program(1.2) [buildInfo = dict, tensor>({{"coremlc-component-MIL", "3400.8.1"}, {"coremlc-version", "3400.7.1"}}), mldb_token = string("mldb-7nwypnpa9o")] { func main(tensor audio, tensor cast_1_in_state, tensor input1_3_cast_in_state, tensor input_107_cast_in_state, tensor input_117_cast_in_state, tensor input_127_cast_in_state, tensor input_137_cast_in_state, tensor input_13_cast_concat_in_state, tensor input_147_cast_in_state, tensor input_157_cast_in_state, tensor input_167_cast_in_state, tensor input_177_cast_in_state, tensor input_17_cast_in_state, tensor input_187_cast_in_state, tensor input_197_cast_in_state, tensor input_207_cast_in_state, tensor input_217_cast_in_state, tensor input_227_cast_in_state, tensor input_237_cast_in_state, tensor input_23_cast_concat_in_state, tensor input_247_cast_in_state, tensor input_257_cast_in_state, tensor input_267_cast_concat_in_state, tensor input_27_cast_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_77_cast_in_state, tensor input_7_cast_in_state, tensor input_87_cast_in_state, tensor input_97_cast_in_state, tensor var_1682_cast_concat_in_state) [FlexibleShapeInformation = tuple, dict, tensor>>, tuple, dict, list, ?>>>>((("DefaultShapes", {{"audio", [1, 1, 1280]}}), ("RangeDims", {{"audio", [[1, 1], [1, 1], [1280, 1280]]}}))), UserMetadata = dict, tensor>({{"iteration", "829205"}, {"taskid", "g4niigfuc4"}})] { tensor var_17 = const()[name = tensor("op_17"), val = tensor(1)]; tensor var_21 = const()[name = tensor("op_21"), val = tensor([40])]; tensor var_23 = const()[name = tensor("op_23"), 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([40, 40])]; tensor audio_to_fp16_dtype_0 = const()[name = tensor("audio_to_fp16_dtype_0"), val = tensor("fp16")]; tensor front_end_0_weight_to_fp16 = const()[name = tensor("front_end_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(64)))]; tensor cast_1 = cast(dtype = audio_to_fp16_dtype_0, x = audio)[name = tensor("cast_1")]; tensor cast_1_expanded = concat(axis = tensor(-1), interleave = tensor(false), values = (cast_1_in_state, cast_1)); tensor cast_1_out_state = slice_by_size(begin = tensor([0, 0, -40]), size = tensor([-1, 1, 40]), x = cast_1_expanded); tensor input0_1_cast = conv(dilations = var_23, groups = var_17, pad = tensor([0, 0]), pad_type = input0_1_pad_type_0, strides = var_21, weight = front_end_0_weight_to_fp16, x = cast_1_expanded); tensor var_26_cast = relu(x = input0_1_cast)[name = tensor("op_26_cast")]; tensor var_29 = const()[name = tensor("op_29"), val = tensor(true)]; tensor var_34 = const()[name = tensor("op_34"), val = tensor([1])]; tensor mean_y_4_cast = reduce_mean(axes = var_34, keep_dims = var_29, x = var_26_cast)[name = tensor("mean_y_4_cast")]; tensor var_36_cast = sub(x = var_26_cast, y = mean_y_4_cast)[name = tensor("op_36_cast")]; tensor var_37_cast = square(x = var_36_cast); tensor var_38 = const()[name = tensor("op_38"), val = tensor([1])]; tensor var_39_cast = reduce_mean(axes = var_38, keep_dims = var_29, x = var_37_cast)[name = tensor("op_39_cast")]; tensor var_40_to_fp16 = const()[name = tensor("op_40_to_fp16"), val = tensor(0x1p-14)]; tensor var_41_cast = add(x = var_39_cast, y = var_40_to_fp16)[name = tensor("op_41_cast")]; tensor std_y_4_cast = sqrt(x = var_41_cast)[name = tensor("std_y_4_cast")]; tensor front_norm_norm_gamma_to_fp16 = const()[name = tensor("front_norm_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(61568)))]; tensor var_44_cast = mul(x = front_norm_norm_gamma_to_fp16, y = var_36_cast)[name = tensor("op_44_cast")]; tensor var_45_cast = real_div(x = var_44_cast, y = std_y_4_cast)[name = tensor("op_45_cast")]; tensor front_norm_norm_beta_to_fp16 = const()[name = tensor("front_norm_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(62400)))]; tensor input_263_cast = add(x = var_45_cast, y = front_norm_norm_beta_to_fp16)[name = tensor("input_263_cast")]; tensor var_48 = const()[name = tensor("op_48"), val = tensor(1)]; tensor var_53 = const()[name = tensor("op_53"), val = tensor([1])]; tensor var_55 = const()[name = tensor("op_55"), val = tensor([1])]; tensor input_267_pad_type_0 = const()[name = tensor("input_267_pad_type_0"), val = tensor("custom")]; tensor input_267_pad_0 = const()[name = tensor("input_267_pad_0"), val = tensor([0, 0])]; tensor to_latent_weight_to_fp16 = const()[name = tensor("to_latent_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(63232)))]; tensor input_267_cast = conv(dilations = var_55, groups = var_48, pad = input_267_pad_0, pad_type = input_267_pad_type_0, strides = var_53, weight = to_latent_weight_to_fp16, x = input_263_cast)[name = tensor("input_267_cast")]; tensor var_67 = const()[name = tensor("op_67"), val = tensor(1)]; tensor var_68 = const()[name = tensor("op_68"), val = tensor(384)]; tensor var_71 = const()[name = tensor("op_71"), val = tensor(true)]; tensor var_110 = const()[name = tensor("op_110"), val = tensor([1])]; tensor var_112 = const()[name = tensor("op_112"), 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 sep_module_0_tcn_0_weight_to_fp16 = const()[name = tensor("sep_module_0_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(358208)))]; tensor input_5_cast = conv(dilations = var_112, groups = var_67, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = var_110, weight = sep_module_0_tcn_0_weight_to_fp16, x = input_267_cast)[name = tensor("input_5_cast")]; tensor var_116_alpha_1_to_fp16 = const()[name = tensor("op_116_alpha_1_to_fp16"), val = tensor(0x1.59cp-2)]; tensor var_116_cast = leaky_relu(alpha = var_116_alpha_1_to_fp16, x = input_5_cast)[name = tensor("op_116_cast")]; tensor var_120 = const()[name = tensor("op_120"), val = tensor([1])]; tensor mean_y_3_cast = reduce_mean(axes = var_120, keep_dims = var_71, x = var_116_cast)[name = tensor("mean_y_3_cast")]; tensor var_122_cast = sub(x = var_116_cast, y = mean_y_3_cast)[name = tensor("op_122_cast")]; tensor var_123_cast = square(x = var_122_cast); tensor var_124 = const()[name = tensor("op_124"), val = tensor([1])]; tensor var_125_cast = reduce_mean(axes = var_124, keep_dims = var_71, x = var_123_cast)[name = tensor("op_125_cast")]; tensor var_126_to_fp16 = const()[name = tensor("op_126_to_fp16"), val = tensor(0x1p-14)]; tensor var_127_cast = add(x = var_125_cast, y = var_126_to_fp16)[name = tensor("op_127_cast")]; tensor std_y_3_cast = sqrt(x = var_127_cast)[name = tensor("std_y_3_cast")]; tensor sep_module_0_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_0_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(653184)))]; tensor var_130_cast = mul(x = sep_module_0_tcn_2_norm_gamma_to_fp16, y = var_122_cast)[name = tensor("op_130_cast")]; tensor var_131_cast = real_div(x = var_130_cast, y = std_y_3_cast)[name = tensor("op_131_cast")]; tensor sep_module_0_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_0_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(654016)))]; tensor input_7_cast = add(x = var_131_cast, y = sep_module_0_tcn_2_norm_beta_to_fp16)[name = tensor("input_7_cast")]; 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, 384, 2]), x = input_9_cast); tensor var_136 = const()[name = tensor("op_136"), val = tensor([1])]; tensor var_138 = const()[name = tensor("op_138"), 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 sep_module_0_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_0_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(654848)))]; tensor input_11_cast = conv(dilations = var_138, groups = var_68, pad = input_11_pad_0, pad_type = input_11_pad_type_0, strides = var_136, weight = sep_module_0_tcn_4_weight_to_fp16, x = input_9_cast)[name = tensor("input_11_cast")]; tensor var_142_alpha_1_to_fp16 = const()[name = tensor("op_142_alpha_1_to_fp16"), val = tensor(0x1.6f4p-7)]; tensor var_142_cast = leaky_relu(alpha = var_142_alpha_1_to_fp16, x = input_11_cast)[name = tensor("op_142_cast")]; tensor var_146 = const()[name = tensor("op_146"), val = tensor([1])]; tensor mean_y_5_cast = reduce_mean(axes = var_146, keep_dims = var_71, x = var_142_cast)[name = tensor("mean_y_5_cast")]; tensor var_148_cast = sub(x = var_142_cast, y = mean_y_5_cast)[name = tensor("op_148_cast")]; tensor var_149_cast = square(x = var_148_cast); tensor var_150 = const()[name = tensor("op_150"), val = tensor([1])]; tensor var_151_cast = reduce_mean(axes = var_150, keep_dims = var_71, x = var_149_cast)[name = tensor("op_151_cast")]; tensor var_152_to_fp16 = const()[name = tensor("op_152_to_fp16"), val = tensor(0x1p-14)]; tensor var_153_cast = add(x = var_151_cast, y = var_152_to_fp16)[name = tensor("op_153_cast")]; tensor std_y_5_cast = sqrt(x = var_153_cast)[name = tensor("std_y_5_cast")]; tensor sep_module_0_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_0_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(657216)))]; tensor var_156_cast = mul(x = sep_module_0_tcn_6_norm_gamma_to_fp16, y = var_148_cast)[name = tensor("op_156_cast")]; tensor var_157_cast = real_div(x = var_156_cast, y = std_y_5_cast)[name = tensor("op_157_cast")]; tensor sep_module_0_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_0_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(658048)))]; tensor y_2_cast = add(x = var_157_cast, y = sep_module_0_tcn_6_norm_beta_to_fp16)[name = tensor("y_2_cast")]; tensor input_267_cast_concat_expanded = concat(axis = tensor(-1), interleave = tensor(false), values = (input_267_cast_concat_in_state, input_267_cast)); tensor input_267_cast_delayed = slice_by_size(begin = tensor([0, 0, 0]), size = tensor([-1, 384, 32]), x = input_267_cast_concat_expanded); tensor input_267_cast_concat_out_state = slice_by_size(begin = tensor([0, 0, -1]), size = tensor([-1, 384, 1]), x = input_267_cast_concat_expanded); tensor input_13_cast = add(x = input_267_cast_delayed, y = y_2_cast)[name = tensor("input_13_cast")]; tensor var_168 = const()[name = tensor("op_168"), val = tensor([1])]; tensor var_170 = const()[name = tensor("op_170"), 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 sep_module_1_tcn_0_weight_to_fp16 = const()[name = tensor("sep_module_1_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(658880)))]; tensor input_15_cast = conv(dilations = var_170, groups = var_67, pad = input_15_pad_0, pad_type = input_15_pad_type_0, strides = var_168, weight = sep_module_1_tcn_0_weight_to_fp16, x = input_13_cast)[name = tensor("input_15_cast")]; tensor var_174_alpha_1_to_fp16 = const()[name = tensor("op_174_alpha_1_to_fp16"), val = tensor(0x1.0f4p-1)]; tensor var_174_cast = leaky_relu(alpha = var_174_alpha_1_to_fp16, x = input_15_cast)[name = tensor("op_174_cast")]; tensor var_178 = const()[name = tensor("op_178"), val = tensor([1])]; tensor mean_y_7_cast = reduce_mean(axes = var_178, keep_dims = var_71, x = var_174_cast)[name = tensor("mean_y_7_cast")]; tensor var_180_cast = sub(x = var_174_cast, y = mean_y_7_cast)[name = tensor("op_180_cast")]; tensor var_181_cast = square(x = var_180_cast); tensor var_182 = const()[name = tensor("op_182"), val = tensor([1])]; tensor var_183_cast = reduce_mean(axes = var_182, keep_dims = var_71, x = var_181_cast)[name = tensor("op_183_cast")]; tensor var_184_to_fp16 = const()[name = tensor("op_184_to_fp16"), val = tensor(0x1p-14)]; tensor var_185_cast = add(x = var_183_cast, y = var_184_to_fp16)[name = tensor("op_185_cast")]; tensor std_y_7_cast = sqrt(x = var_185_cast)[name = tensor("std_y_7_cast")]; tensor sep_module_1_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_1_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(953856)))]; tensor var_188_cast = mul(x = sep_module_1_tcn_2_norm_gamma_to_fp16, y = var_180_cast)[name = tensor("op_188_cast")]; tensor var_189_cast = real_div(x = var_188_cast, y = std_y_7_cast)[name = tensor("op_189_cast")]; tensor sep_module_1_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_1_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(954688)))]; tensor input_17_cast = add(x = var_189_cast, y = sep_module_1_tcn_2_norm_beta_to_fp16)[name = tensor("input_17_cast")]; 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, 384, 4]), x = input_19_cast); tensor var_194 = const()[name = tensor("op_194"), val = tensor([1])]; tensor var_196 = const()[name = tensor("op_196"), 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 sep_module_1_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_1_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(955520)))]; tensor input_21_cast = conv(dilations = var_196, groups = var_68, pad = input_21_pad_0, pad_type = input_21_pad_type_0, strides = var_194, weight = sep_module_1_tcn_4_weight_to_fp16, x = input_19_cast)[name = tensor("input_21_cast")]; tensor var_200_alpha_1_to_fp16 = const()[name = tensor("op_200_alpha_1_to_fp16"), val = tensor(-0x1.5f8p-3)]; tensor var_200_cast = leaky_relu(alpha = var_200_alpha_1_to_fp16, x = input_21_cast)[name = tensor("op_200_cast")]; tensor var_204 = const()[name = tensor("op_204"), val = tensor([1])]; tensor mean_y_9_cast = reduce_mean(axes = var_204, keep_dims = var_71, x = var_200_cast)[name = tensor("mean_y_9_cast")]; tensor var_206_cast = sub(x = var_200_cast, y = mean_y_9_cast)[name = tensor("op_206_cast")]; tensor var_207_cast = square(x = var_206_cast); tensor var_208 = const()[name = tensor("op_208"), val = tensor([1])]; tensor var_209_cast = reduce_mean(axes = var_208, keep_dims = var_71, x = var_207_cast)[name = tensor("op_209_cast")]; tensor var_210_to_fp16 = const()[name = tensor("op_210_to_fp16"), val = tensor(0x1p-14)]; tensor var_211_cast = add(x = var_209_cast, y = var_210_to_fp16)[name = tensor("op_211_cast")]; tensor std_y_9_cast = sqrt(x = var_211_cast)[name = tensor("std_y_9_cast")]; tensor sep_module_1_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_1_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(957888)))]; tensor var_214_cast = mul(x = sep_module_1_tcn_6_norm_gamma_to_fp16, y = var_206_cast)[name = tensor("op_214_cast")]; tensor var_215_cast = real_div(x = var_214_cast, y = std_y_9_cast)[name = tensor("op_215_cast")]; tensor sep_module_1_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_1_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(958720)))]; tensor y_4_cast = add(x = var_215_cast, y = sep_module_1_tcn_6_norm_beta_to_fp16)[name = tensor("y_4_cast")]; tensor input_13_cast_concat_expanded = concat(axis = tensor(-1), interleave = tensor(false), values = (input_13_cast_concat_in_state, input_13_cast)); tensor input_13_cast_delayed = slice_by_size(begin = tensor([0, 0, 0]), size = tensor([-1, 384, 32]), x = input_13_cast_concat_expanded); tensor input_13_cast_concat_out_state = slice_by_size(begin = tensor([0, 0, -2]), size = tensor([-1, 384, 2]), x = input_13_cast_concat_expanded); tensor input_23_cast = add(x = input_13_cast_delayed, y = y_4_cast)[name = tensor("input_23_cast")]; tensor var_226 = const()[name = tensor("op_226"), val = tensor([1])]; tensor var_228 = const()[name = tensor("op_228"), 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 sep_module_2_tcn_0_weight_to_fp16 = const()[name = tensor("sep_module_2_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(959552)))]; tensor input_25_cast = conv(dilations = var_228, groups = var_67, pad = input_25_pad_0, pad_type = input_25_pad_type_0, strides = var_226, weight = sep_module_2_tcn_0_weight_to_fp16, x = input_23_cast)[name = tensor("input_25_cast")]; tensor var_232_alpha_1_to_fp16 = const()[name = tensor("op_232_alpha_1_to_fp16"), val = tensor(0x1.d04p-1)]; tensor var_232_cast = leaky_relu(alpha = var_232_alpha_1_to_fp16, x = input_25_cast)[name = tensor("op_232_cast")]; tensor var_236 = const()[name = tensor("op_236"), val = tensor([1])]; tensor mean_y_11_cast = reduce_mean(axes = var_236, keep_dims = var_71, x = var_232_cast)[name = tensor("mean_y_11_cast")]; tensor var_238_cast = sub(x = var_232_cast, y = mean_y_11_cast)[name = tensor("op_238_cast")]; tensor var_239_cast = square(x = var_238_cast); tensor var_240 = const()[name = tensor("op_240"), val = tensor([1])]; tensor var_241_cast = reduce_mean(axes = var_240, keep_dims = var_71, x = var_239_cast)[name = tensor("op_241_cast")]; tensor var_242_to_fp16 = const()[name = tensor("op_242_to_fp16"), val = tensor(0x1p-14)]; tensor var_243_cast = add(x = var_241_cast, y = var_242_to_fp16)[name = tensor("op_243_cast")]; tensor std_y_11_cast = sqrt(x = var_243_cast)[name = tensor("std_y_11_cast")]; tensor sep_module_2_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_2_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1254528)))]; tensor var_246_cast = mul(x = sep_module_2_tcn_2_norm_gamma_to_fp16, y = var_238_cast)[name = tensor("op_246_cast")]; tensor var_247_cast = real_div(x = var_246_cast, y = std_y_11_cast)[name = tensor("op_247_cast")]; tensor sep_module_2_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_2_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1255360)))]; tensor input_27_cast = add(x = var_247_cast, y = sep_module_2_tcn_2_norm_beta_to_fp16)[name = tensor("input_27_cast")]; 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, 384, 8]), x = input_29_cast); tensor var_252 = const()[name = tensor("op_252"), val = tensor([1])]; tensor var_254 = const()[name = tensor("op_254"), 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 sep_module_2_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_2_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1256192)))]; tensor input_31_cast = conv(dilations = var_254, groups = var_68, pad = input_31_pad_0, pad_type = input_31_pad_type_0, strides = var_252, weight = sep_module_2_tcn_4_weight_to_fp16, x = input_29_cast)[name = tensor("input_31_cast")]; tensor var_258_alpha_1_to_fp16 = const()[name = tensor("op_258_alpha_1_to_fp16"), val = tensor(0x1.dbcp-4)]; tensor var_258_cast = leaky_relu(alpha = var_258_alpha_1_to_fp16, x = input_31_cast)[name = tensor("op_258_cast")]; tensor var_262 = const()[name = tensor("op_262"), val = tensor([1])]; tensor mean_y_13_cast = reduce_mean(axes = var_262, keep_dims = var_71, x = var_258_cast)[name = tensor("mean_y_13_cast")]; tensor var_264_cast = sub(x = var_258_cast, y = mean_y_13_cast)[name = tensor("op_264_cast")]; tensor var_265_cast = square(x = var_264_cast); tensor var_266 = const()[name = tensor("op_266"), val = tensor([1])]; tensor var_267_cast = reduce_mean(axes = var_266, keep_dims = var_71, x = var_265_cast)[name = tensor("op_267_cast")]; tensor var_268_to_fp16 = const()[name = tensor("op_268_to_fp16"), val = tensor(0x1p-14)]; tensor var_269_cast = add(x = var_267_cast, y = var_268_to_fp16)[name = tensor("op_269_cast")]; tensor std_y_13_cast = sqrt(x = var_269_cast)[name = tensor("std_y_13_cast")]; tensor sep_module_2_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_2_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1258560)))]; tensor var_272_cast = mul(x = sep_module_2_tcn_6_norm_gamma_to_fp16, y = var_264_cast)[name = tensor("op_272_cast")]; tensor var_273_cast = real_div(x = var_272_cast, y = std_y_13_cast)[name = tensor("op_273_cast")]; tensor sep_module_2_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_2_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1259392)))]; tensor y_6_cast = add(x = var_273_cast, y = sep_module_2_tcn_6_norm_beta_to_fp16)[name = tensor("y_6_cast")]; tensor input_23_cast_concat_expanded = concat(axis = tensor(-1), interleave = tensor(false), values = (input_23_cast_concat_in_state, input_23_cast)); tensor input_23_cast_delayed = slice_by_size(begin = tensor([0, 0, 0]), size = tensor([-1, 384, 32]), x = input_23_cast_concat_expanded); tensor input_23_cast_concat_out_state = slice_by_size(begin = tensor([0, 0, -4]), size = tensor([-1, 384, 4]), x = input_23_cast_concat_expanded); tensor input_33_cast = add(x = input_23_cast_delayed, y = y_6_cast)[name = tensor("input_33_cast")]; tensor var_284 = const()[name = tensor("op_284"), val = tensor([1])]; tensor var_286 = const()[name = tensor("op_286"), 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 sep_module_3_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1260224))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1334016))), name = tensor("sep_module_3_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_35_cast = conv(dilations = var_286, groups = var_67, pad = input_35_pad_0, pad_type = input_35_pad_type_0, strides = var_284, weight = sep_module_3_tcn_0_weight_to_fp16_palettized, x = input_33_cast)[name = tensor("input_35_cast")]; tensor var_290_alpha_1_to_fp16 = const()[name = tensor("op_290_alpha_1_to_fp16"), val = tensor(0x1.2c4p-1)]; tensor var_290_cast = leaky_relu(alpha = var_290_alpha_1_to_fp16, x = input_35_cast)[name = tensor("op_290_cast")]; tensor var_294 = const()[name = tensor("op_294"), val = tensor([1])]; tensor mean_y_15_cast = reduce_mean(axes = var_294, keep_dims = var_71, x = var_290_cast)[name = tensor("mean_y_15_cast")]; tensor var_296_cast = sub(x = var_290_cast, y = mean_y_15_cast)[name = tensor("op_296_cast")]; tensor var_297_cast = square(x = var_296_cast); tensor var_298 = const()[name = tensor("op_298"), val = tensor([1])]; tensor var_299_cast = reduce_mean(axes = var_298, keep_dims = var_71, x = var_297_cast)[name = tensor("op_299_cast")]; tensor var_300_to_fp16 = const()[name = tensor("op_300_to_fp16"), val = tensor(0x1p-14)]; tensor var_301_cast = add(x = var_299_cast, y = var_300_to_fp16)[name = tensor("op_301_cast")]; tensor std_y_15_cast = sqrt(x = var_301_cast)[name = tensor("std_y_15_cast")]; tensor sep_module_3_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_3_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1334144)))]; tensor var_304_cast = mul(x = sep_module_3_tcn_2_norm_gamma_to_fp16, y = var_296_cast)[name = tensor("op_304_cast")]; tensor var_305_cast = real_div(x = var_304_cast, y = std_y_15_cast)[name = tensor("op_305_cast")]; tensor sep_module_3_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_3_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1334976)))]; tensor input_37_cast = add(x = var_305_cast, y = sep_module_3_tcn_2_norm_beta_to_fp16)[name = tensor("input_37_cast")]; tensor input_39_pad_0 = const()[name = tensor("input_39_pad_0"), val = tensor([0, 0, 0, 0, 16, 0])]; 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, 384, 16]), x = input_39_cast); tensor var_310 = const()[name = tensor("op_310"), val = tensor([1])]; tensor var_312 = const()[name = tensor("op_312"), 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 sep_module_3_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_3_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1335808)))]; tensor input_41_cast = conv(dilations = var_312, groups = var_68, pad = input_41_pad_0, pad_type = input_41_pad_type_0, strides = var_310, weight = sep_module_3_tcn_4_weight_to_fp16, x = input_39_cast)[name = tensor("input_41_cast")]; tensor var_316_alpha_1_to_fp16 = const()[name = tensor("op_316_alpha_1_to_fp16"), val = tensor(-0x1.968p-2)]; tensor var_316_cast = leaky_relu(alpha = var_316_alpha_1_to_fp16, x = input_41_cast)[name = tensor("op_316_cast")]; tensor var_320 = const()[name = tensor("op_320"), val = tensor([1])]; tensor mean_y_17_cast = reduce_mean(axes = var_320, keep_dims = var_71, x = var_316_cast)[name = tensor("mean_y_17_cast")]; tensor var_322_cast = sub(x = var_316_cast, y = mean_y_17_cast)[name = tensor("op_322_cast")]; tensor var_323_cast = square(x = var_322_cast); tensor var_324 = const()[name = tensor("op_324"), val = tensor([1])]; tensor var_325_cast = reduce_mean(axes = var_324, keep_dims = var_71, x = var_323_cast)[name = tensor("op_325_cast")]; tensor var_326_to_fp16 = const()[name = tensor("op_326_to_fp16"), val = tensor(0x1p-14)]; tensor var_327_cast = add(x = var_325_cast, y = var_326_to_fp16)[name = tensor("op_327_cast")]; tensor std_y_17_cast = sqrt(x = var_327_cast)[name = tensor("std_y_17_cast")]; tensor sep_module_3_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_3_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1338176)))]; tensor var_330_cast = mul(x = sep_module_3_tcn_6_norm_gamma_to_fp16, y = var_322_cast)[name = tensor("op_330_cast")]; tensor var_331_cast = real_div(x = var_330_cast, y = std_y_17_cast)[name = tensor("op_331_cast")]; tensor sep_module_3_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_3_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1339008)))]; tensor y_8_cast = add(x = var_331_cast, y = sep_module_3_tcn_6_norm_beta_to_fp16)[name = tensor("y_8_cast")]; tensor input_43_cast = add(x = input_33_cast, y = y_8_cast)[name = tensor("input_43_cast")]; tensor var_342 = const()[name = tensor("op_342"), val = tensor([1])]; tensor var_344 = const()[name = tensor("op_344"), 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 sep_module_4_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1339840))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1413632))), name = tensor("sep_module_4_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_45_cast = conv(dilations = var_344, groups = var_67, pad = input_45_pad_0, pad_type = input_45_pad_type_0, strides = var_342, weight = sep_module_4_tcn_0_weight_to_fp16_palettized, x = input_43_cast)[name = tensor("input_45_cast")]; tensor var_348_alpha_1_to_fp16 = const()[name = tensor("op_348_alpha_1_to_fp16"), val = tensor(0x1.e68p-1)]; tensor var_348_cast = leaky_relu(alpha = var_348_alpha_1_to_fp16, x = input_45_cast)[name = tensor("op_348_cast")]; tensor var_352 = const()[name = tensor("op_352"), val = tensor([1])]; tensor mean_y_19_cast = reduce_mean(axes = var_352, keep_dims = var_71, x = var_348_cast)[name = tensor("mean_y_19_cast")]; tensor var_354_cast = sub(x = var_348_cast, y = mean_y_19_cast)[name = tensor("op_354_cast")]; tensor var_355_cast = square(x = var_354_cast); tensor var_356 = const()[name = tensor("op_356"), val = tensor([1])]; tensor var_357_cast = reduce_mean(axes = var_356, keep_dims = var_71, x = var_355_cast)[name = tensor("op_357_cast")]; tensor var_358_to_fp16 = const()[name = tensor("op_358_to_fp16"), val = tensor(0x1p-14)]; tensor var_359_cast = add(x = var_357_cast, y = var_358_to_fp16)[name = tensor("op_359_cast")]; tensor std_y_19_cast = sqrt(x = var_359_cast)[name = tensor("std_y_19_cast")]; tensor sep_module_4_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_4_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1413760)))]; tensor var_362_cast = mul(x = sep_module_4_tcn_2_norm_gamma_to_fp16, y = var_354_cast)[name = tensor("op_362_cast")]; tensor var_363_cast = real_div(x = var_362_cast, y = std_y_19_cast)[name = tensor("op_363_cast")]; tensor sep_module_4_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_4_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1414592)))]; tensor input_47_cast = add(x = var_363_cast, y = sep_module_4_tcn_2_norm_beta_to_fp16)[name = tensor("input_47_cast")]; 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, 384, 32]), x = input_49_cast); tensor var_368 = const()[name = tensor("op_368"), val = tensor([1])]; tensor var_370 = const()[name = tensor("op_370"), 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 sep_module_4_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_4_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1415424)))]; tensor input_51_cast = conv(dilations = var_370, groups = var_68, pad = input_51_pad_0, pad_type = input_51_pad_type_0, strides = var_368, weight = sep_module_4_tcn_4_weight_to_fp16, x = input_49_cast)[name = tensor("input_51_cast")]; tensor var_374_alpha_1_to_fp16 = const()[name = tensor("op_374_alpha_1_to_fp16"), val = tensor(-0x1.05p-5)]; tensor var_374_cast = leaky_relu(alpha = var_374_alpha_1_to_fp16, x = input_51_cast)[name = tensor("op_374_cast")]; tensor var_378 = const()[name = tensor("op_378"), val = tensor([1])]; tensor mean_y_21_cast = reduce_mean(axes = var_378, keep_dims = var_71, x = var_374_cast)[name = tensor("mean_y_21_cast")]; tensor var_380_cast = sub(x = var_374_cast, y = mean_y_21_cast)[name = tensor("op_380_cast")]; tensor var_381_cast = square(x = var_380_cast); tensor var_382 = const()[name = tensor("op_382"), val = tensor([1])]; tensor var_383_cast = reduce_mean(axes = var_382, keep_dims = var_71, x = var_381_cast)[name = tensor("op_383_cast")]; tensor var_384_to_fp16 = const()[name = tensor("op_384_to_fp16"), val = tensor(0x1p-14)]; tensor var_385_cast = add(x = var_383_cast, y = var_384_to_fp16)[name = tensor("op_385_cast")]; tensor std_y_21_cast = sqrt(x = var_385_cast)[name = tensor("std_y_21_cast")]; tensor sep_module_4_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_4_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1417792)))]; tensor var_388_cast = mul(x = sep_module_4_tcn_6_norm_gamma_to_fp16, y = var_380_cast)[name = tensor("op_388_cast")]; tensor var_389_cast = real_div(x = var_388_cast, y = std_y_21_cast)[name = tensor("op_389_cast")]; tensor sep_module_4_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_4_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1418624)))]; tensor y_10_cast = add(x = var_389_cast, y = sep_module_4_tcn_6_norm_beta_to_fp16)[name = tensor("y_10_cast")]; tensor input_53_cast = add(x = input_43_cast, y = y_10_cast)[name = tensor("input_53_cast")]; tensor var_400 = const()[name = tensor("op_400"), val = tensor([1])]; tensor var_402 = const()[name = tensor("op_402"), 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 sep_module_5_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1419456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1493248))), name = tensor("sep_module_5_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_55_cast = conv(dilations = var_402, groups = var_67, pad = input_55_pad_0, pad_type = input_55_pad_type_0, strides = var_400, weight = sep_module_5_tcn_0_weight_to_fp16_palettized, x = input_53_cast)[name = tensor("input_55_cast")]; tensor var_406_alpha_1_to_fp16 = const()[name = tensor("op_406_alpha_1_to_fp16"), val = tensor(0x1.55p-1)]; tensor var_406_cast = leaky_relu(alpha = var_406_alpha_1_to_fp16, x = input_55_cast)[name = tensor("op_406_cast")]; tensor var_410 = const()[name = tensor("op_410"), val = tensor([1])]; tensor mean_y_23_cast = reduce_mean(axes = var_410, keep_dims = var_71, x = var_406_cast)[name = tensor("mean_y_23_cast")]; tensor var_412_cast = sub(x = var_406_cast, y = mean_y_23_cast)[name = tensor("op_412_cast")]; tensor var_413_cast = square(x = var_412_cast); tensor var_414 = const()[name = tensor("op_414"), val = tensor([1])]; tensor var_415_cast = reduce_mean(axes = var_414, keep_dims = var_71, x = var_413_cast)[name = tensor("op_415_cast")]; tensor var_416_to_fp16 = const()[name = tensor("op_416_to_fp16"), val = tensor(0x1p-14)]; tensor var_417_cast = add(x = var_415_cast, y = var_416_to_fp16)[name = tensor("op_417_cast")]; tensor std_y_23_cast = sqrt(x = var_417_cast)[name = tensor("std_y_23_cast")]; tensor sep_module_5_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_5_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1493376)))]; tensor var_420_cast = mul(x = sep_module_5_tcn_2_norm_gamma_to_fp16, y = var_412_cast)[name = tensor("op_420_cast")]; tensor var_421_cast = real_div(x = var_420_cast, y = std_y_23_cast)[name = tensor("op_421_cast")]; tensor sep_module_5_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_5_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1494208)))]; tensor input_57_cast = add(x = var_421_cast, y = sep_module_5_tcn_2_norm_beta_to_fp16)[name = tensor("input_57_cast")]; 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, 384, 64]), x = input_59_cast); tensor var_426 = const()[name = tensor("op_426"), val = tensor([1])]; tensor var_428 = const()[name = tensor("op_428"), 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 sep_module_5_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_5_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1495040)))]; tensor input_61_cast = conv(dilations = var_428, groups = var_68, pad = input_61_pad_0, pad_type = input_61_pad_type_0, strides = var_426, weight = sep_module_5_tcn_4_weight_to_fp16, x = input_59_cast)[name = tensor("input_61_cast")]; tensor var_432_alpha_1_to_fp16 = const()[name = tensor("op_432_alpha_1_to_fp16"), val = tensor(-0x1.eacp-3)]; tensor var_432_cast = leaky_relu(alpha = var_432_alpha_1_to_fp16, x = input_61_cast)[name = tensor("op_432_cast")]; tensor var_436 = const()[name = tensor("op_436"), val = tensor([1])]; tensor mean_y_25_cast = reduce_mean(axes = var_436, keep_dims = var_71, x = var_432_cast)[name = tensor("mean_y_25_cast")]; tensor var_438_cast = sub(x = var_432_cast, y = mean_y_25_cast)[name = tensor("op_438_cast")]; tensor var_439_cast = square(x = var_438_cast); tensor var_440 = const()[name = tensor("op_440"), val = tensor([1])]; tensor var_441_cast = reduce_mean(axes = var_440, keep_dims = var_71, x = var_439_cast)[name = tensor("op_441_cast")]; tensor var_442_to_fp16 = const()[name = tensor("op_442_to_fp16"), val = tensor(0x1p-14)]; tensor var_443_cast = add(x = var_441_cast, y = var_442_to_fp16)[name = tensor("op_443_cast")]; tensor std_y_25_cast = sqrt(x = var_443_cast)[name = tensor("std_y_25_cast")]; tensor sep_module_5_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_5_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1497408)))]; tensor var_446_cast = mul(x = sep_module_5_tcn_6_norm_gamma_to_fp16, y = var_438_cast)[name = tensor("op_446_cast")]; tensor var_447_cast = real_div(x = var_446_cast, y = std_y_25_cast)[name = tensor("op_447_cast")]; tensor sep_module_5_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_5_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1498240)))]; tensor y_12_cast = add(x = var_447_cast, y = sep_module_5_tcn_6_norm_beta_to_fp16)[name = tensor("y_12_cast")]; tensor input_63_cast = add(x = input_53_cast, y = y_12_cast)[name = tensor("input_63_cast")]; tensor var_458 = const()[name = tensor("op_458"), val = tensor([1])]; tensor var_460 = const()[name = tensor("op_460"), 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 sep_module_6_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1499072))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1572864))), name = tensor("sep_module_6_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_65_cast = conv(dilations = var_460, groups = var_67, pad = input_65_pad_0, pad_type = input_65_pad_type_0, strides = var_458, weight = sep_module_6_tcn_0_weight_to_fp16_palettized, x = input_63_cast)[name = tensor("input_65_cast")]; tensor var_464_alpha_1_to_fp16 = const()[name = tensor("op_464_alpha_1_to_fp16"), val = tensor(0x1.98cp-1)]; tensor var_464_cast = leaky_relu(alpha = var_464_alpha_1_to_fp16, x = input_65_cast)[name = tensor("op_464_cast")]; tensor var_468 = const()[name = tensor("op_468"), val = tensor([1])]; tensor mean_y_27_cast = reduce_mean(axes = var_468, keep_dims = var_71, x = var_464_cast)[name = tensor("mean_y_27_cast")]; tensor var_470_cast = sub(x = var_464_cast, y = mean_y_27_cast)[name = tensor("op_470_cast")]; tensor var_471_cast = square(x = var_470_cast); tensor var_472 = const()[name = tensor("op_472"), val = tensor([1])]; tensor var_473_cast = reduce_mean(axes = var_472, keep_dims = var_71, x = var_471_cast)[name = tensor("op_473_cast")]; tensor var_474_to_fp16 = const()[name = tensor("op_474_to_fp16"), val = tensor(0x1p-14)]; tensor var_475_cast = add(x = var_473_cast, y = var_474_to_fp16)[name = tensor("op_475_cast")]; tensor std_y_27_cast = sqrt(x = var_475_cast)[name = tensor("std_y_27_cast")]; tensor sep_module_6_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_6_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1572992)))]; tensor var_478_cast = mul(x = sep_module_6_tcn_2_norm_gamma_to_fp16, y = var_470_cast)[name = tensor("op_478_cast")]; tensor var_479_cast = real_div(x = var_478_cast, y = std_y_27_cast)[name = tensor("op_479_cast")]; tensor sep_module_6_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_6_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1573824)))]; tensor input_67_cast = add(x = var_479_cast, y = sep_module_6_tcn_2_norm_beta_to_fp16)[name = tensor("input_67_cast")]; 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, 384, 128]), x = input_69_cast); tensor var_484 = const()[name = tensor("op_484"), val = tensor([1])]; tensor var_486 = const()[name = tensor("op_486"), 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 sep_module_6_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_6_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1574656)))]; tensor input_71_cast = conv(dilations = var_486, groups = var_68, pad = input_71_pad_0, pad_type = input_71_pad_type_0, strides = var_484, weight = sep_module_6_tcn_4_weight_to_fp16, x = input_69_cast)[name = tensor("input_71_cast")]; tensor var_490_alpha_1_to_fp16 = const()[name = tensor("op_490_alpha_1_to_fp16"), val = tensor(-0x1.4e4p-4)]; tensor var_490_cast = leaky_relu(alpha = var_490_alpha_1_to_fp16, x = input_71_cast)[name = tensor("op_490_cast")]; tensor var_494 = const()[name = tensor("op_494"), val = tensor([1])]; tensor mean_y_29_cast = reduce_mean(axes = var_494, keep_dims = var_71, x = var_490_cast)[name = tensor("mean_y_29_cast")]; tensor var_496_cast = sub(x = var_490_cast, y = mean_y_29_cast)[name = tensor("op_496_cast")]; tensor var_497_cast = square(x = var_496_cast); tensor var_498 = const()[name = tensor("op_498"), val = tensor([1])]; tensor var_499_cast = reduce_mean(axes = var_498, keep_dims = var_71, x = var_497_cast)[name = tensor("op_499_cast")]; tensor var_500_to_fp16 = const()[name = tensor("op_500_to_fp16"), val = tensor(0x1p-14)]; tensor var_501_cast = add(x = var_499_cast, y = var_500_to_fp16)[name = tensor("op_501_cast")]; tensor std_y_29_cast = sqrt(x = var_501_cast)[name = tensor("std_y_29_cast")]; tensor sep_module_6_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_6_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1577024)))]; tensor var_504_cast = mul(x = sep_module_6_tcn_6_norm_gamma_to_fp16, y = var_496_cast)[name = tensor("op_504_cast")]; tensor var_505_cast = real_div(x = var_504_cast, y = std_y_29_cast)[name = tensor("op_505_cast")]; tensor sep_module_6_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_6_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1577856)))]; tensor y_14_cast = add(x = var_505_cast, y = sep_module_6_tcn_6_norm_beta_to_fp16)[name = tensor("y_14_cast")]; tensor input_73_cast = add(x = input_63_cast, y = y_14_cast)[name = tensor("input_73_cast")]; tensor var_516 = const()[name = tensor("op_516"), val = tensor([1])]; tensor var_518 = const()[name = tensor("op_518"), val = tensor([1])]; tensor input_75_pad_type_0 = const()[name = tensor("input_75_pad_type_0"), val = tensor("custom")]; tensor input_75_pad_0 = const()[name = tensor("input_75_pad_0"), val = tensor([0, 0])]; tensor sep_module_7_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1578688))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1652480))), name = tensor("sep_module_7_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_75_cast = conv(dilations = var_518, groups = var_67, pad = input_75_pad_0, pad_type = input_75_pad_type_0, strides = var_516, weight = sep_module_7_tcn_0_weight_to_fp16_palettized, x = input_73_cast)[name = tensor("input_75_cast")]; tensor var_522_alpha_1_to_fp16 = const()[name = tensor("op_522_alpha_1_to_fp16"), val = tensor(0x1.1d8p-1)]; tensor var_522_cast = leaky_relu(alpha = var_522_alpha_1_to_fp16, x = input_75_cast)[name = tensor("op_522_cast")]; tensor var_526 = const()[name = tensor("op_526"), val = tensor([1])]; tensor mean_y_31_cast = reduce_mean(axes = var_526, keep_dims = var_71, x = var_522_cast)[name = tensor("mean_y_31_cast")]; tensor var_528_cast = sub(x = var_522_cast, y = mean_y_31_cast)[name = tensor("op_528_cast")]; tensor var_529_cast = square(x = var_528_cast); tensor var_530 = const()[name = tensor("op_530"), val = tensor([1])]; tensor var_531_cast = reduce_mean(axes = var_530, keep_dims = var_71, x = var_529_cast)[name = tensor("op_531_cast")]; tensor var_532_to_fp16 = const()[name = tensor("op_532_to_fp16"), val = tensor(0x1p-14)]; tensor var_533_cast = add(x = var_531_cast, y = var_532_to_fp16)[name = tensor("op_533_cast")]; tensor std_y_31_cast = sqrt(x = var_533_cast)[name = tensor("std_y_31_cast")]; tensor sep_module_7_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_7_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1652608)))]; tensor var_536_cast = mul(x = sep_module_7_tcn_2_norm_gamma_to_fp16, y = var_528_cast)[name = tensor("op_536_cast")]; tensor var_537_cast = real_div(x = var_536_cast, y = std_y_31_cast)[name = tensor("op_537_cast")]; tensor sep_module_7_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_7_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1653440)))]; tensor input_77_cast = add(x = var_537_cast, y = sep_module_7_tcn_2_norm_beta_to_fp16)[name = tensor("input_77_cast")]; tensor input_79_pad_0 = const()[name = tensor("input_79_pad_0"), val = tensor([0, 0, 0, 0, 256, 0])]; tensor input_79_mode_0 = const()[name = tensor("input_79_mode_0"), val = tensor("constant")]; tensor input_79_constant_val_0_to_fp16 = const()[name = tensor("input_79_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_79_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_77_cast_in_state, input_77_cast)); tensor input_77_cast_out_state = slice_by_size(begin = tensor([0, 0, -256]), size = tensor([-1, 384, 256]), x = input_79_cast); tensor var_542 = const()[name = tensor("op_542"), val = tensor([1])]; tensor var_544 = const()[name = tensor("op_544"), val = tensor([128])]; tensor input_81_pad_type_0 = const()[name = tensor("input_81_pad_type_0"), val = tensor("custom")]; tensor input_81_pad_0 = const()[name = tensor("input_81_pad_0"), val = tensor([0, 0])]; tensor sep_module_7_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_7_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1654272)))]; tensor input_81_cast = conv(dilations = var_544, groups = var_68, pad = input_81_pad_0, pad_type = input_81_pad_type_0, strides = var_542, weight = sep_module_7_tcn_4_weight_to_fp16, x = input_79_cast)[name = tensor("input_81_cast")]; tensor var_548_alpha_1_to_fp16 = const()[name = tensor("op_548_alpha_1_to_fp16"), val = tensor(-0x1.d9cp-5)]; tensor var_548_cast = leaky_relu(alpha = var_548_alpha_1_to_fp16, x = input_81_cast)[name = tensor("op_548_cast")]; tensor var_552 = const()[name = tensor("op_552"), val = tensor([1])]; tensor mean_y_33_cast = reduce_mean(axes = var_552, keep_dims = var_71, x = var_548_cast)[name = tensor("mean_y_33_cast")]; tensor var_554_cast = sub(x = var_548_cast, y = mean_y_33_cast)[name = tensor("op_554_cast")]; tensor var_555_cast = square(x = var_554_cast); tensor var_556 = const()[name = tensor("op_556"), val = tensor([1])]; tensor var_557_cast = reduce_mean(axes = var_556, keep_dims = var_71, x = var_555_cast)[name = tensor("op_557_cast")]; tensor var_558_to_fp16 = const()[name = tensor("op_558_to_fp16"), val = tensor(0x1p-14)]; tensor var_559_cast = add(x = var_557_cast, y = var_558_to_fp16)[name = tensor("op_559_cast")]; tensor std_y_33_cast = sqrt(x = var_559_cast)[name = tensor("std_y_33_cast")]; tensor sep_module_7_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_7_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1656640)))]; tensor var_562_cast = mul(x = sep_module_7_tcn_6_norm_gamma_to_fp16, y = var_554_cast)[name = tensor("op_562_cast")]; tensor var_563_cast = real_div(x = var_562_cast, y = std_y_33_cast)[name = tensor("op_563_cast")]; tensor sep_module_7_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_7_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1657472)))]; tensor y_16_cast = add(x = var_563_cast, y = sep_module_7_tcn_6_norm_beta_to_fp16)[name = tensor("y_16_cast")]; tensor input_83_cast = add(x = input_73_cast, y = y_16_cast)[name = tensor("input_83_cast")]; tensor var_574 = const()[name = tensor("op_574"), val = tensor([1])]; tensor var_576 = const()[name = tensor("op_576"), val = tensor([1])]; tensor input_85_pad_type_0 = const()[name = tensor("input_85_pad_type_0"), val = tensor("custom")]; tensor input_85_pad_0 = const()[name = tensor("input_85_pad_0"), val = tensor([0, 0])]; tensor sep_module_8_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1658304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1732096))), name = tensor("sep_module_8_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_85_cast = conv(dilations = var_576, groups = var_67, pad = input_85_pad_0, pad_type = input_85_pad_type_0, strides = var_574, weight = sep_module_8_tcn_0_weight_to_fp16_palettized, x = input_83_cast)[name = tensor("input_85_cast")]; tensor var_580_alpha_1_to_fp16 = const()[name = tensor("op_580_alpha_1_to_fp16"), val = tensor(0x1.1b4p-1)]; tensor var_580_cast = leaky_relu(alpha = var_580_alpha_1_to_fp16, x = input_85_cast)[name = tensor("op_580_cast")]; tensor var_584 = const()[name = tensor("op_584"), val = tensor([1])]; tensor mean_y_35_cast = reduce_mean(axes = var_584, keep_dims = var_71, x = var_580_cast)[name = tensor("mean_y_35_cast")]; tensor var_586_cast = sub(x = var_580_cast, y = mean_y_35_cast)[name = tensor("op_586_cast")]; tensor var_587_cast = square(x = var_586_cast); tensor var_588 = const()[name = tensor("op_588"), val = tensor([1])]; tensor var_589_cast = reduce_mean(axes = var_588, keep_dims = var_71, x = var_587_cast)[name = tensor("op_589_cast")]; tensor var_590_to_fp16 = const()[name = tensor("op_590_to_fp16"), val = tensor(0x1p-14)]; tensor var_591_cast = add(x = var_589_cast, y = var_590_to_fp16)[name = tensor("op_591_cast")]; tensor std_y_35_cast = sqrt(x = var_591_cast)[name = tensor("std_y_35_cast")]; tensor sep_module_8_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_8_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1732224)))]; tensor var_594_cast = mul(x = sep_module_8_tcn_2_norm_gamma_to_fp16, y = var_586_cast)[name = tensor("op_594_cast")]; tensor var_595_cast = real_div(x = var_594_cast, y = std_y_35_cast)[name = tensor("op_595_cast")]; tensor sep_module_8_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_8_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1733056)))]; tensor input_87_cast = add(x = var_595_cast, y = sep_module_8_tcn_2_norm_beta_to_fp16)[name = tensor("input_87_cast")]; tensor input_89_pad_0 = const()[name = tensor("input_89_pad_0"), val = tensor([0, 0, 0, 0, 512, 0])]; tensor input_89_mode_0 = const()[name = tensor("input_89_mode_0"), val = tensor("constant")]; tensor input_89_constant_val_0_to_fp16 = const()[name = tensor("input_89_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_89_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_87_cast_in_state, input_87_cast)); tensor input_87_cast_out_state = slice_by_size(begin = tensor([0, 0, -512]), size = tensor([-1, 384, 512]), x = input_89_cast); tensor var_600 = const()[name = tensor("op_600"), val = tensor([1])]; tensor var_602 = const()[name = tensor("op_602"), val = tensor([256])]; tensor input_91_pad_type_0 = const()[name = tensor("input_91_pad_type_0"), val = tensor("custom")]; tensor input_91_pad_0 = const()[name = tensor("input_91_pad_0"), val = tensor([0, 0])]; tensor sep_module_8_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_8_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1733888)))]; tensor input_91_cast = conv(dilations = var_602, groups = var_68, pad = input_91_pad_0, pad_type = input_91_pad_type_0, strides = var_600, weight = sep_module_8_tcn_4_weight_to_fp16, x = input_89_cast)[name = tensor("input_91_cast")]; tensor var_606_alpha_1_to_fp16 = const()[name = tensor("op_606_alpha_1_to_fp16"), val = tensor(-0x1.e5p-4)]; tensor var_606_cast = leaky_relu(alpha = var_606_alpha_1_to_fp16, x = input_91_cast)[name = tensor("op_606_cast")]; tensor var_610 = const()[name = tensor("op_610"), val = tensor([1])]; tensor mean_y_37_cast = reduce_mean(axes = var_610, keep_dims = var_71, x = var_606_cast)[name = tensor("mean_y_37_cast")]; tensor var_612_cast = sub(x = var_606_cast, y = mean_y_37_cast)[name = tensor("op_612_cast")]; tensor var_613_cast = square(x = var_612_cast); tensor var_614 = const()[name = tensor("op_614"), val = tensor([1])]; tensor var_615_cast = reduce_mean(axes = var_614, keep_dims = var_71, x = var_613_cast)[name = tensor("op_615_cast")]; tensor var_616_to_fp16 = const()[name = tensor("op_616_to_fp16"), val = tensor(0x1p-14)]; tensor var_617_cast = add(x = var_615_cast, y = var_616_to_fp16)[name = tensor("op_617_cast")]; tensor std_y_37_cast = sqrt(x = var_617_cast)[name = tensor("std_y_37_cast")]; tensor sep_module_8_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_8_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1736256)))]; tensor var_620_cast = mul(x = sep_module_8_tcn_6_norm_gamma_to_fp16, y = var_612_cast)[name = tensor("op_620_cast")]; tensor var_621_cast = real_div(x = var_620_cast, y = std_y_37_cast)[name = tensor("op_621_cast")]; tensor sep_module_8_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_8_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1737088)))]; tensor y_18_cast = add(x = var_621_cast, y = sep_module_8_tcn_6_norm_beta_to_fp16)[name = tensor("y_18_cast")]; tensor input_93_cast = add(x = input_83_cast, y = y_18_cast)[name = tensor("input_93_cast")]; tensor var_632 = const()[name = tensor("op_632"), val = tensor([1])]; tensor var_634 = const()[name = tensor("op_634"), val = tensor([1])]; tensor input_95_pad_type_0 = const()[name = tensor("input_95_pad_type_0"), val = tensor("custom")]; tensor input_95_pad_0 = const()[name = tensor("input_95_pad_0"), val = tensor([0, 0])]; tensor sep_module_9_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1737920))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1811712))), name = tensor("sep_module_9_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_95_cast = conv(dilations = var_634, groups = var_67, pad = input_95_pad_0, pad_type = input_95_pad_type_0, strides = var_632, weight = sep_module_9_tcn_0_weight_to_fp16_palettized, x = input_93_cast)[name = tensor("input_95_cast")]; tensor var_638_alpha_1_to_fp16 = const()[name = tensor("op_638_alpha_1_to_fp16"), val = tensor(0x1.12p-1)]; tensor var_638_cast = leaky_relu(alpha = var_638_alpha_1_to_fp16, x = input_95_cast)[name = tensor("op_638_cast")]; tensor var_642 = const()[name = tensor("op_642"), val = tensor([1])]; tensor mean_y_39_cast = reduce_mean(axes = var_642, keep_dims = var_71, x = var_638_cast)[name = tensor("mean_y_39_cast")]; tensor var_644_cast = sub(x = var_638_cast, y = mean_y_39_cast)[name = tensor("op_644_cast")]; tensor var_645_cast = square(x = var_644_cast); tensor var_646 = const()[name = tensor("op_646"), val = tensor([1])]; tensor var_647_cast = reduce_mean(axes = var_646, keep_dims = var_71, x = var_645_cast)[name = tensor("op_647_cast")]; tensor var_648_to_fp16 = const()[name = tensor("op_648_to_fp16"), val = tensor(0x1p-14)]; tensor var_649_cast = add(x = var_647_cast, y = var_648_to_fp16)[name = tensor("op_649_cast")]; tensor std_y_39_cast = sqrt(x = var_649_cast)[name = tensor("std_y_39_cast")]; tensor sep_module_9_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_9_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1811840)))]; tensor var_652_cast = mul(x = sep_module_9_tcn_2_norm_gamma_to_fp16, y = var_644_cast)[name = tensor("op_652_cast")]; tensor var_653_cast = real_div(x = var_652_cast, y = std_y_39_cast)[name = tensor("op_653_cast")]; tensor sep_module_9_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_9_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1812672)))]; tensor input_97_cast = add(x = var_653_cast, y = sep_module_9_tcn_2_norm_beta_to_fp16)[name = tensor("input_97_cast")]; tensor input_99_pad_0 = const()[name = tensor("input_99_pad_0"), val = tensor([0, 0, 0, 0, 2, 0])]; tensor input_99_mode_0 = const()[name = tensor("input_99_mode_0"), val = tensor("constant")]; tensor input_99_constant_val_0_to_fp16 = const()[name = tensor("input_99_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_99_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_97_cast_in_state, input_97_cast)); tensor input_97_cast_out_state = slice_by_size(begin = tensor([0, 0, -2]), size = tensor([-1, 384, 2]), x = input_99_cast); tensor var_658 = const()[name = tensor("op_658"), val = tensor([1])]; tensor var_660 = const()[name = tensor("op_660"), val = tensor([1])]; tensor input_101_pad_type_0 = const()[name = tensor("input_101_pad_type_0"), val = tensor("custom")]; tensor input_101_pad_0 = const()[name = tensor("input_101_pad_0"), val = tensor([0, 0])]; tensor sep_module_9_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_9_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1813504)))]; tensor input_101_cast = conv(dilations = var_660, groups = var_68, pad = input_101_pad_0, pad_type = input_101_pad_type_0, strides = var_658, weight = sep_module_9_tcn_4_weight_to_fp16, x = input_99_cast)[name = tensor("input_101_cast")]; tensor var_664_alpha_1_to_fp16 = const()[name = tensor("op_664_alpha_1_to_fp16"), val = tensor(-0x1.14cp-3)]; tensor var_664_cast = leaky_relu(alpha = var_664_alpha_1_to_fp16, x = input_101_cast)[name = tensor("op_664_cast")]; tensor var_668 = const()[name = tensor("op_668"), val = tensor([1])]; tensor mean_y_41_cast = reduce_mean(axes = var_668, keep_dims = var_71, x = var_664_cast)[name = tensor("mean_y_41_cast")]; tensor var_670_cast = sub(x = var_664_cast, y = mean_y_41_cast)[name = tensor("op_670_cast")]; tensor var_671_cast = square(x = var_670_cast); tensor var_672 = const()[name = tensor("op_672"), val = tensor([1])]; tensor var_673_cast = reduce_mean(axes = var_672, keep_dims = var_71, x = var_671_cast)[name = tensor("op_673_cast")]; tensor var_674_to_fp16 = const()[name = tensor("op_674_to_fp16"), val = tensor(0x1p-14)]; tensor var_675_cast = add(x = var_673_cast, y = var_674_to_fp16)[name = tensor("op_675_cast")]; tensor std_y_41_cast = sqrt(x = var_675_cast)[name = tensor("std_y_41_cast")]; tensor sep_module_9_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_9_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1815872)))]; tensor var_678_cast = mul(x = sep_module_9_tcn_6_norm_gamma_to_fp16, y = var_670_cast)[name = tensor("op_678_cast")]; tensor var_679_cast = real_div(x = var_678_cast, y = std_y_41_cast)[name = tensor("op_679_cast")]; tensor sep_module_9_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_9_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1816704)))]; tensor y_20_cast = add(x = var_679_cast, y = sep_module_9_tcn_6_norm_beta_to_fp16)[name = tensor("y_20_cast")]; tensor input_103_cast = add(x = input_93_cast, y = y_20_cast)[name = tensor("input_103_cast")]; tensor var_690 = const()[name = tensor("op_690"), val = tensor([1])]; tensor var_692 = const()[name = tensor("op_692"), val = tensor([1])]; tensor input_105_pad_type_0 = const()[name = tensor("input_105_pad_type_0"), val = tensor("custom")]; tensor input_105_pad_0 = const()[name = tensor("input_105_pad_0"), val = tensor([0, 0])]; tensor sep_module_10_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1817536))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1891328))), name = tensor("sep_module_10_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_105_cast = conv(dilations = var_692, groups = var_67, pad = input_105_pad_0, pad_type = input_105_pad_type_0, strides = var_690, weight = sep_module_10_tcn_0_weight_to_fp16_palettized, x = input_103_cast)[name = tensor("input_105_cast")]; tensor var_696_alpha_1_to_fp16 = const()[name = tensor("op_696_alpha_1_to_fp16"), val = tensor(0x1.73p-2)]; tensor var_696_cast = leaky_relu(alpha = var_696_alpha_1_to_fp16, x = input_105_cast)[name = tensor("op_696_cast")]; tensor var_700 = const()[name = tensor("op_700"), val = tensor([1])]; tensor mean_y_43_cast = reduce_mean(axes = var_700, keep_dims = var_71, x = var_696_cast)[name = tensor("mean_y_43_cast")]; tensor var_702_cast = sub(x = var_696_cast, y = mean_y_43_cast)[name = tensor("op_702_cast")]; tensor var_703_cast = square(x = var_702_cast); tensor var_704 = const()[name = tensor("op_704"), val = tensor([1])]; tensor var_705_cast = reduce_mean(axes = var_704, keep_dims = var_71, x = var_703_cast)[name = tensor("op_705_cast")]; tensor var_706_to_fp16 = const()[name = tensor("op_706_to_fp16"), val = tensor(0x1p-14)]; tensor var_707_cast = add(x = var_705_cast, y = var_706_to_fp16)[name = tensor("op_707_cast")]; tensor std_y_43_cast = sqrt(x = var_707_cast)[name = tensor("std_y_43_cast")]; tensor sep_module_10_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_10_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1891456)))]; tensor var_710_cast = mul(x = sep_module_10_tcn_2_norm_gamma_to_fp16, y = var_702_cast)[name = tensor("op_710_cast")]; tensor var_711_cast = real_div(x = var_710_cast, y = std_y_43_cast)[name = tensor("op_711_cast")]; tensor