| program(1.0) |
| [buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}})] |
| { |
| func main<ios17>(tensor<fp16, [1, ?]> F0_curve, tensor<fp16, [1, ?]> N_pred, tensor<fp16, [1, 512, ?]> asr, tensor<fp16, [1, 128]> style_timbre, tensor<fp16, [1, 256, ?]> x_source_0, tensor<fp16, [1, 128, ?]> x_source_1) [FlexibleShapeInformation = tuple<tuple<tensor<string, []>, dict<tensor<string, []>, tensor<int32, [?]>>>, tuple<tensor<string, []>, dict<tensor<string, []>, list<tensor<int32, [2]>, ?>>>>((("DefaultShapes", {{"F0_curve", [1, 240]}, {"N_pred", [1, 240]}, {"asr", [1, 512, 120]}, {"x_source_0", [1, 256, 2400]}, {"x_source_1", [1, 128, 14401]}}), ("RangeDims", {{"F0_curve", [[1, 1], [2, 4000]]}, {"N_pred", [[1, 1], [2, 4000]]}, {"asr", [[1, 1], [512, 512], [1, 2000]]}, {"x_source_0", [[1, 1], [256, 256], [1, 40000]]}, {"x_source_1", [[1, 1], [128, 128], [1, 240001]]}})))] { |
| tensor<int32, [1]> input_1_axes_0 = const()[name = tensor<string, []>("input_1_axes_0"), val = tensor<int32, [1]>([1])]; |
| tensor<fp16, [1, 1, ?]> input_1_cast_fp16 = expand_dims(axes = input_1_axes_0, x = F0_curve)[name = tensor<string, []>("input_1_cast_fp16")]; |
| tensor<string, []> F0_pad_type_0 = const()[name = tensor<string, []>("F0_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> F0_pad_0 = const()[name = tensor<string, []>("F0_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> F0_strides_0 = const()[name = tensor<string, []>("F0_strides_0"), val = tensor<int32, [1]>([2])]; |
| tensor<int32, [1]> F0_dilations_0 = const()[name = tensor<string, []>("F0_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> F0_groups_0 = const()[name = tensor<string, []>("F0_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 1, 3]> weight_1_to_fp16 = const()[name = tensor<string, []>("weight_1_to_fp16"), val = tensor<fp16, [1, 1, 3]>([[[0x1.a88p-5, 0x1.b18p-5, -0x1.6d8p-6]]])]; |
| tensor<fp16, [1]> F0_conv_bias_to_fp16 = const()[name = tensor<string, []>("F0_conv_bias_to_fp16"), val = tensor<fp16, [1]>([-0x1.004p-2])]; |
| tensor<fp16, [1, 1, ?]> F0_cast_fp16 = conv(bias = F0_conv_bias_to_fp16, dilations = F0_dilations_0, groups = F0_groups_0, pad = F0_pad_0, pad_type = F0_pad_type_0, strides = F0_strides_0, weight = weight_1_to_fp16, x = input_1_cast_fp16)[name = tensor<string, []>("F0_cast_fp16")]; |
| tensor<int32, [1]> input_3_axes_0 = const()[name = tensor<string, []>("input_3_axes_0"), val = tensor<int32, [1]>([1])]; |
| tensor<fp16, [1, 1, ?]> input_3_cast_fp16 = expand_dims(axes = input_3_axes_0, x = N_pred)[name = tensor<string, []>("input_3_cast_fp16")]; |
| tensor<string, []> N_feat_pad_type_0 = const()[name = tensor<string, []>("N_feat_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> N_feat_pad_0 = const()[name = tensor<string, []>("N_feat_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> N_feat_strides_0 = const()[name = tensor<string, []>("N_feat_strides_0"), val = tensor<int32, [1]>([2])]; |
| tensor<int32, [1]> N_feat_dilations_0 = const()[name = tensor<string, []>("N_feat_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> N_feat_groups_0 = const()[name = tensor<string, []>("N_feat_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 1, 3]> weight_3_to_fp16 = const()[name = tensor<string, []>("weight_3_to_fp16"), val = tensor<fp16, [1, 1, 3]>([[[0x1.cc4p-2, 0x1.35cp-1, 0x1.b98p-2]]])]; |
| tensor<fp16, [1]> N_conv_bias_to_fp16 = const()[name = tensor<string, []>("N_conv_bias_to_fp16"), val = tensor<fp16, [1]>([-0x1.e68p-2])]; |
| tensor<fp16, [1, 1, ?]> N_feat_cast_fp16 = conv(bias = N_conv_bias_to_fp16, dilations = N_feat_dilations_0, groups = N_feat_groups_0, pad = N_feat_pad_0, pad_type = N_feat_pad_type_0, strides = N_feat_strides_0, weight = weight_3_to_fp16, x = input_3_cast_fp16)[name = tensor<string, []>("N_feat_cast_fp16")]; |
| tensor<int32, []> var_86 = const()[name = tensor<string, []>("op_86"), val = tensor<int32, []>(1)]; |
| tensor<bool, []> input_5_interleave_0 = const()[name = tensor<string, []>("input_5_interleave_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [1, 514, ?]> input_5_cast_fp16 = concat(axis = var_86, interleave = input_5_interleave_0, values = (asr, F0_cast_fp16, N_feat_cast_fp16))[name = tensor<string, []>("input_5_cast_fp16")]; |
| tensor<fp32, []> var_90 = const()[name = tensor<string, []>("op_90"), val = tensor<fp32, []>(0x1.99999ap-3)]; |
| tensor<fp16, [1028, 128]> encode_norm1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [131584]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(131712))), name = tensor<string, []>("encode_norm1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1028, 128])]; |
| tensor<fp16, [1028]> encode_norm1_fc_bias_to_fp16 = const()[name = tensor<string, []>("encode_norm1_fc_bias_to_fp16"), val = tensor<fp16, [1028]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(132288)))]; |
| tensor<fp16, [1, 1028]> linear_0_cast_fp16 = linear(bias = encode_norm1_fc_bias_to_fp16, weight = encode_norm1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_0_cast_fp16")]; |
| tensor<int32, [3]> var_120 = const()[name = tensor<string, []>("op_120"), val = tensor<int32, [3]>([1, 1028, 1])]; |
| tensor<fp16, [1, 1028, 1]> h_3_cast_fp16 = reshape(shape = var_120, x = linear_0_cast_fp16)[name = tensor<string, []>("h_3_cast_fp16")]; |
| tensor<int32, [2]> var_122_split_sizes_0 = const()[name = tensor<string, []>("op_122_split_sizes_0"), val = tensor<int32, [2]>([514, 514])]; |
| tensor<int32, []> var_122_axis_0 = const()[name = tensor<string, []>("op_122_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 514, 1]> var_122_cast_fp16_0, tensor<fp16, [1, 514, 1]> var_122_cast_fp16_1 = split(axis = var_122_axis_0, split_sizes = var_122_split_sizes_0, x = h_3_cast_fp16)[name = tensor<string, []>("op_122_cast_fp16")]; |
| tensor<fp16, []> var_124_promoted_to_fp16 = const()[name = tensor<string, []>("op_124_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 514, 1]> var_125_cast_fp16 = add(x = var_122_cast_fp16_0, y = var_124_promoted_to_fp16)[name = tensor<string, []>("op_125_cast_fp16")]; |
| tensor<fp16, [514]> encode_norm1_norm_weight_to_fp16 = const()[name = tensor<string, []>("encode_norm1_norm_weight_to_fp16"), val = tensor<fp16, [514]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134464)))]; |
| tensor<fp16, [514]> encode_norm1_norm_bias_to_fp16 = const()[name = tensor<string, []>("encode_norm1_norm_bias_to_fp16"), val = tensor<fp16, [514]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(135616)))]; |
| tensor<fp16, []> var_93_to_fp16 = const()[name = tensor<string, []>("op_93_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| tensor<fp16, [1, 514, ?]> var_128_cast_fp16 = instance_norm(beta = encode_norm1_norm_bias_to_fp16, epsilon = var_93_to_fp16, gamma = encode_norm1_norm_weight_to_fp16, x = input_5_cast_fp16)[name = tensor<string, []>("op_128_cast_fp16")]; |
| tensor<fp16, [1, 514, ?]> var_129_cast_fp16 = mul(x = var_125_cast_fp16, y = var_128_cast_fp16)[name = tensor<string, []>("op_129_cast_fp16")]; |
| tensor<fp16, [1, 514, ?]> input_7_cast_fp16 = add(x = var_129_cast_fp16, y = var_122_cast_fp16_1)[name = tensor<string, []>("input_7_cast_fp16")]; |
| tensor<fp16, [1, 514, ?]> input_9_cast_fp16 = leaky_relu(alpha = var_90, x = input_7_cast_fp16)[name = tensor<string, []>("input_9_cast_fp16")]; |
| tensor<string, []> input_13_pad_type_0 = const()[name = tensor<string, []>("input_13_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_13_pad_0 = const()[name = tensor<string, []>("input_13_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> input_13_strides_0 = const()[name = tensor<string, []>("input_13_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> input_13_dilations_0 = const()[name = tensor<string, []>("input_13_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_13_groups_0 = const()[name = tensor<string, []>("input_13_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1024, 514, 3]> weight_7_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1579008]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136768))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1715840))), name = tensor<string, []>("weight_7_to_fp16_palettized"), shape = tensor<uint32, [3]>([1024, 514, 3])]; |
| tensor<fp16, [1024]> encode_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encode_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1716416)))]; |
| tensor<fp16, [1, 1024, ?]> input_13_cast_fp16 = conv(bias = encode_conv1_bias_to_fp16, dilations = input_13_dilations_0, groups = input_13_groups_0, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = input_13_strides_0, weight = weight_7_to_fp16_palettized, x = input_9_cast_fp16)[name = tensor<string, []>("input_13_cast_fp16")]; |
| tensor<fp16, [2048, 128]> encode_norm2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [262144]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1718528))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1980736))), name = tensor<string, []>("encode_norm2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([2048, 128])]; |
| tensor<fp16, [2048]> encode_norm2_fc_bias_to_fp16 = const()[name = tensor<string, []>("encode_norm2_fc_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1981312)))]; |
| tensor<fp16, [1, 2048]> linear_1_cast_fp16 = linear(bias = encode_norm2_fc_bias_to_fp16, weight = encode_norm2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_1_cast_fp16")]; |
| tensor<int32, [3]> var_147 = const()[name = tensor<string, []>("op_147"), val = tensor<int32, [3]>([1, 2048, 1])]; |
| tensor<fp16, [1, 2048, 1]> h_7_cast_fp16 = reshape(shape = var_147, x = linear_1_cast_fp16)[name = tensor<string, []>("h_7_cast_fp16")]; |
| tensor<int32, [2]> var_149_split_sizes_0 = const()[name = tensor<string, []>("op_149_split_sizes_0"), val = tensor<int32, [2]>([1024, 1024])]; |
| tensor<int32, []> var_149_axis_0 = const()[name = tensor<string, []>("op_149_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 1024, 1]> var_149_cast_fp16_0, tensor<fp16, [1, 1024, 1]> var_149_cast_fp16_1 = split(axis = var_149_axis_0, split_sizes = var_149_split_sizes_0, x = h_7_cast_fp16)[name = tensor<string, []>("op_149_cast_fp16")]; |
| tensor<fp16, []> var_151_promoted_to_fp16 = const()[name = tensor<string, []>("op_151_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 1024, 1]> var_152_cast_fp16 = add(x = var_149_cast_fp16_0, y = var_151_promoted_to_fp16)[name = tensor<string, []>("op_152_cast_fp16")]; |
| tensor<fp16, [1024]> encode_norm2_norm_weight_to_fp16 = const()[name = tensor<string, []>("encode_norm2_norm_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1985472)))]; |
| tensor<fp16, [1024]> encode_norm2_norm_bias_to_fp16 = const()[name = tensor<string, []>("encode_norm2_norm_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1987584)))]; |
| tensor<fp16, [1, 1024, ?]> var_155_cast_fp16 = instance_norm(beta = encode_norm2_norm_bias_to_fp16, epsilon = var_93_to_fp16, gamma = encode_norm2_norm_weight_to_fp16, x = input_13_cast_fp16)[name = tensor<string, []>("op_155_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> var_156_cast_fp16 = mul(x = var_152_cast_fp16, y = var_155_cast_fp16)[name = tensor<string, []>("op_156_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> input_15_cast_fp16 = add(x = var_156_cast_fp16, y = var_149_cast_fp16_1)[name = tensor<string, []>("input_15_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> input_17_cast_fp16 = leaky_relu(alpha = var_90, x = input_15_cast_fp16)[name = tensor<string, []>("input_17_cast_fp16")]; |
| tensor<string, []> out_1_pad_type_0 = const()[name = tensor<string, []>("out_1_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> out_1_pad_0 = const()[name = tensor<string, []>("out_1_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> out_1_strides_0 = const()[name = tensor<string, []>("out_1_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> out_1_dilations_0 = const()[name = tensor<string, []>("out_1_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> out_1_groups_0 = const()[name = tensor<string, []>("out_1_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1024, 1024, 3]> weight_11_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1989696))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5135488))), name = tensor<string, []>("weight_11_to_fp16_palettized"), shape = tensor<uint32, [3]>([1024, 1024, 3])]; |
| tensor<fp16, [1024]> encode_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encode_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5136064)))]; |
| tensor<fp16, [1, 1024, ?]> out_1_cast_fp16 = conv(bias = encode_conv2_bias_to_fp16, dilations = out_1_dilations_0, groups = out_1_groups_0, pad = out_1_pad_0, pad_type = out_1_pad_type_0, strides = out_1_strides_0, weight = weight_11_to_fp16_palettized, x = input_17_cast_fp16)[name = tensor<string, []>("out_1_cast_fp16")]; |
| tensor<string, []> var_172_pad_type_0 = const()[name = tensor<string, []>("op_172_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [1]> var_172_strides_0 = const()[name = tensor<string, []>("op_172_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [2]> var_172_pad_0 = const()[name = tensor<string, []>("op_172_pad_0"), val = tensor<int32, [2]>([0, 0])]; |
| tensor<int32, [1]> var_172_dilations_0 = const()[name = tensor<string, []>("op_172_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> var_172_groups_0 = const()[name = tensor<string, []>("op_172_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1024, 514, 1]> weight_13_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [526336]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5138176))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5664576))), name = tensor<string, []>("weight_13_to_fp16_palettized"), shape = tensor<uint32, [3]>([1024, 514, 1])]; |
| tensor<fp16, [1, 1024, ?]> var_172_cast_fp16 = conv(dilations = var_172_dilations_0, groups = var_172_groups_0, pad = var_172_pad_0, pad_type = var_172_pad_type_0, strides = var_172_strides_0, weight = weight_13_to_fp16_palettized, x = input_5_cast_fp16)[name = tensor<string, []>("op_172_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> var_173_cast_fp16 = add(x = out_1_cast_fp16, y = var_172_cast_fp16)[name = tensor<string, []>("op_173_cast_fp16")]; |
| tensor<fp16, []> var_174_to_fp16 = const()[name = tensor<string, []>("op_174_to_fp16"), val = tensor<fp16, []>(0x1.6ap-1)]; |
| tensor<fp16, [1, 1024, ?]> x_1_cast_fp16 = mul(x = var_173_cast_fp16, y = var_174_to_fp16)[name = tensor<string, []>("x_1_cast_fp16")]; |
| tensor<string, []> asr_res_1_pad_type_0 = const()[name = tensor<string, []>("asr_res_1_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [1]> asr_res_1_strides_0 = const()[name = tensor<string, []>("asr_res_1_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [2]> asr_res_1_pad_0 = const()[name = tensor<string, []>("asr_res_1_pad_0"), val = tensor<int32, [2]>([0, 0])]; |
| tensor<int32, [1]> asr_res_1_dilations_0 = const()[name = tensor<string, []>("asr_res_1_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> asr_res_1_groups_0 = const()[name = tensor<string, []>("asr_res_1_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [64, 512, 1]> weight_15_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5665152))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5697984))), name = tensor<string, []>("weight_15_to_fp16_palettized"), shape = tensor<uint32, [3]>([64, 512, 1])]; |
| tensor<fp16, [64]> asr_res_0_bias_to_fp16 = const()[name = tensor<string, []>("asr_res_0_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5698560)))]; |
| tensor<fp16, [1, 64, ?]> asr_res_1_cast_fp16 = conv(bias = asr_res_0_bias_to_fp16, dilations = asr_res_1_dilations_0, groups = asr_res_1_groups_0, pad = asr_res_1_pad_0, pad_type = asr_res_1_pad_type_0, strides = asr_res_1_strides_0, weight = weight_15_to_fp16_palettized, x = asr)[name = tensor<string, []>("asr_res_1_cast_fp16")]; |
| tensor<int32, []> var_193 = const()[name = tensor<string, []>("op_193"), val = tensor<int32, []>(1)]; |
| tensor<bool, []> input_21_interleave_0 = const()[name = tensor<string, []>("input_21_interleave_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [1, 1090, ?]> input_21_cast_fp16 = concat(axis = var_193, interleave = input_21_interleave_0, values = (x_1_cast_fp16, asr_res_1_cast_fp16, F0_cast_fp16, N_feat_cast_fp16))[name = tensor<string, []>("input_21_cast_fp16")]; |
| tensor<fp32, []> var_197 = const()[name = tensor<string, []>("op_197"), val = tensor<fp32, []>(0x1.99999ap-3)]; |
| tensor<fp16, [2180, 128]> decode_0_norm1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [279040]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5698752))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5977856))), name = tensor<string, []>("decode_0_norm1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([2180, 128])]; |
| tensor<fp16, [2180]> decode_0_norm1_fc_bias_to_fp16 = const()[name = tensor<string, []>("decode_0_norm1_fc_bias_to_fp16"), val = tensor<fp16, [2180]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5978432)))]; |
| tensor<fp16, [1, 2180]> linear_2_cast_fp16 = linear(bias = decode_0_norm1_fc_bias_to_fp16, weight = decode_0_norm1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_2_cast_fp16")]; |
| tensor<int32, [3]> var_227 = const()[name = tensor<string, []>("op_227"), val = tensor<int32, [3]>([1, 2180, 1])]; |
| tensor<fp16, [1, 2180, 1]> h_11_cast_fp16 = reshape(shape = var_227, x = linear_2_cast_fp16)[name = tensor<string, []>("h_11_cast_fp16")]; |
| tensor<int32, [2]> var_229_split_sizes_0 = const()[name = tensor<string, []>("op_229_split_sizes_0"), val = tensor<int32, [2]>([1090, 1090])]; |
| tensor<int32, []> var_229_axis_0 = const()[name = tensor<string, []>("op_229_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 1090, 1]> var_229_cast_fp16_0, tensor<fp16, [1, 1090, 1]> var_229_cast_fp16_1 = split(axis = var_229_axis_0, split_sizes = var_229_split_sizes_0, x = h_11_cast_fp16)[name = tensor<string, []>("op_229_cast_fp16")]; |
| tensor<fp16, []> var_231_promoted_to_fp16 = const()[name = tensor<string, []>("op_231_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 1090, 1]> var_232_cast_fp16 = add(x = var_229_cast_fp16_0, y = var_231_promoted_to_fp16)[name = tensor<string, []>("op_232_cast_fp16")]; |
| tensor<fp16, [1090]> decode_0_norm1_norm_weight_to_fp16 = const()[name = tensor<string, []>("decode_0_norm1_norm_weight_to_fp16"), val = tensor<fp16, [1090]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5982912)))]; |
| tensor<fp16, [1090]> decode_0_norm1_norm_bias_to_fp16 = const()[name = tensor<string, []>("decode_0_norm1_norm_bias_to_fp16"), val = tensor<fp16, [1090]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5985216)))]; |
| tensor<fp16, []> var_200_to_fp16 = const()[name = tensor<string, []>("op_200_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| tensor<fp16, [1, 1090, ?]> var_235_cast_fp16 = instance_norm(beta = decode_0_norm1_norm_bias_to_fp16, epsilon = var_200_to_fp16, gamma = decode_0_norm1_norm_weight_to_fp16, x = input_21_cast_fp16)[name = tensor<string, []>("op_235_cast_fp16")]; |
| tensor<fp16, [1, 1090, ?]> var_236_cast_fp16 = mul(x = var_232_cast_fp16, y = var_235_cast_fp16)[name = tensor<string, []>("op_236_cast_fp16")]; |
| tensor<fp16, [1, 1090, ?]> input_23_cast_fp16 = add(x = var_236_cast_fp16, y = var_229_cast_fp16_1)[name = tensor<string, []>("input_23_cast_fp16")]; |
| tensor<fp16, [1, 1090, ?]> input_25_cast_fp16 = leaky_relu(alpha = var_197, x = input_23_cast_fp16)[name = tensor<string, []>("input_25_cast_fp16")]; |
| tensor<string, []> input_29_pad_type_0 = const()[name = tensor<string, []>("input_29_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_29_pad_0 = const()[name = tensor<string, []>("input_29_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> input_29_strides_0 = const()[name = tensor<string, []>("input_29_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> input_29_dilations_0 = const()[name = tensor<string, []>("input_29_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_29_groups_0 = const()[name = tensor<string, []>("input_29_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1024, 1090, 3]> weight_19_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3348480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5987520))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9336064))), name = tensor<string, []>("weight_19_to_fp16_palettized"), shape = tensor<uint32, [3]>([1024, 1090, 3])]; |
| tensor<fp16, [1024]> decode_0_conv1_bias_to_fp16 = const()[name = tensor<string, []>("decode_0_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9336640)))]; |
| tensor<fp16, [1, 1024, ?]> input_29_cast_fp16 = conv(bias = decode_0_conv1_bias_to_fp16, dilations = input_29_dilations_0, groups = input_29_groups_0, pad = input_29_pad_0, pad_type = input_29_pad_type_0, strides = input_29_strides_0, weight = weight_19_to_fp16_palettized, x = input_25_cast_fp16)[name = tensor<string, []>("input_29_cast_fp16")]; |
| tensor<fp16, [2048, 128]> decode_0_norm2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [262144]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9338752))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9600960))), name = tensor<string, []>("decode_0_norm2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([2048, 128])]; |
| tensor<fp16, [2048]> decode_0_norm2_fc_bias_to_fp16 = const()[name = tensor<string, []>("decode_0_norm2_fc_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9601536)))]; |
| tensor<fp16, [1, 2048]> linear_3_cast_fp16 = linear(bias = decode_0_norm2_fc_bias_to_fp16, weight = decode_0_norm2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_3_cast_fp16")]; |
| tensor<int32, [3]> var_254 = const()[name = tensor<string, []>("op_254"), val = tensor<int32, [3]>([1, 2048, 1])]; |
| tensor<fp16, [1, 2048, 1]> h_15_cast_fp16 = reshape(shape = var_254, x = linear_3_cast_fp16)[name = tensor<string, []>("h_15_cast_fp16")]; |
| tensor<int32, [2]> var_256_split_sizes_0 = const()[name = tensor<string, []>("op_256_split_sizes_0"), val = tensor<int32, [2]>([1024, 1024])]; |
| tensor<int32, []> var_256_axis_0 = const()[name = tensor<string, []>("op_256_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 1024, 1]> var_256_cast_fp16_0, tensor<fp16, [1, 1024, 1]> var_256_cast_fp16_1 = split(axis = var_256_axis_0, split_sizes = var_256_split_sizes_0, x = h_15_cast_fp16)[name = tensor<string, []>("op_256_cast_fp16")]; |
| tensor<fp16, []> var_258_promoted_to_fp16 = const()[name = tensor<string, []>("op_258_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 1024, 1]> var_259_cast_fp16 = add(x = var_256_cast_fp16_0, y = var_258_promoted_to_fp16)[name = tensor<string, []>("op_259_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> var_262_cast_fp16 = instance_norm(beta = encode_norm2_norm_bias_to_fp16, epsilon = var_200_to_fp16, gamma = encode_norm2_norm_weight_to_fp16, x = input_29_cast_fp16)[name = tensor<string, []>("op_262_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> var_263_cast_fp16 = mul(x = var_259_cast_fp16, y = var_262_cast_fp16)[name = tensor<string, []>("op_263_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> input_31_cast_fp16 = add(x = var_263_cast_fp16, y = var_256_cast_fp16_1)[name = tensor<string, []>("input_31_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> input_33_cast_fp16 = leaky_relu(alpha = var_197, x = input_31_cast_fp16)[name = tensor<string, []>("input_33_cast_fp16")]; |
| tensor<string, []> out_3_pad_type_0 = const()[name = tensor<string, []>("out_3_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> out_3_pad_0 = const()[name = tensor<string, []>("out_3_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> out_3_strides_0 = const()[name = tensor<string, []>("out_3_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> out_3_dilations_0 = const()[name = tensor<string, []>("out_3_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> out_3_groups_0 = const()[name = tensor<string, []>("out_3_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1024, 1024, 3]> weight_23_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9605696))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12751488))), name = tensor<string, []>("weight_23_to_fp16_palettized"), shape = tensor<uint32, [3]>([1024, 1024, 3])]; |
| tensor<fp16, [1024]> decode_0_conv2_bias_to_fp16 = const()[name = tensor<string, []>("decode_0_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12752064)))]; |
| tensor<fp16, [1, 1024, ?]> out_3_cast_fp16 = conv(bias = decode_0_conv2_bias_to_fp16, dilations = out_3_dilations_0, groups = out_3_groups_0, pad = out_3_pad_0, pad_type = out_3_pad_type_0, strides = out_3_strides_0, weight = weight_23_to_fp16_palettized, x = input_33_cast_fp16)[name = tensor<string, []>("out_3_cast_fp16")]; |
| tensor<string, []> var_279_pad_type_0 = const()[name = tensor<string, []>("op_279_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [1]> var_279_strides_0 = const()[name = tensor<string, []>("op_279_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [2]> var_279_pad_0 = const()[name = tensor<string, []>("op_279_pad_0"), val = tensor<int32, [2]>([0, 0])]; |
| tensor<int32, [1]> var_279_dilations_0 = const()[name = tensor<string, []>("op_279_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> var_279_groups_0 = const()[name = tensor<string, []>("op_279_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1024, 1090, 1]> weight_25_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1116160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12754176))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13870400))), name = tensor<string, []>("weight_25_to_fp16_palettized"), shape = tensor<uint32, [3]>([1024, 1090, 1])]; |
| tensor<fp16, [1, 1024, ?]> var_279_cast_fp16 = conv(dilations = var_279_dilations_0, groups = var_279_groups_0, pad = var_279_pad_0, pad_type = var_279_pad_type_0, strides = var_279_strides_0, weight = weight_25_to_fp16_palettized, x = input_21_cast_fp16)[name = tensor<string, []>("op_279_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> var_280_cast_fp16 = add(x = out_3_cast_fp16, y = var_279_cast_fp16)[name = tensor<string, []>("op_280_cast_fp16")]; |
| tensor<fp16, []> var_281_to_fp16 = const()[name = tensor<string, []>("op_281_to_fp16"), val = tensor<fp16, []>(0x1.6ap-1)]; |
| tensor<fp16, [1, 1024, ?]> x_3_cast_fp16 = mul(x = var_280_cast_fp16, y = var_281_to_fp16)[name = tensor<string, []>("x_3_cast_fp16")]; |
| tensor<int32, []> var_284 = const()[name = tensor<string, []>("op_284"), val = tensor<int32, []>(1)]; |
| tensor<bool, []> input_37_interleave_0 = const()[name = tensor<string, []>("input_37_interleave_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [1, 1090, ?]> input_37_cast_fp16 = concat(axis = var_284, interleave = input_37_interleave_0, values = (x_3_cast_fp16, asr_res_1_cast_fp16, F0_cast_fp16, N_feat_cast_fp16))[name = tensor<string, []>("input_37_cast_fp16")]; |
| tensor<fp32, []> var_288 = const()[name = tensor<string, []>("op_288"), val = tensor<fp32, []>(0x1.99999ap-3)]; |
| tensor<fp16, [2180, 128]> decode_1_norm1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [279040]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13870976))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14150080))), name = tensor<string, []>("decode_1_norm1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([2180, 128])]; |
| tensor<fp16, [2180]> decode_1_norm1_fc_bias_to_fp16 = const()[name = tensor<string, []>("decode_1_norm1_fc_bias_to_fp16"), val = tensor<fp16, [2180]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14150656)))]; |
| tensor<fp16, [1, 2180]> linear_4_cast_fp16 = linear(bias = decode_1_norm1_fc_bias_to_fp16, weight = decode_1_norm1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_4_cast_fp16")]; |
| tensor<int32, [3]> var_318 = const()[name = tensor<string, []>("op_318"), val = tensor<int32, [3]>([1, 2180, 1])]; |
| tensor<fp16, [1, 2180, 1]> h_19_cast_fp16 = reshape(shape = var_318, x = linear_4_cast_fp16)[name = tensor<string, []>("h_19_cast_fp16")]; |
