axes = reduce_mean_23_axes_0, keep_dims = reduce_mean_23_keep_dims_0, x = square_11_cast); tensor sqrt_11_cast = sqrt(x = reduce_mean_23_cast); tensor mul_11_y_0_to_fp16 = const()[name = tensor("mul_11_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_11_cast = mul(x = sqrt_11_cast, y = mul_11_y_0_to_fp16); tensor var_342_to_fp16 = const()[name = tensor("op_342_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_23_cast = add(x = mul_11_cast, y = var_342_to_fp16); tensor stem_sep_module_5_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_5_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1404352)))]; tensor var_345_cast = mul(x = stem_sep_module_5_tcn_2_norm_gamma_to_fp16, y = sub_11_cast); tensor var_346_cast = real_div(x = var_345_cast, y = std_y_23_cast); tensor stem_sep_module_5_tcn_2_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_5_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1404928)))]; tensor input_57_cast = add(x = var_346_cast, y = stem_sep_module_5_tcn_2_norm_beta_to_fp16); tensor input_59_pad_0 = const()[name = tensor("input_59_pad_0"), val = tensor([0, 0, 0, 0, 64, 0])]; tensor input_59_mode_0 = const()[name = tensor("input_59_mode_0"), val = tensor("constant")]; tensor input_59_constant_val_0_to_fp16 = const()[name = tensor("input_59_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_59_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_57_cast_in_state, input_57_cast)); tensor input_57_cast_out_state = slice_by_size(begin = tensor([0, 0, -64]), size = tensor([1, 256, 64]), x = input_59_cast); tensor var_351 = const()[name = tensor("op_351"), val = tensor([1])]; tensor var_353 = const()[name = tensor("op_353"), val = tensor([32])]; tensor input_61_pad_type_0 = const()[name = tensor("input_61_pad_type_0"), val = tensor("custom")]; tensor input_61_pad_0 = const()[name = tensor("input_61_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_5_tcn_4_weight_to_fp16 = const()[name = tensor("stem_sep_module_5_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1405504)))]; tensor input_61_cast = conv(dilations = var_353, groups = var_4, pad = input_61_pad_0, pad_type = input_61_pad_type_0, strides = var_351, weight = stem_sep_module_5_tcn_4_weight_to_fp16, x = input_59_cast); tensor var_357_alpha_0_to_fp16 = const()[name = tensor("op_357_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1407104)))]; tensor var_357_cast = leaky_relu(alpha = tensor(-0x1.2a8p-1), x = input_61_cast); tensor var_361 = const()[name = tensor("op_361"), val = tensor([1])]; tensor mean_y_25_cast = reduce_mean(axes = var_361, keep_dims = var_12, x = var_357_cast); tensor sub_12_cast = sub(x = var_357_cast, y = mean_y_25_cast); tensor square_12_cast = square(x = sub_12_cast); tensor reduce_mean_25_axes_0 = const()[name = tensor("reduce_mean_25_axes_0"), val = tensor([1])]; tensor reduce_mean_25_keep_dims_0 = const()[name = tensor("reduce_mean_25_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_25_cast = reduce_mean(axes = reduce_mean_25_axes_0, keep_dims = reduce_mean_25_keep_dims_0, x = square_12_cast); tensor sqrt_12_cast = sqrt(x = reduce_mean_25_cast); tensor mul_12_y_0_to_fp16 = const()[name = tensor("mul_12_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_12_cast = mul(x = sqrt_12_cast, y = mul_12_y_0_to_fp16); tensor var_365_to_fp16 = const()[name = tensor("op_365_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_25_cast = add(x = mul_12_cast, y = var_365_to_fp16); tensor stem_sep_module_5_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_5_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1407680)))]; tensor var_368_cast = mul(x = stem_sep_module_5_tcn_6_norm_gamma_to_fp16, y = sub_12_cast); tensor var_369_cast = real_div(x = var_368_cast, y = std_y_25_cast); tensor stem_sep_module_5_tcn_6_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_5_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1408256)))]; tensor y_12_cast = add(x = var_369_cast, y = stem_sep_module_5_tcn_6_norm_beta_to_fp16); tensor input_63_cast = add(x = input_53_cast, y = y_12_cast); tensor var_380 = const()[name = tensor("op_380"), val = tensor([1])]; tensor var_382 = const()[name = tensor("op_382"), val = tensor([1])]; tensor input_65_pad_type_0 = const()[name = tensor("input_65_pad_type_0"), val = tensor("custom")]; tensor input_65_pad_0 = const()[name = tensor("input_65_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_6_tcn_0_weight_to_fp16 = const()[name = tensor("stem_sep_module_6_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1408832)))]; tensor input_65_cast = conv(dilations = var_382, groups = var_16, pad = input_65_pad_0, pad_type = input_65_pad_type_0, strides = var_380, weight = stem_sep_module_6_tcn_0_weight_to_fp16, x = input_63_cast); tensor var_386_alpha_0_to_fp16 = const()[name = tensor("op_386_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1539968)))]; tensor var_386_cast = leaky_relu(alpha = tensor(0x1.28p-2), x = input_65_cast); tensor var_390 = const()[name = tensor("op_390"), val = tensor([1])]; tensor mean_y_27_cast = reduce_mean(axes = var_390, keep_dims = var_12, x = var_386_cast); tensor sub_13_cast = sub(x = var_386_cast, y = mean_y_27_cast); tensor square_13_cast = square(x = sub_13_cast); tensor reduce_mean_27_axes_0 = const()[name = tensor("reduce_mean_27_axes_0"), val = tensor([1])]; tensor reduce_mean_27_keep_dims_0 = const()[name = tensor("reduce_mean_27_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_27_cast = reduce_mean(axes = reduce_mean_27_axes_0, keep_dims = reduce_mean_27_keep_dims_0, x = square_13_cast); tensor sqrt_13_cast = sqrt(x = reduce_mean_27_cast); tensor mul_13_y_0_to_fp16 = const()[name = tensor("mul_13_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_13_cast = mul(x = sqrt_13_cast, y = mul_13_y_0_to_fp16); tensor var_394_to_fp16 = const()[name = tensor("op_394_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_27_cast = add(x = mul_13_cast, y = var_394_to_fp16); tensor stem_sep_module_6_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_6_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1540544)))]; tensor var_397_cast = mul(x = stem_sep_module_6_tcn_2_norm_gamma_to_fp16, y = sub_13_cast); tensor var_398_cast = real_div(x = var_397_cast, y = std_y_27_cast); tensor stem_sep_module_6_tcn_2_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_6_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1541120)))]; tensor input_67_cast = add(x = var_398_cast, y = stem_sep_module_6_tcn_2_norm_beta_to_fp16); tensor input_69_pad_0 = const()[name = tensor("input_69_pad_0"), val = tensor([0, 0, 0, 0, 128, 0])]; tensor input_69_mode_0 = const()[name = tensor("input_69_mode_0"), val = tensor("constant")]; tensor input_69_constant_val_0_to_fp16 = const()[name = tensor("input_69_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_69_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_67_cast_in_state, input_67_cast)); tensor input_67_cast_out_state = slice_by_size(begin = tensor([0, 0, -128]), size = tensor([1, 256, 128]), x = input_69_cast); tensor var_403 = const()[name = tensor("op_403"), val = tensor([1])]; tensor var_405 = const()[name = tensor("op_405"), val = tensor([64])]; tensor input_71_pad_type_0 = const()[name = tensor("input_71_pad_type_0"), val = tensor("custom")]; tensor input_71_pad_0 = const()[name = tensor("input_71_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_6_tcn_4_weight_to_fp16 = const()[name = tensor("stem_sep_module_6_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1541696)))]; tensor input_71_cast = conv(dilations = var_405, groups = var_4, pad = input_71_pad_0, pad_type = input_71_pad_type_0, strides = var_403, weight = stem_sep_module_6_tcn_4_weight_to_fp16, x = input_69_cast); tensor var_409_alpha_0_to_fp16 = const()[name = tensor("op_409_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1543296)))]; tensor var_409_cast = leaky_relu(alpha = tensor(-0x1.38cp-1), x = input_71_cast); tensor var_413 = const()[name = tensor("op_413"), val = tensor([1])]; tensor mean_y_29_cast = reduce_mean(axes = var_413, keep_dims = var_12, x = var_409_cast); tensor sub_14_cast = sub(x = var_409_cast, y = mean_y_29_cast); tensor square_14_cast = square(x = sub_14_cast); tensor reduce_mean_29_axes_0 = const()[name = tensor("reduce_mean_29_axes_0"), val = tensor([1])]; tensor reduce_mean_29_keep_dims_0 = const()[name = tensor("reduce_mean_29_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_29_cast = reduce_mean(axes = reduce_mean_29_axes_0, keep_dims = reduce_mean_29_keep_dims_0, x = square_14_cast); tensor sqrt_14_cast = sqrt(x = reduce_mean_29_cast); tensor mul_14_y_0_to_fp16 = const()[name = tensor("mul_14_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_14_cast = mul(x = sqrt_14_cast, y = mul_14_y_0_to_fp16); tensor var_417_to_fp16 = const()[name = tensor("op_417_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_29_cast = add(x = mul_14_cast, y = var_417_to_fp16); tensor stem_sep_module_6_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_6_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1543872)))]; tensor var_420_cast = mul(x = stem_sep_module_6_tcn_6_norm_gamma_to_fp16, y = sub_14_cast); tensor var_421_cast = real_div(x = var_420_cast, y = std_y_29_cast); tensor stem_sep_module_6_tcn_6_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_6_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1544448)))]; tensor y_14_cast = add(x = var_421_cast, y = stem_sep_module_6_tcn_6_norm_beta_to_fp16); tensor input_3_cast = add(x = input_63_cast, y = y_14_cast); tensor var_432 = const()[name = tensor("op_432"), val = tensor([1])]; tensor var_434 = const()[name = tensor("op_434"), val = tensor([1])]; tensor input_2_pad_type_0 = const()[name = tensor("input_2_pad_type_0"), val = tensor("custom")]; tensor input_2_pad_0 = const()[name = tensor("input_2_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_7_tcn_0_weight_to_fp16 = const()[name = tensor("stem_sep_module_7_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1545024)))]; tensor input_2_cast = conv(dilations = var_434, groups = var_16, pad = input_2_pad_0, pad_type = input_2_pad_type_0, strides = var_432, weight = stem_sep_module_7_tcn_0_weight_to_fp16, x = input_3_cast); tensor var_438_alpha_0_to_fp16 = const()[name = tensor("op_438_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1676160)))]; tensor var_438_cast = leaky_relu(alpha = tensor(0x1p+0), x = input_2_cast); tensor var_442 = const()[name = tensor("op_442"), val = tensor([1])]; tensor mean_y_2_cast = reduce_mean(axes = var_442, keep_dims = var_12, x = var_438_cast); tensor sub_15_cast = sub(x = var_438_cast, y = mean_y_2_cast); tensor square_15_cast = square(x = sub_15_cast); tensor reduce_mean_31_axes_0 = const()[name = tensor("reduce_mean_31_axes_0"), val = tensor([1])]; tensor reduce_mean_31_keep_dims_0 = const()[name = tensor("reduce_mean_31_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_31_cast = reduce_mean(axes = reduce_mean_31_axes_0, keep_dims = reduce_mean_31_keep_dims_0, x = square_15_cast); tensor sqrt_15_cast = sqrt(x = reduce_mean_31_cast); tensor mul_15_y_0_to_fp16 = const()[name = tensor("mul_15_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_15_cast = mul(x = sqrt_15_cast, y = mul_15_y_0_to_fp16); tensor var_446_to_fp16 = const()[name = tensor("op_446_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_2_cast = add(x = mul_15_cast, y = var_446_to_fp16); tensor stem_sep_module_7_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_7_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1676736)))]; tensor var_449_cast = mul(x = stem_sep_module_7_tcn_2_norm_gamma_to_fp16, y = sub_15_cast); tensor var_450_cast = real_div(x = var_449_cast, y = std_y_2_cast); tensor stem_sep_module_7_tcn_2_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_7_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1677312)))]; tensor input_4_cast = add(x = var_450_cast, y = stem_sep_module_7_tcn_2_norm_beta_to_fp16); tensor input_6_pad_0 = const()[name = tensor("input_6_pad_0"), val = tensor([0, 0, 0, 0, 256, 0])]; tensor input_6_mode_0 = const()[name = tensor("input_6_mode_0"), val = tensor("constant")]; tensor input_6_constant_val_0_to_fp16 = const()[name = tensor("input_6_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_6_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_4_cast_in_state, input_4_cast)); tensor input_4_cast_out_state = slice_by_size(begin = tensor([0, 0, -256]), size = tensor([1, 256, 256]), x = input_6_cast); tensor var_455 = const()[name = tensor("op_455"), val = tensor([1])]; tensor var_457 = const()[name = tensor("op_457"), val = tensor([128])]; tensor input_1_pad_type_0 = const()[name = tensor("input_1_pad_type_0"), val = tensor("custom")]; tensor input_1_pad_0 = const()[name = tensor("input_1_pad_0"), val = tensor([0, 0])]; tensor stem_sep_module_7_tcn_4_weight_to_fp16 = const()[name = tensor("stem_sep_module_7_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1677888)))]; tensor input_1_cast = conv(dilations = var_457, groups = var_4, pad = input_1_pad_0, pad_type = input_1_pad_type_0, strides = var_455, weight = stem_sep_module_7_tcn_4_weight_to_fp16, x = input_6_cast); tensor var_461_alpha_0_to_fp16 = const()[name = tensor("op_461_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1679488)))]; tensor var_461_cast = leaky_relu(alpha = tensor(0x1p+0), x = input_1_cast); tensor var_465 = const()[name = tensor("op_465"), val = tensor([1])]; tensor mean_y_1_cast = reduce_mean(axes = var_465, keep_dims = var_12, x = var_461_cast); tensor sub_16_cast = sub(x = var_461_cast, y = mean_y_1_cast); tensor square_16_cast = square(x = sub_16_cast); tensor reduce_mean_33_axes_0 = const()[name = tensor("reduce_mean_33_axes_0"), val = tensor([1])]; tensor reduce_mean_33_keep_dims_0 = const()[name = tensor("reduce_mean_33_keep_dims_0"), val = tensor(true)]; tensor reduce_mean_33_cast = reduce_mean(axes = reduce_mean_33_axes_0, keep_dims = reduce_mean_33_keep_dims_0, x = square_16_cast); tensor sqrt_16_cast = sqrt(x = reduce_mean_33_cast); tensor mul_16_y_0_to_fp16 = const()[name = tensor("mul_16_y_0_to_fp16"), val = tensor(0x1.008p+0)]; tensor mul_16_cast = mul(x = sqrt_16_cast, y = mul_16_y_0_to_fp16); tensor var_469_to_fp16 = const()[name = tensor("op_469_to_fp16"), val = tensor(0x1p-24)]; tensor std_y_1_cast = add(x = mul_16_cast, y = var_469_to_fp16); tensor stem_sep_module_7_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("stem_sep_module_7_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1680064)))]; tensor var_472_cast = mul(x = stem_sep_module_7_tcn_6_norm_gamma_to_fp16, y = sub_16_cast); tensor var_473_cast = real_div(x = var_472_cast, y = std_y_1_cast); tensor stem_sep_module_7_tcn_6_norm_beta_to_fp16 = const()[name = tensor("stem_sep_module_7_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1680640)))]; tensor y_1_cast = add(x = var_473_cast, y = stem_sep_module_7_tcn_6_norm_beta_to_fp16); tensor x_1_cast = add(x = input_3_cast, y = y_1_cast); tensor input0_2_axes_0 = const()[name = tensor("input0_2_axes_0"), val = tensor([1])]; tensor input0_2_cast = expand_dims(axes = input0_2_axes_0, x = x_1_cast); tensor var_478 = const()[name = tensor("op_478"), val = tensor([1, 1])]; tensor var_480 = const()[name = tensor("op_480"), val = tensor([1, 1])]; tensor input1_1_pad_type_0 = const()[name = tensor("input1_1_pad_type_0"), val = tensor("custom")]; tensor input1_1_pad_0 = const()[name = tensor("input1_1_pad_0"), val = tensor([256, 256, 0, 0])]; tensor stem_mask_layer_weight_to_fp16 = const()[name = tensor("stem_mask_layer_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1681216)))]; tensor input1_1_cast = conv(dilations = var_480, groups = var_16, pad = input1_1_pad_0, pad_type = input1_1_pad_type_0, strides = var_478, weight = stem_mask_layer_weight_to_fp16, x = input0_2_cast); tensor var_483_cast = tanh(x = input1_1_cast); tensor var_484_axes_0 = const()[name = tensor("op_484_axes_0"), val = tensor([1])]; tensor var_484_cast = expand_dims(axes = var_484_axes_0, x = var_31_cast); tensor var_484_cast_elementwise_expanded = concat(axis = tensor(-1), interleave = tensor(false), values = (var_484_cast_elementwise_in_state, var_484_cast)); tensor var_484_cast_elementwise_delayed = slice_by_size(begin = tensor([0, 0, 0, 0]), size = tensor([1, 1, 384, 30]), x = var_484_cast_elementwise_expanded); tensor var_484_cast_elementwise_out_state = slice_by_size(begin = tensor([0, 0, 0, -15]), size = tensor([1, 1, 384, 15]), x = var_484_cast_elementwise_expanded); tensor x_2_cast = mul(x = var_483_cast, y = var_484_cast_elementwise_delayed); tensor concat_0x = const()[name = tensor("concat_0x"), val = tensor([1, 4608, -1])]; tensor input1_2_cast = reshape(shape = concat_0x, x = x_2_cast); tensor var_497 = const()[name = tensor("op_497"), val = tensor([64])]; tensor var_499 = const()[name = tensor("op_499"), val = tensor([1])]; tensor target_1_pad_type_0 = const()[name = tensor("target_1_pad_type_0"), val = tensor("custom")]; tensor target_1_pad_0 = const()[name = tensor("target_1_pad_0"), val = tensor([64, 64])]; tensor stem_resynthesizer_weight_to_fp16 = const()[name = tensor("stem_resynthesizer_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1690560)))]; tensor input1_2_cast_padded = concat(axis = tensor(-1), interleave = tensor(false), values = (input1_2_cast_in_state, input1_2_cast)); tensor input1_2_cast_out_state = slice_by_size(begin = tensor([0, 0, -1]), size = tensor([1, 4608, 1]), x = input1_2_cast_padded); tensor target_1_cast = conv_transpose(dilations = var_499, groups = var_3, pad = target_1_pad_0, pad_type = target_1_pad_type_0, strides = var_497, weight = stem_resynthesizer_weight_to_fp16, x = input1_2_cast_padded); tensor target_1_cast_to_fp32_dtype_0 = const()[name = tensor("target_1_cast_to_fp32_dtype_0"), val = tensor("fp32")]; tensor target_1 = cast(dtype = target_1_cast_to_fp32_dtype_0, x = target_1_cast); } -> (target_1, input1_2_cast_out_state, var_484_cast_elementwise_out_state, input_4_cast_out_state, input_67_cast_out_state, input_57_cast_out_state, input_47_cast_out_state, input_33_cast_elementwise_out_state, input_37_cast_out_state, input_23_cast_elementwise_out_state, input_27_cast_out_state, input_13_cast_elementwise_out_state, input_17_cast_out_state, input_12_cast_elementwise_out_state, input_7_cast_out_state, cast_229_out_state); }