sep_module_10_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_10_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1892288)))]; tensor input_107_cast = add(x = var_711_cast, y = sep_module_10_tcn_2_norm_beta_to_fp16)[name = tensor("input_107_cast")]; tensor input_109_pad_0 = const()[name = tensor("input_109_pad_0"), val = tensor([0, 0, 0, 0, 4, 0])]; tensor input_109_mode_0 = const()[name = tensor("input_109_mode_0"), val = tensor("constant")]; tensor input_109_constant_val_0_to_fp16 = const()[name = tensor("input_109_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_109_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_107_cast_in_state, input_107_cast)); tensor input_107_cast_out_state = slice_by_size(begin = tensor([0, 0, -4]), size = tensor([-1, 384, 4]), x = input_109_cast); tensor var_716 = const()[name = tensor("op_716"), val = tensor([1])]; tensor var_718 = const()[name = tensor("op_718"), val = tensor([2])]; tensor input_111_pad_type_0 = const()[name = tensor("input_111_pad_type_0"), val = tensor("custom")]; tensor input_111_pad_0 = const()[name = tensor("input_111_pad_0"), val = tensor([0, 0])]; tensor sep_module_10_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_10_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1893120)))]; tensor input_111_cast = conv(dilations = var_718, groups = var_68, pad = input_111_pad_0, pad_type = input_111_pad_type_0, strides = var_716, weight = sep_module_10_tcn_4_weight_to_fp16, x = input_109_cast)[name = tensor("input_111_cast")]; tensor var_722_alpha_1_to_fp16 = const()[name = tensor("op_722_alpha_1_to_fp16"), val = tensor(-0x1.c54p-2)]; tensor var_722_cast = leaky_relu(alpha = var_722_alpha_1_to_fp16, x = input_111_cast)[name = tensor("op_722_cast")]; tensor var_726 = const()[name = tensor("op_726"), val = tensor([1])]; tensor mean_y_45_cast = reduce_mean(axes = var_726, keep_dims = var_71, x = var_722_cast)[name = tensor("mean_y_45_cast")]; tensor var_728_cast = sub(x = var_722_cast, y = mean_y_45_cast)[name = tensor("op_728_cast")]; tensor var_729_cast = square(x = var_728_cast); tensor var_730 = const()[name = tensor("op_730"), val = tensor([1])]; tensor var_731_cast = reduce_mean(axes = var_730, keep_dims = var_71, x = var_729_cast)[name = tensor("op_731_cast")]; tensor var_732_to_fp16 = const()[name = tensor("op_732_to_fp16"), val = tensor(0x1p-14)]; tensor var_733_cast = add(x = var_731_cast, y = var_732_to_fp16)[name = tensor("op_733_cast")]; tensor std_y_45_cast = sqrt(x = var_733_cast)[name = tensor("std_y_45_cast")]; tensor sep_module_10_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_10_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1895488)))]; tensor var_736_cast = mul(x = sep_module_10_tcn_6_norm_gamma_to_fp16, y = var_728_cast)[name = tensor("op_736_cast")]; tensor var_737_cast = real_div(x = var_736_cast, y = std_y_45_cast)[name = tensor("op_737_cast")]; tensor sep_module_10_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_10_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1896320)))]; tensor y_22_cast = add(x = var_737_cast, y = sep_module_10_tcn_6_norm_beta_to_fp16)[name = tensor("y_22_cast")]; tensor input_113_cast = add(x = input_103_cast, y = y_22_cast)[name = tensor("input_113_cast")]; tensor var_748 = const()[name = tensor("op_748"), val = tensor([1])]; tensor var_750 = const()[name = tensor("op_750"), val = tensor([1])]; tensor input_115_pad_type_0 = const()[name = tensor("input_115_pad_type_0"), val = tensor("custom")]; tensor input_115_pad_0 = const()[name = tensor("input_115_pad_0"), val = tensor([0, 0])]; tensor sep_module_11_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1897152))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1970944))), name = tensor("sep_module_11_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_115_cast = conv(dilations = var_750, groups = var_67, pad = input_115_pad_0, pad_type = input_115_pad_type_0, strides = var_748, weight = sep_module_11_tcn_0_weight_to_fp16_palettized, x = input_113_cast)[name = tensor("input_115_cast")]; tensor var_754_alpha_1_to_fp16 = const()[name = tensor("op_754_alpha_1_to_fp16"), val = tensor(-0x1.a14p-2)]; tensor var_754_cast = leaky_relu(alpha = var_754_alpha_1_to_fp16, x = input_115_cast)[name = tensor("op_754_cast")]; tensor var_758 = const()[name = tensor("op_758"), val = tensor([1])]; tensor mean_y_47_cast = reduce_mean(axes = var_758, keep_dims = var_71, x = var_754_cast)[name = tensor("mean_y_47_cast")]; tensor var_760_cast = sub(x = var_754_cast, y = mean_y_47_cast)[name = tensor("op_760_cast")]; tensor var_761_cast = square(x = var_760_cast); tensor var_762 = const()[name = tensor("op_762"), val = tensor([1])]; tensor var_763_cast = reduce_mean(axes = var_762, keep_dims = var_71, x = var_761_cast)[name = tensor("op_763_cast")]; tensor var_764_to_fp16 = const()[name = tensor("op_764_to_fp16"), val = tensor(0x1p-14)]; tensor var_765_cast = add(x = var_763_cast, y = var_764_to_fp16)[name = tensor("op_765_cast")]; tensor std_y_47_cast = sqrt(x = var_765_cast)[name = tensor("std_y_47_cast")]; tensor sep_module_11_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_11_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1971072)))]; tensor var_768_cast = mul(x = sep_module_11_tcn_2_norm_gamma_to_fp16, y = var_760_cast)[name = tensor("op_768_cast")]; tensor var_769_cast = real_div(x = var_768_cast, y = std_y_47_cast)[name = tensor("op_769_cast")]; tensor sep_module_11_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_11_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1971904)))]; tensor input_117_cast = add(x = var_769_cast, y = sep_module_11_tcn_2_norm_beta_to_fp16)[name = tensor("input_117_cast")]; tensor input_119_pad_0 = const()[name = tensor("input_119_pad_0"), val = tensor([0, 0, 0, 0, 8, 0])]; tensor input_119_mode_0 = const()[name = tensor("input_119_mode_0"), val = tensor("constant")]; tensor input_119_constant_val_0_to_fp16 = const()[name = tensor("input_119_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_119_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_117_cast_in_state, input_117_cast)); tensor input_117_cast_out_state = slice_by_size(begin = tensor([0, 0, -8]), size = tensor([-1, 384, 8]), x = input_119_cast); tensor var_774 = const()[name = tensor("op_774"), val = tensor([1])]; tensor var_776 = const()[name = tensor("op_776"), val = tensor([4])]; tensor input_121_pad_type_0 = const()[name = tensor("input_121_pad_type_0"), val = tensor("custom")]; tensor input_121_pad_0 = const()[name = tensor("input_121_pad_0"), val = tensor([0, 0])]; tensor sep_module_11_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_11_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1972736)))]; tensor input_121_cast = conv(dilations = var_776, groups = var_68, pad = input_121_pad_0, pad_type = input_121_pad_type_0, strides = var_774, weight = sep_module_11_tcn_4_weight_to_fp16, x = input_119_cast)[name = tensor("input_121_cast")]; tensor var_780_alpha_1_to_fp16 = const()[name = tensor("op_780_alpha_1_to_fp16"), val = tensor(0x1.ef8p-3)]; tensor var_780_cast = leaky_relu(alpha = var_780_alpha_1_to_fp16, x = input_121_cast)[name = tensor("op_780_cast")]; tensor var_784 = const()[name = tensor("op_784"), val = tensor([1])]; tensor mean_y_49_cast = reduce_mean(axes = var_784, keep_dims = var_71, x = var_780_cast)[name = tensor("mean_y_49_cast")]; tensor var_786_cast = sub(x = var_780_cast, y = mean_y_49_cast)[name = tensor("op_786_cast")]; tensor var_787_cast = square(x = var_786_cast); tensor var_788 = const()[name = tensor("op_788"), val = tensor([1])]; tensor var_789_cast = reduce_mean(axes = var_788, keep_dims = var_71, x = var_787_cast)[name = tensor("op_789_cast")]; tensor var_790_to_fp16 = const()[name = tensor("op_790_to_fp16"), val = tensor(0x1p-14)]; tensor var_791_cast = add(x = var_789_cast, y = var_790_to_fp16)[name = tensor("op_791_cast")]; tensor std_y_49_cast = sqrt(x = var_791_cast)[name = tensor("std_y_49_cast")]; tensor sep_module_11_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_11_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1975104)))]; tensor var_794_cast = mul(x = sep_module_11_tcn_6_norm_gamma_to_fp16, y = var_786_cast)[name = tensor("op_794_cast")]; tensor var_795_cast = real_div(x = var_794_cast, y = std_y_49_cast)[name = tensor("op_795_cast")]; tensor sep_module_11_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_11_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1975936)))]; tensor y_24_cast = add(x = var_795_cast, y = sep_module_11_tcn_6_norm_beta_to_fp16)[name = tensor("y_24_cast")]; tensor input_123_cast = add(x = input_113_cast, y = y_24_cast)[name = tensor("input_123_cast")]; tensor var_806 = const()[name = tensor("op_806"), val = tensor([1])]; tensor var_808 = const()[name = tensor("op_808"), val = tensor([1])]; tensor input_125_pad_type_0 = const()[name = tensor("input_125_pad_type_0"), val = tensor("custom")]; tensor input_125_pad_0 = const()[name = tensor("input_125_pad_0"), val = tensor([0, 0])]; tensor sep_module_12_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(1976768))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2050560))), name = tensor("sep_module_12_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_125_cast = conv(dilations = var_808, groups = var_67, pad = input_125_pad_0, pad_type = input_125_pad_type_0, strides = var_806, weight = sep_module_12_tcn_0_weight_to_fp16_palettized, x = input_123_cast)[name = tensor("input_125_cast")]; tensor var_812_alpha_1_to_fp16 = const()[name = tensor("op_812_alpha_1_to_fp16"), val = tensor(0x1.cbcp-2)]; tensor var_812_cast = leaky_relu(alpha = var_812_alpha_1_to_fp16, x = input_125_cast)[name = tensor("op_812_cast")]; tensor var_816 = const()[name = tensor("op_816"), val = tensor([1])]; tensor mean_y_51_cast = reduce_mean(axes = var_816, keep_dims = var_71, x = var_812_cast)[name = tensor("mean_y_51_cast")]; tensor var_818_cast = sub(x = var_812_cast, y = mean_y_51_cast)[name = tensor("op_818_cast")]; tensor var_819_cast = square(x = var_818_cast); tensor var_820 = const()[name = tensor("op_820"), val = tensor([1])]; tensor var_821_cast = reduce_mean(axes = var_820, keep_dims = var_71, x = var_819_cast)[name = tensor("op_821_cast")]; tensor var_822_to_fp16 = const()[name = tensor("op_822_to_fp16"), val = tensor(0x1p-14)]; tensor var_823_cast = add(x = var_821_cast, y = var_822_to_fp16)[name = tensor("op_823_cast")]; tensor std_y_51_cast = sqrt(x = var_823_cast)[name = tensor("std_y_51_cast")]; tensor sep_module_12_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_12_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2050688)))]; tensor var_826_cast = mul(x = sep_module_12_tcn_2_norm_gamma_to_fp16, y = var_818_cast)[name = tensor("op_826_cast")]; tensor var_827_cast = real_div(x = var_826_cast, y = std_y_51_cast)[name = tensor("op_827_cast")]; tensor sep_module_12_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_12_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2051520)))]; tensor input_127_cast = add(x = var_827_cast, y = sep_module_12_tcn_2_norm_beta_to_fp16)[name = tensor("input_127_cast")]; tensor input_129_pad_0 = const()[name = tensor("input_129_pad_0"), val = tensor([0, 0, 0, 0, 16, 0])]; tensor input_129_mode_0 = const()[name = tensor("input_129_mode_0"), val = tensor("constant")]; tensor input_129_constant_val_0_to_fp16 = const()[name = tensor("input_129_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_129_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_127_cast_in_state, input_127_cast)); tensor input_127_cast_out_state = slice_by_size(begin = tensor([0, 0, -16]), size = tensor([-1, 384, 16]), x = input_129_cast); tensor var_832 = const()[name = tensor("op_832"), val = tensor([1])]; tensor var_834 = const()[name = tensor("op_834"), val = tensor([8])]; tensor input_131_pad_type_0 = const()[name = tensor("input_131_pad_type_0"), val = tensor("custom")]; tensor input_131_pad_0 = const()[name = tensor("input_131_pad_0"), val = tensor([0, 0])]; tensor sep_module_12_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_12_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2052352)))]; tensor input_131_cast = conv(dilations = var_834, groups = var_68, pad = input_131_pad_0, pad_type = input_131_pad_type_0, strides = var_832, weight = sep_module_12_tcn_4_weight_to_fp16, x = input_129_cast)[name = tensor("input_131_cast")]; tensor var_838_alpha_1_to_fp16 = const()[name = tensor("op_838_alpha_1_to_fp16"), val = tensor(-0x1.514p-3)]; tensor var_838_cast = leaky_relu(alpha = var_838_alpha_1_to_fp16, x = input_131_cast)[name = tensor("op_838_cast")]; tensor var_842 = const()[name = tensor("op_842"), val = tensor([1])]; tensor mean_y_53_cast = reduce_mean(axes = var_842, keep_dims = var_71, x = var_838_cast)[name = tensor("mean_y_53_cast")]; tensor var_844_cast = sub(x = var_838_cast, y = mean_y_53_cast)[name = tensor("op_844_cast")]; tensor var_845_cast = square(x = var_844_cast); tensor var_846 = const()[name = tensor("op_846"), val = tensor([1])]; tensor var_847_cast = reduce_mean(axes = var_846, keep_dims = var_71, x = var_845_cast)[name = tensor("op_847_cast")]; tensor var_848_to_fp16 = const()[name = tensor("op_848_to_fp16"), val = tensor(0x1p-14)]; tensor var_849_cast = add(x = var_847_cast, y = var_848_to_fp16)[name = tensor("op_849_cast")]; tensor std_y_53_cast = sqrt(x = var_849_cast)[name = tensor("std_y_53_cast")]; tensor sep_module_12_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_12_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2054720)))]; tensor var_852_cast = mul(x = sep_module_12_tcn_6_norm_gamma_to_fp16, y = var_844_cast)[name = tensor("op_852_cast")]; tensor var_853_cast = real_div(x = var_852_cast, y = std_y_53_cast)[name = tensor("op_853_cast")]; tensor sep_module_12_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_12_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2055552)))]; tensor y_26_cast = add(x = var_853_cast, y = sep_module_12_tcn_6_norm_beta_to_fp16)[name = tensor("y_26_cast")]; tensor input_133_cast = add(x = input_123_cast, y = y_26_cast)[name = tensor("input_133_cast")]; tensor var_864 = const()[name = tensor("op_864"), val = tensor([1])]; tensor var_866 = const()[name = tensor("op_866"), val = tensor([1])]; tensor input_135_pad_type_0 = const()[name = tensor("input_135_pad_type_0"), val = tensor("custom")]; tensor input_135_pad_0 = const()[name = tensor("input_135_pad_0"), val = tensor([0, 0])]; tensor sep_module_13_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2056384))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2130176))), name = tensor("sep_module_13_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_135_cast = conv(dilations = var_866, groups = var_67, pad = input_135_pad_0, pad_type = input_135_pad_type_0, strides = var_864, weight = sep_module_13_tcn_0_weight_to_fp16_palettized, x = input_133_cast)[name = tensor("input_135_cast")]; tensor var_870_alpha_1_to_fp16 = const()[name = tensor("op_870_alpha_1_to_fp16"), val = tensor(-0x1.434p-2)]; tensor var_870_cast = leaky_relu(alpha = var_870_alpha_1_to_fp16, x = input_135_cast)[name = tensor("op_870_cast")]; tensor var_874 = const()[name = tensor("op_874"), val = tensor([1])]; tensor mean_y_55_cast = reduce_mean(axes = var_874, keep_dims = var_71, x = var_870_cast)[name = tensor("mean_y_55_cast")]; tensor var_876_cast = sub(x = var_870_cast, y = mean_y_55_cast)[name = tensor("op_876_cast")]; tensor var_877_cast = square(x = var_876_cast); tensor var_878 = const()[name = tensor("op_878"), val = tensor([1])]; tensor var_879_cast = reduce_mean(axes = var_878, keep_dims = var_71, x = var_877_cast)[name = tensor("op_879_cast")]; tensor var_880_to_fp16 = const()[name = tensor("op_880_to_fp16"), val = tensor(0x1p-14)]; tensor var_881_cast = add(x = var_879_cast, y = var_880_to_fp16)[name = tensor("op_881_cast")]; tensor std_y_55_cast = sqrt(x = var_881_cast)[name = tensor("std_y_55_cast")]; tensor sep_module_13_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_13_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2130304)))]; tensor var_884_cast = mul(x = sep_module_13_tcn_2_norm_gamma_to_fp16, y = var_876_cast)[name = tensor("op_884_cast")]; tensor var_885_cast = real_div(x = var_884_cast, y = std_y_55_cast)[name = tensor("op_885_cast")]; tensor sep_module_13_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_13_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2131136)))]; tensor input_137_cast = add(x = var_885_cast, y = sep_module_13_tcn_2_norm_beta_to_fp16)[name = tensor("input_137_cast")]; tensor input_139_pad_0 = const()[name = tensor("input_139_pad_0"), val = tensor([0, 0, 0, 0, 32, 0])]; tensor input_139_mode_0 = const()[name = tensor("input_139_mode_0"), val = tensor("constant")]; tensor input_139_constant_val_0_to_fp16 = const()[name = tensor("input_139_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_139_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_137_cast_in_state, input_137_cast)); tensor input_137_cast_out_state = slice_by_size(begin = tensor([0, 0, -32]), size = tensor([-1, 384, 32]), x = input_139_cast); tensor var_890 = const()[name = tensor("op_890"), val = tensor([1])]; tensor var_892 = const()[name = tensor("op_892"), val = tensor([16])]; tensor input_141_pad_type_0 = const()[name = tensor("input_141_pad_type_0"), val = tensor("custom")]; tensor input_141_pad_0 = const()[name = tensor("input_141_pad_0"), val = tensor([0, 0])]; tensor sep_module_13_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_13_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2131968)))]; tensor input_141_cast = conv(dilations = var_892, groups = var_68, pad = input_141_pad_0, pad_type = input_141_pad_type_0, strides = var_890, weight = sep_module_13_tcn_4_weight_to_fp16, x = input_139_cast)[name = tensor("input_141_cast")]; tensor var_896_alpha_1_to_fp16 = const()[name = tensor("op_896_alpha_1_to_fp16"), val = tensor(0x1.648p-2)]; tensor var_896_cast = leaky_relu(alpha = var_896_alpha_1_to_fp16, x = input_141_cast)[name = tensor("op_896_cast")]; tensor var_900 = const()[name = tensor("op_900"), val = tensor([1])]; tensor mean_y_57_cast = reduce_mean(axes = var_900, keep_dims = var_71, x = var_896_cast)[name = tensor("mean_y_57_cast")]; tensor var_902_cast = sub(x = var_896_cast, y = mean_y_57_cast)[name = tensor("op_902_cast")]; tensor var_903_cast = square(x = var_902_cast); tensor var_904 = const()[name = tensor("op_904"), val = tensor([1])]; tensor var_905_cast = reduce_mean(axes = var_904, keep_dims = var_71, x = var_903_cast)[name = tensor("op_905_cast")]; tensor var_906_to_fp16 = const()[name = tensor("op_906_to_fp16"), val = tensor(0x1p-14)]; tensor var_907_cast = add(x = var_905_cast, y = var_906_to_fp16)[name = tensor("op_907_cast")]; tensor std_y_57_cast = sqrt(x = var_907_cast)[name = tensor("std_y_57_cast")]; tensor