| tensor<int32, [2]> var_320_split_sizes_0 = const()[name = tensor<string, []>("op_320_split_sizes_0"), val = tensor<int32, [2]>([1090, 1090])]; |
| tensor<int32, []> var_320_axis_0 = const()[name = tensor<string, []>("op_320_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 1090, 1]> var_320_cast_fp16_0, tensor<fp16, [1, 1090, 1]> var_320_cast_fp16_1 = split(axis = var_320_axis_0, split_sizes = var_320_split_sizes_0, x = h_19_cast_fp16)[name = tensor<string, []>("op_320_cast_fp16")]; |
| tensor<fp16, []> var_322_promoted_to_fp16 = const()[name = tensor<string, []>("op_322_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 1090, 1]> var_323_cast_fp16 = add(x = var_320_cast_fp16_0, y = var_322_promoted_to_fp16)[name = tensor<string, []>("op_323_cast_fp16")]; |
| tensor<fp16, []> var_291_to_fp16 = const()[name = tensor<string, []>("op_291_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| tensor<fp16, [1, 1090, ?]> var_326_cast_fp16 = instance_norm(beta = decode_0_norm1_norm_bias_to_fp16, epsilon = var_291_to_fp16, gamma = decode_0_norm1_norm_weight_to_fp16, x = input_37_cast_fp16)[name = tensor<string, []>("op_326_cast_fp16")]; |
| tensor<fp16, [1, 1090, ?]> var_327_cast_fp16 = mul(x = var_323_cast_fp16, y = var_326_cast_fp16)[name = tensor<string, []>("op_327_cast_fp16")]; |
| tensor<fp16, [1, 1090, ?]> input_39_cast_fp16 = add(x = var_327_cast_fp16, y = var_320_cast_fp16_1)[name = tensor<string, []>("input_39_cast_fp16")]; |
| tensor<fp16, [1, 1090, ?]> input_41_cast_fp16 = leaky_relu(alpha = var_288, x = input_39_cast_fp16)[name = tensor<string, []>("input_41_cast_fp16")]; |
| tensor<string, []> input_45_pad_type_0 = const()[name = tensor<string, []>("input_45_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_45_pad_0 = const()[name = tensor<string, []>("input_45_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> input_45_strides_0 = const()[name = tensor<string, []>("input_45_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> input_45_dilations_0 = const()[name = tensor<string, []>("input_45_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_45_groups_0 = const()[name = tensor<string, []>("input_45_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1024, 1090, 3]> weight_29_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3348480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14155136))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17503680))), name = tensor<string, []>("weight_29_to_fp16_palettized"), shape = tensor<uint32, [3]>([1024, 1090, 3])]; |
| tensor<fp16, [1024]> decode_1_conv1_bias_to_fp16 = const()[name = tensor<string, []>("decode_1_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17504256)))]; |
| tensor<fp16, [1, 1024, ?]> input_45_cast_fp16 = conv(bias = decode_1_conv1_bias_to_fp16, dilations = input_45_dilations_0, groups = input_45_groups_0, pad = input_45_pad_0, pad_type = input_45_pad_type_0, strides = input_45_strides_0, weight = weight_29_to_fp16_palettized, x = input_41_cast_fp16)[name = tensor<string, []>("input_45_cast_fp16")]; |
| tensor<fp16, [2048, 128]> decode_1_norm2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [262144]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17506368))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17768576))), name = tensor<string, []>("decode_1_norm2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([2048, 128])]; |
| tensor<fp16, [2048]> decode_1_norm2_fc_bias_to_fp16 = const()[name = tensor<string, []>("decode_1_norm2_fc_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17769152)))]; |
| tensor<fp16, [1, 2048]> linear_5_cast_fp16 = linear(bias = decode_1_norm2_fc_bias_to_fp16, weight = decode_1_norm2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_5_cast_fp16")]; |
| tensor<int32, [3]> var_345 = const()[name = tensor<string, []>("op_345"), val = tensor<int32, [3]>([1, 2048, 1])]; |
| tensor<fp16, [1, 2048, 1]> h_23_cast_fp16 = reshape(shape = var_345, x = linear_5_cast_fp16)[name = tensor<string, []>("h_23_cast_fp16")]; |
| tensor<int32, [2]> var_347_split_sizes_0 = const()[name = tensor<string, []>("op_347_split_sizes_0"), val = tensor<int32, [2]>([1024, 1024])]; |
| tensor<int32, []> var_347_axis_0 = const()[name = tensor<string, []>("op_347_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 1024, 1]> var_347_cast_fp16_0, tensor<fp16, [1, 1024, 1]> var_347_cast_fp16_1 = split(axis = var_347_axis_0, split_sizes = var_347_split_sizes_0, x = h_23_cast_fp16)[name = tensor<string, []>("op_347_cast_fp16")]; |
| tensor<fp16, []> var_349_promoted_to_fp16 = const()[name = tensor<string, []>("op_349_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 1024, 1]> var_350_cast_fp16 = add(x = var_347_cast_fp16_0, y = var_349_promoted_to_fp16)[name = tensor<string, []>("op_350_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> var_353_cast_fp16 = instance_norm(beta = encode_norm2_norm_bias_to_fp16, epsilon = var_291_to_fp16, gamma = encode_norm2_norm_weight_to_fp16, x = input_45_cast_fp16)[name = tensor<string, []>("op_353_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> var_354_cast_fp16 = mul(x = var_350_cast_fp16, y = var_353_cast_fp16)[name = tensor<string, []>("op_354_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> input_47_cast_fp16 = add(x = var_354_cast_fp16, y = var_347_cast_fp16_1)[name = tensor<string, []>("input_47_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> input_49_cast_fp16 = leaky_relu(alpha = var_288, x = input_47_cast_fp16)[name = tensor<string, []>("input_49_cast_fp16")]; |
| tensor<string, []> out_5_pad_type_0 = const()[name = tensor<string, []>("out_5_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> out_5_pad_0 = const()[name = tensor<string, []>("out_5_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> out_5_strides_0 = const()[name = tensor<string, []>("out_5_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> out_5_dilations_0 = const()[name = tensor<string, []>("out_5_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> out_5_groups_0 = const()[name = tensor<string, []>("out_5_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1024, 1024, 3]> weight_33_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17773312))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20919104))), name = tensor<string, []>("weight_33_to_fp16_palettized"), shape = tensor<uint32, [3]>([1024, 1024, 3])]; |
| tensor<fp16, [1024]> decode_1_conv2_bias_to_fp16 = const()[name = tensor<string, []>("decode_1_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20919680)))]; |
| tensor<fp16, [1, 1024, ?]> out_5_cast_fp16 = conv(bias = decode_1_conv2_bias_to_fp16, dilations = out_5_dilations_0, groups = out_5_groups_0, pad = out_5_pad_0, pad_type = out_5_pad_type_0, strides = out_5_strides_0, weight = weight_33_to_fp16_palettized, x = input_49_cast_fp16)[name = tensor<string, []>("out_5_cast_fp16")]; |
| tensor<string, []> var_370_pad_type_0 = const()[name = tensor<string, []>("op_370_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [1]> var_370_strides_0 = const()[name = tensor<string, []>("op_370_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [2]> var_370_pad_0 = const()[name = tensor<string, []>("op_370_pad_0"), val = tensor<int32, [2]>([0, 0])]; |
| tensor<int32, [1]> var_370_dilations_0 = const()[name = tensor<string, []>("op_370_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> var_370_groups_0 = const()[name = tensor<string, []>("op_370_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1024, 1090, 1]> weight_35_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1116160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20921792))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22038016))), name = tensor<string, []>("weight_35_to_fp16_palettized"), shape = tensor<uint32, [3]>([1024, 1090, 1])]; |
| tensor<fp16, [1, 1024, ?]> var_370_cast_fp16 = conv(dilations = var_370_dilations_0, groups = var_370_groups_0, pad = var_370_pad_0, pad_type = var_370_pad_type_0, strides = var_370_strides_0, weight = weight_35_to_fp16_palettized, x = input_37_cast_fp16)[name = tensor<string, []>("op_370_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> var_371_cast_fp16 = add(x = out_5_cast_fp16, y = var_370_cast_fp16)[name = tensor<string, []>("op_371_cast_fp16")]; |
| tensor<fp16, []> var_372_to_fp16 = const()[name = tensor<string, []>("op_372_to_fp16"), val = tensor<fp16, []>(0x1.6ap-1)]; |
| tensor<fp16, [1, 1024, ?]> x_5_cast_fp16 = mul(x = var_371_cast_fp16, y = var_372_to_fp16)[name = tensor<string, []>("x_5_cast_fp16")]; |
| tensor<int32, []> var_375 = const()[name = tensor<string, []>("op_375"), val = tensor<int32, []>(1)]; |
| tensor<bool, []> input_53_interleave_0 = const()[name = tensor<string, []>("input_53_interleave_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [1, 1090, ?]> input_53_cast_fp16 = concat(axis = var_375, interleave = input_53_interleave_0, values = (x_5_cast_fp16, asr_res_1_cast_fp16, F0_cast_fp16, N_feat_cast_fp16))[name = tensor<string, []>("input_53_cast_fp16")]; |
| tensor<fp32, []> var_379 = const()[name = tensor<string, []>("op_379"), val = tensor<fp32, []>(0x1.99999ap-3)]; |
| tensor<fp16, [2180, 128]> decode_2_norm1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [279040]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22038592))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22317696))), name = tensor<string, []>("decode_2_norm1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([2180, 128])]; |
| tensor<fp16, [2180]> decode_2_norm1_fc_bias_to_fp16 = const()[name = tensor<string, []>("decode_2_norm1_fc_bias_to_fp16"), val = tensor<fp16, [2180]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22318272)))]; |
| tensor<fp16, [1, 2180]> linear_6_cast_fp16 = linear(bias = decode_2_norm1_fc_bias_to_fp16, weight = decode_2_norm1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_6_cast_fp16")]; |
| tensor<int32, [3]> var_409 = const()[name = tensor<string, []>("op_409"), val = tensor<int32, [3]>([1, 2180, 1])]; |
| tensor<fp16, [1, 2180, 1]> h_27_cast_fp16 = reshape(shape = var_409, x = linear_6_cast_fp16)[name = tensor<string, []>("h_27_cast_fp16")]; |
| tensor<int32, [2]> var_411_split_sizes_0 = const()[name = tensor<string, []>("op_411_split_sizes_0"), val = tensor<int32, [2]>([1090, 1090])]; |
| tensor<int32, []> var_411_axis_0 = const()[name = tensor<string, []>("op_411_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 1090, 1]> var_411_cast_fp16_0, tensor<fp16, [1, 1090, 1]> var_411_cast_fp16_1 = split(axis = var_411_axis_0, split_sizes = var_411_split_sizes_0, x = h_27_cast_fp16)[name = tensor<string, []>("op_411_cast_fp16")]; |
| tensor<fp16, []> var_413_promoted_to_fp16 = const()[name = tensor<string, []>("op_413_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 1090, 1]> var_414_cast_fp16 = add(x = var_411_cast_fp16_0, y = var_413_promoted_to_fp16)[name = tensor<string, []>("op_414_cast_fp16")]; |
| tensor<fp16, []> var_382_to_fp16 = const()[name = tensor<string, []>("op_382_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| tensor<fp16, [1, 1090, ?]> var_417_cast_fp16 = instance_norm(beta = decode_0_norm1_norm_bias_to_fp16, epsilon = var_382_to_fp16, gamma = decode_0_norm1_norm_weight_to_fp16, x = input_53_cast_fp16)[name = tensor<string, []>("op_417_cast_fp16")]; |
| tensor<fp16, [1, 1090, ?]> var_418_cast_fp16 = mul(x = var_414_cast_fp16, y = var_417_cast_fp16)[name = tensor<string, []>("op_418_cast_fp16")]; |
| tensor<fp16, [1, 1090, ?]> input_55_cast_fp16 = add(x = var_418_cast_fp16, y = var_411_cast_fp16_1)[name = tensor<string, []>("input_55_cast_fp16")]; |
| tensor<fp16, [1, 1090, ?]> input_57_cast_fp16 = leaky_relu(alpha = var_379, x = input_55_cast_fp16)[name = tensor<string, []>("input_57_cast_fp16")]; |
| tensor<string, []> input_61_pad_type_0 = const()[name = tensor<string, []>("input_61_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_61_pad_0 = const()[name = tensor<string, []>("input_61_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> input_61_strides_0 = const()[name = tensor<string, []>("input_61_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> input_61_dilations_0 = const()[name = tensor<string, []>("input_61_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_61_groups_0 = const()[name = tensor<string, []>("input_61_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1024, 1090, 3]> weight_39_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3348480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22322752))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25671296))), name = tensor<string, []>("weight_39_to_fp16_palettized"), shape = tensor<uint32, [3]>([1024, 1090, 3])]; |
| tensor<fp16, [1024]> decode_2_conv1_bias_to_fp16 = const()[name = tensor<string, []>("decode_2_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25671872)))]; |
| tensor<fp16, [1, 1024, ?]> input_61_cast_fp16 = conv(bias = decode_2_conv1_bias_to_fp16, dilations = input_61_dilations_0, groups = input_61_groups_0, pad = input_61_pad_0, pad_type = input_61_pad_type_0, strides = input_61_strides_0, weight = weight_39_to_fp16_palettized, x = input_57_cast_fp16)[name = tensor<string, []>("input_61_cast_fp16")]; |
| tensor<fp16, [2048, 128]> decode_2_norm2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [262144]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25673984))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25936192))), name = tensor<string, []>("decode_2_norm2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([2048, 128])]; |
| tensor<fp16, [2048]> decode_2_norm2_fc_bias_to_fp16 = const()[name = tensor<string, []>("decode_2_norm2_fc_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25936768)))]; |
| tensor<fp16, [1, 2048]> linear_7_cast_fp16 = linear(bias = decode_2_norm2_fc_bias_to_fp16, weight = decode_2_norm2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_7_cast_fp16")]; |
| tensor<int32, [3]> var_436 = const()[name = tensor<string, []>("op_436"), val = tensor<int32, [3]>([1, 2048, 1])]; |
| tensor<fp16, [1, 2048, 1]> h_31_cast_fp16 = reshape(shape = var_436, x = linear_7_cast_fp16)[name = tensor<string, []>("h_31_cast_fp16")]; |
| tensor<int32, [2]> var_438_split_sizes_0 = const()[name = tensor<string, []>("op_438_split_sizes_0"), val = tensor<int32, [2]>([1024, 1024])]; |
| tensor<int32, []> var_438_axis_0 = const()[name = tensor<string, []>("op_438_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 1024, 1]> var_438_cast_fp16_0, tensor<fp16, [1, 1024, 1]> var_438_cast_fp16_1 = split(axis = var_438_axis_0, split_sizes = var_438_split_sizes_0, x = h_31_cast_fp16)[name = tensor<string, []>("op_438_cast_fp16")]; |
| tensor<fp16, []> var_440_promoted_to_fp16 = const()[name = tensor<string, []>("op_440_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 1024, 1]> var_441_cast_fp16 = add(x = var_438_cast_fp16_0, y = var_440_promoted_to_fp16)[name = tensor<string, []>("op_441_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> var_444_cast_fp16 = instance_norm(beta = encode_norm2_norm_bias_to_fp16, epsilon = var_382_to_fp16, gamma = encode_norm2_norm_weight_to_fp16, x = input_61_cast_fp16)[name = tensor<string, []>("op_444_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> var_445_cast_fp16 = mul(x = var_441_cast_fp16, y = var_444_cast_fp16)[name = tensor<string, []>("op_445_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> input_63_cast_fp16 = add(x = var_445_cast_fp16, y = var_438_cast_fp16_1)[name = tensor<string, []>("input_63_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> input_65_cast_fp16 = leaky_relu(alpha = var_379, x = input_63_cast_fp16)[name = tensor<string, []>("input_65_cast_fp16")]; |
| tensor<string, []> out_7_pad_type_0 = const()[name = tensor<string, []>("out_7_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> out_7_pad_0 = const()[name = tensor<string, []>("out_7_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> out_7_strides_0 = const()[name = tensor<string, []>("out_7_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> out_7_dilations_0 = const()[name = tensor<string, []>("out_7_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> out_7_groups_0 = const()[name = tensor<string, []>("out_7_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1024, 1024, 3]> weight_43_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25940928))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29086720))), name = tensor<string, []>("weight_43_to_fp16_palettized"), shape = tensor<uint32, [3]>([1024, 1024, 3])]; |
| tensor<fp16, [1024]> decode_2_conv2_bias_to_fp16 = const()[name = tensor<string, []>("decode_2_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29087296)))]; |
| tensor<fp16, [1, 1024, ?]> out_7_cast_fp16 = conv(bias = decode_2_conv2_bias_to_fp16, dilations = out_7_dilations_0, groups = out_7_groups_0, pad = out_7_pad_0, pad_type = out_7_pad_type_0, strides = out_7_strides_0, weight = weight_43_to_fp16_palettized, x = input_65_cast_fp16)[name = tensor<string, []>("out_7_cast_fp16")]; |
| tensor<string, []> var_461_pad_type_0 = const()[name = tensor<string, []>("op_461_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [1]> var_461_strides_0 = const()[name = tensor<string, []>("op_461_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [2]> var_461_pad_0 = const()[name = tensor<string, []>("op_461_pad_0"), val = tensor<int32, [2]>([0, 0])]; |
| tensor<int32, [1]> var_461_dilations_0 = const()[name = tensor<string, []>("op_461_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> var_461_groups_0 = const()[name = tensor<string, []>("op_461_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1024, 1090, 1]> weight_45_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1116160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29089408))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30205632))), name = tensor<string, []>("weight_45_to_fp16_palettized"), shape = tensor<uint32, [3]>([1024, 1090, 1])]; |
| tensor<fp16, [1, 1024, ?]> var_461_cast_fp16 = conv(dilations = var_461_dilations_0, groups = var_461_groups_0, pad = var_461_pad_0, pad_type = var_461_pad_type_0, strides = var_461_strides_0, weight = weight_45_to_fp16_palettized, x = input_53_cast_fp16)[name = tensor<string, []>("op_461_cast_fp16")]; |
| tensor<fp16, [1, 1024, ?]> var_462_cast_fp16 = add(x = out_7_cast_fp16, y = var_461_cast_fp16)[name = tensor<string, []>("op_462_cast_fp16")]; |
| tensor<fp16, []> var_463_to_fp16 = const()[name = tensor<string, []>("op_463_to_fp16"), val = tensor<fp16, []>(0x1.6ap-1)]; |
| tensor<fp16, [1, 1024, ?]> x_7_cast_fp16 = mul(x = var_462_cast_fp16, y = var_463_to_fp16)[name = tensor<string, []>("x_7_cast_fp16")]; |
| tensor<int32, []> var_466 = const()[name = tensor<string, []>("op_466"), val = tensor<int32, []>(1)]; |
| tensor<bool, []> input_69_interleave_0 = const()[name = tensor<string, []>("input_69_interleave_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [1, 1090, ?]> input_69_cast_fp16 = concat(axis = var_466, interleave = input_69_interleave_0, values = (x_7_cast_fp16, asr_res_1_cast_fp16, F0_cast_fp16, N_feat_cast_fp16))[name = tensor<string, []>("input_69_cast_fp16")]; |
| tensor<fp32, []> var_472 = const()[name = tensor<string, []>("op_472"), val = tensor<fp32, []>(0x1.99999ap-3)]; |
| tensor<fp16, [2180, 128]> decode_3_norm1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [279040]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30206208))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30485312))), name = tensor<string, []>("decode_3_norm1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([2180, 128])]; |
| tensor<fp16, [2180]> decode_3_norm1_fc_bias_to_fp16 = const()[name = tensor<string, []>("decode_3_norm1_fc_bias_to_fp16"), val = tensor<fp16, [2180]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30485888)))]; |
| tensor<fp16, [1, 2180]> linear_8_cast_fp16 = linear(bias = decode_3_norm1_fc_bias_to_fp16, weight = decode_3_norm1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_8_cast_fp16")]; |
| tensor<int32, [3]> var_508 = const()[name = tensor<string, []>("op_508"), val = tensor<int32, [3]>([1, 2180, 1])]; |
| tensor<fp16, [1, 2180, 1]> h_35_cast_fp16 = reshape(shape = var_508, x = linear_8_cast_fp16)[name = tensor<string, []>("h_35_cast_fp16")]; |
| tensor<int32, [2]> var_510_split_sizes_0 = const()[name = tensor<string, []>("op_510_split_sizes_0"), val = tensor<int32, [2]>([1090, 1090])]; |
| tensor<int32, []> var_510_axis_0 = const()[name = tensor<string, []>("op_510_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 1090, 1]> var_510_cast_fp16_0, tensor<fp16, [1, 1090, 1]> var_510_cast_fp16_1 = split(axis = var_510_axis_0, split_sizes = var_510_split_sizes_0, x = h_35_cast_fp16)[name = tensor<string, []>("op_510_cast_fp16")]; |
| tensor<fp16, []> var_512_promoted_to_fp16 = const()[name = tensor<string, []>("op_512_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 1090, 1]> var_513_cast_fp16 = add(x = var_510_cast_fp16_0, y = var_512_promoted_to_fp16)[name = tensor<string, []>("op_513_cast_fp16")]; |
| tensor<fp16, []> var_476_to_fp16 = const()[name = tensor<string, []>("op_476_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| tensor<fp16, [1, 1090, ?]> var_516_cast_fp16 = instance_norm(beta = decode_0_norm1_norm_bias_to_fp16, epsilon = var_476_to_fp16, gamma = decode_0_norm1_norm_weight_to_fp16, x = input_69_cast_fp16)[name = tensor<string, []>("op_516_cast_fp16")]; |
| tensor<fp16, [1, 1090, ?]> var_517_cast_fp16 = mul(x = var_513_cast_fp16, y = var_516_cast_fp16)[name = tensor<string, []>("op_517_cast_fp16")]; |
| tensor<fp16, [1, 1090, ?]> input_71_cast_fp16 = add(x = var_517_cast_fp16, y = var_510_cast_fp16_1)[name = tensor<string, []>("input_71_cast_fp16")]; |
| tensor<fp16, [1, 1090, ?]> input_73_cast_fp16 = leaky_relu(alpha = var_472, x = input_71_cast_fp16)[name = tensor<string, []>("input_73_cast_fp16")]; |
| tensor<string, []> conv_transpose_0_pad_type_0 = const()[name = tensor<string, []>("conv_transpose_0_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> conv_transpose_0_pad_0 = const()[name = tensor<string, []>("conv_transpose_0_pad_0"), val = tensor<int32, [2]>([0, 0])]; |
| tensor<int32, [1]> conv_transpose_0_strides_0 = const()[name = tensor<string, []>("conv_transpose_0_strides_0"), val = tensor<int32, [1]>([2])]; |
| tensor<int32, []> conv_transpose_0_groups_0 = const()[name = tensor<string, []>("conv_transpose_0_groups_0"), val = tensor<int32, []>(1090)]; |
| tensor<int32, [1]> conv_transpose_0_dilations_0 = const()[name = tensor<string, []>("conv_transpose_0_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<fp16, [1090, 1, 3]> op_520_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3270]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30490368))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30493760))), name = tensor<string, []>("op_520_to_fp16_palettized"), shape = tensor<uint32, [3]>([1090, 1, 3])]; |
| tensor<fp16, [1090]> decode_3_pool_bias_to_fp16 = const()[name = tensor<string, []>("decode_3_pool_bias_to_fp16"), val = tensor<fp16, [1090]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30494336)))]; |
| tensor<fp16, [1, 1090, ?]> conv_transpose_0_cast_fp16 = conv_transpose(bias = decode_3_pool_bias_to_fp16, dilations = conv_transpose_0_dilations_0, groups = conv_transpose_0_groups_0, pad = conv_transpose_0_pad_0, pad_type = conv_transpose_0_pad_type_0, strides = conv_transpose_0_strides_0, weight = op_520_to_fp16_palettized, x = input_73_cast_fp16)[name = tensor<string, []>("conv_transpose_0_cast_fp16")]; |
| tensor<int32, [3]> input_75_begin_0 = const()[name = tensor<string, []>("input_75_begin_0"), val = tensor<int32, [3]>([0, 0, 1])]; |
| tensor<int32, [3]> input_75_end_0 = const()[name = tensor<string, []>("input_75_end_0"), val = tensor<int32, [3]>([0, 0, 0])]; |
| tensor<bool, [3]> input_75_begin_mask_0 = const()[name = tensor<string, []>("input_75_begin_mask_0"), val = tensor<bool, [3]>([true, true, false])]; |
| tensor<bool, [3]> input_75_end_mask_0 = const()[name = tensor<string, []>("input_75_end_mask_0"), val = tensor<bool, [3]>([true, true, true])]; |
| tensor<fp16, [1, 1090, ?]> input_75_cast_fp16 = slice_by_index(begin = input_75_begin_0, begin_mask = input_75_begin_mask_0, end = input_75_end_0, end_mask = input_75_end_mask_0, x = conv_transpose_0_cast_fp16)[name = tensor<string, []>("input_75_cast_fp16")]; |
| tensor<string, []> input_79_pad_type_0 = const()[name = tensor<string, []>("input_79_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_79_pad_0 = const()[name = tensor<string, []>("input_79_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> input_79_strides_0 = const()[name = tensor<string, []>("input_79_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> input_79_dilations_0 = const()[name = tensor<string, []>("input_79_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_79_groups_0 = const()[name = tensor<string, []>("input_79_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [512, 1090, 3]> weight_49_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1674240]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30496640))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32170944))), name = tensor<string, []>("weight_49_to_fp16_palettized"), shape = tensor<uint32, [3]>([512, 1090, 3])]; |
| tensor<fp16, [512]> decode_3_conv1_bias_to_fp16 = const()[name = tensor<string, []>("decode_3_conv1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32171520)))]; |
| tensor<fp16, [1, 512, ?]> input_79_cast_fp16 = conv(bias = decode_3_conv1_bias_to_fp16, dilations = input_79_dilations_0, groups = input_79_groups_0, pad = input_79_pad_0, pad_type = input_79_pad_type_0, strides = input_79_strides_0, weight = weight_49_to_fp16_palettized, x = input_75_cast_fp16)[name = tensor<string, []>("input_79_cast_fp16")]; |
| tensor<fp16, [1024, 128]> decode_3_norm2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [131072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32172608))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32303744))), name = tensor<string, []>("decode_3_norm2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 128])]; |
| tensor<fp16, [1024]> decode_3_norm2_fc_bias_to_fp16 = const()[name = tensor<string, []>("decode_3_norm2_fc_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32304320)))]; |
| tensor<fp16, [1, 1024]> linear_9_cast_fp16 = linear(bias = decode_3_norm2_fc_bias_to_fp16, weight = decode_3_norm2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_9_cast_fp16")]; |
| tensor<int32, [3]> var_542 = const()[name = tensor<string, []>("op_542"), val = tensor<int32, [3]>([1, 1024, 1])]; |
| tensor<fp16, [1, 1024, 1]> h_39_cast_fp16 = reshape(shape = var_542, x = linear_9_cast_fp16)[name = tensor<string, []>("h_39_cast_fp16")]; |
| tensor<int32, [2]> var_544_split_sizes_0 = const()[name = tensor<string, []>("op_544_split_sizes_0"), val = tensor<int32, [2]>([512, 512])]; |
| tensor<int32, []> var_544_axis_0 = const()[name = tensor<string, []>("op_544_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 512, 1]> var_544_cast_fp16_0, tensor<fp16, [1, 512, 1]> var_544_cast_fp16_1 = split(axis = var_544_axis_0, split_sizes = var_544_split_sizes_0, x = h_39_cast_fp16)[name = tensor<string, []>("op_544_cast_fp16")]; |
| tensor<fp16, []> var_546_promoted_to_fp16 = const()[name = tensor<string, []>("op_546_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 512, 1]> var_547_cast_fp16 = add(x = var_544_cast_fp16_0, y = var_546_promoted_to_fp16)[name = tensor<string, []>("op_547_cast_fp16")]; |
| tensor<fp16, [512]> decode_3_norm2_norm_weight_to_fp16 = const()[name = tensor<string, []>("decode_3_norm2_norm_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32306432)))]; |
| tensor<fp16, [512]> decode_3_norm2_norm_bias_to_fp16 = const()[name = tensor<string, []>("decode_3_norm2_norm_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32307520)))]; |
| tensor<fp16, [1, 512, ?]> var_550_cast_fp16 = instance_norm(beta = decode_3_norm2_norm_bias_to_fp16, epsilon = var_476_to_fp16, gamma = decode_3_norm2_norm_weight_to_fp16, x = input_79_cast_fp16)[name = tensor<string, []>("op_550_cast_fp16")]; |
| tensor<fp16, [1, 512, ?]> var_551_cast_fp16 = mul(x = var_547_cast_fp16, y = var_550_cast_fp16)[name = tensor<string, []>("op_551_cast_fp16")]; |
| tensor<fp16, [1, 512, ?]> input_81_cast_fp16 = add(x = var_551_cast_fp16, y = var_544_cast_fp16_1)[name = tensor<string, []>("input_81_cast_fp16")]; |
| tensor<fp16, [1, 512, ?]> input_83_cast_fp16 = leaky_relu(alpha = var_472, x = input_81_cast_fp16)[name = tensor<string, []>("input_83_cast_fp16")]; |
| tensor<string, []> out_pad_type_0 = const()[name = tensor<string, []>("out_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> out_pad_0 = const()[name = tensor<string, []>("out_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> out_strides_0 = const()[name = tensor<string, []>("out_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> out_dilations_0 = const()[name = tensor<string, []>("out_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> out_groups_0 = const()[name = tensor<string, []>("out_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [512, 512, 3]> weight_53_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32308608))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33095104))), name = tensor<string, []>("weight_53_to_fp16_palettized"), shape = tensor<uint32, [3]>([512, 512, 3])]; |
| tensor<fp16, [512]> decode_3_conv2_bias_to_fp16 = const()[name = tensor<string, []>("decode_3_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33095680)))]; |
| tensor<fp16, [1, 512, ?]> out_cast_fp16 = conv(bias = decode_3_conv2_bias_to_fp16, dilations = out_dilations_0, groups = out_groups_0, pad = out_pad_0, pad_type = out_pad_type_0, strides = out_strides_0, weight = weight_53_to_fp16_palettized, x = input_83_cast_fp16)[name = tensor<string, []>("out_cast_fp16")]; |
| tensor<int32, [1]> expand_dims_0_axes_0 = const()[name = tensor<string, []>("expand_dims_0_axes_0"), val = tensor<int32, [1]>([3])]; |
| tensor<fp16, [1, 1090, ?, 1]> expand_dims_0_cast_fp16 = expand_dims(axes = expand_dims_0_axes_0, x = input_69_cast_fp16)[name = tensor<string, []>("expand_dims_0_cast_fp16")]; |
| tensor<int32, []> upsample_nearest_neighbor_0_scale_factor_height_0 = const()[name = tensor<string, []>("upsample_nearest_neighbor_0_scale_factor_height_0"), val = tensor<int32, []>(2)]; |
| tensor<int32, []> upsample_nearest_neighbor_0_scale_factor_width_0 = const()[name = tensor<string, []>("upsample_nearest_neighbor_0_scale_factor_width_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 1090, ?, 1]> upsample_nearest_neighbor_0_cast_fp16 = upsample_nearest_neighbor(scale_factor_height = upsample_nearest_neighbor_0_scale_factor_height_0, scale_factor_width = upsample_nearest_neighbor_0_scale_factor_width_0, x = expand_dims_0_cast_fp16)[name = tensor<string, []>("upsample_nearest_neighbor_0_cast_fp16")]; |
| tensor<int32, [1]> input_87_axes_0 = const()[name = tensor<string, []>("input_87_axes_0"), val = tensor<int32, [1]>([3])]; |
| tensor<fp16, [1, 1090, ?]> input_87_cast_fp16 = squeeze(axes = input_87_axes_0, x = upsample_nearest_neighbor_0_cast_fp16)[name = tensor<string, []>("input_87_cast_fp16")]; |
| tensor<string, []> var_569_pad_type_0 = const()[name = tensor<string, []>("op_569_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [1]> var_569_strides_0 = const()[name = tensor<string, []>("op_569_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [2]> var_569_pad_0 = const()[name = tensor<string, []>("op_569_pad_0"), val = tensor<int32, [2]>([0, 0])]; |
| tensor<int32, [1]> var_569_dilations_0 = const()[name = tensor<string, []>("op_569_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> var_569_groups_0 = const()[name = tensor<string, []>("op_569_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [512, 1090, 1]> weight_55_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [558080]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33096768))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33654912))), name = tensor<string, []>("weight_55_to_fp16_palettized"), shape = tensor<uint32, [3]>([512, 1090, 1])]; |
| tensor<fp16, [1, 512, ?]> var_569_cast_fp16 = conv(dilations = var_569_dilations_0, groups = var_569_groups_0, pad = var_569_pad_0, pad_type = var_569_pad_type_0, strides = var_569_strides_0, weight = weight_55_to_fp16_palettized, x = input_87_cast_fp16)[name = tensor<string, []>("op_569_cast_fp16")]; |
| tensor<fp16, [1, 512, ?]> var_570_cast_fp16 = add(x = out_cast_fp16, y = var_569_cast_fp16)[name = tensor<string, []>("op_570_cast_fp16")]; |
| tensor<fp16, []> var_571_to_fp16 = const()[name = tensor<string, []>("op_571_to_fp16"), val = tensor<fp16, []>(0x1.6ap-1)]; |
| tensor<fp16, [1, 512, ?]> input_89_cast_fp16 = mul(x = var_570_cast_fp16, y = var_571_to_fp16)[name = tensor<string, []>("input_89_cast_fp16")]; |
| tensor<fp32, []> var_573 = const()[name = tensor<string, []>("op_573"), val = tensor<fp32, []>(0x1.99999ap-4)]; |
| tensor<fp16, [1, 512, ?]> input_91_cast_fp16 = leaky_relu(alpha = var_573, x = input_89_cast_fp16)[name = tensor<string, []>("input_91_cast_fp16")]; |
| tensor<string, []> x_9_pad_type_0 = const()[name = tensor<string, []>("x_9_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> x_9_pad_0 = const()[name = tensor<string, []>("x_9_pad_0"), val = tensor<int32, [2]>([5, 5])]; |
| tensor<int32, [1]> x_9_strides_0 = const()[name = tensor<string, []>("x_9_strides_0"), val = tensor<int32, [1]>([10])]; |
| tensor<int32, [1]> x_9_dilations_0 = const()[name = tensor<string, []>("x_9_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> x_9_groups_0 = const()[name = tensor<string, []>("x_9_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [512, 256, 20]> op_576_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [2621440]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33655488))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36276992))), name = tensor<string, []>("op_576_to_fp16_palettized"), shape = tensor<uint32, [3]>([512, 256, 20])]; |
| tensor<fp16, [256]> ups_0_bias_to_fp16 = const()[name = tensor<string, []>("ups_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36277568)))]; |
| tensor<fp16, [1, 256, ?]> x_9_cast_fp16 = conv_transpose(bias = ups_0_bias_to_fp16, dilations = x_9_dilations_0, groups = x_9_groups_0, pad = x_9_pad_0, pad_type = x_9_pad_type_0, strides = x_9_strides_0, weight = op_576_to_fp16_palettized, x = input_91_cast_fp16)[name = tensor<string, []>("x_9_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_93_cast_fp16 = add(x = x_9_cast_fp16, y = x_source_0)[name = tensor<string, []>("input_93_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_0_adain1_0_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36278144))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36343744))), name = tensor<string, []>("resblocks_0_adain1_0_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_0_adain1_0_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_0_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36344320)))]; |
| tensor<fp16, [1, 512]> linear_10_cast_fp16 = linear(bias = resblocks_0_adain1_0_fc_bias_to_fp16, weight = resblocks_0_adain1_0_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_10_cast_fp16")]; |
| tensor<int32, [3]> var_679 = const()[name = tensor<string, []>("op_679"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_43_cast_fp16 = reshape(shape = var_679, x = linear_10_cast_fp16)[name = tensor<string, []>("h_43_cast_fp16")]; |
| tensor<int32, [2]> var_681_split_sizes_0 = const()[name = tensor<string, []>("op_681_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_681_axis_0 = const()[name = tensor<string, []>("op_681_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_681_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_681_cast_fp16_1 = split(axis = var_681_axis_0, split_sizes = var_681_split_sizes_0, x = h_43_cast_fp16)[name = tensor<string, []>("op_681_cast_fp16")]; |
| tensor<fp16, []> var_683_promoted_to_fp16 = const()[name = tensor<string, []>("op_683_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_684_cast_fp16 = add(x = var_681_cast_fp16_0, y = var_683_promoted_to_fp16)[name = tensor<string, []>("op_684_cast_fp16")]; |
| tensor<fp16, [256]> resblocks_0_adain1_0_norm_weight_to_fp16 = const()[name = tensor<string, []>("resblocks_0_adain1_0_norm_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36345408)))]; |
| tensor<fp16, [256]> resblocks_0_adain1_0_norm_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_0_adain1_0_norm_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36345984)))]; |
| tensor<fp16, []> var_596_to_fp16 = const()[name = tensor<string, []>("op_596_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| tensor<fp16, [1, 256, ?]> var_687_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_596_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_93_cast_fp16)[name = tensor<string, []>("op_687_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_688_cast_fp16 = mul(x = var_684_cast_fp16, y = var_687_cast_fp16)[name = tensor<string, []>("op_688_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_1_cast_fp16 = add(x = var_688_cast_fp16, y = var_681_cast_fp16_1)[name = tensor<string, []>("xt_1_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_691_to_fp16 = const()[name = tensor<string, []>("op_691_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36346560)))]; |
| tensor<fp16, [1, 256, ?]> var_692_cast_fp16 = mul(x = xt_1_cast_fp16, y = var_691_to_fp16)[name = tensor<string, []>("op_692_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_1_cast_fp16 = cos(x = var_692_cast_fp16)[name = tensor<string, []>("cv_1_cast_fp16")]; |
| tensor<fp16, []> var_694_to_fp16 = const()[name = tensor<string, []>("op_694_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_695_cast_fp16 = mul(x = cv_1_cast_fp16, y = var_694_to_fp16)[name = tensor<string, []>("op_695_cast_fp16")]; |
| tensor<fp16, []> var_696_to_fp16 = const()[name = tensor<string, []>("op_696_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_697_cast_fp16 = add(x = var_695_cast_fp16, y = var_696_to_fp16)[name = tensor<string, []>("op_697_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_698_to_fp16 = const()[name = tensor<string, []>("op_698_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36347136)))]; |
| tensor<fp16, [1, 256, ?]> var_701_cast_fp16 = mul(x = var_697_cast_fp16, y = var_698_to_fp16)[name = tensor<string, []>("op_701_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_95_cast_fp16 = add(x = xt_1_cast_fp16, y = var_701_cast_fp16)[name = tensor<string, []>("input_95_cast_fp16")]; |
| tensor<string, []> input_97_pad_type_0 = const()[name = tensor<string, []>("input_97_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_97_pad_0 = const()[name = tensor<string, []>("input_97_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> input_97_strides_0 = const()[name = tensor<string, []>("input_97_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> input_97_dilations_0 = const()[name = tensor<string, []>("input_97_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_97_groups_0 = const()[name = tensor<string, []>("input_97_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 3]> weight_59_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [196608]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36347712))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36544384))), name = tensor<string, []>("weight_59_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 3])]; |
| tensor<fp16, [256]> resblocks_0_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_0_convs1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36544960)))]; |
| tensor<fp16, [1, 256, ?]> input_97_cast_fp16 = conv(bias = resblocks_0_convs1_0_bias_to_fp16, dilations = input_97_dilations_0, groups = input_97_groups_0, pad = input_97_pad_0, pad_type = input_97_pad_type_0, strides = input_97_strides_0, weight = weight_59_to_fp16_palettized, x = input_95_cast_fp16)[name = tensor<string, []>("input_97_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_0_adain2_0_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36545536))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36611136))), name = tensor<string, []>("resblocks_0_adain2_0_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_0_adain2_0_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_0_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36611712)))]; |
| tensor<fp16, [1, 512]> linear_11_cast_fp16 = linear(bias = resblocks_0_adain2_0_fc_bias_to_fp16, weight = resblocks_0_adain2_0_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_11_cast_fp16")]; |
| tensor<int32, [3]> var_717 = const()[name = tensor<string, []>("op_717"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_47_cast_fp16 = reshape(shape = var_717, x = linear_11_cast_fp16)[name = tensor<string, []>("h_47_cast_fp16")]; |
| tensor<int32, [2]> var_719_split_sizes_0 = const()[name = tensor<string, []>("op_719_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_719_axis_0 = const()[name = tensor<string, []>("op_719_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_719_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_719_cast_fp16_1 = split(axis = var_719_axis_0, split_sizes = var_719_split_sizes_0, x = h_47_cast_fp16)[name = tensor<string, []>("op_719_cast_fp16")]; |
| tensor<fp16, []> var_721_promoted_to_fp16 = const()[name = tensor<string, []>("op_721_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_722_cast_fp16 = add(x = var_719_cast_fp16_0, y = var_721_promoted_to_fp16)[name = tensor<string, []>("op_722_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_725_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_596_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_97_cast_fp16)[name = tensor<string, []>("op_725_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_726_cast_fp16 = mul(x = var_722_cast_fp16, y = var_725_cast_fp16)[name = tensor<string, []>("op_726_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_3_cast_fp16 = add(x = var_726_cast_fp16, y = var_719_cast_fp16_1)[name = tensor<string, []>("xt_3_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_729_to_fp16 = const()[name = tensor<string, []>("op_729_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36612800)))]; |
| tensor<fp16, [1, 256, ?]> var_730_cast_fp16 = mul(x = xt_3_cast_fp16, y = var_729_to_fp16)[name = tensor<string, []>("op_730_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_3_cast_fp16 = cos(x = var_730_cast_fp16)[name = tensor<string, []>("cv_3_cast_fp16")]; |
| tensor<fp16, []> var_732_to_fp16 = const()[name = tensor<string, []>("op_732_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_733_cast_fp16 = mul(x = cv_3_cast_fp16, y = var_732_to_fp16)[name = tensor<string, []>("op_733_cast_fp16")]; |
| tensor<fp16, []> var_734_to_fp16 = const()[name = tensor<string, []>("op_734_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_735_cast_fp16 = add(x = var_733_cast_fp16, y = var_734_to_fp16)[name = tensor<string, []>("op_735_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_736_to_fp16 = const()[name = tensor<string, []>("op_736_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36613376)))]; |
| tensor<fp16, [1, 256, ?]> var_739_cast_fp16 = mul(x = var_735_cast_fp16, y = var_736_to_fp16)[name = tensor<string, []>("op_739_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_99_cast_fp16 = add(x = xt_3_cast_fp16, y = var_739_cast_fp16)[name = tensor<string, []>("input_99_cast_fp16")]; |
| tensor<string, []> xt_5_pad_type_0 = const()[name = tensor<string, []>("xt_5_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_5_pad_0 = const()[name = tensor<string, []>("xt_5_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> xt_5_strides_0 = const()[name = tensor<string, []>("xt_5_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_5_dilations_0 = const()[name = tensor<string, []>("xt_5_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_5_groups_0 = const()[name = tensor<string, []>("xt_5_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 3]> weight_63_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [196608]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36613952))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36810624))), name = tensor<string, []>("weight_63_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 3])]; |
| tensor<fp16, [256]> resblocks_0_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_0_convs2_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36811200)))]; |
| tensor<fp16, [1, 256, ?]> xt_5_cast_fp16 = conv(bias = resblocks_0_convs2_0_bias_to_fp16, dilations = xt_5_dilations_0, groups = xt_5_groups_0, pad = xt_5_pad_0, pad_type = xt_5_pad_type_0, strides = xt_5_strides_0, weight = weight_63_to_fp16_palettized, x = input_99_cast_fp16)[name = tensor<string, []>("xt_5_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_101_cast_fp16 = add(x = xt_5_cast_fp16, y = input_93_cast_fp16)[name = tensor<string, []>("input_101_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_0_adain1_1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36811776))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36877376))), name = tensor<string, []>("resblocks_0_adain1_1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_0_adain1_1_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_0_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36877952)))]; |
| tensor<fp16, [1, 512]> linear_12_cast_fp16 = linear(bias = resblocks_0_adain1_1_fc_bias_to_fp16, weight = resblocks_0_adain1_1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_12_cast_fp16")]; |
| tensor<int32, [3]> var_756 = const()[name = tensor<string, []>("op_756"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_51_cast_fp16 = reshape(shape = var_756, x = linear_12_cast_fp16)[name = tensor<string, []>("h_51_cast_fp16")]; |
| tensor<int32, [2]> var_758_split_sizes_0 = const()[name = tensor<string, []>("op_758_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_758_axis_0 = const()[name = tensor<string, []>("op_758_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_758_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_758_cast_fp16_1 = split(axis = var_758_axis_0, split_sizes = var_758_split_sizes_0, x = h_51_cast_fp16)[name = tensor<string, []>("op_758_cast_fp16")]; |
| tensor<fp16, []> var_760_promoted_to_fp16 = const()[name = tensor<string, []>("op_760_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_761_cast_fp16 = add(x = var_758_cast_fp16_0, y = var_760_promoted_to_fp16)[name = tensor<string, []>("op_761_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_764_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_596_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_101_cast_fp16)[name = tensor<string, []>("op_764_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_765_cast_fp16 = mul(x = var_761_cast_fp16, y = var_764_cast_fp16)[name = tensor<string, []>("op_765_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_7_cast_fp16 = add(x = var_765_cast_fp16, y = var_758_cast_fp16_1)[name = tensor<string, []>("xt_7_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_768_to_fp16 = const()[name = tensor<string, []>("op_768_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36879040)))]; |
| tensor<fp16, [1, 256, ?]> var_769_cast_fp16 = mul(x = xt_7_cast_fp16, y = var_768_to_fp16)[name = tensor<string, []>("op_769_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_5_cast_fp16 = cos(x = var_769_cast_fp16)[name = tensor<string, []>("cv_5_cast_fp16")]; |
| tensor<fp16, []> var_771_to_fp16 = const()[name = tensor<string, []>("op_771_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_772_cast_fp16 = mul(x = cv_5_cast_fp16, y = var_771_to_fp16)[name = tensor<string, []>("op_772_cast_fp16")]; |
| tensor<fp16, []> var_773_to_fp16 = const()[name = tensor<string, []>("op_773_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_774_cast_fp16 = add(x = var_772_cast_fp16, y = var_773_to_fp16)[name = tensor<string, []>("op_774_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_775_to_fp16 = const()[name = tensor<string, []>("op_775_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36879616)))]; |
| tensor<fp16, [1, 256, ?]> var_778_cast_fp16 = mul(x = var_774_cast_fp16, y = var_775_to_fp16)[name = tensor<string, []>("op_778_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_103_cast_fp16 = add(x = xt_7_cast_fp16, y = var_778_cast_fp16)[name = tensor<string, []>("input_103_cast_fp16")]; |
| tensor<string, []> input_105_pad_type_0 = const()[name = tensor<string, []>("input_105_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_105_pad_0 = const()[name = tensor<string, []>("input_105_pad_0"), val = tensor<int32, [2]>([3, 3])]; |
| tensor<int32, [1]> input_105_dilations_0 = const()[name = tensor<string, []>("input_105_dilations_0"), val = tensor<int32, [1]>([3])]; |
| tensor<int32, [1]> input_105_strides_0 = const()[name = tensor<string, []>("input_105_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_105_groups_0 = const()[name = tensor<string, []>("input_105_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 3]> weight_67_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [196608]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36880192))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37076864))), name = tensor<string, []>("weight_67_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 3])]; |
| tensor<fp16, [256]> resblocks_0_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_0_convs1_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37077440)))]; |
| tensor<fp16, [1, 256, ?]> input_105_cast_fp16 = conv(bias = resblocks_0_convs1_1_bias_to_fp16, dilations = input_105_dilations_0, groups = input_105_groups_0, pad = input_105_pad_0, pad_type = input_105_pad_type_0, strides = input_105_strides_0, weight = weight_67_to_fp16_palettized, x = input_103_cast_fp16)[name = tensor<string, []>("input_105_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_0_adain2_1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37078016))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37143616))), name = tensor<string, []>("resblocks_0_adain2_1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_0_adain2_1_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_0_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37144192)))]; |
| tensor<fp16, [1, 512]> linear_13_cast_fp16 = linear(bias = resblocks_0_adain2_1_fc_bias_to_fp16, weight = resblocks_0_adain2_1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_13_cast_fp16")]; |
| tensor<int32, [3]> var_794 = const()[name = tensor<string, []>("op_794"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_55_cast_fp16 = reshape(shape = var_794, x = linear_13_cast_fp16)[name = tensor<string, []>("h_55_cast_fp16")]; |
| tensor<int32, [2]> var_796_split_sizes_0 = const()[name = tensor<string, []>("op_796_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_796_axis_0 = const()[name = tensor<string, []>("op_796_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_796_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_796_cast_fp16_1 = split(axis = var_796_axis_0, split_sizes = var_796_split_sizes_0, x = h_55_cast_fp16)[name = tensor<string, []>("op_796_cast_fp16")]; |
| tensor<fp16, []> var_798_promoted_to_fp16 = const()[name = tensor<string, []>("op_798_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_799_cast_fp16 = add(x = var_796_cast_fp16_0, y = var_798_promoted_to_fp16)[name = tensor<string, []>("op_799_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_802_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_596_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_105_cast_fp16)[name = tensor<string, []>("op_802_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_803_cast_fp16 = mul(x = var_799_cast_fp16, y = var_802_cast_fp16)[name = tensor<string, []>("op_803_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_9_cast_fp16 = add(x = var_803_cast_fp16, y = var_796_cast_fp16_1)[name = tensor<string, []>("xt_9_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_806_to_fp16 = const()[name = tensor<string, []>("op_806_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37145280)))]; |
| tensor<fp16, [1, 256, ?]> var_807_cast_fp16 = mul(x = xt_9_cast_fp16, y = var_806_to_fp16)[name = tensor<string, []>("op_807_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_7_cast_fp16 = cos(x = var_807_cast_fp16)[name = tensor<string, []>("cv_7_cast_fp16")]; |
| tensor<fp16, []> var_809_to_fp16 = const()[name = tensor<string, []>("op_809_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_810_cast_fp16 = mul(x = cv_7_cast_fp16, y = var_809_to_fp16)[name = tensor<string, []>("op_810_cast_fp16")]; |
| tensor<fp16, []> var_811_to_fp16 = const()[name = tensor<string, []>("op_811_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_812_cast_fp16 = add(x = var_810_cast_fp16, y = var_811_to_fp16)[name = tensor<string, []>("op_812_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_813_to_fp16 = const()[name = tensor<string, []>("op_813_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37145856)))]; |
| tensor<fp16, [1, 256, ?]> var_816_cast_fp16 = mul(x = var_812_cast_fp16, y = var_813_to_fp16)[name = tensor<string, []>("op_816_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_107_cast_fp16 = add(x = xt_9_cast_fp16, y = var_816_cast_fp16)[name = tensor<string, []>("input_107_cast_fp16")]; |
| tensor<string, []> xt_11_pad_type_0 = const()[name = tensor<string, []>("xt_11_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_11_pad_0 = const()[name = tensor<string, []>("xt_11_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> xt_11_strides_0 = const()[name = tensor<string, []>("xt_11_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_11_dilations_0 = const()[name = tensor<string, []>("xt_11_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_11_groups_0 = const()[name = tensor<string, []>("xt_11_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 3]> weight_71_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [196608]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37146432))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37343104))), name = tensor<string, []>("weight_71_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 3])]; |
| tensor<fp16, [256]> resblocks_0_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_0_convs2_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37343680)))]; |
| tensor<fp16, [1, 256, ?]> xt_11_cast_fp16 = conv(bias = resblocks_0_convs2_1_bias_to_fp16, dilations = xt_11_dilations_0, groups = xt_11_groups_0, pad = xt_11_pad_0, pad_type = xt_11_pad_type_0, strides = xt_11_strides_0, weight = weight_71_to_fp16_palettized, x = input_107_cast_fp16)[name = tensor<string, []>("xt_11_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_109_cast_fp16 = add(x = xt_11_cast_fp16, y = input_101_cast_fp16)[name = tensor<string, []>("input_109_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_0_adain1_2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37344256))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37409856))), name = tensor<string, []>("resblocks_0_adain1_2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_0_adain1_2_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_0_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37410432)))]; |
| tensor<fp16, [1, 512]> linear_14_cast_fp16 = linear(bias = resblocks_0_adain1_2_fc_bias_to_fp16, weight = resblocks_0_adain1_2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_14_cast_fp16")]; |
| tensor<int32, [3]> var_833 = const()[name = tensor<string, []>("op_833"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_59_cast_fp16 = reshape(shape = var_833, x = linear_14_cast_fp16)[name = tensor<string, []>("h_59_cast_fp16")]; |
| tensor<int32, [2]> var_835_split_sizes_0 = const()[name = tensor<string, []>("op_835_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_835_axis_0 = const()[name = tensor<string, []>("op_835_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_835_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_835_cast_fp16_1 = split(axis = var_835_axis_0, split_sizes = var_835_split_sizes_0, x = h_59_cast_fp16)[name = tensor<string, []>("op_835_cast_fp16")]; |