sep_module_13_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_13_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2134336)))]; tensor var_910_cast = mul(x = sep_module_13_tcn_6_norm_gamma_to_fp16, y = var_902_cast)[name = tensor("op_910_cast")]; tensor var_911_cast = real_div(x = var_910_cast, y = std_y_57_cast)[name = tensor("op_911_cast")]; tensor sep_module_13_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_13_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2135168)))]; tensor y_28_cast = add(x = var_911_cast, y = sep_module_13_tcn_6_norm_beta_to_fp16)[name = tensor("y_28_cast")]; tensor input_143_cast = add(x = input_133_cast, y = y_28_cast)[name = tensor("input_143_cast")]; tensor var_922 = const()[name = tensor("op_922"), val = tensor([1])]; tensor var_924 = const()[name = tensor("op_924"), val = tensor([1])]; tensor input_145_pad_type_0 = const()[name = tensor("input_145_pad_type_0"), val = tensor("custom")]; tensor input_145_pad_0 = const()[name = tensor("input_145_pad_0"), val = tensor([0, 0])]; tensor sep_module_14_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2136000))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2209792))), name = tensor("sep_module_14_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_145_cast = conv(dilations = var_924, groups = var_67, pad = input_145_pad_0, pad_type = input_145_pad_type_0, strides = var_922, weight = sep_module_14_tcn_0_weight_to_fp16_palettized, x = input_143_cast)[name = tensor("input_145_cast")]; tensor var_928_alpha_1_to_fp16 = const()[name = tensor("op_928_alpha_1_to_fp16"), val = tensor(-0x1.dfcp-2)]; tensor var_928_cast = leaky_relu(alpha = var_928_alpha_1_to_fp16, x = input_145_cast)[name = tensor("op_928_cast")]; tensor var_932 = const()[name = tensor("op_932"), val = tensor([1])]; tensor mean_y_59_cast = reduce_mean(axes = var_932, keep_dims = var_71, x = var_928_cast)[name = tensor("mean_y_59_cast")]; tensor var_934_cast = sub(x = var_928_cast, y = mean_y_59_cast)[name = tensor("op_934_cast")]; tensor var_935_cast = square(x = var_934_cast); tensor var_936 = const()[name = tensor("op_936"), val = tensor([1])]; tensor var_937_cast = reduce_mean(axes = var_936, keep_dims = var_71, x = var_935_cast)[name = tensor("op_937_cast")]; tensor var_938_to_fp16 = const()[name = tensor("op_938_to_fp16"), val = tensor(0x1p-14)]; tensor var_939_cast = add(x = var_937_cast, y = var_938_to_fp16)[name = tensor("op_939_cast")]; tensor std_y_59_cast = sqrt(x = var_939_cast)[name = tensor("std_y_59_cast")]; tensor sep_module_14_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_14_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2209920)))]; tensor var_942_cast = mul(x = sep_module_14_tcn_2_norm_gamma_to_fp16, y = var_934_cast)[name = tensor("op_942_cast")]; tensor var_943_cast = real_div(x = var_942_cast, y = std_y_59_cast)[name = tensor("op_943_cast")]; tensor sep_module_14_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_14_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2210752)))]; tensor input_147_cast = add(x = var_943_cast, y = sep_module_14_tcn_2_norm_beta_to_fp16)[name = tensor("input_147_cast")]; tensor input_149_pad_0 = const()[name = tensor("input_149_pad_0"), val = tensor([0, 0, 0, 0, 64, 0])]; tensor input_149_mode_0 = const()[name = tensor("input_149_mode_0"), val = tensor("constant")]; tensor input_149_constant_val_0_to_fp16 = const()[name = tensor("input_149_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_149_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_147_cast_in_state, input_147_cast)); tensor input_147_cast_out_state = slice_by_size(begin = tensor([0, 0, -64]), size = tensor([-1, 384, 64]), x = input_149_cast); tensor var_948 = const()[name = tensor("op_948"), val = tensor([1])]; tensor var_950 = const()[name = tensor("op_950"), val = tensor([32])]; tensor input_151_pad_type_0 = const()[name = tensor("input_151_pad_type_0"), val = tensor("custom")]; tensor input_151_pad_0 = const()[name = tensor("input_151_pad_0"), val = tensor([0, 0])]; tensor sep_module_14_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_14_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2211584)))]; tensor input_151_cast = conv(dilations = var_950, groups = var_68, pad = input_151_pad_0, pad_type = input_151_pad_type_0, strides = var_948, weight = sep_module_14_tcn_4_weight_to_fp16, x = input_149_cast)[name = tensor("input_151_cast")]; tensor var_954_alpha_1_to_fp16 = const()[name = tensor("op_954_alpha_1_to_fp16"), val = tensor(0x1.18cp-1)]; tensor var_954_cast = leaky_relu(alpha = var_954_alpha_1_to_fp16, x = input_151_cast)[name = tensor("op_954_cast")]; tensor var_958 = const()[name = tensor("op_958"), val = tensor([1])]; tensor mean_y_61_cast = reduce_mean(axes = var_958, keep_dims = var_71, x = var_954_cast)[name = tensor("mean_y_61_cast")]; tensor var_960_cast = sub(x = var_954_cast, y = mean_y_61_cast)[name = tensor("op_960_cast")]; tensor var_961_cast = square(x = var_960_cast); tensor var_962 = const()[name = tensor("op_962"), val = tensor([1])]; tensor var_963_cast = reduce_mean(axes = var_962, keep_dims = var_71, x = var_961_cast)[name = tensor("op_963_cast")]; tensor var_964_to_fp16 = const()[name = tensor("op_964_to_fp16"), val = tensor(0x1p-14)]; tensor var_965_cast = add(x = var_963_cast, y = var_964_to_fp16)[name = tensor("op_965_cast")]; tensor std_y_61_cast = sqrt(x = var_965_cast)[name = tensor("std_y_61_cast")]; tensor sep_module_14_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_14_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2213952)))]; tensor var_968_cast = mul(x = sep_module_14_tcn_6_norm_gamma_to_fp16, y = var_960_cast)[name = tensor("op_968_cast")]; tensor var_969_cast = real_div(x = var_968_cast, y = std_y_61_cast)[name = tensor("op_969_cast")]; tensor sep_module_14_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_14_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2214784)))]; tensor y_30_cast = add(x = var_969_cast, y = sep_module_14_tcn_6_norm_beta_to_fp16)[name = tensor("y_30_cast")]; tensor input_153_cast = add(x = input_143_cast, y = y_30_cast)[name = tensor("input_153_cast")]; tensor var_980 = const()[name = tensor("op_980"), val = tensor([1])]; tensor var_982 = const()[name = tensor("op_982"), val = tensor([1])]; tensor input_155_pad_type_0 = const()[name = tensor("input_155_pad_type_0"), val = tensor("custom")]; tensor input_155_pad_0 = const()[name = tensor("input_155_pad_0"), val = tensor([0, 0])]; tensor sep_module_15_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2215616))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2289408))), name = tensor("sep_module_15_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_155_cast = conv(dilations = var_982, groups = var_67, pad = input_155_pad_0, pad_type = input_155_pad_type_0, strides = var_980, weight = sep_module_15_tcn_0_weight_to_fp16_palettized, x = input_153_cast)[name = tensor("input_155_cast")]; tensor var_986_alpha_1_to_fp16 = const()[name = tensor("op_986_alpha_1_to_fp16"), val = tensor(-0x1.838p-2)]; tensor var_986_cast = leaky_relu(alpha = var_986_alpha_1_to_fp16, x = input_155_cast)[name = tensor("op_986_cast")]; tensor var_990 = const()[name = tensor("op_990"), val = tensor([1])]; tensor mean_y_63_cast = reduce_mean(axes = var_990, keep_dims = var_71, x = var_986_cast)[name = tensor("mean_y_63_cast")]; tensor var_992_cast = sub(x = var_986_cast, y = mean_y_63_cast)[name = tensor("op_992_cast")]; tensor var_993_cast = square(x = var_992_cast); tensor var_994 = const()[name = tensor("op_994"), val = tensor([1])]; tensor var_995_cast = reduce_mean(axes = var_994, keep_dims = var_71, x = var_993_cast)[name = tensor("op_995_cast")]; tensor var_996_to_fp16 = const()[name = tensor("op_996_to_fp16"), val = tensor(0x1p-14)]; tensor var_997_cast = add(x = var_995_cast, y = var_996_to_fp16)[name = tensor("op_997_cast")]; tensor std_y_63_cast = sqrt(x = var_997_cast)[name = tensor("std_y_63_cast")]; tensor sep_module_15_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_15_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2289536)))]; tensor var_1000_cast = mul(x = sep_module_15_tcn_2_norm_gamma_to_fp16, y = var_992_cast)[name = tensor("op_1000_cast")]; tensor var_1001_cast = real_div(x = var_1000_cast, y = std_y_63_cast)[name = tensor("op_1001_cast")]; tensor sep_module_15_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_15_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2290368)))]; tensor input_157_cast = add(x = var_1001_cast, y = sep_module_15_tcn_2_norm_beta_to_fp16)[name = tensor("input_157_cast")]; tensor input_159_pad_0 = const()[name = tensor("input_159_pad_0"), val = tensor([0, 0, 0, 0, 128, 0])]; tensor input_159_mode_0 = const()[name = tensor("input_159_mode_0"), val = tensor("constant")]; tensor input_159_constant_val_0_to_fp16 = const()[name = tensor("input_159_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_159_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_157_cast_in_state, input_157_cast)); tensor input_157_cast_out_state = slice_by_size(begin = tensor([0, 0, -128]), size = tensor([-1, 384, 128]), x = input_159_cast); tensor var_1006 = const()[name = tensor("op_1006"), val = tensor([1])]; tensor var_1008 = const()[name = tensor("op_1008"), val = tensor([64])]; tensor input_161_pad_type_0 = const()[name = tensor("input_161_pad_type_0"), val = tensor("custom")]; tensor input_161_pad_0 = const()[name = tensor("input_161_pad_0"), val = tensor([0, 0])]; tensor sep_module_15_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_15_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2291200)))]; tensor input_161_cast = conv(dilations = var_1008, groups = var_68, pad = input_161_pad_0, pad_type = input_161_pad_type_0, strides = var_1006, weight = sep_module_15_tcn_4_weight_to_fp16, x = input_159_cast)[name = tensor("input_161_cast")]; tensor var_1012_alpha_1_to_fp16 = const()[name = tensor("op_1012_alpha_1_to_fp16"), val = tensor(0x1.3ccp-1)]; tensor var_1012_cast = leaky_relu(alpha = var_1012_alpha_1_to_fp16, x = input_161_cast)[name = tensor("op_1012_cast")]; tensor var_1016 = const()[name = tensor("op_1016"), val = tensor([1])]; tensor mean_y_65_cast = reduce_mean(axes = var_1016, keep_dims = var_71, x = var_1012_cast)[name = tensor("mean_y_65_cast")]; tensor var_1018_cast = sub(x = var_1012_cast, y = mean_y_65_cast)[name = tensor("op_1018_cast")]; tensor var_1019_cast = square(x = var_1018_cast); tensor var_1020 = const()[name = tensor("op_1020"), val = tensor([1])]; tensor var_1021_cast = reduce_mean(axes = var_1020, keep_dims = var_71, x = var_1019_cast)[name = tensor("op_1021_cast")]; tensor var_1022_to_fp16 = const()[name = tensor("op_1022_to_fp16"), val = tensor(0x1p-14)]; tensor var_1023_cast = add(x = var_1021_cast, y = var_1022_to_fp16)[name = tensor("op_1023_cast")]; tensor std_y_65_cast = sqrt(x = var_1023_cast)[name = tensor("std_y_65_cast")]; tensor sep_module_15_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_15_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2293568)))]; tensor var_1026_cast = mul(x = sep_module_15_tcn_6_norm_gamma_to_fp16, y = var_1018_cast)[name = tensor("op_1026_cast")]; tensor var_1027_cast = real_div(x = var_1026_cast, y = std_y_65_cast)[name = tensor("op_1027_cast")]; tensor sep_module_15_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_15_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2294400)))]; tensor y_32_cast = add(x = var_1027_cast, y = sep_module_15_tcn_6_norm_beta_to_fp16)[name = tensor("y_32_cast")]; tensor input_163_cast = add(x = input_153_cast, y = y_32_cast)[name = tensor("input_163_cast")]; tensor var_1038 = const()[name = tensor("op_1038"), val = tensor([1])]; tensor var_1040 = const()[name = tensor("op_1040"), val = tensor([1])]; tensor input_165_pad_type_0 = const()[name = tensor("input_165_pad_type_0"), val = tensor("custom")]; tensor input_165_pad_0 = const()[name = tensor("input_165_pad_0"), val = tensor([0, 0])]; tensor sep_module_16_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2295232))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2369024))), name = tensor("sep_module_16_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_165_cast = conv(dilations = var_1040, groups = var_67, pad = input_165_pad_0, pad_type = input_165_pad_type_0, strides = var_1038, weight = sep_module_16_tcn_0_weight_to_fp16_palettized, x = input_163_cast)[name = tensor("input_165_cast")]; tensor var_1044_alpha_1_to_fp16 = const()[name = tensor("op_1044_alpha_1_to_fp16"), val = tensor(-0x1.5d4p-2)]; tensor var_1044_cast = leaky_relu(alpha = var_1044_alpha_1_to_fp16, x = input_165_cast)[name = tensor("op_1044_cast")]; tensor var_1048 = const()[name = tensor("op_1048"), val = tensor([1])]; tensor mean_y_67_cast = reduce_mean(axes = var_1048, keep_dims = var_71, x = var_1044_cast)[name = tensor("mean_y_67_cast")]; tensor var_1050_cast = sub(x = var_1044_cast, y = mean_y_67_cast)[name = tensor("op_1050_cast")]; tensor var_1051_cast = square(x = var_1050_cast); tensor var_1052 = const()[name = tensor("op_1052"), val = tensor([1])]; tensor var_1053_cast = reduce_mean(axes = var_1052, keep_dims = var_71, x = var_1051_cast)[name = tensor("op_1053_cast")]; tensor var_1054_to_fp16 = const()[name = tensor("op_1054_to_fp16"), val = tensor(0x1p-14)]; tensor var_1055_cast = add(x = var_1053_cast, y = var_1054_to_fp16)[name = tensor("op_1055_cast")]; tensor std_y_67_cast = sqrt(x = var_1055_cast)[name = tensor("std_y_67_cast")]; tensor sep_module_16_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_16_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2369152)))]; tensor var_1058_cast = mul(x = sep_module_16_tcn_2_norm_gamma_to_fp16, y = var_1050_cast)[name = tensor("op_1058_cast")]; tensor var_1059_cast = real_div(x = var_1058_cast, y = std_y_67_cast)[name = tensor("op_1059_cast")]; tensor sep_module_16_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_16_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2369984)))]; tensor input_167_cast = add(x = var_1059_cast, y = sep_module_16_tcn_2_norm_beta_to_fp16)[name = tensor("input_167_cast")]; tensor input_169_pad_0 = const()[name = tensor("input_169_pad_0"), val = tensor([0, 0, 0, 0, 256, 0])]; tensor input_169_mode_0 = const()[name = tensor("input_169_mode_0"), val = tensor("constant")]; tensor input_169_constant_val_0_to_fp16 = const()[name = tensor("input_169_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_169_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_167_cast_in_state, input_167_cast)); tensor input_167_cast_out_state = slice_by_size(begin = tensor([0, 0, -256]), size = tensor([-1, 384, 256]), x = input_169_cast); tensor var_1064 = const()[name = tensor("op_1064"), val = tensor([1])]; tensor var_1066 = const()[name = tensor("op_1066"), val = tensor([128])]; tensor input_171_pad_type_0 = const()[name = tensor("input_171_pad_type_0"), val = tensor("custom")]; tensor input_171_pad_0 = const()[name = tensor("input_171_pad_0"), val = tensor([0, 0])]; tensor sep_module_16_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_16_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2370816)))]; tensor input_171_cast = conv(dilations = var_1066, groups = var_68, pad = input_171_pad_0, pad_type = input_171_pad_type_0, strides = var_1064, weight = sep_module_16_tcn_4_weight_to_fp16, x = input_169_cast)[name = tensor("input_171_cast")]; tensor var_1070_alpha_1_to_fp16 = const()[name = tensor("op_1070_alpha_1_to_fp16"), val = tensor(0x1.b5cp-1)]; tensor var_1070_cast = leaky_relu(alpha = var_1070_alpha_1_to_fp16, x = input_171_cast)[name = tensor("op_1070_cast")]; tensor var_1074 = const()[name = tensor("op_1074"), val = tensor([1])]; tensor mean_y_69_cast = reduce_mean(axes = var_1074, keep_dims = var_71, x = var_1070_cast)[name = tensor("mean_y_69_cast")]; tensor var_1076_cast = sub(x = var_1070_cast, y = mean_y_69_cast)[name = tensor("op_1076_cast")]; tensor var_1077_cast = square(x = var_1076_cast); tensor var_1078 = const()[name = tensor("op_1078"), val = tensor([1])]; tensor var_1079_cast = reduce_mean(axes = var_1078, keep_dims = var_71, x = var_1077_cast)[name = tensor("op_1079_cast")]; tensor var_1080_to_fp16 = const()[name = tensor("op_1080_to_fp16"), val = tensor(0x1p-14)]; tensor var_1081_cast = add(x = var_1079_cast, y = var_1080_to_fp16)[name = tensor("op_1081_cast")]; tensor std_y_69_cast = sqrt(x = var_1081_cast)[name = tensor("std_y_69_cast")]; tensor sep_module_16_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_16_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2373184)))]; tensor var_1084_cast = mul(x = sep_module_16_tcn_6_norm_gamma_to_fp16, y = var_1076_cast)[name = tensor("op_1084_cast")]; tensor var_1085_cast = real_div(x = var_1084_cast, y = std_y_69_cast)[name = tensor("op_1085_cast")]; tensor sep_module_16_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_16_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2374016)))]; tensor y_34_cast = add(x = var_1085_cast, y = sep_module_16_tcn_6_norm_beta_to_fp16)[name = tensor("y_34_cast")]; tensor input_173_cast = add(x = input_163_cast, y = y_34_cast)[name = tensor("input_173_cast")]; tensor var_1096 = const()[name = tensor("op_1096"), val = tensor([1])]; tensor var_1098 = const()[name = tensor("op_1098"), val = tensor([1])]; tensor input_175_pad_type_0 = const()[name = tensor("input_175_pad_type_0"), val = tensor("custom")]; tensor input_175_pad_0 = const()[name = tensor("input_175_pad_0"), val = tensor([0, 0])]; tensor sep_module_17_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2374848))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2448640))), name = tensor("sep_module_17_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_175_cast = conv(dilations = var_1098, groups = var_67, pad = input_175_pad_0, pad_type = input_175_pad_type_0, strides = var_1096, weight = sep_module_17_tcn_0_weight_to_fp16_palettized, x = input_173_cast)[name = tensor("input_175_cast")]; tensor var_1102_alpha_1_to_fp16 = const()[name = tensor("op_1102_alpha_1_to_fp16"), val = tensor(-0x1.ad8p-2)]; tensor var_1102_cast = leaky_relu(alpha = var_1102_alpha_1_to_fp16, x = input_175_cast)[name = tensor("op_1102_cast")]; tensor var_1106 = const()[name = tensor("op_1106"), val = tensor([1])]; tensor mean_y_71_cast = reduce_mean(axes = var_1106, keep_dims = var_71, x = var_1102_cast)[name = tensor("mean_y_71_cast")]; tensor var_1108_cast = sub(x = var_1102_cast, y = mean_y_71_cast)[name = tensor("op_1108_cast")]; tensor var_1109_cast = square(x = var_1108_cast); tensor var_1110 = const()[name = tensor("op_1110"), val = tensor([1])]; tensor var_1111_cast = reduce_mean(axes = var_1110, keep_dims = var_71, x = var_1109_cast)[name = tensor("op_1111_cast")]; tensor var_1112_to_fp16 = const()[name = tensor("op_1112_to_fp16"), val = tensor(0x1p-14)]; tensor var_1113_cast = add(x = var_1111_cast, y = var_1112_to_fp16)[name = tensor("op_1113_cast")]; tensor std_y_71_cast = sqrt(x = var_1113_cast)[name = tensor("std_y_71_cast")]; tensor sep_module_17_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_17_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2448768)))]; tensor var_1116_cast = mul(x = sep_module_17_tcn_2_norm_gamma_to_fp16, y = var_1108_cast)[name = tensor("op_1116_cast")]; tensor var_1117_cast = real_div(x = var_1116_cast, y = std_y_71_cast)[name = tensor("op_1117_cast")]; tensor sep_module_17_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_17_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2449600)))]; tensor input_177_cast = add(x = var_1117_cast, y = sep_module_17_tcn_2_norm_beta_to_fp16)[name = tensor("input_177_cast")]; tensor input_179_pad_0 = const()[name = tensor("input_179_pad_0"), val = tensor([0, 0, 0, 0, 512, 0])]; tensor input_179_mode_0 = const()[name = tensor("input_179_mode_0"), val = tensor("constant")]; tensor input_179_constant_val_0_to_fp16 = const()[name = tensor("input_179_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_179_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_177_cast_in_state, input_177_cast)); tensor input_177_cast_out_state = slice_by_size(begin = tensor([0, 0, -512]), size = tensor([-1, 384, 512]), x = input_179_cast); tensor var_1122 = const()[name = tensor("op_1122"), val = tensor([1])]; tensor var_1124 = const()[name = tensor("op_1124"), val = tensor([256])]; tensor input_181_pad_type_0 = const()[name = tensor("input_181_pad_type_0"), val = tensor("custom")]; tensor input_181_pad_0 = const()[name = tensor("input_181_pad_0"), val = tensor([0, 0])]; tensor sep_module_17_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_17_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2450432)))]; tensor input_181_cast = conv(dilations = var_1124, groups = var_68, pad = input_181_pad_0, pad_type = input_181_pad_type_0, strides = var_1122, weight = sep_module_17_tcn_4_weight_to_fp16, x = input_179_cast)[name = tensor("input_181_cast")]; tensor var_1128_alpha_1_to_fp16 = const()[name = tensor("op_1128_alpha_1_to_fp16"), val = tensor(0x1.e84p-3)]; tensor var_1128_cast = leaky_relu(alpha = var_1128_alpha_1_to_fp16, x = input_181_cast)[name = tensor("op_1128_cast")]; tensor var_1132 = const()[name = tensor("op_1132"), val = tensor([1])]; tensor mean_y_73_cast = reduce_mean(axes = var_1132, keep_dims = var_71, x = var_1128_cast)[name = tensor("mean_y_73_cast")]; tensor var_1134_cast = sub(x = var_1128_cast, y = mean_y_73_cast)[name = tensor("op_1134_cast")]; tensor var_1135_cast = square(x = var_1134_cast); tensor var_1136 = const()[name = tensor("op_1136"), val = tensor([1])]; tensor var_1137_cast = reduce_mean(axes = var_1136, keep_dims = var_71, x = var_1135_cast)[name = tensor("op_1137_cast")]; tensor var_1138_to_fp16 = const()[name = tensor("op_1138_to_fp16"), val = tensor(0x1p-14)]; tensor var_1139_cast = add(x = var_1137_cast, y = var_1138_to_fp16)[name = tensor("op_1139_cast")]; tensor std_y_73_cast = sqrt(x = var_1139_cast)[name = tensor("std_y_73_cast")]; tensor sep_module_17_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_17_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2452800)))]; tensor var_1142_cast = mul(x = sep_module_17_tcn_6_norm_gamma_to_fp16, y = var_1134_cast)[name = tensor("op_1142_cast")]; tensor var_1143_cast = real_div(x = var_1142_cast, y = std_y_73_cast)[name = tensor("op_1143_cast")]; tensor sep_module_17_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_17_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2453632)))]; tensor y_36_cast = add(x = var_1143_cast, y = sep_module_17_tcn_6_norm_beta_to_fp16)[name = tensor("y_36_cast")]; tensor input_183_cast = add(x = input_173_cast, y = y_36_cast)[name = tensor("input_183_cast")]; tensor var_1154 = const()[name = tensor("op_1154"), val = tensor([1])]; tensor var_1156 = const()[name = tensor("op_1156"), val = tensor([1])]; tensor input_185_pad_type_0 = const()[name = tensor("input_185_pad_type_0"), val = tensor("custom")]; tensor input_185_pad_0 = const()[name = tensor("input_185_pad_0"), val = tensor([0, 0])]; tensor sep_module_18_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2454464))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2528256))), name = tensor("sep_module_18_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_185_cast = conv(dilations = var_1156, groups = var_67, pad = input_185_pad_0, pad_type = input_185_pad_type_0, strides = var_1154, weight = sep_module_18_tcn_0_weight_to_fp16_palettized, x = input_183_cast)[name = tensor("input_185_cast")]; tensor var_1160_alpha_1_to_fp16 = const()[name = tensor("op_1160_alpha_1_to_fp16"), val = tensor(-0x1.038p-1)]; tensor var_1160_cast = leaky_relu(alpha = var_1160_alpha_1_to_fp16, x = input_185_cast)[name = tensor("op_1160_cast")]; tensor var_1164 = const()[name = tensor("op_1164"), val = tensor([1])]; tensor mean_y_75_cast = reduce_mean(axes = var_1164, keep_dims = var_71, x = var_1160_cast)[name = tensor("mean_y_75_cast")]; tensor var_1166_cast = sub(x = var_1160_cast, y = mean_y_75_cast)[name = tensor("op_1166_cast")]; tensor var_1167_cast = square(x = var_1166_cast); tensor var_1168 = const()[name = tensor("op_1168"), val = tensor([1])]; tensor var_1169_cast = reduce_mean(axes = var_1168, keep_dims = var_71, x = var_1167_cast)[name = tensor("op_1169_cast")]; tensor var_1170_to_fp16 = const()[name = tensor("op_1170_to_fp16"), val = tensor(0x1p-14)]; tensor var_1171_cast = add(x = var_1169_cast, y = var_1170_to_fp16)[name = tensor("op_1171_cast")]; tensor std_y_75_cast = sqrt(x = var_1171_cast)[name = tensor("std_y_75_cast")]; tensor sep_module_18_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_18_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2528384)))]; tensor var_1174_cast = mul(x = sep_module_18_tcn_2_norm_gamma_to_fp16, y = var_1166_cast)[name = tensor("op_1174_cast")]; tensor var_1175_cast = real_div(x = var_1174_cast, y = std_y_75_cast)[name = tensor("op_1175_cast")]; tensor sep_module_18_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_18_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2529216)))]; tensor input_187_cast = add(x = var_1175_cast, y = sep_module_18_tcn_2_norm_beta_to_fp16)[name = tensor("input_187_cast")]; tensor input_189_pad_0 = const()[name = tensor("input_189_pad_0"), val = tensor([0, 0, 0, 0, 2, 0])]; tensor input_189_mode_0 = const()[name = tensor("input_189_mode_0"), val = tensor("constant")]; tensor input_189_constant_val_0_to_fp16 = const()[name = tensor("input_189_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_189_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_187_cast_in_state, input_187_cast)); tensor input_187_cast_out_state = slice_by_size(begin = tensor([0, 0, -2]), size = tensor([-1, 384, 2]), x = input_189_cast); tensor var_1180 = const()[name = tensor("op_1180"), val = tensor([1])]; tensor var_1182 = const()[name = tensor("op_1182"), val = tensor([1])]; tensor input_191_pad_type_0 = const()[name = tensor("input_191_pad_type_0"), val = tensor("custom")]; tensor input_191_pad_0 = const()[name = tensor("input_191_pad_0"), val = tensor([0, 0])]; tensor sep_module_18_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_18_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2530048)))]; tensor input_191_cast = conv(dilations = var_1182, groups = var_68, pad = input_191_pad_0, pad_type = input_191_pad_type_0, strides = var_1180, weight = sep_module_18_tcn_4_weight_to_fp16, x = input_189_cast)[name = tensor("input_191_cast")]; tensor var_1186_alpha_1_to_fp16 = const()[name = tensor("op_1186_alpha_1_to_fp16"), val = tensor(0x1.ebcp-1)]; tensor var_1186_cast = leaky_relu(alpha = var_1186_alpha_1_to_fp16, x = input_191_cast)[name = tensor("op_1186_cast")]; tensor var_1190 = const()[name = tensor("op_1190"), val = tensor([1])]; tensor mean_y_77_cast = reduce_mean(axes = var_1190, keep_dims = var_71, x = var_1186_cast)[name = tensor("mean_y_77_cast")]; tensor var_1192_cast = sub(x = var_1186_cast, y = mean_y_77_cast)[name = tensor("op_1192_cast")]; tensor var_1193_cast = square(x = var_1192_cast); tensor var_1194 = const()[name = tensor("op_1194"), val = tensor([1])]; tensor var_1195_cast = reduce_mean(axes = var_1194, keep_dims = var_71, x = var_1193_cast)[name = tensor("op_1195_cast")]; tensor var_1196_to_fp16 = const()[name = tensor("op_1196_to_fp16"), val = tensor(0x1p-14)]; tensor var_1197_cast = add(x = var_1195_cast, y = var_1196_to_fp16)[name = tensor("op_1197_cast")]; tensor std_y_77_cast = sqrt(x = var_1197_cast)[name = tensor("std_y_77_cast")]; tensor sep_module_18_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_18_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2532416)))]; tensor var_1200_cast = mul(x = sep_module_18_tcn_6_norm_gamma_to_fp16, y = var_1192_cast)[name = tensor("op_1200_cast")]; tensor var_1201_cast = real_div(x = var_1200_cast, y = std_y_77_cast)[name = tensor("op_1201_cast")]; tensor sep_module_18_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_18_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2533248)))]; tensor y_38_cast = add(x = var_1201_cast, y = sep_module_18_tcn_6_norm_beta_to_fp16)[name = tensor("y_38_cast")]; tensor input_193_cast = add(x = input_183_cast, y = y_38_cast)[name = tensor("input_193_cast")]; tensor var_1212 = const()[name = tensor("op_1212"), val = tensor([1])]; tensor var_1214 = const()[name = tensor("op_1214"), val = tensor([1])]; tensor input_195_pad_type_0 = const()[name = tensor("input_195_pad_type_0"), val = tensor("custom")]; tensor input_195_pad_0 = const()[name = tensor("input_195_pad_0"), val = tensor([0, 0])]; tensor sep_module_19_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2534080))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2607872))), name = tensor("sep_module_19_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_195_cast = conv(dilations = var_1214, groups = var_67, pad = input_195_pad_0, pad_type = input_195_pad_type_0, strides = var_1212, weight = sep_module_19_tcn_0_weight_to_fp16_palettized, x = input_193_cast)[name = tensor("input_195_cast")]; tensor var_1218_alpha_1_to_fp16 = const()[name = tensor("op_1218_alpha_1_to_fp16"), val = tensor(-0x1.bfp-2)]; tensor var_1218_cast = leaky_relu(alpha = var_1218_alpha_1_to_fp16, x = input_195_cast)[name = tensor("op_1218_cast")]; tensor var_1222 = const()[name = tensor("op_1222"), val = tensor([1])]; tensor mean_y_79_cast = reduce_mean(axes = var_1222, keep_dims = var_71, x = var_1218_cast)[name = tensor("mean_y_79_cast")]; tensor var_1224_cast = sub(x = var_1218_cast, y = mean_y_79_cast)[name = tensor("op_1224_cast")]; tensor var_1225_cast = square(x = var_1224_cast); tensor var_1226 = const()[name = tensor("op_1226"), val = tensor([1])]; tensor var_1227_cast = reduce_mean(axes = var_1226, keep_dims = var_71, x = var_1225_cast)[name = tensor("op_1227_cast")]; tensor var_1228_to_fp16 = const()[name = tensor("op_1228_to_fp16"), val = tensor(0x1p-14)]; tensor var_1229_cast = add(x = var_1227_cast, y = var_1228_to_fp16)[name = tensor("op_1229_cast")]; tensor std_y_79_cast = sqrt(x = var_1229_cast)[name = tensor("std_y_79_cast")]; tensor sep_module_19_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_19_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2608000)))]; tensor var_1232_cast = mul(x = sep_module_19_tcn_2_norm_gamma_to_fp16, y = var_1224_cast)[name = tensor("op_1232_cast")]; tensor var_1233_cast = real_div(x = var_1232_cast, y = std_y_79_cast)[name = tensor("op_1233_cast")]; tensor sep_module_19_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_19_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2608832)))]; tensor input_197_cast = add(x = var_1233_cast, y = sep_module_19_tcn_2_norm_beta_to_fp16)[name = tensor("input_197_cast")]; tensor input_199_pad_0 = const()[name = tensor("input_199_pad_0"), val = tensor([0, 0, 0, 0, 4, 0])]; tensor input_199_mode_0 = const()[name = tensor("input_199_mode_0"), val = tensor("constant")]; tensor input_199_constant_val_0_to_fp16 = const()[name = tensor("input_199_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_199_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_197_cast_in_state, input_197_cast)); tensor input_197_cast_out_state = slice_by_size(begin = tensor([0, 0, -4]), size = tensor([-1, 384, 4]), x = input_199_cast); tensor var_1238 = const()[name = tensor("op_1238"), val = tensor([1])]; tensor var_1240 = const()[name = tensor("op_1240"), val = tensor([2])]; tensor input_201_pad_type_0 = const()[name = tensor("input_201_pad_type_0"), val = tensor("custom")]; tensor input_201_pad_0 = const()[name = tensor("input_201_pad_0"), val = tensor([0, 0])]; tensor sep_module_19_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_19_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2609664)))]; tensor input_201_cast = conv(dilations = var_1240, groups = var_68, pad = input_201_pad_0, pad_type = input_201_pad_type_0, strides = var_1238, weight = sep_module_19_tcn_4_weight_to_fp16, x = input_199_cast)[name = tensor("input_201_cast")]; tensor var_1244_alpha_1_to_fp16 = const()[name = tensor("op_1244_alpha_1_to_fp16"), val = tensor(0x1.f88p-1)]; tensor var_1244_cast = leaky_relu(alpha = var_1244_alpha_1_to_fp16, x = input_201_cast)[name = tensor("op_1244_cast")]; tensor var_1248 = const()[name = tensor("op_1248"), val = tensor([1])]; tensor mean_y_81_cast = reduce_mean(axes = var_1248, keep_dims = var_71, x = var_1244_cast)[name = tensor("mean_y_81_cast")]; tensor var_1250_cast = sub(x = var_1244_cast, y = mean_y_81_cast)[name = tensor("op_1250_cast")]; tensor var_1251_cast = square(x = var_1250_cast); tensor var_1252 = const()[name = tensor("op_1252"), val = tensor([1])]; tensor var_1253_cast = reduce_mean(axes = var_1252, keep_dims = var_71, x = var_1251_cast)[name = tensor("op_1253_cast")]; tensor var_1254_to_fp16 = const()[name = tensor("op_1254_to_fp16"), val = tensor(0x1p-14)]; tensor var_1255_cast = add(x = var_1253_cast, y = var_1254_to_fp16)[name = tensor("op_1255_cast")]; tensor std_y_81_cast = sqrt(x = var_1255_cast)[name = tensor("std_y_81_cast")]; tensor sep_module_19_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_19_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2612032)))]; tensor var_1258_cast = mul(x = sep_module_19_tcn_6_norm_gamma_to_fp16, y = var_1250_cast)[name = tensor("op_1258_cast")]; tensor var_1259_cast = real_div(x = var_1258_cast, y = std_y_81_cast)[name = tensor("op_1259_cast")]; tensor sep_module_19_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_19_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2612864)))]; tensor y_40_cast = add(x = var_1259_cast, y = sep_module_19_tcn_6_norm_beta_to_fp16)[name = tensor("y_40_cast")]; tensor input_203_cast = add(x = input_193_cast, y = y_40_cast)[name = tensor("input_203_cast")]; tensor var_1270 = const()[name = tensor("op_1270"), val = tensor([1])]; tensor var_1272 = const()[name = tensor("op_1272"), val = tensor([1])]; tensor input_205_pad_type_0 = const()[name = tensor("input_205_pad_type_0"), val = tensor("custom")]; tensor input_205_pad_0 = const()[name = tensor("input_205_pad_0"), val = tensor([0, 0])]; tensor sep_module_20_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2613696))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2687488))), name = tensor("sep_module_20_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_205_cast = conv(dilations = var_1272, groups = var_67, pad = input_205_pad_0, pad_type = input_205_pad_type_0, strides = var_1270, weight = sep_module_20_tcn_0_weight_to_fp16_palettized, x = input_203_cast)[name = tensor("input_205_cast")]; tensor var_1276_alpha_1_to_fp16 = const()[name = tensor("op_1276_alpha_1_to_fp16"), val = tensor(-0x1.fdcp-2)]; tensor var_1276_cast = leaky_relu(alpha = var_1276_alpha_1_to_fp16, x = input_205_cast)[name = tensor("op_1276_cast")]; tensor var_1280 = const()[name = tensor("op_1280"), val = tensor([1])]; tensor mean_y_83_cast = reduce_mean(axes = var_1280, keep_dims = var_71, x = var_1276_cast)[name = tensor("mean_y_83_cast")]; tensor var_1282_cast = sub(x = var_1276_cast, y = mean_y_83_cast)[name = tensor("op_1282_cast")]; tensor var_1283_cast = square(x = var_1282_cast); tensor var_1284 = const()[name = tensor("op_1284"), val = tensor([1])]; tensor var_1285_cast = reduce_mean(axes = var_1284, keep_dims = var_71, x = var_1283_cast)[name = tensor("op_1285_cast")]; tensor var_1286_to_fp16 = const()[name = tensor("op_1286_to_fp16"), val = tensor(0x1p-14)]; tensor var_1287_cast = add(x = var_1285_cast, y = var_1286_to_fp16)[name = tensor("op_1287_cast")]; tensor std_y_83_cast = sqrt(x = var_1287_cast)[name = tensor("std_y_83_cast")]; tensor sep_module_20_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_20_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2687616)))]; tensor var_1290_cast = mul(x = sep_module_20_tcn_2_norm_gamma_to_fp16, y = var_1282_cast)[name = tensor("op_1290_cast")]; tensor var_1291_cast = real_div(x = var_1290_cast, y = std_y_83_cast)[name = tensor("op_1291_cast")]; tensor sep_module_20_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_20_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2688448)))]; tensor input_207_cast = add(x = var_1291_cast, y = sep_module_20_tcn_2_norm_beta_to_fp16)[name = tensor("input_207_cast")]; tensor input_209_pad_0 = const()[name = tensor("input_209_pad_0"), val = tensor([0, 0, 0, 0, 8, 0])]; tensor input_209_mode_0 = const()[name = tensor("input_209_mode_0"), val = tensor("constant")]; tensor input_209_constant_val_0_to_fp16 = const()[name = tensor("input_209_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_209_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_207_cast_in_state, input_207_cast)); tensor input_207_cast_out_state = slice_by_size(begin = tensor([0, 0, -8]), size = tensor([-1, 384, 8]), x = input_209_cast); tensor var_1296 = const()[name = tensor("op_1296"), val = tensor([1])]; tensor var_1298 = const()[name = tensor("op_1298"), val = tensor([4])]; tensor input_211_pad_type_0 = const()[name = tensor("input_211_pad_type_0"), val = tensor("custom")]; tensor input_211_pad_0 = const()[name = tensor("input_211_pad_0"), val = tensor([0, 0])]; tensor sep_module_20_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_20_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2689280)))]; tensor input_211_cast = conv(dilations = var_1298, groups = var_68, pad = input_211_pad_0, pad_type = input_211_pad_type_0, strides = var_1296, weight = sep_module_20_tcn_4_weight_to_fp16, x = input_209_cast)[name = tensor("input_211_cast")]; tensor var_1302_alpha_1_to_fp16 = const()[name = tensor("op_1302_alpha_1_to_fp16"), val = tensor(0x1.fa4p-1)]; tensor var_1302_cast = leaky_relu(alpha = var_1302_alpha_1_to_fp16, x = input_211_cast)[name = tensor("op_1302_cast")]; tensor var_1306 = const()[name = tensor("op_1306"), val = tensor([1])]; tensor mean_y_85_cast = reduce_mean(axes = var_1306, keep_dims = var_71, x = var_1302_cast)[name = tensor("mean_y_85_cast")]; tensor var_1308_cast = sub(x = var_1302_cast, y = mean_y_85_cast)[name = tensor("op_1308_cast")]; tensor var_1309_cast = square(x = var_1308_cast); tensor var_1310 = const()[name = tensor("op_1310"), val = tensor([1])]; tensor var_1311_cast = reduce_mean(axes = var_1310, keep_dims = var_71, x = var_1309_cast)[name = tensor("op_1311_cast")]; tensor var_1312_to_fp16 = const()[name = tensor("op_1312_to_fp16"), val = tensor(0x1p-14)]; tensor var_1313_cast = add(x = var_1311_cast, y = var_1312_to_fp16)[name = tensor("op_1313_cast")]; tensor std_y_85_cast = sqrt(x = var_1313_cast)[name = tensor("std_y_85_cast")]; tensor sep_module_20_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_20_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2691648)))]; tensor var_1316_cast = mul(x = sep_module_20_tcn_6_norm_gamma_to_fp16, y = var_1308_cast)[name = tensor("op_1316_cast")]; tensor var_1317_cast = real_div(x = var_1316_cast, y = std_y_85_cast)[name = tensor("op_1317_cast")]; tensor sep_module_20_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_20_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2692480)))]; tensor y_42_cast = add(x = var_1317_cast, y = sep_module_20_tcn_6_norm_beta_to_fp16)[name = tensor("y_42_cast")]; tensor input_213_cast = add(x = input_203_cast, y = y_42_cast)[name = tensor("input_213_cast")]; tensor var_1328 = const()[name = tensor("op_1328"), val = tensor([1])]; tensor var_1330 = const()[name = tensor("op_1330"), val = tensor([1])]; tensor input_215_pad_type_0 = const()[name = tensor("input_215_pad_type_0"), val = tensor("custom")]; tensor input_215_pad_0 = const()[name = tensor("input_215_pad_0"), val = tensor([0, 0])]; tensor sep_module_21_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2693312))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2767104))), name = tensor("sep_module_21_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_215_cast = conv(dilations = var_1330, groups = var_67, pad = input_215_pad_0, pad_type = input_215_pad_type_0, strides = var_1328, weight = sep_module_21_tcn_0_weight_to_fp16_palettized, x = input_213_cast)[name = tensor("input_215_cast")]; tensor var_1334_alpha_1_to_fp16 = const()[name = tensor("op_1334_alpha_1_to_fp16"), val = tensor(-0x1.eacp-2)]; tensor var_1334_cast = leaky_relu(alpha = var_1334_alpha_1_to_fp16, x = input_215_cast)[name = tensor("op_1334_cast")]; tensor var_1338 = const()[name = tensor("op_1338"), val = tensor([1])]; tensor mean_y_87_cast = reduce_mean(axes = var_1338, keep_dims = var_71, x = var_1334_cast)[name = tensor("mean_y_87_cast")]; tensor var_1340_cast = sub(x = var_1334_cast, y = mean_y_87_cast)[name = tensor("op_1340_cast")]; tensor var_1341_cast = square(x = var_1340_cast); tensor var_1342 = const()[name = tensor("op_1342"), val = tensor([1])]; tensor var_1343_cast = reduce_mean(axes = var_1342, keep_dims = var_71, x = var_1341_cast)[name = tensor("op_1343_cast")]; tensor var_1344_to_fp16 = const()[name = tensor("op_1344_to_fp16"), val = tensor(0x1p-14)]; tensor var_1345_cast = add(x = var_1343_cast, y = var_1344_to_fp16)[name = tensor("op_1345_cast")]; tensor std_y_87_cast = sqrt(x = var_1345_cast)[name = tensor("std_y_87_cast")]; tensor sep_module_21_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_21_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2767232)))]; tensor var_1348_cast = mul(x = sep_module_21_tcn_2_norm_gamma_to_fp16, y = var_1340_cast)[name = tensor("op_1348_cast")]; tensor var_1349_cast = real_div(x = var_1348_cast, y = std_y_87_cast)[name = tensor("op_1349_cast")]; tensor sep_module_21_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_21_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2768064)))]; tensor input_217_cast = add(x = var_1349_cast, y = sep_module_21_tcn_2_norm_beta_to_fp16)[name = tensor("input_217_cast")]; tensor input_219_pad_0 = const()[name = tensor("input_219_pad_0"), val = tensor([0, 0, 0, 0, 16, 0])]; tensor input_219_mode_0 = const()[name = tensor("input_219_mode_0"), val = tensor("constant")]; tensor input_219_constant_val_0_to_fp16 = const()[name = tensor("input_219_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_219_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_217_cast_in_state, input_217_cast)); tensor input_217_cast_out_state = slice_by_size(begin = tensor([0, 0, -16]), size = tensor([-1, 384, 16]), x = input_219_cast); tensor var_1354 = const()[name = tensor("op_1354"), val = tensor([1])]; tensor var_1356 = const()[name = tensor("op_1356"), val = tensor([8])]; tensor input_221_pad_type_0 = const()[name = tensor("input_221_pad_type_0"), val = tensor("custom")]; tensor input_221_pad_0 = const()[name = tensor("input_221_pad_0"), val = tensor([0, 0])]; tensor sep_module_21_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_21_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2768896)))]; tensor input_221_cast = conv(dilations = var_1356, groups = var_68, pad = input_221_pad_0, pad_type = input_221_pad_type_0, strides = var_1354, weight = sep_module_21_tcn_4_weight_to_fp16, x = input_219_cast)[name = tensor("input_221_cast")]; tensor var_1360_alpha_1_to_fp16 = const()[name = tensor("op_1360_alpha_1_to_fp16"), val = tensor(0x1.ec4p-1)]; tensor var_1360_cast = leaky_relu(alpha = var_1360_alpha_1_to_fp16, x = input_221_cast)[name = tensor("op_1360_cast")]; tensor var_1364 = const()[name = tensor("op_1364"), val = tensor([1])]; tensor mean_y_89_cast = reduce_mean(axes = var_1364, keep_dims = var_71, x = var_1360_cast)[name = tensor("mean_y_89_cast")]; tensor var_1366_cast = sub(x = var_1360_cast, y = mean_y_89_cast)[name = tensor("op_1366_cast")]; tensor var_1367_cast = square(x = var_1366_cast); tensor var_1368 = const()[name = tensor("op_1368"), val = tensor([1])]; tensor var_1369_cast = reduce_mean(axes = var_1368, keep_dims = var_71, x = var_1367_cast)[name = tensor("op_1369_cast")]; tensor var_1370_to_fp16 = const()[name = tensor("op_1370_to_fp16"), val = tensor(0x1p-14)]; tensor var_1371_cast = add(x = var_1369_cast, y = var_1370_to_fp16)[name = tensor("op_1371_cast")]; tensor std_y_89_cast = sqrt(x = var_1371_cast)[name = tensor("std_y_89_cast")]; tensor sep_module_21_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_21_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2771264)))]; tensor var_1374_cast = mul(x = sep_module_21_tcn_6_norm_gamma_to_fp16, y = var_1366_cast)[name = tensor("op_1374_cast")]; tensor var_1375_cast = real_div(x = var_1374_cast, y = std_y_89_cast)[name = tensor("op_1375_cast")]; tensor sep_module_21_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_21_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2772096)))]; tensor y_44_cast = add(x = var_1375_cast, y = sep_module_21_tcn_6_norm_beta_to_fp16)[name = tensor("y_44_cast")]; tensor input_223_cast = add(x = input_213_cast, y = y_44_cast)[name = tensor("input_223_cast")]; tensor var_1386 = const()[name = tensor("op_1386"), val = tensor([1])]; tensor var_1388 = const()[name = tensor("op_1388"), val = tensor([1])]; tensor input_225_pad_type_0 = const()[name = tensor("input_225_pad_type_0"), val = tensor("custom")]; tensor input_225_pad_0 = const()[name = tensor("input_225_pad_0"), val = tensor([0, 0])]; tensor sep_module_22_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2772928))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2846720))), name = tensor("sep_module_22_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_225_cast = conv(dilations = var_1388, groups = var_67, pad = input_225_pad_0, pad_type = input_225_pad_type_0, strides = var_1386, weight = sep_module_22_tcn_0_weight_to_fp16_palettized, x = input_223_cast)[name = tensor("input_225_cast")]; tensor var_1392_alpha_1_to_fp16 = const()[name = tensor("op_1392_alpha_1_to_fp16"), val = tensor(-0x1.35p-1)]; tensor var_1392_cast = leaky_relu(alpha = var_1392_alpha_1_to_fp16, x = input_225_cast)[name = tensor("op_1392_cast")]; tensor var_1396 = const()[name = tensor("op_1396"), val = tensor([1])]; tensor mean_y_91_cast = reduce_mean(axes = var_1396, keep_dims = var_71, x = var_1392_cast)[name = tensor("mean_y_91_cast")]; tensor var_1398_cast = sub(x = var_1392_cast, y = mean_y_91_cast)[name = tensor("op_1398_cast")]; tensor var_1399_cast = square(x = var_1398_cast); tensor var_1400 = const()[name = tensor("op_1400"), val = tensor([1])]; tensor var_1401_cast = reduce_mean(axes = var_1400, keep_dims = var_71, x = var_1399_cast)[name = tensor("op_1401_cast")]; tensor var_1402_to_fp16 = const()[name = tensor("op_1402_to_fp16"), val = tensor(0x1p-14)]; tensor var_1403_cast = add(x = var_1401_cast, y = var_1402_to_fp16)[name = tensor("op_1403_cast")]; tensor std_y_91_cast = sqrt(x = var_1403_cast)[name = tensor("std_y_91_cast")]; tensor sep_module_22_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_22_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2846848)))]; tensor var_1406_cast = mul(x = sep_module_22_tcn_2_norm_gamma_to_fp16, y = var_1398_cast)[name = tensor("op_1406_cast")]; tensor var_1407_cast = real_div(x = var_1406_cast, y = std_y_91_cast)[name = tensor("op_1407_cast")]; tensor sep_module_22_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_22_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2847680)))]; tensor input_227_cast = add(x = var_1407_cast, y = sep_module_22_tcn_2_norm_beta_to_fp16)[name = tensor("input_227_cast")]; tensor input_229_pad_0 = const()[name = tensor("input_229_pad_0"), val = tensor([0, 0, 0, 0, 32, 0])]; tensor input_229_mode_0 = const()[name = tensor("input_229_mode_0"), val = tensor("constant")]; tensor input_229_constant_val_0_to_fp16 = const()[name = tensor("input_229_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_229_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_227_cast_in_state, input_227_cast)); tensor input_227_cast_out_state = slice_by_size(begin = tensor([0, 0, -32]), size = tensor([-1, 384, 32]), x = input_229_cast); tensor var_1412 = const()[name = tensor("op_1412"), val = tensor([1])]; tensor var_1414 = const()[name = tensor("op_1414"), val = tensor([16])]; tensor input_231_pad_type_0 = const()[name = tensor("input_231_pad_type_0"), val = tensor("custom")]; tensor input_231_pad_0 = const()[name = tensor("input_231_pad_0"), val = tensor([0, 0])]; tensor sep_module_22_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_22_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2848512)))]; tensor input_231_cast = conv(dilations = var_1414, groups = var_68, pad = input_231_pad_0, pad_type = input_231_pad_type_0, strides = var_1412, weight = sep_module_22_tcn_4_weight_to_fp16, x = input_229_cast)[name = tensor("input_231_cast")]; tensor var_1418_alpha_1_to_fp16 = const()[name = tensor("op_1418_alpha_1_to_fp16"), val = tensor(0x1.cfp-1)]; tensor var_1418_cast = leaky_relu(alpha = var_1418_alpha_1_to_fp16, x = input_231_cast)[name = tensor("op_1418_cast")]; tensor var_1422 = const()[name = tensor("op_1422"), val = tensor([1])]; tensor mean_y_93_cast = reduce_mean(axes = var_1422, keep_dims = var_71, x = var_1418_cast)[name = tensor("mean_y_93_cast")]; tensor var_1424_cast = sub(x = var_1418_cast, y = mean_y_93_cast)[name = tensor("op_1424_cast")]; tensor var_1425_cast = square(x = var_1424_cast); tensor var_1426 = const()[name = tensor("op_1426"), val = tensor([1])]; tensor var_1427_cast = reduce_mean(axes = var_1426, keep_dims = var_71, x = var_1425_cast)[name = tensor("op_1427_cast")]; tensor var_1428_to_fp16 = const()[name = tensor("op_1428_to_fp16"), val = tensor(0x1p-14)]; tensor var_1429_cast = add(x = var_1427_cast, y = var_1428_to_fp16)[name = tensor("op_1429_cast")]; tensor std_y_93_cast = sqrt(x = var_1429_cast)[name = tensor("std_y_93_cast")]; tensor sep_module_22_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_22_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2850880)))]; tensor var_1432_cast = mul(x = sep_module_22_tcn_6_norm_gamma_to_fp16, y = var_1424_cast)[name = tensor("op_1432_cast")]; tensor var_1433_cast = real_div(x = var_1432_cast, y = std_y_93_cast)[name = tensor("op_1433_cast")]; tensor sep_module_22_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_22_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2851712)))]; tensor y_46_cast = add(x = var_1433_cast, y = sep_module_22_tcn_6_norm_beta_to_fp16)[name = tensor("y_46_cast")]; tensor input_233_cast = add(x = input_223_cast, y = y_46_cast)[name = tensor("input_233_cast")]; tensor var_1444 = const()[name = tensor("op_1444"), val = tensor([1])]; tensor var_1446 = const()[name = tensor("op_1446"), val = tensor([1])]; tensor input_235_pad_type_0 = const()[name = tensor("input_235_pad_type_0"), val = tensor("custom")]; tensor input_235_pad_0 = const()[name = tensor("input_235_pad_0"), val = tensor([0, 0])]; tensor sep_module_23_tcn_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2852544))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2926336))), name = tensor("sep_module_23_tcn_0_weight_to_fp16_palettized"), shape = tensor([384, 384, 1])]; tensor input_235_cast = conv(dilations = var_1446, groups = var_67, pad = input_235_pad_0, pad_type = input_235_pad_type_0, strides = var_1444, weight = sep_module_23_tcn_0_weight_to_fp16_palettized, x = input_233_cast)[name = tensor("input_235_cast")]; tensor var_1450_alpha_1_to_fp16 = const()[name = tensor("op_1450_alpha_1_to_fp16"), val = tensor(-0x1.8ap-2)]; tensor var_1450_cast = leaky_relu(alpha = var_1450_alpha_1_to_fp16, x = input_235_cast)[name = tensor("op_1450_cast")]; tensor var_1454 = const()[name = tensor("op_1454"), val = tensor([1])]; tensor mean_y_95_cast = reduce_mean(axes = var_1454, keep_dims = var_71, x = var_1450_cast)[name = tensor("mean_y_95_cast")]; tensor var_1456_cast = sub(x = var_1450_cast, y = mean_y_95_cast)[name = tensor("op_1456_cast")]; tensor var_1457_cast = square(x = var_1456_cast); tensor var_1458 = const()[name = tensor("op_1458"), val = tensor([1])]; tensor var_1459_cast = reduce_mean(axes = var_1458, keep_dims = var_71, x = var_1457_cast)[name = tensor("op_1459_cast")]; tensor var_1460_to_fp16 = const()[name = tensor("op_1460_to_fp16"), val = tensor(0x1p-14)]; tensor var_1461_cast = add(x = var_1459_cast, y = var_1460_to_fp16)[name = tensor("op_1461_cast")]; tensor std_y_95_cast = sqrt(x = var_1461_cast)[name = tensor("std_y_95_cast")]; tensor sep_module_23_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_23_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2926464)))]; tensor var_1464_cast = mul(x = sep_module_23_tcn_2_norm_gamma_to_fp16, y = var_1456_cast)[name = tensor("op_1464_cast")]; tensor var_1465_cast = real_div(x = var_1464_cast, y = std_y_95_cast)[name = tensor("op_1465_cast")]; tensor sep_module_23_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_23_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2927296)))]; tensor input_237_cast = add(x = var_1465_cast, y = sep_module_23_tcn_2_norm_beta_to_fp16)[name = tensor("input_237_cast")]; tensor input_239_pad_0 = const()[name = tensor("input_239_pad_0"), val = tensor([0, 0, 0, 0, 64, 0])]; tensor input_239_mode_0 = const()[name = tensor("input_239_mode_0"), val = tensor("constant")]; tensor input_239_constant_val_0_to_fp16 = const()[name = tensor("input_239_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_239_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_237_cast_in_state, input_237_cast)); tensor input_237_cast_out_state = slice_by_size(begin = tensor([0, 0, -64]), size = tensor([-1, 384, 64]), x = input_239_cast); tensor var_1470 = const()[name = tensor("op_1470"), val = tensor([1])]; tensor var_1472 = const()[name = tensor("op_1472"), val = tensor([32])]; tensor input_241_pad_type_0 = const()[name = tensor("input_241_pad_type_0"), val = tensor("custom")]; tensor input_241_pad_0 = const()[name = tensor("input_241_pad_0"), val = tensor([0, 0])]; tensor sep_module_23_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_23_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2928128)))]; tensor input_241_cast = conv(dilations = var_1472, groups = var_68, pad = input_241_pad_0, pad_type = input_241_pad_type_0, strides = var_1470, weight = sep_module_23_tcn_4_weight_to_fp16, x = input_239_cast)[name = tensor("input_241_cast")]; tensor var_1476_alpha_1_to_fp16 = const()[name = tensor("op_1476_alpha_1_to_fp16"), val = tensor(0x1.f1p-1)]; tensor var_1476_cast = leaky_relu(alpha = var_1476_alpha_1_to_fp16, x = input_241_cast)[name = tensor("op_1476_cast")]; tensor var_1480 = const()[name = tensor("op_1480"), val = tensor([1])]; tensor mean_y_97_cast = reduce_mean(axes = var_1480, keep_dims = var_71, x = var_1476_cast)[name = tensor("mean_y_97_cast")]; tensor var_1482_cast = sub(x = var_1476_cast, y = mean_y_97_cast)[name = tensor("op_1482_cast")]; tensor var_1483_cast = square(x = var_1482_cast); tensor var_1484 = const()[name = tensor("op_1484"), val = tensor([1])]; tensor var_1485_cast = reduce_mean(axes = var_1484, keep_dims = var_71, x = var_1483_cast)[name = tensor("op_1485_cast")]; tensor var_1486_to_fp16 = const()[name = tensor("op_1486_to_fp16"), val = tensor(0x1p-14)]; tensor var_1487_cast = add(x = var_1485_cast, y = var_1486_to_fp16)[name = tensor("op_1487_cast")]; tensor std_y_97_cast = sqrt(x = var_1487_cast)[name = tensor("std_y_97_cast")]; tensor sep_module_23_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_23_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2930496)))]; tensor var_1490_cast = mul(x = sep_module_23_tcn_6_norm_gamma_to_fp16, y = var_1482_cast)[name = tensor("op_1490_cast")]; tensor var_1491_cast = real_div(x = var_1490_cast, y = std_y_97_cast)[name = tensor("op_1491_cast")]; tensor sep_module_23_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_23_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2931328)))]; tensor y_48_cast = add(x = var_1491_cast, y = sep_module_23_tcn_6_norm_beta_to_fp16)[name = tensor("y_48_cast")]; tensor input_243_cast = add(x = input_233_cast, y = y_48_cast)[name = tensor("input_243_cast")]; tensor var_1502 = const()[name = tensor("op_1502"), val = tensor([1])]; tensor var_1504 = const()[name = tensor("op_1504"), val = tensor([1])]; tensor input_245_pad_type_0 = const()[name = tensor("input_245_pad_type_0"), val = tensor("custom")]; tensor input_245_pad_0 = const()[name = tensor("input_245_pad_0"), val = tensor([0, 0])]; tensor sep_module_24_tcn_0_weight_to_fp16 = const()[name = tensor("sep_module_24_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(2932160)))]; tensor input_245_cast = conv(dilations = var_1504, groups = var_67, pad = input_245_pad_0, pad_type = input_245_pad_type_0, strides = var_1502, weight = sep_module_24_tcn_0_weight_to_fp16, x = input_243_cast)[name = tensor("input_245_cast")]; tensor var_1508_alpha_1_to_fp16 = const()[name = tensor("op_1508_alpha_1_to_fp16"), val = tensor(-0x1.b14p-1)]; tensor var_1508_cast = leaky_relu(alpha = var_1508_alpha_1_to_fp16, x = input_245_cast)[name = tensor("op_1508_cast")]; tensor var_1512 = const()[name = tensor("op_1512"), val = tensor([1])]; tensor mean_y_99_cast = reduce_mean(axes = var_1512, keep_dims = var_71, x = var_1508_cast)[name = tensor("mean_y_99_cast")]; tensor var_1514_cast = sub(x = var_1508_cast, y = mean_y_99_cast)[name = tensor("op_1514_cast")]; tensor var_1515_cast = square(x = var_1514_cast); tensor var_1516 = const()[name = tensor("op_1516"), val = tensor([1])]; tensor var_1517_cast = reduce_mean(axes = var_1516, keep_dims = var_71, x = var_1515_cast)[name = tensor("op_1517_cast")]; tensor var_1518_to_fp16 = const()[name = tensor("op_1518_to_fp16"), val = tensor(0x1p-14)]; tensor var_1519_cast = add(x = var_1517_cast, y = var_1518_to_fp16)[name = tensor("op_1519_cast")]; tensor std_y_99_cast = sqrt(x = var_1519_cast)[name = tensor("std_y_99_cast")]; tensor sep_module_24_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_24_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3227136)))]; tensor var_1522_cast = mul(x = sep_module_24_tcn_2_norm_gamma_to_fp16, y = var_1514_cast)[name = tensor("op_1522_cast")]; tensor var_1523_cast = real_div(x = var_1522_cast, y = std_y_99_cast)[name = tensor("op_1523_cast")]; tensor sep_module_24_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_24_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3227968)))]; tensor input_247_cast = add(x = var_1523_cast, y = sep_module_24_tcn_2_norm_beta_to_fp16)[name = tensor("input_247_cast")]; tensor input_249_pad_0 = const()[name = tensor("input_249_pad_0"), val = tensor([0, 0, 0, 0, 128, 0])]; tensor input_249_mode_0 = const()[name = tensor("input_249_mode_0"), val = tensor("constant")]; tensor input_249_constant_val_0_to_fp16 = const()[name = tensor("input_249_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_249_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_247_cast_in_state, input_247_cast)); tensor input_247_cast_out_state = slice_by_size(begin = tensor([0, 0, -128]), size = tensor([-1, 384, 128]), x = input_249_cast); tensor var_1528 = const()[name = tensor("op_1528"), val = tensor([1])]; tensor var_1530 = const()[name = tensor("op_1530"), val = tensor([64])]; tensor input_251_pad_type_0 = const()[name = tensor("input_251_pad_type_0"), val = tensor("custom")]; tensor input_251_pad_0 = const()[name = tensor("input_251_pad_0"), val = tensor([0, 0])]; tensor sep_module_24_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_24_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3228800)))]; tensor input_251_cast = conv(dilations = var_1530, groups = var_68, pad = input_251_pad_0, pad_type = input_251_pad_type_0, strides = var_1528, weight = sep_module_24_tcn_4_weight_to_fp16, x = input_249_cast)[name = tensor("input_251_cast")]; tensor var_1534_alpha_1_to_fp16 = const()[name = tensor("op_1534_alpha_1_to_fp16"), val = tensor(0x1.098p-1)]; tensor var_1534_cast = leaky_relu(alpha = var_1534_alpha_1_to_fp16, x = input_251_cast)[name = tensor("op_1534_cast")]; tensor var_1538 = const()[name = tensor("op_1538"), val = tensor([1])]; tensor mean_y_101_cast = reduce_mean(axes = var_1538, keep_dims = var_71, x = var_1534_cast)[name = tensor("mean_y_101_cast")]; tensor var_1540_cast = sub(x = var_1534_cast, y = mean_y_101_cast)[name = tensor("op_1540_cast")]; tensor var_1541_cast = square(x = var_1540_cast); tensor var_1542 = const()[name = tensor("op_1542"), val = tensor([1])]; tensor var_1543_cast = reduce_mean(axes = var_1542, keep_dims = var_71, x = var_1541_cast)[name = tensor("op_1543_cast")]; tensor var_1544_to_fp16 = const()[name = tensor("op_1544_to_fp16"), val = tensor(0x1p-14)]; tensor var_1545_cast = add(x = var_1543_cast, y = var_1544_to_fp16)[name = tensor("op_1545_cast")]; tensor std_y_101_cast = sqrt(x = var_1545_cast)[name = tensor("std_y_101_cast")]; tensor sep_module_24_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_24_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3231168)))]; tensor var_1548_cast = mul(x = sep_module_24_tcn_6_norm_gamma_to_fp16, y = var_1540_cast)[name = tensor("op_1548_cast")]; tensor var_1549_cast = real_div(x = var_1548_cast, y = std_y_101_cast)[name = tensor("op_1549_cast")]; tensor sep_module_24_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_24_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3232000)))]; tensor y_50_cast = add(x = var_1549_cast, y = sep_module_24_tcn_6_norm_beta_to_fp16)[name = tensor("y_50_cast")]; tensor input_253_cast = add(x = input_243_cast, y = y_50_cast)[name = tensor("input_253_cast")]; tensor var_1560 = const()[name = tensor("op_1560"), val = tensor([1])]; tensor var_1562 = const()[name = tensor("op_1562"), val = tensor([1])]; tensor input_255_pad_type_0 = const()[name = tensor("input_255_pad_type_0"), val = tensor("custom")]; tensor input_255_pad_0 = const()[name = tensor("input_255_pad_0"), val = tensor([0, 0])]; tensor sep_module_25_tcn_0_weight_to_fp16 = const()[name = tensor("sep_module_25_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3232832)))]; tensor input_255_cast = conv(dilations = var_1562, groups = var_67, pad = input_255_pad_0, pad_type = input_255_pad_type_0, strides = var_1560, weight = sep_module_25_tcn_0_weight_to_fp16, x = input_253_cast)[name = tensor("input_255_cast")]; tensor var_1566_alpha_1_to_fp16 = const()[name = tensor("op_1566_alpha_1_to_fp16"), val = tensor(-0x1.e7p-2)]; tensor var_1566_cast = leaky_relu(alpha = var_1566_alpha_1_to_fp16, x = input_255_cast)[name = tensor("op_1566_cast")]; tensor var_1570 = const()[name = tensor("op_1570"), val = tensor([1])]; tensor mean_y_103_cast = reduce_mean(axes = var_1570, keep_dims = var_71, x = var_1566_cast)[name = tensor("mean_y_103_cast")]; tensor var_1572_cast = sub(x = var_1566_cast, y = mean_y_103_cast)[name = tensor("op_1572_cast")]; tensor var_1573_cast = square(x = var_1572_cast); tensor var_1574 = const()[name = tensor("op_1574"), val = tensor([1])]; tensor var_1575_cast = reduce_mean(axes = var_1574, keep_dims = var_71, x = var_1573_cast)[name = tensor("op_1575_cast")]; tensor var_1576_to_fp16 = const()[name = tensor("op_1576_to_fp16"), val = tensor(0x1p-14)]; tensor var_1577_cast = add(x = var_1575_cast, y = var_1576_to_fp16)[name = tensor("op_1577_cast")]; tensor std_y_103_cast = sqrt(x = var_1577_cast)[name = tensor("std_y_103_cast")]; tensor sep_module_25_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_25_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3527808)))]; tensor var_1580_cast = mul(x = sep_module_25_tcn_2_norm_gamma_to_fp16, y = var_1572_cast)[name = tensor("op_1580_cast")]; tensor var_1581_cast = real_div(x = var_1580_cast, y = std_y_103_cast)[name = tensor("op_1581_cast")]; tensor sep_module_25_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_25_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3528640)))]; tensor input_257_cast = add(x = var_1581_cast, y = sep_module_25_tcn_2_norm_beta_to_fp16)[name = tensor("input_257_cast")]; tensor input_259_pad_0 = const()[name = tensor("input_259_pad_0"), val = tensor([0, 0, 0, 0, 256, 0])]; tensor input_259_mode_0 = const()[name = tensor("input_259_mode_0"), val = tensor("constant")]; tensor input_259_constant_val_0_to_fp16 = const()[name = tensor("input_259_constant_val_0_to_fp16"), val = tensor(0x0p+0)]; tensor input_259_cast = concat(axis = tensor(-1), interleave = tensor(false), values = (input_257_cast_in_state, input_257_cast)); tensor input_257_cast_out_state = slice_by_size(begin = tensor([0, 0, -256]), size = tensor([-1, 384, 256]), x = input_259_cast); tensor var_1586 = const()[name = tensor("op_1586"), val = tensor([1])]; tensor var_1588 = const()[name = tensor("op_1588"), val = tensor([128])]; tensor input_261_pad_type_0 = const()[name = tensor("input_261_pad_type_0"), val = tensor("custom")]; tensor input_261_pad_0 = const()[name = tensor("input_261_pad_0"), val = tensor([0, 0])]; tensor sep_module_25_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_25_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3529472)))]; tensor input_261_cast = conv(dilations = var_1588, groups = var_68, pad = input_261_pad_0, pad_type = input_261_pad_type_0, strides = var_1586, weight = sep_module_25_tcn_4_weight_to_fp16, x = input_259_cast)[name = tensor("input_261_cast")]; tensor var_1592_alpha_1_to_fp16 = const()[name = tensor("op_1592_alpha_1_to_fp16"), val = tensor(0x1.f9cp-1)]; tensor var_1592_cast = leaky_relu(alpha = var_1592_alpha_1_to_fp16, x = input_261_cast)[name = tensor("op_1592_cast")]; tensor var_1596 = const()[name = tensor("op_1596"), val = tensor([1])]; tensor mean_y_105_cast = reduce_mean(axes = var_1596, keep_dims = var_71, x = var_1592_cast)[name = tensor("mean_y_105_cast")]; tensor var_1598_cast = sub(x = var_1592_cast, y = mean_y_105_cast)[name = tensor("op_1598_cast")]; tensor var_1599_cast = square(x = var_1598_cast); tensor var_1600 = const()[name = tensor("op_1600"), val = tensor([1])]; tensor var_1601_cast = reduce_mean(axes = var_1600, keep_dims = var_71, x = var_1599_cast)[name = tensor("op_1601_cast")]; tensor var_1602_to_fp16 = const()[name = tensor("op_1602_to_fp16"), val = tensor(0x1p-14)]; tensor var_1603_cast = add(x = var_1601_cast, y = var_1602_to_fp16)[name = tensor("op_1603_cast")]; tensor std_y_105_cast = sqrt(x = var_1603_cast)[name = tensor("std_y_105_cast")]; tensor sep_module_25_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_25_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3531840)))]; tensor var_1606_cast = mul(x = sep_module_25_tcn_6_norm_gamma_to_fp16, y = var_1598_cast)[name = tensor("op_1606_cast")]; tensor var_1607_cast = real_div(x = var_1606_cast, y = std_y_105_cast)[name = tensor("op_1607_cast")]; tensor sep_module_25_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_25_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3532672)))]; tensor y_52_cast = add(x = var_1607_cast, y = sep_module_25_tcn_6_norm_beta_to_fp16)[name = tensor("y_52_cast")]; tensor input_3_cast = add(x = input_253_cast, y = y_52_cast)[name = tensor("input_3_cast")]; tensor var_1618 = const()[name = tensor("op_1618"), val = tensor([1])]; tensor var_1620 = const()[name = tensor("op_1620"), 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 sep_module_26_tcn_0_weight_to_fp16 = const()[name = tensor("sep_module_26_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3533504)))]; tensor input_2_cast = conv(dilations = var_1620, groups = var_67, pad = input_2_pad_0, pad_type = input_2_pad_type_0, strides = var_1618, weight = sep_module_26_tcn_0_weight_to_fp16, x = input_3_cast)[name = tensor("input_2_cast")]; tensor var_1624_alpha_1_to_fp16 = const()[name = tensor("op_1624_alpha_1_to_fp16"), val = tensor(-0x1.e8cp-3)]; tensor var_1624_cast = leaky_relu(alpha = var_1624_alpha_1_to_fp16, x = input_2_cast)[name = tensor("op_1624_cast")]; tensor var_1628 = const()[name = tensor("op_1628"), val = tensor([1])]; tensor mean_y_2_cast = reduce_mean(axes = var_1628, keep_dims = var_71, x = var_1624_cast)[name = tensor("mean_y_2_cast")]; tensor var_1630_cast = sub(x = var_1624_cast, y = mean_y_2_cast)[name = tensor("op_1630_cast")]; tensor var_1631_cast = square(x = var_1630_cast); tensor var_1632 = const()[name = tensor("op_1632"), val = tensor([1])]; tensor var_1633_cast = reduce_mean(axes = var_1632, keep_dims = var_71, x = var_1631_cast)[name = tensor("op_1633_cast")]; tensor var_1634_to_fp16 = const()[name = tensor("op_1634_to_fp16"), val = tensor(0x1p-14)]; tensor var_1635_cast = add(x = var_1633_cast, y = var_1634_to_fp16)[name = tensor("op_1635_cast")]; tensor std_y_2_cast = sqrt(x = var_1635_cast)[name = tensor("std_y_2_cast")]; tensor sep_module_26_tcn_2_norm_gamma_to_fp16 = const()[name = tensor("sep_module_26_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3828480)))]; tensor var_1638_cast = mul(x = sep_module_26_tcn_2_norm_gamma_to_fp16, y = var_1630_cast)[name = tensor("op_1638_cast")]; tensor var_1639_cast = real_div(x = var_1638_cast, y = std_y_2_cast)[name = tensor("op_1639_cast")]; tensor sep_module_26_tcn_2_norm_beta_to_fp16 = const()[name = tensor("sep_module_26_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3829312)))]; tensor input_4_cast = add(x = var_1639_cast, y = sep_module_26_tcn_2_norm_beta_to_fp16)[name = tensor("input_4_cast")]; tensor input_6_pad_0 = const()[name = tensor("input_6_pad_0"), val = tensor([0, 0, 0, 0, 512, 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, -512]), size = tensor([-1, 384, 512]), x = input_6_cast); tensor var_1644 = const()[name = tensor("op_1644"), val = tensor([1])]; tensor var_1646 = const()[name = tensor("op_1646"), val = tensor([256])]; 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 sep_module_26_tcn_4_weight_to_fp16 = const()[name = tensor("sep_module_26_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3830144)))]; tensor input_1_cast = conv(dilations = var_1646, groups = var_68, pad = input_1_pad_0, pad_type = input_1_pad_type_0, strides = var_1644, weight = sep_module_26_tcn_4_weight_to_fp16, x = input_6_cast)[name = tensor("input_1_cast")]; tensor var_1650_alpha_1_to_fp16 = const()[name = tensor("op_1650_alpha_1_to_fp16"), val = tensor(0x1.004p+0)]; tensor var_1650_cast = leaky_relu(alpha = var_1650_alpha_1_to_fp16, x = input_1_cast)[name = tensor("op_1650_cast")]; tensor var_1654 = const()[name = tensor("op_1654"), val = tensor([1])]; tensor mean_y_1_cast = reduce_mean(axes = var_1654, keep_dims = var_71, x = var_1650_cast)[name = tensor("mean_y_1_cast")]; tensor var_1656_cast = sub(x = var_1650_cast, y = mean_y_1_cast)[name = tensor("op_1656_cast")]; tensor var_1657_cast = square(x = var_1656_cast); tensor var_1658 = const()[name = tensor("op_1658"), val = tensor([1])]; tensor var_1659_cast = reduce_mean(axes = var_1658, keep_dims = var_71, x = var_1657_cast)[name = tensor("op_1659_cast")]; tensor var_1660_to_fp16 = const()[name = tensor("op_1660_to_fp16"), val = tensor(0x1p-14)]; tensor var_1661_cast = add(x = var_1659_cast, y = var_1660_to_fp16)[name = tensor("op_1661_cast")]; tensor std_y_1_cast = sqrt(x = var_1661_cast)[name = tensor("std_y_1_cast")]; tensor sep_module_26_tcn_6_norm_gamma_to_fp16 = const()[name = tensor("sep_module_26_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3832512)))]; tensor var_1664_cast = mul(x = sep_module_26_tcn_6_norm_gamma_to_fp16, y = var_1656_cast)[name = tensor("op_1664_cast")]; tensor var_1665_cast = real_div(x = var_1664_cast, y = std_y_1_cast)[name = tensor("op_1665_cast")]; tensor sep_module_26_tcn_6_norm_beta_to_fp16 = const()[name = tensor("sep_module_26_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3833344)))]; tensor y_1_cast = add(x = var_1665_cast, y = sep_module_26_tcn_6_norm_beta_to_fp16)[name = tensor("y_1_cast")]; tensor x_1_cast = add(x = input_3_cast, y = y_1_cast)[name = tensor("x_1_cast")]; tensor input0_3_axes_0 = const()[name = tensor("input0_3_axes_0"), val = tensor([1])]; tensor input0_3_cast = expand_dims(axes = input0_3_axes_0, x = x_1_cast)[name = tensor("input0_3_cast")]; tensor var_1671 = const()[name = tensor("op_1671"), val = tensor(1)]; tensor var_1676 = const()[name = tensor("op_1676"), val = tensor([1, 1])]; tensor var_1678 = const()[name = tensor("op_1678"), 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([192, 192, 0, 0])]; tensor mask_layer_weight_to_fp16 = const()[name = tensor("mask_layer_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3834176)))]; tensor input1_1_cast = conv(dilations = var_1678, groups = var_1671, pad = input1_1_pad_0, pad_type = input1_1_pad_type_0, strides = var_1676, weight = mask_layer_weight_to_fp16, x = input0_3_cast)[name = tensor("input1_1_cast")]; tensor var_1681_cast = sigmoid(x = input1_1_cast)[name = tensor("op_1681_cast")]; tensor var_1682_axes_0 = const()[name = tensor("op_1682_axes_0"), val = tensor([1])]; tensor var_1682_cast = expand_dims(axes = var_1682_axes_0, x = var_26_cast)[name = tensor("op_1682_cast")]; tensor var_1682_cast_concat_expanded = concat(axis = tensor(-1), interleave = tensor(false), values = (var_1682_cast_concat_in_state, var_1682_cast)); tensor var_1682_cast_delayed = slice_by_size(begin = tensor([0, 0, 0, 0]), size = tensor([-1, 1, 384, 32]), x = var_1682_cast_concat_expanded); tensor var_1682_cast_concat_out_state = slice_by_size(begin = tensor([0, 0, 0, -7]), size = tensor([-1, 1, 384, 7]), x = var_1682_cast_concat_expanded); tensor x_11_cast = mul(x = var_1681_cast, y = var_1682_cast_delayed)[name = tensor("x_11_cast")]; tensor concat_0x = const()[name = tensor("concat_0x"), val = tensor([1, 384, -1])]; tensor input1_3_cast = reshape(shape = tensor([-1, 384, 32]), x = x_11_cast); tensor var_1699 = const()[name = tensor("op_1699"), val = tensor(1)]; tensor var_1705 = const()[name = tensor("op_1705"), val = tensor([40])]; tensor var_1707 = const()[name = tensor("op_1707"), val = tensor([1])]; tensor var_1709_pad_type_0 = const()[name = tensor("op_1709_pad_type_0"), val = tensor("custom")]; tensor var_1709_pad_0 = const()[name = tensor("op_1709_pad_0"), val = tensor([40, 40])]; tensor resynthesizer_weight_to_fp16 = const()[name = tensor("resynthesizer_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/vi-nnet-high-quality-voice.weight.bin"), offset = tensor(3835072)))]; tensor input1_3_cast_padded = concat(axis = tensor(-1), interleave = tensor(false), values = (input1_3_cast_in_state, input1_3_cast)); tensor input1_3_cast_out_state = slice_by_size(begin = tensor([0, 0, -1]), size = tensor([-1, 384, 1]), x = input1_3_cast_padded); tensor var_1709_cast = conv_transpose(dilations = var_1707, groups = var_1699, pad = var_1709_pad_0, pad_type = var_1709_pad_type_0, strides = var_1705, weight = resynthesizer_weight_to_fp16, x = input1_3_cast_padded); tensor var_1709_cast_to_fp32_dtype_0 = const()[name = tensor("op_1709_cast_to_fp32_dtype_0"), val = tensor("fp32")]; tensor var_1709 = cast(dtype = var_1709_cast_to_fp32_dtype_0, x = var_1709_cast)[name = tensor("cast_0")]; } -> (var_1709, cast_1_out_state, input_7_cast_out_state, input_267_cast_concat_out_state, input_17_cast_out_state, input_13_cast_concat_out_state, input_27_cast_out_state, input_23_cast_concat_out_state, input_37_cast_out_state, input_47_cast_out_state, input_57_cast_out_state, input_67_cast_out_state, input_77_cast_out_state, input_87_cast_out_state, input_97_cast_out_state, input_107_cast_out_state, input_117_cast_out_state, input_127_cast_out_state, input_137_cast_out_state, input_147_cast_out_state, input_157_cast_out_state, input_167_cast_out_state, input_177_cast_out_state, input_187_cast_out_state, input_197_cast_out_state, input_207_cast_out_state, input_217_cast_out_state, input_227_cast_out_state, input_237_cast_out_state, input_247_cast_out_state, input_257_cast_out_state, input_4_cast_out_state, var_1682_cast_concat_out_state, input1_3_cast_out_state); }