| tensor<fp16, []> var_837_promoted_to_fp16 = const()[name = tensor<string, []>("op_837_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_838_cast_fp16 = add(x = var_835_cast_fp16_0, y = var_837_promoted_to_fp16)[name = tensor<string, []>("op_838_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_841_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_596_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_109_cast_fp16)[name = tensor<string, []>("op_841_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_842_cast_fp16 = mul(x = var_838_cast_fp16, y = var_841_cast_fp16)[name = tensor<string, []>("op_842_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_13_cast_fp16 = add(x = var_842_cast_fp16, y = var_835_cast_fp16_1)[name = tensor<string, []>("xt_13_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_845_to_fp16 = const()[name = tensor<string, []>("op_845_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37411520)))]; |
| tensor<fp16, [1, 256, ?]> var_846_cast_fp16 = mul(x = xt_13_cast_fp16, y = var_845_to_fp16)[name = tensor<string, []>("op_846_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_9_cast_fp16 = cos(x = var_846_cast_fp16)[name = tensor<string, []>("cv_9_cast_fp16")]; |
| tensor<fp16, []> var_848_to_fp16 = const()[name = tensor<string, []>("op_848_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_849_cast_fp16 = mul(x = cv_9_cast_fp16, y = var_848_to_fp16)[name = tensor<string, []>("op_849_cast_fp16")]; |
| tensor<fp16, []> var_850_to_fp16 = const()[name = tensor<string, []>("op_850_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_851_cast_fp16 = add(x = var_849_cast_fp16, y = var_850_to_fp16)[name = tensor<string, []>("op_851_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_852_to_fp16 = const()[name = tensor<string, []>("op_852_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37412096)))]; |
| tensor<fp16, [1, 256, ?]> var_855_cast_fp16 = mul(x = var_851_cast_fp16, y = var_852_to_fp16)[name = tensor<string, []>("op_855_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_111_cast_fp16 = add(x = xt_13_cast_fp16, y = var_855_cast_fp16)[name = tensor<string, []>("input_111_cast_fp16")]; |
| tensor<string, []> input_113_pad_type_0 = const()[name = tensor<string, []>("input_113_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_113_pad_0 = const()[name = tensor<string, []>("input_113_pad_0"), val = tensor<int32, [2]>([5, 5])]; |
| tensor<int32, [1]> input_113_dilations_0 = const()[name = tensor<string, []>("input_113_dilations_0"), val = tensor<int32, [1]>([5])]; |
| tensor<int32, [1]> input_113_strides_0 = const()[name = tensor<string, []>("input_113_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_113_groups_0 = const()[name = tensor<string, []>("input_113_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 3]> weight_75_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [196608]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37412672))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37609344))), name = tensor<string, []>("weight_75_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 3])]; |
| tensor<fp16, [256]> resblocks_0_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_0_convs1_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37609920)))]; |
| tensor<fp16, [1, 256, ?]> input_113_cast_fp16 = conv(bias = resblocks_0_convs1_2_bias_to_fp16, dilations = input_113_dilations_0, groups = input_113_groups_0, pad = input_113_pad_0, pad_type = input_113_pad_type_0, strides = input_113_strides_0, weight = weight_75_to_fp16_palettized, x = input_111_cast_fp16)[name = tensor<string, []>("input_113_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_0_adain2_2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37610496))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37676096))), name = tensor<string, []>("resblocks_0_adain2_2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_0_adain2_2_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_0_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37676672)))]; |
| tensor<fp16, [1, 512]> linear_15_cast_fp16 = linear(bias = resblocks_0_adain2_2_fc_bias_to_fp16, weight = resblocks_0_adain2_2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_15_cast_fp16")]; |
| tensor<int32, [3]> var_871 = const()[name = tensor<string, []>("op_871"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_63_cast_fp16 = reshape(shape = var_871, x = linear_15_cast_fp16)[name = tensor<string, []>("h_63_cast_fp16")]; |
| tensor<int32, [2]> var_873_split_sizes_0 = const()[name = tensor<string, []>("op_873_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_873_axis_0 = const()[name = tensor<string, []>("op_873_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_873_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_873_cast_fp16_1 = split(axis = var_873_axis_0, split_sizes = var_873_split_sizes_0, x = h_63_cast_fp16)[name = tensor<string, []>("op_873_cast_fp16")]; |
| tensor<fp16, []> var_875_promoted_to_fp16 = const()[name = tensor<string, []>("op_875_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_876_cast_fp16 = add(x = var_873_cast_fp16_0, y = var_875_promoted_to_fp16)[name = tensor<string, []>("op_876_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_879_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_596_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_113_cast_fp16)[name = tensor<string, []>("op_879_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_880_cast_fp16 = mul(x = var_876_cast_fp16, y = var_879_cast_fp16)[name = tensor<string, []>("op_880_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_15_cast_fp16 = add(x = var_880_cast_fp16, y = var_873_cast_fp16_1)[name = tensor<string, []>("xt_15_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_883_to_fp16 = const()[name = tensor<string, []>("op_883_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37677760)))]; |
| tensor<fp16, [1, 256, ?]> var_884_cast_fp16 = mul(x = xt_15_cast_fp16, y = var_883_to_fp16)[name = tensor<string, []>("op_884_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_11_cast_fp16 = cos(x = var_884_cast_fp16)[name = tensor<string, []>("cv_11_cast_fp16")]; |
| tensor<fp16, []> var_886_to_fp16 = const()[name = tensor<string, []>("op_886_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_887_cast_fp16 = mul(x = cv_11_cast_fp16, y = var_886_to_fp16)[name = tensor<string, []>("op_887_cast_fp16")]; |
| tensor<fp16, []> var_888_to_fp16 = const()[name = tensor<string, []>("op_888_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_889_cast_fp16 = add(x = var_887_cast_fp16, y = var_888_to_fp16)[name = tensor<string, []>("op_889_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_890_to_fp16 = const()[name = tensor<string, []>("op_890_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37678336)))]; |
| tensor<fp16, [1, 256, ?]> var_893_cast_fp16 = mul(x = var_889_cast_fp16, y = var_890_to_fp16)[name = tensor<string, []>("op_893_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_115_cast_fp16 = add(x = xt_15_cast_fp16, y = var_893_cast_fp16)[name = tensor<string, []>("input_115_cast_fp16")]; |
| tensor<string, []> xt_17_pad_type_0 = const()[name = tensor<string, []>("xt_17_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_17_pad_0 = const()[name = tensor<string, []>("xt_17_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> xt_17_strides_0 = const()[name = tensor<string, []>("xt_17_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_17_dilations_0 = const()[name = tensor<string, []>("xt_17_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_17_groups_0 = const()[name = tensor<string, []>("xt_17_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 3]> weight_79_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [196608]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37678912))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37875584))), name = tensor<string, []>("weight_79_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 3])]; |
| tensor<fp16, [256]> resblocks_0_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_0_convs2_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37876160)))]; |
| tensor<fp16, [1, 256, ?]> xt_17_cast_fp16 = conv(bias = resblocks_0_convs2_2_bias_to_fp16, dilations = xt_17_dilations_0, groups = xt_17_groups_0, pad = xt_17_pad_0, pad_type = xt_17_pad_type_0, strides = xt_17_strides_0, weight = weight_79_to_fp16_palettized, x = input_115_cast_fp16)[name = tensor<string, []>("xt_17_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xs_1_cast_fp16 = add(x = xt_17_cast_fp16, y = input_109_cast_fp16)[name = tensor<string, []>("xs_1_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_1_adain1_0_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37876736))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37942336))), name = tensor<string, []>("resblocks_1_adain1_0_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_1_adain1_0_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_1_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37942912)))]; |
| tensor<fp16, [1, 512]> linear_16_cast_fp16 = linear(bias = resblocks_1_adain1_0_fc_bias_to_fp16, weight = resblocks_1_adain1_0_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_16_cast_fp16")]; |
| tensor<int32, [3]> var_993 = const()[name = tensor<string, []>("op_993"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_67_cast_fp16 = reshape(shape = var_993, x = linear_16_cast_fp16)[name = tensor<string, []>("h_67_cast_fp16")]; |
| tensor<int32, [2]> var_995_split_sizes_0 = const()[name = tensor<string, []>("op_995_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_995_axis_0 = const()[name = tensor<string, []>("op_995_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_995_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_995_cast_fp16_1 = split(axis = var_995_axis_0, split_sizes = var_995_split_sizes_0, x = h_67_cast_fp16)[name = tensor<string, []>("op_995_cast_fp16")]; |
| tensor<fp16, []> var_997_promoted_to_fp16 = const()[name = tensor<string, []>("op_997_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_998_cast_fp16 = add(x = var_995_cast_fp16_0, y = var_997_promoted_to_fp16)[name = tensor<string, []>("op_998_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1002_cast_fp16 = mul(x = var_998_cast_fp16, y = var_687_cast_fp16)[name = tensor<string, []>("op_1002_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_19_cast_fp16 = add(x = var_1002_cast_fp16, y = var_995_cast_fp16_1)[name = tensor<string, []>("xt_19_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1005_to_fp16 = const()[name = tensor<string, []>("op_1005_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37944000)))]; |
| tensor<fp16, [1, 256, ?]> var_1006_cast_fp16 = mul(x = xt_19_cast_fp16, y = var_1005_to_fp16)[name = tensor<string, []>("op_1006_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_13_cast_fp16 = cos(x = var_1006_cast_fp16)[name = tensor<string, []>("cv_13_cast_fp16")]; |
| tensor<fp16, []> var_1008_to_fp16 = const()[name = tensor<string, []>("op_1008_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1009_cast_fp16 = mul(x = cv_13_cast_fp16, y = var_1008_to_fp16)[name = tensor<string, []>("op_1009_cast_fp16")]; |
| tensor<fp16, []> var_1010_to_fp16 = const()[name = tensor<string, []>("op_1010_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1011_cast_fp16 = add(x = var_1009_cast_fp16, y = var_1010_to_fp16)[name = tensor<string, []>("op_1011_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1012_to_fp16 = const()[name = tensor<string, []>("op_1012_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37944576)))]; |
| tensor<fp16, [1, 256, ?]> var_1015_cast_fp16 = mul(x = var_1011_cast_fp16, y = var_1012_to_fp16)[name = tensor<string, []>("op_1015_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_117_cast_fp16 = add(x = xt_19_cast_fp16, y = var_1015_cast_fp16)[name = tensor<string, []>("input_117_cast_fp16")]; |
| tensor<string, []> input_119_pad_type_0 = const()[name = tensor<string, []>("input_119_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_119_pad_0 = const()[name = tensor<string, []>("input_119_pad_0"), val = tensor<int32, [2]>([3, 3])]; |
| tensor<int32, [1]> input_119_strides_0 = const()[name = tensor<string, []>("input_119_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> input_119_dilations_0 = const()[name = tensor<string, []>("input_119_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_119_groups_0 = const()[name = tensor<string, []>("input_119_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 7]> weight_83_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [458752]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37945152))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38403968))), name = tensor<string, []>("weight_83_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 7])]; |
| tensor<fp16, [256]> resblocks_1_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_1_convs1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38404544)))]; |
| tensor<fp16, [1, 256, ?]> input_119_cast_fp16 = conv(bias = resblocks_1_convs1_0_bias_to_fp16, dilations = input_119_dilations_0, groups = input_119_groups_0, pad = input_119_pad_0, pad_type = input_119_pad_type_0, strides = input_119_strides_0, weight = weight_83_to_fp16_palettized, x = input_117_cast_fp16)[name = tensor<string, []>("input_119_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_1_adain2_0_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38405120))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38470720))), name = tensor<string, []>("resblocks_1_adain2_0_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_1_adain2_0_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_1_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38471296)))]; |
| tensor<fp16, [1, 512]> linear_17_cast_fp16 = linear(bias = resblocks_1_adain2_0_fc_bias_to_fp16, weight = resblocks_1_adain2_0_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_17_cast_fp16")]; |
| tensor<int32, [3]> var_1031 = const()[name = tensor<string, []>("op_1031"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_71_cast_fp16 = reshape(shape = var_1031, x = linear_17_cast_fp16)[name = tensor<string, []>("h_71_cast_fp16")]; |
| tensor<int32, [2]> var_1033_split_sizes_0 = const()[name = tensor<string, []>("op_1033_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_1033_axis_0 = const()[name = tensor<string, []>("op_1033_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_1033_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_1033_cast_fp16_1 = split(axis = var_1033_axis_0, split_sizes = var_1033_split_sizes_0, x = h_71_cast_fp16)[name = tensor<string, []>("op_1033_cast_fp16")]; |
| tensor<fp16, []> var_1035_promoted_to_fp16 = const()[name = tensor<string, []>("op_1035_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_1036_cast_fp16 = add(x = var_1033_cast_fp16_0, y = var_1035_promoted_to_fp16)[name = tensor<string, []>("op_1036_cast_fp16")]; |
| tensor<fp16, []> var_910_to_fp16 = const()[name = tensor<string, []>("op_910_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| tensor<fp16, [1, 256, ?]> var_1039_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_910_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_119_cast_fp16)[name = tensor<string, []>("op_1039_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1040_cast_fp16 = mul(x = var_1036_cast_fp16, y = var_1039_cast_fp16)[name = tensor<string, []>("op_1040_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_21_cast_fp16 = add(x = var_1040_cast_fp16, y = var_1033_cast_fp16_1)[name = tensor<string, []>("xt_21_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1043_to_fp16 = const()[name = tensor<string, []>("op_1043_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38472384)))]; |
| tensor<fp16, [1, 256, ?]> var_1044_cast_fp16 = mul(x = xt_21_cast_fp16, y = var_1043_to_fp16)[name = tensor<string, []>("op_1044_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_15_cast_fp16 = cos(x = var_1044_cast_fp16)[name = tensor<string, []>("cv_15_cast_fp16")]; |
| tensor<fp16, []> var_1046_to_fp16 = const()[name = tensor<string, []>("op_1046_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1047_cast_fp16 = mul(x = cv_15_cast_fp16, y = var_1046_to_fp16)[name = tensor<string, []>("op_1047_cast_fp16")]; |
| tensor<fp16, []> var_1048_to_fp16 = const()[name = tensor<string, []>("op_1048_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1049_cast_fp16 = add(x = var_1047_cast_fp16, y = var_1048_to_fp16)[name = tensor<string, []>("op_1049_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1050_to_fp16 = const()[name = tensor<string, []>("op_1050_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38472960)))]; |
| tensor<fp16, [1, 256, ?]> var_1053_cast_fp16 = mul(x = var_1049_cast_fp16, y = var_1050_to_fp16)[name = tensor<string, []>("op_1053_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_121_cast_fp16 = add(x = xt_21_cast_fp16, y = var_1053_cast_fp16)[name = tensor<string, []>("input_121_cast_fp16")]; |
| tensor<string, []> xt_23_pad_type_0 = const()[name = tensor<string, []>("xt_23_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_23_pad_0 = const()[name = tensor<string, []>("xt_23_pad_0"), val = tensor<int32, [2]>([3, 3])]; |
| tensor<int32, [1]> xt_23_strides_0 = const()[name = tensor<string, []>("xt_23_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_23_dilations_0 = const()[name = tensor<string, []>("xt_23_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_23_groups_0 = const()[name = tensor<string, []>("xt_23_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 7]> weight_87_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [458752]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38473536))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38932352))), name = tensor<string, []>("weight_87_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 7])]; |
| tensor<fp16, [256]> resblocks_1_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_1_convs2_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38932928)))]; |
| tensor<fp16, [1, 256, ?]> xt_23_cast_fp16 = conv(bias = resblocks_1_convs2_0_bias_to_fp16, dilations = xt_23_dilations_0, groups = xt_23_groups_0, pad = xt_23_pad_0, pad_type = xt_23_pad_type_0, strides = xt_23_strides_0, weight = weight_87_to_fp16_palettized, x = input_121_cast_fp16)[name = tensor<string, []>("xt_23_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_123_cast_fp16 = add(x = xt_23_cast_fp16, y = input_93_cast_fp16)[name = tensor<string, []>("input_123_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_1_adain1_1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38933504))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38999104))), name = tensor<string, []>("resblocks_1_adain1_1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_1_adain1_1_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_1_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38999680)))]; |
| tensor<fp16, [1, 512]> linear_18_cast_fp16 = linear(bias = resblocks_1_adain1_1_fc_bias_to_fp16, weight = resblocks_1_adain1_1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_18_cast_fp16")]; |
| tensor<int32, [3]> var_1070 = const()[name = tensor<string, []>("op_1070"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_75_cast_fp16 = reshape(shape = var_1070, x = linear_18_cast_fp16)[name = tensor<string, []>("h_75_cast_fp16")]; |
| tensor<int32, [2]> var_1072_split_sizes_0 = const()[name = tensor<string, []>("op_1072_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_1072_axis_0 = const()[name = tensor<string, []>("op_1072_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_1072_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_1072_cast_fp16_1 = split(axis = var_1072_axis_0, split_sizes = var_1072_split_sizes_0, x = h_75_cast_fp16)[name = tensor<string, []>("op_1072_cast_fp16")]; |
| tensor<fp16, []> var_1074_promoted_to_fp16 = const()[name = tensor<string, []>("op_1074_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_1075_cast_fp16 = add(x = var_1072_cast_fp16_0, y = var_1074_promoted_to_fp16)[name = tensor<string, []>("op_1075_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1078_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_910_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_123_cast_fp16)[name = tensor<string, []>("op_1078_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1079_cast_fp16 = mul(x = var_1075_cast_fp16, y = var_1078_cast_fp16)[name = tensor<string, []>("op_1079_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_25_cast_fp16 = add(x = var_1079_cast_fp16, y = var_1072_cast_fp16_1)[name = tensor<string, []>("xt_25_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1082_to_fp16 = const()[name = tensor<string, []>("op_1082_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39000768)))]; |
| tensor<fp16, [1, 256, ?]> var_1083_cast_fp16 = mul(x = xt_25_cast_fp16, y = var_1082_to_fp16)[name = tensor<string, []>("op_1083_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_17_cast_fp16 = cos(x = var_1083_cast_fp16)[name = tensor<string, []>("cv_17_cast_fp16")]; |
| tensor<fp16, []> var_1085_to_fp16 = const()[name = tensor<string, []>("op_1085_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1086_cast_fp16 = mul(x = cv_17_cast_fp16, y = var_1085_to_fp16)[name = tensor<string, []>("op_1086_cast_fp16")]; |
| tensor<fp16, []> var_1087_to_fp16 = const()[name = tensor<string, []>("op_1087_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1088_cast_fp16 = add(x = var_1086_cast_fp16, y = var_1087_to_fp16)[name = tensor<string, []>("op_1088_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1089_to_fp16 = const()[name = tensor<string, []>("op_1089_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39001344)))]; |
| tensor<fp16, [1, 256, ?]> var_1092_cast_fp16 = mul(x = var_1088_cast_fp16, y = var_1089_to_fp16)[name = tensor<string, []>("op_1092_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_125_cast_fp16 = add(x = xt_25_cast_fp16, y = var_1092_cast_fp16)[name = tensor<string, []>("input_125_cast_fp16")]; |
| tensor<string, []> input_127_pad_type_0 = const()[name = tensor<string, []>("input_127_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_127_pad_0 = const()[name = tensor<string, []>("input_127_pad_0"), val = tensor<int32, [2]>([9, 9])]; |
| tensor<int32, [1]> input_127_dilations_0 = const()[name = tensor<string, []>("input_127_dilations_0"), val = tensor<int32, [1]>([3])]; |
| tensor<int32, [1]> input_127_strides_0 = const()[name = tensor<string, []>("input_127_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_127_groups_0 = const()[name = tensor<string, []>("input_127_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 7]> weight_91_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [458752]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39001920))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39460736))), name = tensor<string, []>("weight_91_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 7])]; |
| tensor<fp16, [256]> resblocks_1_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_1_convs1_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39461312)))]; |
| tensor<fp16, [1, 256, ?]> input_127_cast_fp16 = conv(bias = resblocks_1_convs1_1_bias_to_fp16, dilations = input_127_dilations_0, groups = input_127_groups_0, pad = input_127_pad_0, pad_type = input_127_pad_type_0, strides = input_127_strides_0, weight = weight_91_to_fp16_palettized, x = input_125_cast_fp16)[name = tensor<string, []>("input_127_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_1_adain2_1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39461888))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39527488))), name = tensor<string, []>("resblocks_1_adain2_1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_1_adain2_1_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_1_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39528064)))]; |
| tensor<fp16, [1, 512]> linear_19_cast_fp16 = linear(bias = resblocks_1_adain2_1_fc_bias_to_fp16, weight = resblocks_1_adain2_1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_19_cast_fp16")]; |
| tensor<int32, [3]> var_1108 = const()[name = tensor<string, []>("op_1108"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_79_cast_fp16 = reshape(shape = var_1108, x = linear_19_cast_fp16)[name = tensor<string, []>("h_79_cast_fp16")]; |
| tensor<int32, [2]> var_1110_split_sizes_0 = const()[name = tensor<string, []>("op_1110_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_1110_axis_0 = const()[name = tensor<string, []>("op_1110_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_1110_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_1110_cast_fp16_1 = split(axis = var_1110_axis_0, split_sizes = var_1110_split_sizes_0, x = h_79_cast_fp16)[name = tensor<string, []>("op_1110_cast_fp16")]; |
| tensor<fp16, []> var_1112_promoted_to_fp16 = const()[name = tensor<string, []>("op_1112_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_1113_cast_fp16 = add(x = var_1110_cast_fp16_0, y = var_1112_promoted_to_fp16)[name = tensor<string, []>("op_1113_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1116_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_910_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_127_cast_fp16)[name = tensor<string, []>("op_1116_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1117_cast_fp16 = mul(x = var_1113_cast_fp16, y = var_1116_cast_fp16)[name = tensor<string, []>("op_1117_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_27_cast_fp16 = add(x = var_1117_cast_fp16, y = var_1110_cast_fp16_1)[name = tensor<string, []>("xt_27_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1120_to_fp16 = const()[name = tensor<string, []>("op_1120_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39529152)))]; |
| tensor<fp16, [1, 256, ?]> var_1121_cast_fp16 = mul(x = xt_27_cast_fp16, y = var_1120_to_fp16)[name = tensor<string, []>("op_1121_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_19_cast_fp16 = cos(x = var_1121_cast_fp16)[name = tensor<string, []>("cv_19_cast_fp16")]; |
| tensor<fp16, []> var_1123_to_fp16 = const()[name = tensor<string, []>("op_1123_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1124_cast_fp16 = mul(x = cv_19_cast_fp16, y = var_1123_to_fp16)[name = tensor<string, []>("op_1124_cast_fp16")]; |
| tensor<fp16, []> var_1125_to_fp16 = const()[name = tensor<string, []>("op_1125_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1126_cast_fp16 = add(x = var_1124_cast_fp16, y = var_1125_to_fp16)[name = tensor<string, []>("op_1126_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1127_to_fp16 = const()[name = tensor<string, []>("op_1127_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39529728)))]; |
| tensor<fp16, [1, 256, ?]> var_1130_cast_fp16 = mul(x = var_1126_cast_fp16, y = var_1127_to_fp16)[name = tensor<string, []>("op_1130_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_129_cast_fp16 = add(x = xt_27_cast_fp16, y = var_1130_cast_fp16)[name = tensor<string, []>("input_129_cast_fp16")]; |
| tensor<string, []> xt_29_pad_type_0 = const()[name = tensor<string, []>("xt_29_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_29_pad_0 = const()[name = tensor<string, []>("xt_29_pad_0"), val = tensor<int32, [2]>([3, 3])]; |
| tensor<int32, [1]> xt_29_strides_0 = const()[name = tensor<string, []>("xt_29_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_29_dilations_0 = const()[name = tensor<string, []>("xt_29_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_29_groups_0 = const()[name = tensor<string, []>("xt_29_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 7]> weight_95_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [458752]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39530304))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39989120))), name = tensor<string, []>("weight_95_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 7])]; |
| tensor<fp16, [256]> resblocks_1_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_1_convs2_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39989696)))]; |
| tensor<fp16, [1, 256, ?]> xt_29_cast_fp16 = conv(bias = resblocks_1_convs2_1_bias_to_fp16, dilations = xt_29_dilations_0, groups = xt_29_groups_0, pad = xt_29_pad_0, pad_type = xt_29_pad_type_0, strides = xt_29_strides_0, weight = weight_95_to_fp16_palettized, x = input_129_cast_fp16)[name = tensor<string, []>("xt_29_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_131_cast_fp16 = add(x = xt_29_cast_fp16, y = input_123_cast_fp16)[name = tensor<string, []>("input_131_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_1_adain1_2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39990272))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40055872))), name = tensor<string, []>("resblocks_1_adain1_2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_1_adain1_2_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_1_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40056448)))]; |
| tensor<fp16, [1, 512]> linear_20_cast_fp16 = linear(bias = resblocks_1_adain1_2_fc_bias_to_fp16, weight = resblocks_1_adain1_2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_20_cast_fp16")]; |
| tensor<int32, [3]> var_1147 = const()[name = tensor<string, []>("op_1147"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_83_cast_fp16 = reshape(shape = var_1147, x = linear_20_cast_fp16)[name = tensor<string, []>("h_83_cast_fp16")]; |
| tensor<int32, [2]> var_1149_split_sizes_0 = const()[name = tensor<string, []>("op_1149_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_1149_axis_0 = const()[name = tensor<string, []>("op_1149_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_1149_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_1149_cast_fp16_1 = split(axis = var_1149_axis_0, split_sizes = var_1149_split_sizes_0, x = h_83_cast_fp16)[name = tensor<string, []>("op_1149_cast_fp16")]; |
| tensor<fp16, []> var_1151_promoted_to_fp16 = const()[name = tensor<string, []>("op_1151_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_1152_cast_fp16 = add(x = var_1149_cast_fp16_0, y = var_1151_promoted_to_fp16)[name = tensor<string, []>("op_1152_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1155_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_910_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_131_cast_fp16)[name = tensor<string, []>("op_1155_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1156_cast_fp16 = mul(x = var_1152_cast_fp16, y = var_1155_cast_fp16)[name = tensor<string, []>("op_1156_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_31_cast_fp16 = add(x = var_1156_cast_fp16, y = var_1149_cast_fp16_1)[name = tensor<string, []>("xt_31_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1159_to_fp16 = const()[name = tensor<string, []>("op_1159_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40057536)))]; |
| tensor<fp16, [1, 256, ?]> var_1160_cast_fp16 = mul(x = xt_31_cast_fp16, y = var_1159_to_fp16)[name = tensor<string, []>("op_1160_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_21_cast_fp16 = cos(x = var_1160_cast_fp16)[name = tensor<string, []>("cv_21_cast_fp16")]; |
| tensor<fp16, []> var_1162_to_fp16 = const()[name = tensor<string, []>("op_1162_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1163_cast_fp16 = mul(x = cv_21_cast_fp16, y = var_1162_to_fp16)[name = tensor<string, []>("op_1163_cast_fp16")]; |
| tensor<fp16, []> var_1164_to_fp16 = const()[name = tensor<string, []>("op_1164_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1165_cast_fp16 = add(x = var_1163_cast_fp16, y = var_1164_to_fp16)[name = tensor<string, []>("op_1165_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1166_to_fp16 = const()[name = tensor<string, []>("op_1166_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40058112)))]; |
| tensor<fp16, [1, 256, ?]> var_1169_cast_fp16 = mul(x = var_1165_cast_fp16, y = var_1166_to_fp16)[name = tensor<string, []>("op_1169_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_133_cast_fp16 = add(x = xt_31_cast_fp16, y = var_1169_cast_fp16)[name = tensor<string, []>("input_133_cast_fp16")]; |
| tensor<string, []> input_135_pad_type_0 = const()[name = tensor<string, []>("input_135_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_135_pad_0 = const()[name = tensor<string, []>("input_135_pad_0"), val = tensor<int32, [2]>([15, 15])]; |
| tensor<int32, [1]> input_135_dilations_0 = const()[name = tensor<string, []>("input_135_dilations_0"), val = tensor<int32, [1]>([5])]; |
| tensor<int32, [1]> input_135_strides_0 = const()[name = tensor<string, []>("input_135_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_135_groups_0 = const()[name = tensor<string, []>("input_135_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 7]> weight_99_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [458752]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40058688))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40517504))), name = tensor<string, []>("weight_99_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 7])]; |
| tensor<fp16, [256]> resblocks_1_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_1_convs1_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40518080)))]; |
| tensor<fp16, [1, 256, ?]> input_135_cast_fp16 = conv(bias = resblocks_1_convs1_2_bias_to_fp16, dilations = input_135_dilations_0, groups = input_135_groups_0, pad = input_135_pad_0, pad_type = input_135_pad_type_0, strides = input_135_strides_0, weight = weight_99_to_fp16_palettized, x = input_133_cast_fp16)[name = tensor<string, []>("input_135_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_1_adain2_2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40518656))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40584256))), name = tensor<string, []>("resblocks_1_adain2_2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_1_adain2_2_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_1_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40584832)))]; |
| tensor<fp16, [1, 512]> linear_21_cast_fp16 = linear(bias = resblocks_1_adain2_2_fc_bias_to_fp16, weight = resblocks_1_adain2_2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_21_cast_fp16")]; |
| tensor<int32, [3]> var_1185 = const()[name = tensor<string, []>("op_1185"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_87_cast_fp16 = reshape(shape = var_1185, x = linear_21_cast_fp16)[name = tensor<string, []>("h_87_cast_fp16")]; |
| tensor<int32, [2]> var_1187_split_sizes_0 = const()[name = tensor<string, []>("op_1187_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_1187_axis_0 = const()[name = tensor<string, []>("op_1187_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_1187_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_1187_cast_fp16_1 = split(axis = var_1187_axis_0, split_sizes = var_1187_split_sizes_0, x = h_87_cast_fp16)[name = tensor<string, []>("op_1187_cast_fp16")]; |
| tensor<fp16, []> var_1189_promoted_to_fp16 = const()[name = tensor<string, []>("op_1189_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_1190_cast_fp16 = add(x = var_1187_cast_fp16_0, y = var_1189_promoted_to_fp16)[name = tensor<string, []>("op_1190_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1193_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_910_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_135_cast_fp16)[name = tensor<string, []>("op_1193_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1194_cast_fp16 = mul(x = var_1190_cast_fp16, y = var_1193_cast_fp16)[name = tensor<string, []>("op_1194_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_33_cast_fp16 = add(x = var_1194_cast_fp16, y = var_1187_cast_fp16_1)[name = tensor<string, []>("xt_33_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1197_to_fp16 = const()[name = tensor<string, []>("op_1197_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40585920)))]; |
| tensor<fp16, [1, 256, ?]> var_1198_cast_fp16 = mul(x = xt_33_cast_fp16, y = var_1197_to_fp16)[name = tensor<string, []>("op_1198_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_23_cast_fp16 = cos(x = var_1198_cast_fp16)[name = tensor<string, []>("cv_23_cast_fp16")]; |
| tensor<fp16, []> var_1200_to_fp16 = const()[name = tensor<string, []>("op_1200_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1201_cast_fp16 = mul(x = cv_23_cast_fp16, y = var_1200_to_fp16)[name = tensor<string, []>("op_1201_cast_fp16")]; |
| tensor<fp16, []> var_1202_to_fp16 = const()[name = tensor<string, []>("op_1202_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1203_cast_fp16 = add(x = var_1201_cast_fp16, y = var_1202_to_fp16)[name = tensor<string, []>("op_1203_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1204_to_fp16 = const()[name = tensor<string, []>("op_1204_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40586496)))]; |
| tensor<fp16, [1, 256, ?]> var_1207_cast_fp16 = mul(x = var_1203_cast_fp16, y = var_1204_to_fp16)[name = tensor<string, []>("op_1207_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_137_cast_fp16 = add(x = xt_33_cast_fp16, y = var_1207_cast_fp16)[name = tensor<string, []>("input_137_cast_fp16")]; |
| tensor<string, []> xt_35_pad_type_0 = const()[name = tensor<string, []>("xt_35_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_35_pad_0 = const()[name = tensor<string, []>("xt_35_pad_0"), val = tensor<int32, [2]>([3, 3])]; |
| tensor<int32, [1]> xt_35_strides_0 = const()[name = tensor<string, []>("xt_35_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_35_dilations_0 = const()[name = tensor<string, []>("xt_35_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_35_groups_0 = const()[name = tensor<string, []>("xt_35_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 7]> weight_103_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [458752]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40587072))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41045888))), name = tensor<string, []>("weight_103_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 7])]; |
| tensor<fp16, [256]> resblocks_1_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_1_convs2_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41046464)))]; |
| tensor<fp16, [1, 256, ?]> xt_35_cast_fp16 = conv(bias = resblocks_1_convs2_2_bias_to_fp16, dilations = xt_35_dilations_0, groups = xt_35_groups_0, pad = xt_35_pad_0, pad_type = xt_35_pad_type_0, strides = xt_35_strides_0, weight = weight_103_to_fp16_palettized, x = input_137_cast_fp16)[name = tensor<string, []>("xt_35_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1216_cast_fp16 = add(x = xt_35_cast_fp16, y = input_131_cast_fp16)[name = tensor<string, []>("op_1216_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xs_3_cast_fp16 = add(x = xs_1_cast_fp16, y = var_1216_cast_fp16)[name = tensor<string, []>("xs_3_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_2_adain1_0_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41047040))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41112640))), name = tensor<string, []>("resblocks_2_adain1_0_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_2_adain1_0_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_2_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41113216)))]; |
| tensor<fp16, [1, 512]> linear_22_cast_fp16 = linear(bias = resblocks_2_adain1_0_fc_bias_to_fp16, weight = resblocks_2_adain1_0_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_22_cast_fp16")]; |
| tensor<int32, [3]> var_1309 = const()[name = tensor<string, []>("op_1309"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_91_cast_fp16 = reshape(shape = var_1309, x = linear_22_cast_fp16)[name = tensor<string, []>("h_91_cast_fp16")]; |
| tensor<int32, [2]> var_1311_split_sizes_0 = const()[name = tensor<string, []>("op_1311_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_1311_axis_0 = const()[name = tensor<string, []>("op_1311_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_1311_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_1311_cast_fp16_1 = split(axis = var_1311_axis_0, split_sizes = var_1311_split_sizes_0, x = h_91_cast_fp16)[name = tensor<string, []>("op_1311_cast_fp16")]; |
| tensor<fp16, []> var_1313_promoted_to_fp16 = const()[name = tensor<string, []>("op_1313_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_1314_cast_fp16 = add(x = var_1311_cast_fp16_0, y = var_1313_promoted_to_fp16)[name = tensor<string, []>("op_1314_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1318_cast_fp16 = mul(x = var_1314_cast_fp16, y = var_687_cast_fp16)[name = tensor<string, []>("op_1318_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_37_cast_fp16 = add(x = var_1318_cast_fp16, y = var_1311_cast_fp16_1)[name = tensor<string, []>("xt_37_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1321_to_fp16 = const()[name = tensor<string, []>("op_1321_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41114304)))]; |
| tensor<fp16, [1, 256, ?]> var_1322_cast_fp16 = mul(x = xt_37_cast_fp16, y = var_1321_to_fp16)[name = tensor<string, []>("op_1322_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_25_cast_fp16 = cos(x = var_1322_cast_fp16)[name = tensor<string, []>("cv_25_cast_fp16")]; |
| tensor<fp16, []> var_1324_to_fp16 = const()[name = tensor<string, []>("op_1324_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1325_cast_fp16 = mul(x = cv_25_cast_fp16, y = var_1324_to_fp16)[name = tensor<string, []>("op_1325_cast_fp16")]; |
| tensor<fp16, []> var_1326_to_fp16 = const()[name = tensor<string, []>("op_1326_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1327_cast_fp16 = add(x = var_1325_cast_fp16, y = var_1326_to_fp16)[name = tensor<string, []>("op_1327_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1328_to_fp16 = const()[name = tensor<string, []>("op_1328_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41114880)))]; |
| tensor<fp16, [1, 256, ?]> var_1331_cast_fp16 = mul(x = var_1327_cast_fp16, y = var_1328_to_fp16)[name = tensor<string, []>("op_1331_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_139_cast_fp16 = add(x = xt_37_cast_fp16, y = var_1331_cast_fp16)[name = tensor<string, []>("input_139_cast_fp16")]; |
| tensor<string, []> input_141_pad_type_0 = const()[name = tensor<string, []>("input_141_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_141_pad_0 = const()[name = tensor<string, []>("input_141_pad_0"), val = tensor<int32, [2]>([5, 5])]; |
| tensor<int32, [1]> input_141_strides_0 = const()[name = tensor<string, []>("input_141_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> input_141_dilations_0 = const()[name = tensor<string, []>("input_141_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_141_groups_0 = const()[name = tensor<string, []>("input_141_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 11]> weight_107_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [720896]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41115456))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41836416))), name = tensor<string, []>("weight_107_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 11])]; |
| tensor<fp16, [256]> resblocks_2_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_2_convs1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41836992)))]; |
| tensor<fp16, [1, 256, ?]> input_141_cast_fp16 = conv(bias = resblocks_2_convs1_0_bias_to_fp16, dilations = input_141_dilations_0, groups = input_141_groups_0, pad = input_141_pad_0, pad_type = input_141_pad_type_0, strides = input_141_strides_0, weight = weight_107_to_fp16_palettized, x = input_139_cast_fp16)[name = tensor<string, []>("input_141_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_2_adain2_0_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41837568))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41903168))), name = tensor<string, []>("resblocks_2_adain2_0_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_2_adain2_0_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_2_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41903744)))]; |
| tensor<fp16, [1, 512]> linear_23_cast_fp16 = linear(bias = resblocks_2_adain2_0_fc_bias_to_fp16, weight = resblocks_2_adain2_0_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_23_cast_fp16")]; |
| tensor<int32, [3]> var_1347 = const()[name = tensor<string, []>("op_1347"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_95_cast_fp16 = reshape(shape = var_1347, x = linear_23_cast_fp16)[name = tensor<string, []>("h_95_cast_fp16")]; |
| tensor<int32, [2]> var_1349_split_sizes_0 = const()[name = tensor<string, []>("op_1349_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_1349_axis_0 = const()[name = tensor<string, []>("op_1349_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_1349_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_1349_cast_fp16_1 = split(axis = var_1349_axis_0, split_sizes = var_1349_split_sizes_0, x = h_95_cast_fp16)[name = tensor<string, []>("op_1349_cast_fp16")]; |
| tensor<fp16, []> var_1351_promoted_to_fp16 = const()[name = tensor<string, []>("op_1351_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_1352_cast_fp16 = add(x = var_1349_cast_fp16_0, y = var_1351_promoted_to_fp16)[name = tensor<string, []>("op_1352_cast_fp16")]; |
| tensor<fp16, []> var_1226_to_fp16 = const()[name = tensor<string, []>("op_1226_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| tensor<fp16, [1, 256, ?]> var_1355_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_1226_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_141_cast_fp16)[name = tensor<string, []>("op_1355_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1356_cast_fp16 = mul(x = var_1352_cast_fp16, y = var_1355_cast_fp16)[name = tensor<string, []>("op_1356_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_39_cast_fp16 = add(x = var_1356_cast_fp16, y = var_1349_cast_fp16_1)[name = tensor<string, []>("xt_39_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1359_to_fp16 = const()[name = tensor<string, []>("op_1359_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41904832)))]; |
| tensor<fp16, [1, 256, ?]> var_1360_cast_fp16 = mul(x = xt_39_cast_fp16, y = var_1359_to_fp16)[name = tensor<string, []>("op_1360_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_27_cast_fp16 = cos(x = var_1360_cast_fp16)[name = tensor<string, []>("cv_27_cast_fp16")]; |
| tensor<fp16, []> var_1362_to_fp16 = const()[name = tensor<string, []>("op_1362_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1363_cast_fp16 = mul(x = cv_27_cast_fp16, y = var_1362_to_fp16)[name = tensor<string, []>("op_1363_cast_fp16")]; |
| tensor<fp16, []> var_1364_to_fp16 = const()[name = tensor<string, []>("op_1364_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1365_cast_fp16 = add(x = var_1363_cast_fp16, y = var_1364_to_fp16)[name = tensor<string, []>("op_1365_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1366_to_fp16 = const()[name = tensor<string, []>("op_1366_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41905408)))]; |
| tensor<fp16, [1, 256, ?]> var_1369_cast_fp16 = mul(x = var_1365_cast_fp16, y = var_1366_to_fp16)[name = tensor<string, []>("op_1369_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_143_cast_fp16 = add(x = xt_39_cast_fp16, y = var_1369_cast_fp16)[name = tensor<string, []>("input_143_cast_fp16")]; |
| tensor<string, []> xt_41_pad_type_0 = const()[name = tensor<string, []>("xt_41_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_41_pad_0 = const()[name = tensor<string, []>("xt_41_pad_0"), val = tensor<int32, [2]>([5, 5])]; |
| tensor<int32, [1]> xt_41_strides_0 = const()[name = tensor<string, []>("xt_41_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_41_dilations_0 = const()[name = tensor<string, []>("xt_41_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_41_groups_0 = const()[name = tensor<string, []>("xt_41_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 11]> weight_111_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [720896]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41905984))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42626944))), name = tensor<string, []>("weight_111_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 11])]; |
| tensor<fp16, [256]> resblocks_2_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_2_convs2_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42627520)))]; |
| tensor<fp16, [1, 256, ?]> xt_41_cast_fp16 = conv(bias = resblocks_2_convs2_0_bias_to_fp16, dilations = xt_41_dilations_0, groups = xt_41_groups_0, pad = xt_41_pad_0, pad_type = xt_41_pad_type_0, strides = xt_41_strides_0, weight = weight_111_to_fp16_palettized, x = input_143_cast_fp16)[name = tensor<string, []>("xt_41_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_145_cast_fp16 = add(x = xt_41_cast_fp16, y = input_93_cast_fp16)[name = tensor<string, []>("input_145_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_2_adain1_1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42628096))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42693696))), name = tensor<string, []>("resblocks_2_adain1_1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_2_adain1_1_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_2_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42694272)))]; |
| tensor<fp16, [1, 512]> linear_24_cast_fp16 = linear(bias = resblocks_2_adain1_1_fc_bias_to_fp16, weight = resblocks_2_adain1_1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_24_cast_fp16")]; |
| tensor<int32, [3]> var_1386 = const()[name = tensor<string, []>("op_1386"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_99_cast_fp16 = reshape(shape = var_1386, x = linear_24_cast_fp16)[name = tensor<string, []>("h_99_cast_fp16")]; |
| tensor<int32, [2]> var_1388_split_sizes_0 = const()[name = tensor<string, []>("op_1388_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_1388_axis_0 = const()[name = tensor<string, []>("op_1388_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_1388_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_1388_cast_fp16_1 = split(axis = var_1388_axis_0, split_sizes = var_1388_split_sizes_0, x = h_99_cast_fp16)[name = tensor<string, []>("op_1388_cast_fp16")]; |
| tensor<fp16, []> var_1390_promoted_to_fp16 = const()[name = tensor<string, []>("op_1390_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_1391_cast_fp16 = add(x = var_1388_cast_fp16_0, y = var_1390_promoted_to_fp16)[name = tensor<string, []>("op_1391_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1394_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_1226_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_145_cast_fp16)[name = tensor<string, []>("op_1394_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1395_cast_fp16 = mul(x = var_1391_cast_fp16, y = var_1394_cast_fp16)[name = tensor<string, []>("op_1395_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_43_cast_fp16 = add(x = var_1395_cast_fp16, y = var_1388_cast_fp16_1)[name = tensor<string, []>("xt_43_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1398_to_fp16 = const()[name = tensor<string, []>("op_1398_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42695360)))]; |
| tensor<fp16, [1, 256, ?]> var_1399_cast_fp16 = mul(x = xt_43_cast_fp16, y = var_1398_to_fp16)[name = tensor<string, []>("op_1399_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_29_cast_fp16 = cos(x = var_1399_cast_fp16)[name = tensor<string, []>("cv_29_cast_fp16")]; |
| tensor<fp16, []> var_1401_to_fp16 = const()[name = tensor<string, []>("op_1401_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1402_cast_fp16 = mul(x = cv_29_cast_fp16, y = var_1401_to_fp16)[name = tensor<string, []>("op_1402_cast_fp16")]; |
| tensor<fp16, []> var_1403_to_fp16 = const()[name = tensor<string, []>("op_1403_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1404_cast_fp16 = add(x = var_1402_cast_fp16, y = var_1403_to_fp16)[name = tensor<string, []>("op_1404_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1405_to_fp16 = const()[name = tensor<string, []>("op_1405_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42695936)))]; |
| tensor<fp16, [1, 256, ?]> var_1408_cast_fp16 = mul(x = var_1404_cast_fp16, y = var_1405_to_fp16)[name = tensor<string, []>("op_1408_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_147_cast_fp16 = add(x = xt_43_cast_fp16, y = var_1408_cast_fp16)[name = tensor<string, []>("input_147_cast_fp16")]; |
| tensor<string, []> input_149_pad_type_0 = const()[name = tensor<string, []>("input_149_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_149_pad_0 = const()[name = tensor<string, []>("input_149_pad_0"), val = tensor<int32, [2]>([15, 15])]; |
| tensor<int32, [1]> input_149_dilations_0 = const()[name = tensor<string, []>("input_149_dilations_0"), val = tensor<int32, [1]>([3])]; |
| tensor<int32, [1]> input_149_strides_0 = const()[name = tensor<string, []>("input_149_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_149_groups_0 = const()[name = tensor<string, []>("input_149_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 11]> weight_115_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [720896]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42696512))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(43417472))), name = tensor<string, []>("weight_115_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 11])]; |
| tensor<fp16, [256]> resblocks_2_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_2_convs1_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(43418048)))]; |
| tensor<fp16, [1, 256, ?]> input_149_cast_fp16 = conv(bias = resblocks_2_convs1_1_bias_to_fp16, dilations = input_149_dilations_0, groups = input_149_groups_0, pad = input_149_pad_0, pad_type = input_149_pad_type_0, strides = input_149_strides_0, weight = weight_115_to_fp16_palettized, x = input_147_cast_fp16)[name = tensor<string, []>("input_149_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_2_adain2_1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(43418624))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(43484224))), name = tensor<string, []>("resblocks_2_adain2_1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_2_adain2_1_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_2_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(43484800)))]; |
| tensor<fp16, [1, 512]> linear_25_cast_fp16 = linear(bias = resblocks_2_adain2_1_fc_bias_to_fp16, weight = resblocks_2_adain2_1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_25_cast_fp16")]; |
| tensor<int32, [3]> var_1424 = const()[name = tensor<string, []>("op_1424"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_103_cast_fp16 = reshape(shape = var_1424, x = linear_25_cast_fp16)[name = tensor<string, []>("h_103_cast_fp16")]; |
| tensor<int32, [2]> var_1426_split_sizes_0 = const()[name = tensor<string, []>("op_1426_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_1426_axis_0 = const()[name = tensor<string, []>("op_1426_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_1426_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_1426_cast_fp16_1 = split(axis = var_1426_axis_0, split_sizes = var_1426_split_sizes_0, x = h_103_cast_fp16)[name = tensor<string, []>("op_1426_cast_fp16")]; |
| tensor<fp16, []> var_1428_promoted_to_fp16 = const()[name = tensor<string, []>("op_1428_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_1429_cast_fp16 = add(x = var_1426_cast_fp16_0, y = var_1428_promoted_to_fp16)[name = tensor<string, []>("op_1429_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1432_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_1226_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_149_cast_fp16)[name = tensor<string, []>("op_1432_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1433_cast_fp16 = mul(x = var_1429_cast_fp16, y = var_1432_cast_fp16)[name = tensor<string, []>("op_1433_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_45_cast_fp16 = add(x = var_1433_cast_fp16, y = var_1426_cast_fp16_1)[name = tensor<string, []>("xt_45_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1436_to_fp16 = const()[name = tensor<string, []>("op_1436_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(43485888)))]; |
| tensor<fp16, [1, 256, ?]> var_1437_cast_fp16 = mul(x = xt_45_cast_fp16, y = var_1436_to_fp16)[name = tensor<string, []>("op_1437_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_31_cast_fp16 = cos(x = var_1437_cast_fp16)[name = tensor<string, []>("cv_31_cast_fp16")]; |
| tensor<fp16, []> var_1439_to_fp16 = const()[name = tensor<string, []>("op_1439_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1440_cast_fp16 = mul(x = cv_31_cast_fp16, y = var_1439_to_fp16)[name = tensor<string, []>("op_1440_cast_fp16")]; |
| tensor<fp16, []> var_1441_to_fp16 = const()[name = tensor<string, []>("op_1441_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1442_cast_fp16 = add(x = var_1440_cast_fp16, y = var_1441_to_fp16)[name = tensor<string, []>("op_1442_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1443_to_fp16 = const()[name = tensor<string, []>("op_1443_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(43486464)))]; |
| tensor<fp16, [1, 256, ?]> var_1446_cast_fp16 = mul(x = var_1442_cast_fp16, y = var_1443_to_fp16)[name = tensor<string, []>("op_1446_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_151_cast_fp16 = add(x = xt_45_cast_fp16, y = var_1446_cast_fp16)[name = tensor<string, []>("input_151_cast_fp16")]; |
| tensor<string, []> xt_47_pad_type_0 = const()[name = tensor<string, []>("xt_47_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_47_pad_0 = const()[name = tensor<string, []>("xt_47_pad_0"), val = tensor<int32, [2]>([5, 5])]; |
| tensor<int32, [1]> xt_47_strides_0 = const()[name = tensor<string, []>("xt_47_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_47_dilations_0 = const()[name = tensor<string, []>("xt_47_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_47_groups_0 = const()[name = tensor<string, []>("xt_47_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 11]> weight_119_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [720896]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(43487040))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44208000))), name = tensor<string, []>("weight_119_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 11])]; |
| tensor<fp16, [256]> resblocks_2_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_2_convs2_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44208576)))]; |
| tensor<fp16, [1, 256, ?]> xt_47_cast_fp16 = conv(bias = resblocks_2_convs2_1_bias_to_fp16, dilations = xt_47_dilations_0, groups = xt_47_groups_0, pad = xt_47_pad_0, pad_type = xt_47_pad_type_0, strides = xt_47_strides_0, weight = weight_119_to_fp16_palettized, x = input_151_cast_fp16)[name = tensor<string, []>("xt_47_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_153_cast_fp16 = add(x = xt_47_cast_fp16, y = input_145_cast_fp16)[name = tensor<string, []>("input_153_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_2_adain1_2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44209152))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44274752))), name = tensor<string, []>("resblocks_2_adain1_2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_2_adain1_2_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_2_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44275328)))]; |
| tensor<fp16, [1, 512]> linear_26_cast_fp16 = linear(bias = resblocks_2_adain1_2_fc_bias_to_fp16, weight = resblocks_2_adain1_2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_26_cast_fp16")]; |
| tensor<int32, [3]> var_1463 = const()[name = tensor<string, []>("op_1463"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_107_cast_fp16 = reshape(shape = var_1463, x = linear_26_cast_fp16)[name = tensor<string, []>("h_107_cast_fp16")]; |
| tensor<int32, [2]> var_1465_split_sizes_0 = const()[name = tensor<string, []>("op_1465_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_1465_axis_0 = const()[name = tensor<string, []>("op_1465_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_1465_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_1465_cast_fp16_1 = split(axis = var_1465_axis_0, split_sizes = var_1465_split_sizes_0, x = h_107_cast_fp16)[name = tensor<string, []>("op_1465_cast_fp16")]; |
| tensor<fp16, []> var_1467_promoted_to_fp16 = const()[name = tensor<string, []>("op_1467_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_1468_cast_fp16 = add(x = var_1465_cast_fp16_0, y = var_1467_promoted_to_fp16)[name = tensor<string, []>("op_1468_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1471_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_1226_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_153_cast_fp16)[name = tensor<string, []>("op_1471_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1472_cast_fp16 = mul(x = var_1468_cast_fp16, y = var_1471_cast_fp16)[name = tensor<string, []>("op_1472_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_49_cast_fp16 = add(x = var_1472_cast_fp16, y = var_1465_cast_fp16_1)[name = tensor<string, []>("xt_49_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1475_to_fp16 = const()[name = tensor<string, []>("op_1475_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44276416)))]; |
| tensor<fp16, [1, 256, ?]> var_1476_cast_fp16 = mul(x = xt_49_cast_fp16, y = var_1475_to_fp16)[name = tensor<string, []>("op_1476_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_33_cast_fp16 = cos(x = var_1476_cast_fp16)[name = tensor<string, []>("cv_33_cast_fp16")]; |
| tensor<fp16, []> var_1478_to_fp16 = const()[name = tensor<string, []>("op_1478_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1479_cast_fp16 = mul(x = cv_33_cast_fp16, y = var_1478_to_fp16)[name = tensor<string, []>("op_1479_cast_fp16")]; |
| tensor<fp16, []> var_1480_to_fp16 = const()[name = tensor<string, []>("op_1480_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1481_cast_fp16 = add(x = var_1479_cast_fp16, y = var_1480_to_fp16)[name = tensor<string, []>("op_1481_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1482_to_fp16 = const()[name = tensor<string, []>("op_1482_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44276992)))]; |
| tensor<fp16, [1, 256, ?]> var_1485_cast_fp16 = mul(x = var_1481_cast_fp16, y = var_1482_to_fp16)[name = tensor<string, []>("op_1485_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_155_cast_fp16 = add(x = xt_49_cast_fp16, y = var_1485_cast_fp16)[name = tensor<string, []>("input_155_cast_fp16")]; |
| tensor<string, []> input_157_pad_type_0 = const()[name = tensor<string, []>("input_157_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_157_pad_0 = const()[name = tensor<string, []>("input_157_pad_0"), val = tensor<int32, [2]>([25, 25])]; |
| tensor<int32, [1]> input_157_dilations_0 = const()[name = tensor<string, []>("input_157_dilations_0"), val = tensor<int32, [1]>([5])]; |
| tensor<int32, [1]> input_157_strides_0 = const()[name = tensor<string, []>("input_157_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_157_groups_0 = const()[name = tensor<string, []>("input_157_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 11]> weight_123_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [720896]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44277568))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44998528))), name = tensor<string, []>("weight_123_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 11])]; |
| tensor<fp16, [256]> resblocks_2_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_2_convs1_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44999104)))]; |
| tensor<fp16, [1, 256, ?]> input_157_cast_fp16 = conv(bias = resblocks_2_convs1_2_bias_to_fp16, dilations = input_157_dilations_0, groups = input_157_groups_0, pad = input_157_pad_0, pad_type = input_157_pad_type_0, strides = input_157_strides_0, weight = weight_123_to_fp16_palettized, x = input_155_cast_fp16)[name = tensor<string, []>("input_157_cast_fp16")]; |
| tensor<fp16, [512, 128]> resblocks_2_adain2_2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [65536]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44999680))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45065280))), name = tensor<string, []>("resblocks_2_adain2_2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([512, 128])]; |
| tensor<fp16, [512]> resblocks_2_adain2_2_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_2_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45065856)))]; |
| tensor<fp16, [1, 512]> linear_27_cast_fp16 = linear(bias = resblocks_2_adain2_2_fc_bias_to_fp16, weight = resblocks_2_adain2_2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_27_cast_fp16")]; |
| tensor<int32, [3]> var_1501 = const()[name = tensor<string, []>("op_1501"), val = tensor<int32, [3]>([1, 512, 1])]; |
| tensor<fp16, [1, 512, 1]> h_111_cast_fp16 = reshape(shape = var_1501, x = linear_27_cast_fp16)[name = tensor<string, []>("h_111_cast_fp16")]; |
| tensor<int32, [2]> var_1503_split_sizes_0 = const()[name = tensor<string, []>("op_1503_split_sizes_0"), val = tensor<int32, [2]>([256, 256])]; |
| tensor<int32, []> var_1503_axis_0 = const()[name = tensor<string, []>("op_1503_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 256, 1]> var_1503_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_1503_cast_fp16_1 = split(axis = var_1503_axis_0, split_sizes = var_1503_split_sizes_0, x = h_111_cast_fp16)[name = tensor<string, []>("op_1503_cast_fp16")]; |
| tensor<fp16, []> var_1505_promoted_to_fp16 = const()[name = tensor<string, []>("op_1505_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 256, 1]> var_1506_cast_fp16 = add(x = var_1503_cast_fp16_0, y = var_1505_promoted_to_fp16)[name = tensor<string, []>("op_1506_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1509_cast_fp16 = instance_norm(beta = resblocks_0_adain1_0_norm_bias_to_fp16, epsilon = var_1226_to_fp16, gamma = resblocks_0_adain1_0_norm_weight_to_fp16, x = input_157_cast_fp16)[name = tensor<string, []>("op_1509_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1510_cast_fp16 = mul(x = var_1506_cast_fp16, y = var_1509_cast_fp16)[name = tensor<string, []>("op_1510_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xt_51_cast_fp16 = add(x = var_1510_cast_fp16, y = var_1503_cast_fp16_1)[name = tensor<string, []>("xt_51_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1513_to_fp16 = const()[name = tensor<string, []>("op_1513_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45066944)))]; |
| tensor<fp16, [1, 256, ?]> var_1514_cast_fp16 = mul(x = xt_51_cast_fp16, y = var_1513_to_fp16)[name = tensor<string, []>("op_1514_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> cv_35_cast_fp16 = cos(x = var_1514_cast_fp16)[name = tensor<string, []>("cv_35_cast_fp16")]; |
| tensor<fp16, []> var_1516_to_fp16 = const()[name = tensor<string, []>("op_1516_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1517_cast_fp16 = mul(x = cv_35_cast_fp16, y = var_1516_to_fp16)[name = tensor<string, []>("op_1517_cast_fp16")]; |
| tensor<fp16, []> var_1518_to_fp16 = const()[name = tensor<string, []>("op_1518_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 256, ?]> var_1519_cast_fp16 = add(x = var_1517_cast_fp16, y = var_1518_to_fp16)[name = tensor<string, []>("op_1519_cast_fp16")]; |
| tensor<fp16, [1, 256, 1]> var_1520_to_fp16 = const()[name = tensor<string, []>("op_1520_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45067520)))]; |
| tensor<fp16, [1, 256, ?]> var_1523_cast_fp16 = mul(x = var_1519_cast_fp16, y = var_1520_to_fp16)[name = tensor<string, []>("op_1523_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> input_159_cast_fp16 = add(x = xt_51_cast_fp16, y = var_1523_cast_fp16)[name = tensor<string, []>("input_159_cast_fp16")]; |
| tensor<string, []> xt_53_pad_type_0 = const()[name = tensor<string, []>("xt_53_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_53_pad_0 = const()[name = tensor<string, []>("xt_53_pad_0"), val = tensor<int32, [2]>([5, 5])]; |
| tensor<int32, [1]> xt_53_strides_0 = const()[name = tensor<string, []>("xt_53_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_53_dilations_0 = const()[name = tensor<string, []>("xt_53_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_53_groups_0 = const()[name = tensor<string, []>("xt_53_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 256, 11]> weight_127_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [720896]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45068096))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45789056))), name = tensor<string, []>("weight_127_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 256, 11])]; |
| tensor<fp16, [256]> resblocks_2_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_2_convs2_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45789632)))]; |
| tensor<fp16, [1, 256, ?]> xt_53_cast_fp16 = conv(bias = resblocks_2_convs2_2_bias_to_fp16, dilations = xt_53_dilations_0, groups = xt_53_groups_0, pad = xt_53_pad_0, pad_type = xt_53_pad_type_0, strides = xt_53_strides_0, weight = weight_127_to_fp16_palettized, x = input_159_cast_fp16)[name = tensor<string, []>("xt_53_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> var_1532_cast_fp16 = add(x = xt_53_cast_fp16, y = input_153_cast_fp16)[name = tensor<string, []>("op_1532_cast_fp16")]; |
| tensor<fp16, [1, 256, ?]> xs_5_cast_fp16 = add(x = xs_3_cast_fp16, y = var_1532_cast_fp16)[name = tensor<string, []>("xs_5_cast_fp16")]; |
| tensor<fp16, []> _inversed_input_161_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_input_161_y_0_to_fp16"), val = tensor<fp16, []>(0x1.554p-2)]; |
| tensor<fp16, [1, 256, ?]> _inversed_input_161_cast_fp16 = mul(x = xs_5_cast_fp16, y = _inversed_input_161_y_0_to_fp16)[name = tensor<string, []>("_inversed_input_161_cast_fp16")]; |
| tensor<fp32, []> var_1537 = const()[name = tensor<string, []>("op_1537"), val = tensor<fp32, []>(0x1.99999ap-4)]; |
| tensor<fp16, [1, 256, ?]> input_163_cast_fp16 = leaky_relu(alpha = var_1537, x = _inversed_input_161_cast_fp16)[name = tensor<string, []>("input_163_cast_fp16")]; |
| tensor<string, []> x_11_pad_type_0 = const()[name = tensor<string, []>("x_11_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> x_11_pad_0 = const()[name = tensor<string, []>("x_11_pad_0"), val = tensor<int32, [2]>([3, 3])]; |
| tensor<int32, [1]> x_11_strides_0 = const()[name = tensor<string, []>("x_11_strides_0"), val = tensor<int32, [1]>([6])]; |
| tensor<int32, [1]> x_11_dilations_0 = const()[name = tensor<string, []>("x_11_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> x_11_groups_0 = const()[name = tensor<string, []>("x_11_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [256, 128, 12]> op_1540_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [393216]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45790208))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46183488))), name = tensor<string, []>("op_1540_to_fp16_palettized"), shape = tensor<uint32, [3]>([256, 128, 12])]; |
| tensor<fp16, [128]> ups_1_bias_to_fp16 = const()[name = tensor<string, []>("ups_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46184064)))]; |
| tensor<fp16, [1, 128, ?]> x_11_cast_fp16 = conv_transpose(bias = ups_1_bias_to_fp16, dilations = x_11_dilations_0, groups = x_11_groups_0, pad = x_11_pad_0, pad_type = x_11_pad_type_0, strides = x_11_strides_0, weight = op_1540_to_fp16_palettized, x = input_163_cast_fp16)[name = tensor<string, []>("x_11_cast_fp16")]; |
| tensor<int32, [3]> var_1567_begin_0 = const()[name = tensor<string, []>("op_1567_begin_0"), val = tensor<int32, [3]>([0, 0, 1])]; |
| tensor<int32, [3]> var_1567_end_0 = const()[name = tensor<string, []>("op_1567_end_0"), val = tensor<int32, [3]>([1, 128, 2])]; |
| tensor<bool, [3]> var_1567_end_mask_0 = const()[name = tensor<string, []>("op_1567_end_mask_0"), val = tensor<bool, [3]>([true, true, false])]; |
| tensor<fp16, [1, 128, 1]> var_1567_cast_fp16 = slice_by_index(begin = var_1567_begin_0, end = var_1567_end_0, end_mask = var_1567_end_mask_0, x = x_11_cast_fp16)[name = tensor<string, []>("op_1567_cast_fp16")]; |
| tensor<int32, []> var_1569 = const()[name = tensor<string, []>("op_1569"), val = tensor<int32, []>(2)]; |
| tensor<bool, []> x_interleave_0 = const()[name = tensor<string, []>("x_interleave_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [1, 128, ?]> x_cast_fp16 = concat(axis = var_1569, interleave = x_interleave_0, values = (var_1567_cast_fp16, x_11_cast_fp16))[name = tensor<string, []>("x_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_165_cast_fp16 = add(x = x_cast_fp16, y = x_source_1)[name = tensor<string, []>("input_165_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_3_adain1_0_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46184384))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46217216))), name = tensor<string, []>("resblocks_3_adain1_0_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_3_adain1_0_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_3_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46217792)))]; |
| tensor<fp16, [1, 256]> linear_28_cast_fp16 = linear(bias = resblocks_3_adain1_0_fc_bias_to_fp16, weight = resblocks_3_adain1_0_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_28_cast_fp16")]; |
| tensor<int32, [3]> var_1661 = const()[name = tensor<string, []>("op_1661"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_115_cast_fp16 = reshape(shape = var_1661, x = linear_28_cast_fp16)[name = tensor<string, []>("h_115_cast_fp16")]; |
| tensor<int32, [2]> var_1663_split_sizes_0 = const()[name = tensor<string, []>("op_1663_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_1663_axis_0 = const()[name = tensor<string, []>("op_1663_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_1663_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1663_cast_fp16_1 = split(axis = var_1663_axis_0, split_sizes = var_1663_split_sizes_0, x = h_115_cast_fp16)[name = tensor<string, []>("op_1663_cast_fp16")]; |
| tensor<fp16, []> var_1665_promoted_to_fp16 = const()[name = tensor<string, []>("op_1665_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_1666_cast_fp16 = add(x = var_1663_cast_fp16_0, y = var_1665_promoted_to_fp16)[name = tensor<string, []>("op_1666_cast_fp16")]; |
| tensor<fp16, [128]> resblocks_3_adain1_0_norm_weight_to_fp16 = const()[name = tensor<string, []>("resblocks_3_adain1_0_norm_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46218368)))]; |
| tensor<fp16, [128]> resblocks_3_adain1_0_norm_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_3_adain1_0_norm_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46218688)))]; |
| tensor<fp16, []> var_1578_to_fp16 = const()[name = tensor<string, []>("op_1578_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| tensor<fp16, [1, 128, ?]> var_1669_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_1578_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_165_cast_fp16)[name = tensor<string, []>("op_1669_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_1670_cast_fp16 = mul(x = var_1666_cast_fp16, y = var_1669_cast_fp16)[name = tensor<string, []>("op_1670_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_55_cast_fp16 = add(x = var_1670_cast_fp16, y = var_1663_cast_fp16_1)[name = tensor<string, []>("xt_55_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_1673_to_fp16 = const()[name = tensor<string, []>("op_1673_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46219008)))]; |
| tensor<fp16, [1, 128, ?]> var_1674_cast_fp16 = mul(x = xt_55_cast_fp16, y = var_1673_to_fp16)[name = tensor<string, []>("op_1674_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_37_cast_fp16 = cos(x = var_1674_cast_fp16)[name = tensor<string, []>("cv_37_cast_fp16")]; |
| tensor<fp16, []> var_1676_to_fp16 = const()[name = tensor<string, []>("op_1676_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_1677_cast_fp16 = mul(x = cv_37_cast_fp16, y = var_1676_to_fp16)[name = tensor<string, []>("op_1677_cast_fp16")]; |
| tensor<fp16, []> var_1678_to_fp16 = const()[name = tensor<string, []>("op_1678_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_1679_cast_fp16 = add(x = var_1677_cast_fp16, y = var_1678_to_fp16)[name = tensor<string, []>("op_1679_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_1680_to_fp16 = const()[name = tensor<string, []>("op_1680_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46219328)))]; |
| tensor<fp16, [1, 128, ?]> var_1683_cast_fp16 = mul(x = var_1679_cast_fp16, y = var_1680_to_fp16)[name = tensor<string, []>("op_1683_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_167_cast_fp16 = add(x = xt_55_cast_fp16, y = var_1683_cast_fp16)[name = tensor<string, []>("input_167_cast_fp16")]; |
| tensor<string, []> input_169_pad_type_0 = const()[name = tensor<string, []>("input_169_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_169_pad_0 = const()[name = tensor<string, []>("input_169_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> input_169_strides_0 = const()[name = tensor<string, []>("input_169_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> input_169_dilations_0 = const()[name = tensor<string, []>("input_169_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_169_groups_0 = const()[name = tensor<string, []>("input_169_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 3]> weight_131_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [49152]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46219648))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46268864))), name = tensor<string, []>("weight_131_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 3])]; |
| tensor<fp16, [128]> resblocks_3_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_3_convs1_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46269440)))]; |
| tensor<fp16, [1, 128, ?]> input_169_cast_fp16 = conv(bias = resblocks_3_convs1_0_bias_to_fp16, dilations = input_169_dilations_0, groups = input_169_groups_0, pad = input_169_pad_0, pad_type = input_169_pad_type_0, strides = input_169_strides_0, weight = weight_131_to_fp16_palettized, x = input_167_cast_fp16)[name = tensor<string, []>("input_169_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_3_adain2_0_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46269760))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46302592))), name = tensor<string, []>("resblocks_3_adain2_0_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_3_adain2_0_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_3_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46303168)))]; |
| tensor<fp16, [1, 256]> linear_29_cast_fp16 = linear(bias = resblocks_3_adain2_0_fc_bias_to_fp16, weight = resblocks_3_adain2_0_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_29_cast_fp16")]; |
| tensor<int32, [3]> var_1699 = const()[name = tensor<string, []>("op_1699"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_119_cast_fp16 = reshape(shape = var_1699, x = linear_29_cast_fp16)[name = tensor<string, []>("h_119_cast_fp16")]; |
| tensor<int32, [2]> var_1701_split_sizes_0 = const()[name = tensor<string, []>("op_1701_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_1701_axis_0 = const()[name = tensor<string, []>("op_1701_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_1701_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1701_cast_fp16_1 = split(axis = var_1701_axis_0, split_sizes = var_1701_split_sizes_0, x = h_119_cast_fp16)[name = tensor<string, []>("op_1701_cast_fp16")]; |
| tensor<fp16, []> var_1703_promoted_to_fp16 = const()[name = tensor<string, []>("op_1703_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_1704_cast_fp16 = add(x = var_1701_cast_fp16_0, y = var_1703_promoted_to_fp16)[name = tensor<string, []>("op_1704_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_1707_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_1578_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_169_cast_fp16)[name = tensor<string, []>("op_1707_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_1708_cast_fp16 = mul(x = var_1704_cast_fp16, y = var_1707_cast_fp16)[name = tensor<string, []>("op_1708_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_57_cast_fp16 = add(x = var_1708_cast_fp16, y = var_1701_cast_fp16_1)[name = tensor<string, []>("xt_57_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_1711_to_fp16 = const()[name = tensor<string, []>("op_1711_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46303744)))]; |
| tensor<fp16, [1, 128, ?]> var_1712_cast_fp16 = mul(x = xt_57_cast_fp16, y = var_1711_to_fp16)[name = tensor<string, []>("op_1712_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_39_cast_fp16 = cos(x = var_1712_cast_fp16)[name = tensor<string, []>("cv_39_cast_fp16")]; |
| tensor<fp16, []> var_1714_to_fp16 = const()[name = tensor<string, []>("op_1714_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_1715_cast_fp16 = mul(x = cv_39_cast_fp16, y = var_1714_to_fp16)[name = tensor<string, []>("op_1715_cast_fp16")]; |
| tensor<fp16, []> var_1716_to_fp16 = const()[name = tensor<string, []>("op_1716_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_1717_cast_fp16 = add(x = var_1715_cast_fp16, y = var_1716_to_fp16)[name = tensor<string, []>("op_1717_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_1718_to_fp16 = const()[name = tensor<string, []>("op_1718_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46304064)))]; |
| tensor<fp16, [1, 128, ?]> var_1721_cast_fp16 = mul(x = var_1717_cast_fp16, y = var_1718_to_fp16)[name = tensor<string, []>("op_1721_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_171_cast_fp16 = add(x = xt_57_cast_fp16, y = var_1721_cast_fp16)[name = tensor<string, []>("input_171_cast_fp16")]; |
| tensor<string, []> xt_59_pad_type_0 = const()[name = tensor<string, []>("xt_59_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_59_pad_0 = const()[name = tensor<string, []>("xt_59_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> xt_59_strides_0 = const()[name = tensor<string, []>("xt_59_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_59_dilations_0 = const()[name = tensor<string, []>("xt_59_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_59_groups_0 = const()[name = tensor<string, []>("xt_59_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 3]> weight_135_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [49152]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46304384))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46353600))), name = tensor<string, []>("weight_135_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 3])]; |
| tensor<fp16, [128]> resblocks_3_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_3_convs2_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46354176)))]; |
| tensor<fp16, [1, 128, ?]> xt_59_cast_fp16 = conv(bias = resblocks_3_convs2_0_bias_to_fp16, dilations = xt_59_dilations_0, groups = xt_59_groups_0, pad = xt_59_pad_0, pad_type = xt_59_pad_type_0, strides = xt_59_strides_0, weight = weight_135_to_fp16_palettized, x = input_171_cast_fp16)[name = tensor<string, []>("xt_59_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_173_cast_fp16 = add(x = xt_59_cast_fp16, y = input_165_cast_fp16)[name = tensor<string, []>("input_173_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_3_adain1_1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46354496))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46387328))), name = tensor<string, []>("resblocks_3_adain1_1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_3_adain1_1_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_3_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46387904)))]; |
| tensor<fp16, [1, 256]> linear_30_cast_fp16 = linear(bias = resblocks_3_adain1_1_fc_bias_to_fp16, weight = resblocks_3_adain1_1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_30_cast_fp16")]; |
| tensor<int32, [3]> var_1738 = const()[name = tensor<string, []>("op_1738"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_123_cast_fp16 = reshape(shape = var_1738, x = linear_30_cast_fp16)[name = tensor<string, []>("h_123_cast_fp16")]; |
| tensor<int32, [2]> var_1740_split_sizes_0 = const()[name = tensor<string, []>("op_1740_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_1740_axis_0 = const()[name = tensor<string, []>("op_1740_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_1740_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1740_cast_fp16_1 = split(axis = var_1740_axis_0, split_sizes = var_1740_split_sizes_0, x = h_123_cast_fp16)[name = tensor<string, []>("op_1740_cast_fp16")]; |
| tensor<fp16, []> var_1742_promoted_to_fp16 = const()[name = tensor<string, []>("op_1742_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_1743_cast_fp16 = add(x = var_1740_cast_fp16_0, y = var_1742_promoted_to_fp16)[name = tensor<string, []>("op_1743_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_1746_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_1578_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_173_cast_fp16)[name = tensor<string, []>("op_1746_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_1747_cast_fp16 = mul(x = var_1743_cast_fp16, y = var_1746_cast_fp16)[name = tensor<string, []>("op_1747_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_61_cast_fp16 = add(x = var_1747_cast_fp16, y = var_1740_cast_fp16_1)[name = tensor<string, []>("xt_61_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_1750_to_fp16 = const()[name = tensor<string, []>("op_1750_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46388480)))]; |
| tensor<fp16, [1, 128, ?]> var_1751_cast_fp16 = mul(x = xt_61_cast_fp16, y = var_1750_to_fp16)[name = tensor<string, []>("op_1751_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_41_cast_fp16 = cos(x = var_1751_cast_fp16)[name = tensor<string, []>("cv_41_cast_fp16")]; |
| tensor<fp16, []> var_1753_to_fp16 = const()[name = tensor<string, []>("op_1753_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_1754_cast_fp16 = mul(x = cv_41_cast_fp16, y = var_1753_to_fp16)[name = tensor<string, []>("op_1754_cast_fp16")]; |
| tensor<fp16, []> var_1755_to_fp16 = const()[name = tensor<string, []>("op_1755_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_1756_cast_fp16 = add(x = var_1754_cast_fp16, y = var_1755_to_fp16)[name = tensor<string, []>("op_1756_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_1757_to_fp16 = const()[name = tensor<string, []>("op_1757_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46388800)))]; |
| tensor<fp16, [1, 128, ?]> var_1760_cast_fp16 = mul(x = var_1756_cast_fp16, y = var_1757_to_fp16)[name = tensor<string, []>("op_1760_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_175_cast_fp16 = add(x = xt_61_cast_fp16, y = var_1760_cast_fp16)[name = tensor<string, []>("input_175_cast_fp16")]; |
| tensor<string, []> input_177_pad_type_0 = const()[name = tensor<string, []>("input_177_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_177_pad_0 = const()[name = tensor<string, []>("input_177_pad_0"), val = tensor<int32, [2]>([3, 3])]; |
| tensor<int32, [1]> input_177_dilations_0 = const()[name = tensor<string, []>("input_177_dilations_0"), val = tensor<int32, [1]>([3])]; |
| tensor<int32, [1]> input_177_strides_0 = const()[name = tensor<string, []>("input_177_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_177_groups_0 = const()[name = tensor<string, []>("input_177_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 3]> weight_139_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [49152]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46389120))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46438336))), name = tensor<string, []>("weight_139_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 3])]; |
| tensor<fp16, [128]> resblocks_3_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_3_convs1_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46438912)))]; |
| tensor<fp16, [1, 128, ?]> input_177_cast_fp16 = conv(bias = resblocks_3_convs1_1_bias_to_fp16, dilations = input_177_dilations_0, groups = input_177_groups_0, pad = input_177_pad_0, pad_type = input_177_pad_type_0, strides = input_177_strides_0, weight = weight_139_to_fp16_palettized, x = input_175_cast_fp16)[name = tensor<string, []>("input_177_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_3_adain2_1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46439232))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46472064))), name = tensor<string, []>("resblocks_3_adain2_1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_3_adain2_1_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_3_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46472640)))]; |
| tensor<fp16, [1, 256]> linear_31_cast_fp16 = linear(bias = resblocks_3_adain2_1_fc_bias_to_fp16, weight = resblocks_3_adain2_1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_31_cast_fp16")]; |
| tensor<int32, [3]> var_1776 = const()[name = tensor<string, []>("op_1776"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_127_cast_fp16 = reshape(shape = var_1776, x = linear_31_cast_fp16)[name = tensor<string, []>("h_127_cast_fp16")]; |
| tensor<int32, [2]> var_1778_split_sizes_0 = const()[name = tensor<string, []>("op_1778_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_1778_axis_0 = const()[name = tensor<string, []>("op_1778_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_1778_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1778_cast_fp16_1 = split(axis = var_1778_axis_0, split_sizes = var_1778_split_sizes_0, x = h_127_cast_fp16)[name = tensor<string, []>("op_1778_cast_fp16")]; |
| tensor<fp16, []> var_1780_promoted_to_fp16 = const()[name = tensor<string, []>("op_1780_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_1781_cast_fp16 = add(x = var_1778_cast_fp16_0, y = var_1780_promoted_to_fp16)[name = tensor<string, []>("op_1781_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_1784_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_1578_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_177_cast_fp16)[name = tensor<string, []>("op_1784_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_1785_cast_fp16 = mul(x = var_1781_cast_fp16, y = var_1784_cast_fp16)[name = tensor<string, []>("op_1785_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_63_cast_fp16 = add(x = var_1785_cast_fp16, y = var_1778_cast_fp16_1)[name = tensor<string, []>("xt_63_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_1788_to_fp16 = const()[name = tensor<string, []>("op_1788_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46473216)))]; |
| tensor<fp16, [1, 128, ?]> var_1789_cast_fp16 = mul(x = xt_63_cast_fp16, y = var_1788_to_fp16)[name = tensor<string, []>("op_1789_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_43_cast_fp16 = cos(x = var_1789_cast_fp16)[name = tensor<string, []>("cv_43_cast_fp16")]; |
| tensor<fp16, []> var_1791_to_fp16 = const()[name = tensor<string, []>("op_1791_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_1792_cast_fp16 = mul(x = cv_43_cast_fp16, y = var_1791_to_fp16)[name = tensor<string, []>("op_1792_cast_fp16")]; |
| tensor<fp16, []> var_1793_to_fp16 = const()[name = tensor<string, []>("op_1793_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_1794_cast_fp16 = add(x = var_1792_cast_fp16, y = var_1793_to_fp16)[name = tensor<string, []>("op_1794_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_1795_to_fp16 = const()[name = tensor<string, []>("op_1795_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46473536)))]; |
| tensor<fp16, [1, 128, ?]> var_1798_cast_fp16 = mul(x = var_1794_cast_fp16, y = var_1795_to_fp16)[name = tensor<string, []>("op_1798_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_179_cast_fp16 = add(x = xt_63_cast_fp16, y = var_1798_cast_fp16)[name = tensor<string, []>("input_179_cast_fp16")]; |
| tensor<string, []> xt_65_pad_type_0 = const()[name = tensor<string, []>("xt_65_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_65_pad_0 = const()[name = tensor<string, []>("xt_65_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> xt_65_strides_0 = const()[name = tensor<string, []>("xt_65_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_65_dilations_0 = const()[name = tensor<string, []>("xt_65_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_65_groups_0 = const()[name = tensor<string, []>("xt_65_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 3]> weight_143_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [49152]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46473856))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46523072))), name = tensor<string, []>("weight_143_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 3])]; |
| tensor<fp16, [128]> resblocks_3_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_3_convs2_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46523648)))]; |
| tensor<fp16, [1, 128, ?]> xt_65_cast_fp16 = conv(bias = resblocks_3_convs2_1_bias_to_fp16, dilations = xt_65_dilations_0, groups = xt_65_groups_0, pad = xt_65_pad_0, pad_type = xt_65_pad_type_0, strides = xt_65_strides_0, weight = weight_143_to_fp16_palettized, x = input_179_cast_fp16)[name = tensor<string, []>("xt_65_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_181_cast_fp16 = add(x = xt_65_cast_fp16, y = input_173_cast_fp16)[name = tensor<string, []>("input_181_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_3_adain1_2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46523968))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46556800))), name = tensor<string, []>("resblocks_3_adain1_2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_3_adain1_2_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_3_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46557376)))]; |
| tensor<fp16, [1, 256]> linear_32_cast_fp16 = linear(bias = resblocks_3_adain1_2_fc_bias_to_fp16, weight = resblocks_3_adain1_2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_32_cast_fp16")]; |
| tensor<int32, [3]> var_1815 = const()[name = tensor<string, []>("op_1815"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_131_cast_fp16 = reshape(shape = var_1815, x = linear_32_cast_fp16)[name = tensor<string, []>("h_131_cast_fp16")]; |
| tensor<int32, [2]> var_1817_split_sizes_0 = const()[name = tensor<string, []>("op_1817_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_1817_axis_0 = const()[name = tensor<string, []>("op_1817_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_1817_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1817_cast_fp16_1 = split(axis = var_1817_axis_0, split_sizes = var_1817_split_sizes_0, x = h_131_cast_fp16)[name = tensor<string, []>("op_1817_cast_fp16")]; |
| tensor<fp16, []> var_1819_promoted_to_fp16 = const()[name = tensor<string, []>("op_1819_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_1820_cast_fp16 = add(x = var_1817_cast_fp16_0, y = var_1819_promoted_to_fp16)[name = tensor<string, []>("op_1820_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_1823_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_1578_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_181_cast_fp16)[name = tensor<string, []>("op_1823_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_1824_cast_fp16 = mul(x = var_1820_cast_fp16, y = var_1823_cast_fp16)[name = tensor<string, []>("op_1824_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_67_cast_fp16 = add(x = var_1824_cast_fp16, y = var_1817_cast_fp16_1)[name = tensor<string, []>("xt_67_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_1827_to_fp16 = const()[name = tensor<string, []>("op_1827_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46557952)))]; |
| tensor<fp16, [1, 128, ?]> var_1828_cast_fp16 = mul(x = xt_67_cast_fp16, y = var_1827_to_fp16)[name = tensor<string, []>("op_1828_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_45_cast_fp16 = cos(x = var_1828_cast_fp16)[name = tensor<string, []>("cv_45_cast_fp16")]; |
| tensor<fp16, []> var_1830_to_fp16 = const()[name = tensor<string, []>("op_1830_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_1831_cast_fp16 = mul(x = cv_45_cast_fp16, y = var_1830_to_fp16)[name = tensor<string, []>("op_1831_cast_fp16")]; |
| tensor<fp16, []> var_1832_to_fp16 = const()[name = tensor<string, []>("op_1832_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_1833_cast_fp16 = add(x = var_1831_cast_fp16, y = var_1832_to_fp16)[name = tensor<string, []>("op_1833_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_1834_to_fp16 = const()[name = tensor<string, []>("op_1834_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46558272)))]; |
| tensor<fp16, [1, 128, ?]> var_1837_cast_fp16 = mul(x = var_1833_cast_fp16, y = var_1834_to_fp16)[name = tensor<string, []>("op_1837_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_183_cast_fp16 = add(x = xt_67_cast_fp16, y = var_1837_cast_fp16)[name = tensor<string, []>("input_183_cast_fp16")]; |
| tensor<string, []> input_185_pad_type_0 = const()[name = tensor<string, []>("input_185_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_185_pad_0 = const()[name = tensor<string, []>("input_185_pad_0"), val = tensor<int32, [2]>([5, 5])]; |
| tensor<int32, [1]> input_185_dilations_0 = const()[name = tensor<string, []>("input_185_dilations_0"), val = tensor<int32, [1]>([5])]; |
| tensor<int32, [1]> input_185_strides_0 = const()[name = tensor<string, []>("input_185_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_185_groups_0 = const()[name = tensor<string, []>("input_185_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 3]> weight_147_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [49152]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46558592))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46607808))), name = tensor<string, []>("weight_147_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 3])]; |
| tensor<fp16, [128]> resblocks_3_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_3_convs1_2_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46608384)))]; |
| tensor<fp16, [1, 128, ?]> input_185_cast_fp16 = conv(bias = resblocks_3_convs1_2_bias_to_fp16, dilations = input_185_dilations_0, groups = input_185_groups_0, pad = input_185_pad_0, pad_type = input_185_pad_type_0, strides = input_185_strides_0, weight = weight_147_to_fp16_palettized, x = input_183_cast_fp16)[name = tensor<string, []>("input_185_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_3_adain2_2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46608704))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46641536))), name = tensor<string, []>("resblocks_3_adain2_2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_3_adain2_2_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_3_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46642112)))]; |
| tensor<fp16, [1, 256]> linear_33_cast_fp16 = linear(bias = resblocks_3_adain2_2_fc_bias_to_fp16, weight = resblocks_3_adain2_2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_33_cast_fp16")]; |
| tensor<int32, [3]> var_1853 = const()[name = tensor<string, []>("op_1853"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_135_cast_fp16 = reshape(shape = var_1853, x = linear_33_cast_fp16)[name = tensor<string, []>("h_135_cast_fp16")]; |
| tensor<int32, [2]> var_1855_split_sizes_0 = const()[name = tensor<string, []>("op_1855_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_1855_axis_0 = const()[name = tensor<string, []>("op_1855_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_1855_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1855_cast_fp16_1 = split(axis = var_1855_axis_0, split_sizes = var_1855_split_sizes_0, x = h_135_cast_fp16)[name = tensor<string, []>("op_1855_cast_fp16")]; |
| tensor<fp16, []> var_1857_promoted_to_fp16 = const()[name = tensor<string, []>("op_1857_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_1858_cast_fp16 = add(x = var_1855_cast_fp16_0, y = var_1857_promoted_to_fp16)[name = tensor<string, []>("op_1858_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_1861_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_1578_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_185_cast_fp16)[name = tensor<string, []>("op_1861_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_1862_cast_fp16 = mul(x = var_1858_cast_fp16, y = var_1861_cast_fp16)[name = tensor<string, []>("op_1862_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_69_cast_fp16 = add(x = var_1862_cast_fp16, y = var_1855_cast_fp16_1)[name = tensor<string, []>("xt_69_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_1865_to_fp16 = const()[name = tensor<string, []>("op_1865_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46642688)))]; |
| tensor<fp16, [1, 128, ?]> var_1866_cast_fp16 = mul(x = xt_69_cast_fp16, y = var_1865_to_fp16)[name = tensor<string, []>("op_1866_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_47_cast_fp16 = cos(x = var_1866_cast_fp16)[name = tensor<string, []>("cv_47_cast_fp16")]; |
| tensor<fp16, []> var_1868_to_fp16 = const()[name = tensor<string, []>("op_1868_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_1869_cast_fp16 = mul(x = cv_47_cast_fp16, y = var_1868_to_fp16)[name = tensor<string, []>("op_1869_cast_fp16")]; |
| tensor<fp16, []> var_1870_to_fp16 = const()[name = tensor<string, []>("op_1870_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_1871_cast_fp16 = add(x = var_1869_cast_fp16, y = var_1870_to_fp16)[name = tensor<string, []>("op_1871_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_1872_to_fp16 = const()[name = tensor<string, []>("op_1872_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46643008)))]; |
| tensor<fp16, [1, 128, ?]> var_1875_cast_fp16 = mul(x = var_1871_cast_fp16, y = var_1872_to_fp16)[name = tensor<string, []>("op_1875_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_187_cast_fp16 = add(x = xt_69_cast_fp16, y = var_1875_cast_fp16)[name = tensor<string, []>("input_187_cast_fp16")]; |
| tensor<string, []> xt_71_pad_type_0 = const()[name = tensor<string, []>("xt_71_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_71_pad_0 = const()[name = tensor<string, []>("xt_71_pad_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [1]> xt_71_strides_0 = const()[name = tensor<string, []>("xt_71_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_71_dilations_0 = const()[name = tensor<string, []>("xt_71_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_71_groups_0 = const()[name = tensor<string, []>("xt_71_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 3]> weight_151_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [49152]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46643328))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46692544))), name = tensor<string, []>("weight_151_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 3])]; |
| tensor<fp16, [128]> resblocks_3_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_3_convs2_2_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46693120)))]; |
| tensor<fp16, [1, 128, ?]> xt_71_cast_fp16 = conv(bias = resblocks_3_convs2_2_bias_to_fp16, dilations = xt_71_dilations_0, groups = xt_71_groups_0, pad = xt_71_pad_0, pad_type = xt_71_pad_type_0, strides = xt_71_strides_0, weight = weight_151_to_fp16_palettized, x = input_187_cast_fp16)[name = tensor<string, []>("xt_71_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xs_7_cast_fp16 = add(x = xt_71_cast_fp16, y = input_181_cast_fp16)[name = tensor<string, []>("xs_7_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_4_adain1_0_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46693440))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46726272))), name = tensor<string, []>("resblocks_4_adain1_0_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_4_adain1_0_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_4_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46726848)))]; |
| tensor<fp16, [1, 256]> linear_34_cast_fp16 = linear(bias = resblocks_4_adain1_0_fc_bias_to_fp16, weight = resblocks_4_adain1_0_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_34_cast_fp16")]; |
| tensor<int32, [3]> var_1975 = const()[name = tensor<string, []>("op_1975"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_139_cast_fp16 = reshape(shape = var_1975, x = linear_34_cast_fp16)[name = tensor<string, []>("h_139_cast_fp16")]; |
| tensor<int32, [2]> var_1977_split_sizes_0 = const()[name = tensor<string, []>("op_1977_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_1977_axis_0 = const()[name = tensor<string, []>("op_1977_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_1977_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1977_cast_fp16_1 = split(axis = var_1977_axis_0, split_sizes = var_1977_split_sizes_0, x = h_139_cast_fp16)[name = tensor<string, []>("op_1977_cast_fp16")]; |
| tensor<fp16, []> var_1979_promoted_to_fp16 = const()[name = tensor<string, []>("op_1979_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_1980_cast_fp16 = add(x = var_1977_cast_fp16_0, y = var_1979_promoted_to_fp16)[name = tensor<string, []>("op_1980_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_1984_cast_fp16 = mul(x = var_1980_cast_fp16, y = var_1669_cast_fp16)[name = tensor<string, []>("op_1984_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_73_cast_fp16 = add(x = var_1984_cast_fp16, y = var_1977_cast_fp16_1)[name = tensor<string, []>("xt_73_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_1987_to_fp16 = const()[name = tensor<string, []>("op_1987_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46727424)))]; |
| tensor<fp16, [1, 128, ?]> var_1988_cast_fp16 = mul(x = xt_73_cast_fp16, y = var_1987_to_fp16)[name = tensor<string, []>("op_1988_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_49_cast_fp16 = cos(x = var_1988_cast_fp16)[name = tensor<string, []>("cv_49_cast_fp16")]; |
| tensor<fp16, []> var_1990_to_fp16 = const()[name = tensor<string, []>("op_1990_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_1991_cast_fp16 = mul(x = cv_49_cast_fp16, y = var_1990_to_fp16)[name = tensor<string, []>("op_1991_cast_fp16")]; |
| tensor<fp16, []> var_1992_to_fp16 = const()[name = tensor<string, []>("op_1992_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_1993_cast_fp16 = add(x = var_1991_cast_fp16, y = var_1992_to_fp16)[name = tensor<string, []>("op_1993_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_1994_to_fp16 = const()[name = tensor<string, []>("op_1994_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46727744)))]; |
| tensor<fp16, [1, 128, ?]> var_1997_cast_fp16 = mul(x = var_1993_cast_fp16, y = var_1994_to_fp16)[name = tensor<string, []>("op_1997_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_189_cast_fp16 = add(x = xt_73_cast_fp16, y = var_1997_cast_fp16)[name = tensor<string, []>("input_189_cast_fp16")]; |
| tensor<string, []> input_191_pad_type_0 = const()[name = tensor<string, []>("input_191_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_191_pad_0 = const()[name = tensor<string, []>("input_191_pad_0"), val = tensor<int32, [2]>([3, 3])]; |
| tensor<int32, [1]> input_191_strides_0 = const()[name = tensor<string, []>("input_191_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> input_191_dilations_0 = const()[name = tensor<string, []>("input_191_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_191_groups_0 = const()[name = tensor<string, []>("input_191_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 7]> weight_155_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [114688]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46728064))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46842816))), name = tensor<string, []>("weight_155_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 7])]; |
| tensor<fp16, [128]> resblocks_4_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_4_convs1_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46843392)))]; |
| tensor<fp16, [1, 128, ?]> input_191_cast_fp16 = conv(bias = resblocks_4_convs1_0_bias_to_fp16, dilations = input_191_dilations_0, groups = input_191_groups_0, pad = input_191_pad_0, pad_type = input_191_pad_type_0, strides = input_191_strides_0, weight = weight_155_to_fp16_palettized, x = input_189_cast_fp16)[name = tensor<string, []>("input_191_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_4_adain2_0_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46843712))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46876544))), name = tensor<string, []>("resblocks_4_adain2_0_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_4_adain2_0_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_4_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46877120)))]; |
| tensor<fp16, [1, 256]> linear_35_cast_fp16 = linear(bias = resblocks_4_adain2_0_fc_bias_to_fp16, weight = resblocks_4_adain2_0_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_35_cast_fp16")]; |
| tensor<int32, [3]> var_2013 = const()[name = tensor<string, []>("op_2013"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_143_cast_fp16 = reshape(shape = var_2013, x = linear_35_cast_fp16)[name = tensor<string, []>("h_143_cast_fp16")]; |
| tensor<int32, [2]> var_2015_split_sizes_0 = const()[name = tensor<string, []>("op_2015_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_2015_axis_0 = const()[name = tensor<string, []>("op_2015_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_2015_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_2015_cast_fp16_1 = split(axis = var_2015_axis_0, split_sizes = var_2015_split_sizes_0, x = h_143_cast_fp16)[name = tensor<string, []>("op_2015_cast_fp16")]; |
| tensor<fp16, []> var_2017_promoted_to_fp16 = const()[name = tensor<string, []>("op_2017_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_2018_cast_fp16 = add(x = var_2015_cast_fp16_0, y = var_2017_promoted_to_fp16)[name = tensor<string, []>("op_2018_cast_fp16")]; |
| tensor<fp16, []> var_1892_to_fp16 = const()[name = tensor<string, []>("op_1892_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| tensor<fp16, [1, 128, ?]> var_2021_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_1892_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_191_cast_fp16)[name = tensor<string, []>("op_2021_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2022_cast_fp16 = mul(x = var_2018_cast_fp16, y = var_2021_cast_fp16)[name = tensor<string, []>("op_2022_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_75_cast_fp16 = add(x = var_2022_cast_fp16, y = var_2015_cast_fp16_1)[name = tensor<string, []>("xt_75_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2025_to_fp16 = const()[name = tensor<string, []>("op_2025_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46877696)))]; |
| tensor<fp16, [1, 128, ?]> var_2026_cast_fp16 = mul(x = xt_75_cast_fp16, y = var_2025_to_fp16)[name = tensor<string, []>("op_2026_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_51_cast_fp16 = cos(x = var_2026_cast_fp16)[name = tensor<string, []>("cv_51_cast_fp16")]; |
| tensor<fp16, []> var_2028_to_fp16 = const()[name = tensor<string, []>("op_2028_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2029_cast_fp16 = mul(x = cv_51_cast_fp16, y = var_2028_to_fp16)[name = tensor<string, []>("op_2029_cast_fp16")]; |
| tensor<fp16, []> var_2030_to_fp16 = const()[name = tensor<string, []>("op_2030_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2031_cast_fp16 = add(x = var_2029_cast_fp16, y = var_2030_to_fp16)[name = tensor<string, []>("op_2031_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2032_to_fp16 = const()[name = tensor<string, []>("op_2032_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46878016)))]; |
| tensor<fp16, [1, 128, ?]> var_2035_cast_fp16 = mul(x = var_2031_cast_fp16, y = var_2032_to_fp16)[name = tensor<string, []>("op_2035_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_193_cast_fp16 = add(x = xt_75_cast_fp16, y = var_2035_cast_fp16)[name = tensor<string, []>("input_193_cast_fp16")]; |
| tensor<string, []> xt_77_pad_type_0 = const()[name = tensor<string, []>("xt_77_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_77_pad_0 = const()[name = tensor<string, []>("xt_77_pad_0"), val = tensor<int32, [2]>([3, 3])]; |
| tensor<int32, [1]> xt_77_strides_0 = const()[name = tensor<string, []>("xt_77_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_77_dilations_0 = const()[name = tensor<string, []>("xt_77_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_77_groups_0 = const()[name = tensor<string, []>("xt_77_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 7]> weight_159_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [114688]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46878336))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46993088))), name = tensor<string, []>("weight_159_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 7])]; |
| tensor<fp16, [128]> resblocks_4_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_4_convs2_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46993664)))]; |
| tensor<fp16, [1, 128, ?]> xt_77_cast_fp16 = conv(bias = resblocks_4_convs2_0_bias_to_fp16, dilations = xt_77_dilations_0, groups = xt_77_groups_0, pad = xt_77_pad_0, pad_type = xt_77_pad_type_0, strides = xt_77_strides_0, weight = weight_159_to_fp16_palettized, x = input_193_cast_fp16)[name = tensor<string, []>("xt_77_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_195_cast_fp16 = add(x = xt_77_cast_fp16, y = input_165_cast_fp16)[name = tensor<string, []>("input_195_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_4_adain1_1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46993984))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47026816))), name = tensor<string, []>("resblocks_4_adain1_1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_4_adain1_1_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_4_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47027392)))]; |
| tensor<fp16, [1, 256]> linear_36_cast_fp16 = linear(bias = resblocks_4_adain1_1_fc_bias_to_fp16, weight = resblocks_4_adain1_1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_36_cast_fp16")]; |
| tensor<int32, [3]> var_2052 = const()[name = tensor<string, []>("op_2052"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_147_cast_fp16 = reshape(shape = var_2052, x = linear_36_cast_fp16)[name = tensor<string, []>("h_147_cast_fp16")]; |
| tensor<int32, [2]> var_2054_split_sizes_0 = const()[name = tensor<string, []>("op_2054_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_2054_axis_0 = const()[name = tensor<string, []>("op_2054_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_2054_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_2054_cast_fp16_1 = split(axis = var_2054_axis_0, split_sizes = var_2054_split_sizes_0, x = h_147_cast_fp16)[name = tensor<string, []>("op_2054_cast_fp16")]; |
| tensor<fp16, []> var_2056_promoted_to_fp16 = const()[name = tensor<string, []>("op_2056_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_2057_cast_fp16 = add(x = var_2054_cast_fp16_0, y = var_2056_promoted_to_fp16)[name = tensor<string, []>("op_2057_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2060_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_1892_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_195_cast_fp16)[name = tensor<string, []>("op_2060_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2061_cast_fp16 = mul(x = var_2057_cast_fp16, y = var_2060_cast_fp16)[name = tensor<string, []>("op_2061_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_79_cast_fp16 = add(x = var_2061_cast_fp16, y = var_2054_cast_fp16_1)[name = tensor<string, []>("xt_79_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2064_to_fp16 = const()[name = tensor<string, []>("op_2064_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47027968)))]; |
| tensor<fp16, [1, 128, ?]> var_2065_cast_fp16 = mul(x = xt_79_cast_fp16, y = var_2064_to_fp16)[name = tensor<string, []>("op_2065_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_53_cast_fp16 = cos(x = var_2065_cast_fp16)[name = tensor<string, []>("cv_53_cast_fp16")]; |
| tensor<fp16, []> var_2067_to_fp16 = const()[name = tensor<string, []>("op_2067_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2068_cast_fp16 = mul(x = cv_53_cast_fp16, y = var_2067_to_fp16)[name = tensor<string, []>("op_2068_cast_fp16")]; |
| tensor<fp16, []> var_2069_to_fp16 = const()[name = tensor<string, []>("op_2069_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2070_cast_fp16 = add(x = var_2068_cast_fp16, y = var_2069_to_fp16)[name = tensor<string, []>("op_2070_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2071_to_fp16 = const()[name = tensor<string, []>("op_2071_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47028288)))]; |
| tensor<fp16, [1, 128, ?]> var_2074_cast_fp16 = mul(x = var_2070_cast_fp16, y = var_2071_to_fp16)[name = tensor<string, []>("op_2074_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_197_cast_fp16 = add(x = xt_79_cast_fp16, y = var_2074_cast_fp16)[name = tensor<string, []>("input_197_cast_fp16")]; |
| tensor<string, []> input_199_pad_type_0 = const()[name = tensor<string, []>("input_199_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_199_pad_0 = const()[name = tensor<string, []>("input_199_pad_0"), val = tensor<int32, [2]>([9, 9])]; |
| tensor<int32, [1]> input_199_dilations_0 = const()[name = tensor<string, []>("input_199_dilations_0"), val = tensor<int32, [1]>([3])]; |
| tensor<int32, [1]> input_199_strides_0 = const()[name = tensor<string, []>("input_199_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_199_groups_0 = const()[name = tensor<string, []>("input_199_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 7]> weight_163_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [114688]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47028608))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47143360))), name = tensor<string, []>("weight_163_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 7])]; |
| tensor<fp16, [128]> resblocks_4_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_4_convs1_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47143936)))]; |
| tensor<fp16, [1, 128, ?]> input_199_cast_fp16 = conv(bias = resblocks_4_convs1_1_bias_to_fp16, dilations = input_199_dilations_0, groups = input_199_groups_0, pad = input_199_pad_0, pad_type = input_199_pad_type_0, strides = input_199_strides_0, weight = weight_163_to_fp16_palettized, x = input_197_cast_fp16)[name = tensor<string, []>("input_199_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_4_adain2_1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47144256))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47177088))), name = tensor<string, []>("resblocks_4_adain2_1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_4_adain2_1_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_4_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47177664)))]; |
| tensor<fp16, [1, 256]> linear_37_cast_fp16 = linear(bias = resblocks_4_adain2_1_fc_bias_to_fp16, weight = resblocks_4_adain2_1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_37_cast_fp16")]; |
| tensor<int32, [3]> var_2090 = const()[name = tensor<string, []>("op_2090"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_151_cast_fp16 = reshape(shape = var_2090, x = linear_37_cast_fp16)[name = tensor<string, []>("h_151_cast_fp16")]; |
| tensor<int32, [2]> var_2092_split_sizes_0 = const()[name = tensor<string, []>("op_2092_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_2092_axis_0 = const()[name = tensor<string, []>("op_2092_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_2092_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_2092_cast_fp16_1 = split(axis = var_2092_axis_0, split_sizes = var_2092_split_sizes_0, x = h_151_cast_fp16)[name = tensor<string, []>("op_2092_cast_fp16")]; |
| tensor<fp16, []> var_2094_promoted_to_fp16 = const()[name = tensor<string, []>("op_2094_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_2095_cast_fp16 = add(x = var_2092_cast_fp16_0, y = var_2094_promoted_to_fp16)[name = tensor<string, []>("op_2095_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2098_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_1892_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_199_cast_fp16)[name = tensor<string, []>("op_2098_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2099_cast_fp16 = mul(x = var_2095_cast_fp16, y = var_2098_cast_fp16)[name = tensor<string, []>("op_2099_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_81_cast_fp16 = add(x = var_2099_cast_fp16, y = var_2092_cast_fp16_1)[name = tensor<string, []>("xt_81_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2102_to_fp16 = const()[name = tensor<string, []>("op_2102_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47178240)))]; |
| tensor<fp16, [1, 128, ?]> var_2103_cast_fp16 = mul(x = xt_81_cast_fp16, y = var_2102_to_fp16)[name = tensor<string, []>("op_2103_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_55_cast_fp16 = cos(x = var_2103_cast_fp16)[name = tensor<string, []>("cv_55_cast_fp16")]; |
| tensor<fp16, []> var_2105_to_fp16 = const()[name = tensor<string, []>("op_2105_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2106_cast_fp16 = mul(x = cv_55_cast_fp16, y = var_2105_to_fp16)[name = tensor<string, []>("op_2106_cast_fp16")]; |
| tensor<fp16, []> var_2107_to_fp16 = const()[name = tensor<string, []>("op_2107_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2108_cast_fp16 = add(x = var_2106_cast_fp16, y = var_2107_to_fp16)[name = tensor<string, []>("op_2108_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2109_to_fp16 = const()[name = tensor<string, []>("op_2109_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47178560)))]; |
| tensor<fp16, [1, 128, ?]> var_2112_cast_fp16 = mul(x = var_2108_cast_fp16, y = var_2109_to_fp16)[name = tensor<string, []>("op_2112_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_201_cast_fp16 = add(x = xt_81_cast_fp16, y = var_2112_cast_fp16)[name = tensor<string, []>("input_201_cast_fp16")]; |
| tensor<string, []> xt_83_pad_type_0 = const()[name = tensor<string, []>("xt_83_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_83_pad_0 = const()[name = tensor<string, []>("xt_83_pad_0"), val = tensor<int32, [2]>([3, 3])]; |
| tensor<int32, [1]> xt_83_strides_0 = const()[name = tensor<string, []>("xt_83_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_83_dilations_0 = const()[name = tensor<string, []>("xt_83_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_83_groups_0 = const()[name = tensor<string, []>("xt_83_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 7]> weight_167_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [114688]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47178880))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47293632))), name = tensor<string, []>("weight_167_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 7])]; |
| tensor<fp16, [128]> resblocks_4_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_4_convs2_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47294208)))]; |
| tensor<fp16, [1, 128, ?]> xt_83_cast_fp16 = conv(bias = resblocks_4_convs2_1_bias_to_fp16, dilations = xt_83_dilations_0, groups = xt_83_groups_0, pad = xt_83_pad_0, pad_type = xt_83_pad_type_0, strides = xt_83_strides_0, weight = weight_167_to_fp16_palettized, x = input_201_cast_fp16)[name = tensor<string, []>("xt_83_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_203_cast_fp16 = add(x = xt_83_cast_fp16, y = input_195_cast_fp16)[name = tensor<string, []>("input_203_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_4_adain1_2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47294528))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47327360))), name = tensor<string, []>("resblocks_4_adain1_2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_4_adain1_2_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_4_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47327936)))]; |
| tensor<fp16, [1, 256]> linear_38_cast_fp16 = linear(bias = resblocks_4_adain1_2_fc_bias_to_fp16, weight = resblocks_4_adain1_2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_38_cast_fp16")]; |
| tensor<int32, [3]> var_2129 = const()[name = tensor<string, []>("op_2129"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_155_cast_fp16 = reshape(shape = var_2129, x = linear_38_cast_fp16)[name = tensor<string, []>("h_155_cast_fp16")]; |
| tensor<int32, [2]> var_2131_split_sizes_0 = const()[name = tensor<string, []>("op_2131_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_2131_axis_0 = const()[name = tensor<string, []>("op_2131_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_2131_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_2131_cast_fp16_1 = split(axis = var_2131_axis_0, split_sizes = var_2131_split_sizes_0, x = h_155_cast_fp16)[name = tensor<string, []>("op_2131_cast_fp16")]; |
| tensor<fp16, []> var_2133_promoted_to_fp16 = const()[name = tensor<string, []>("op_2133_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_2134_cast_fp16 = add(x = var_2131_cast_fp16_0, y = var_2133_promoted_to_fp16)[name = tensor<string, []>("op_2134_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2137_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_1892_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_203_cast_fp16)[name = tensor<string, []>("op_2137_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2138_cast_fp16 = mul(x = var_2134_cast_fp16, y = var_2137_cast_fp16)[name = tensor<string, []>("op_2138_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_85_cast_fp16 = add(x = var_2138_cast_fp16, y = var_2131_cast_fp16_1)[name = tensor<string, []>("xt_85_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2141_to_fp16 = const()[name = tensor<string, []>("op_2141_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47328512)))]; |
| tensor<fp16, [1, 128, ?]> var_2142_cast_fp16 = mul(x = xt_85_cast_fp16, y = var_2141_to_fp16)[name = tensor<string, []>("op_2142_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_57_cast_fp16 = cos(x = var_2142_cast_fp16)[name = tensor<string, []>("cv_57_cast_fp16")]; |
| tensor<fp16, []> var_2144_to_fp16 = const()[name = tensor<string, []>("op_2144_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2145_cast_fp16 = mul(x = cv_57_cast_fp16, y = var_2144_to_fp16)[name = tensor<string, []>("op_2145_cast_fp16")]; |
| tensor<fp16, []> var_2146_to_fp16 = const()[name = tensor<string, []>("op_2146_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2147_cast_fp16 = add(x = var_2145_cast_fp16, y = var_2146_to_fp16)[name = tensor<string, []>("op_2147_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2148_to_fp16 = const()[name = tensor<string, []>("op_2148_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47328832)))]; |
| tensor<fp16, [1, 128, ?]> var_2151_cast_fp16 = mul(x = var_2147_cast_fp16, y = var_2148_to_fp16)[name = tensor<string, []>("op_2151_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_205_cast_fp16 = add(x = xt_85_cast_fp16, y = var_2151_cast_fp16)[name = tensor<string, []>("input_205_cast_fp16")]; |
| tensor<string, []> input_207_pad_type_0 = const()[name = tensor<string, []>("input_207_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_207_pad_0 = const()[name = tensor<string, []>("input_207_pad_0"), val = tensor<int32, [2]>([15, 15])]; |
| tensor<int32, [1]> input_207_dilations_0 = const()[name = tensor<string, []>("input_207_dilations_0"), val = tensor<int32, [1]>([5])]; |
| tensor<int32, [1]> input_207_strides_0 = const()[name = tensor<string, []>("input_207_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_207_groups_0 = const()[name = tensor<string, []>("input_207_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 7]> weight_171_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [114688]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47329152))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47443904))), name = tensor<string, []>("weight_171_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 7])]; |
| tensor<fp16, [128]> resblocks_4_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_4_convs1_2_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47444480)))]; |
| tensor<fp16, [1, 128, ?]> input_207_cast_fp16 = conv(bias = resblocks_4_convs1_2_bias_to_fp16, dilations = input_207_dilations_0, groups = input_207_groups_0, pad = input_207_pad_0, pad_type = input_207_pad_type_0, strides = input_207_strides_0, weight = weight_171_to_fp16_palettized, x = input_205_cast_fp16)[name = tensor<string, []>("input_207_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_4_adain2_2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47444800))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47477632))), name = tensor<string, []>("resblocks_4_adain2_2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_4_adain2_2_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_4_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47478208)))]; |
| tensor<fp16, [1, 256]> linear_39_cast_fp16 = linear(bias = resblocks_4_adain2_2_fc_bias_to_fp16, weight = resblocks_4_adain2_2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_39_cast_fp16")]; |
| tensor<int32, [3]> var_2167 = const()[name = tensor<string, []>("op_2167"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_159_cast_fp16 = reshape(shape = var_2167, x = linear_39_cast_fp16)[name = tensor<string, []>("h_159_cast_fp16")]; |
| tensor<int32, [2]> var_2169_split_sizes_0 = const()[name = tensor<string, []>("op_2169_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_2169_axis_0 = const()[name = tensor<string, []>("op_2169_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_2169_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_2169_cast_fp16_1 = split(axis = var_2169_axis_0, split_sizes = var_2169_split_sizes_0, x = h_159_cast_fp16)[name = tensor<string, []>("op_2169_cast_fp16")]; |
| tensor<fp16, []> var_2171_promoted_to_fp16 = const()[name = tensor<string, []>("op_2171_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_2172_cast_fp16 = add(x = var_2169_cast_fp16_0, y = var_2171_promoted_to_fp16)[name = tensor<string, []>("op_2172_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2175_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_1892_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_207_cast_fp16)[name = tensor<string, []>("op_2175_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2176_cast_fp16 = mul(x = var_2172_cast_fp16, y = var_2175_cast_fp16)[name = tensor<string, []>("op_2176_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_87_cast_fp16 = add(x = var_2176_cast_fp16, y = var_2169_cast_fp16_1)[name = tensor<string, []>("xt_87_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2179_to_fp16 = const()[name = tensor<string, []>("op_2179_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47478784)))]; |
| tensor<fp16, [1, 128, ?]> var_2180_cast_fp16 = mul(x = xt_87_cast_fp16, y = var_2179_to_fp16)[name = tensor<string, []>("op_2180_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_59_cast_fp16 = cos(x = var_2180_cast_fp16)[name = tensor<string, []>("cv_59_cast_fp16")]; |
| tensor<fp16, []> var_2182_to_fp16 = const()[name = tensor<string, []>("op_2182_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2183_cast_fp16 = mul(x = cv_59_cast_fp16, y = var_2182_to_fp16)[name = tensor<string, []>("op_2183_cast_fp16")]; |
| tensor<fp16, []> var_2184_to_fp16 = const()[name = tensor<string, []>("op_2184_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2185_cast_fp16 = add(x = var_2183_cast_fp16, y = var_2184_to_fp16)[name = tensor<string, []>("op_2185_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2186_to_fp16 = const()[name = tensor<string, []>("op_2186_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47479104)))]; |
| tensor<fp16, [1, 128, ?]> var_2189_cast_fp16 = mul(x = var_2185_cast_fp16, y = var_2186_to_fp16)[name = tensor<string, []>("op_2189_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_209_cast_fp16 = add(x = xt_87_cast_fp16, y = var_2189_cast_fp16)[name = tensor<string, []>("input_209_cast_fp16")]; |
| tensor<string, []> xt_89_pad_type_0 = const()[name = tensor<string, []>("xt_89_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_89_pad_0 = const()[name = tensor<string, []>("xt_89_pad_0"), val = tensor<int32, [2]>([3, 3])]; |
| tensor<int32, [1]> xt_89_strides_0 = const()[name = tensor<string, []>("xt_89_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_89_dilations_0 = const()[name = tensor<string, []>("xt_89_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_89_groups_0 = const()[name = tensor<string, []>("xt_89_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 7]> weight_175_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [114688]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47479424))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47594176))), name = tensor<string, []>("weight_175_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 7])]; |
| tensor<fp16, [128]> resblocks_4_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_4_convs2_2_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47594752)))]; |
| tensor<fp16, [1, 128, ?]> xt_89_cast_fp16 = conv(bias = resblocks_4_convs2_2_bias_to_fp16, dilations = xt_89_dilations_0, groups = xt_89_groups_0, pad = xt_89_pad_0, pad_type = xt_89_pad_type_0, strides = xt_89_strides_0, weight = weight_175_to_fp16_palettized, x = input_209_cast_fp16)[name = tensor<string, []>("xt_89_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2198_cast_fp16 = add(x = xt_89_cast_fp16, y = input_203_cast_fp16)[name = tensor<string, []>("op_2198_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xs_9_cast_fp16 = add(x = xs_7_cast_fp16, y = var_2198_cast_fp16)[name = tensor<string, []>("xs_9_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_5_adain1_0_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47595072))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47627904))), name = tensor<string, []>("resblocks_5_adain1_0_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_5_adain1_0_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_5_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47628480)))]; |
| tensor<fp16, [1, 256]> linear_40_cast_fp16 = linear(bias = resblocks_5_adain1_0_fc_bias_to_fp16, weight = resblocks_5_adain1_0_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_40_cast_fp16")]; |
| tensor<int32, [3]> var_2291 = const()[name = tensor<string, []>("op_2291"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_163_cast_fp16 = reshape(shape = var_2291, x = linear_40_cast_fp16)[name = tensor<string, []>("h_163_cast_fp16")]; |
| tensor<int32, [2]> var_2293_split_sizes_0 = const()[name = tensor<string, []>("op_2293_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_2293_axis_0 = const()[name = tensor<string, []>("op_2293_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_2293_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_2293_cast_fp16_1 = split(axis = var_2293_axis_0, split_sizes = var_2293_split_sizes_0, x = h_163_cast_fp16)[name = tensor<string, []>("op_2293_cast_fp16")]; |
| tensor<fp16, []> var_2295_promoted_to_fp16 = const()[name = tensor<string, []>("op_2295_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_2296_cast_fp16 = add(x = var_2293_cast_fp16_0, y = var_2295_promoted_to_fp16)[name = tensor<string, []>("op_2296_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2300_cast_fp16 = mul(x = var_2296_cast_fp16, y = var_1669_cast_fp16)[name = tensor<string, []>("op_2300_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_91_cast_fp16 = add(x = var_2300_cast_fp16, y = var_2293_cast_fp16_1)[name = tensor<string, []>("xt_91_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2303_to_fp16 = const()[name = tensor<string, []>("op_2303_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47629056)))]; |
| tensor<fp16, [1, 128, ?]> var_2304_cast_fp16 = mul(x = xt_91_cast_fp16, y = var_2303_to_fp16)[name = tensor<string, []>("op_2304_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_61_cast_fp16 = cos(x = var_2304_cast_fp16)[name = tensor<string, []>("cv_61_cast_fp16")]; |
| tensor<fp16, []> var_2306_to_fp16 = const()[name = tensor<string, []>("op_2306_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2307_cast_fp16 = mul(x = cv_61_cast_fp16, y = var_2306_to_fp16)[name = tensor<string, []>("op_2307_cast_fp16")]; |
| tensor<fp16, []> var_2308_to_fp16 = const()[name = tensor<string, []>("op_2308_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2309_cast_fp16 = add(x = var_2307_cast_fp16, y = var_2308_to_fp16)[name = tensor<string, []>("op_2309_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2310_to_fp16 = const()[name = tensor<string, []>("op_2310_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47629376)))]; |
| tensor<fp16, [1, 128, ?]> var_2313_cast_fp16 = mul(x = var_2309_cast_fp16, y = var_2310_to_fp16)[name = tensor<string, []>("op_2313_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_211_cast_fp16 = add(x = xt_91_cast_fp16, y = var_2313_cast_fp16)[name = tensor<string, []>("input_211_cast_fp16")]; |
| tensor<string, []> input_213_pad_type_0 = const()[name = tensor<string, []>("input_213_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_213_pad_0 = const()[name = tensor<string, []>("input_213_pad_0"), val = tensor<int32, [2]>([5, 5])]; |
| tensor<int32, [1]> input_213_strides_0 = const()[name = tensor<string, []>("input_213_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> input_213_dilations_0 = const()[name = tensor<string, []>("input_213_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_213_groups_0 = const()[name = tensor<string, []>("input_213_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 11]> weight_179_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [180224]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47629696))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47809984))), name = tensor<string, []>("weight_179_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 11])]; |
| tensor<fp16, [128]> resblocks_5_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_5_convs1_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47810560)))]; |
| tensor<fp16, [1, 128, ?]> input_213_cast_fp16 = conv(bias = resblocks_5_convs1_0_bias_to_fp16, dilations = input_213_dilations_0, groups = input_213_groups_0, pad = input_213_pad_0, pad_type = input_213_pad_type_0, strides = input_213_strides_0, weight = weight_179_to_fp16_palettized, x = input_211_cast_fp16)[name = tensor<string, []>("input_213_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_5_adain2_0_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47810880))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47843712))), name = tensor<string, []>("resblocks_5_adain2_0_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_5_adain2_0_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_5_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47844288)))]; |
| tensor<fp16, [1, 256]> linear_41_cast_fp16 = linear(bias = resblocks_5_adain2_0_fc_bias_to_fp16, weight = resblocks_5_adain2_0_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_41_cast_fp16")]; |
| tensor<int32, [3]> var_2329 = const()[name = tensor<string, []>("op_2329"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_167_cast_fp16 = reshape(shape = var_2329, x = linear_41_cast_fp16)[name = tensor<string, []>("h_167_cast_fp16")]; |
| tensor<int32, [2]> var_2331_split_sizes_0 = const()[name = tensor<string, []>("op_2331_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_2331_axis_0 = const()[name = tensor<string, []>("op_2331_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_2331_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_2331_cast_fp16_1 = split(axis = var_2331_axis_0, split_sizes = var_2331_split_sizes_0, x = h_167_cast_fp16)[name = tensor<string, []>("op_2331_cast_fp16")]; |
| tensor<fp16, []> var_2333_promoted_to_fp16 = const()[name = tensor<string, []>("op_2333_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_2334_cast_fp16 = add(x = var_2331_cast_fp16_0, y = var_2333_promoted_to_fp16)[name = tensor<string, []>("op_2334_cast_fp16")]; |
| tensor<fp16, []> var_2208_to_fp16 = const()[name = tensor<string, []>("op_2208_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| tensor<fp16, [1, 128, ?]> var_2337_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_2208_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_213_cast_fp16)[name = tensor<string, []>("op_2337_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2338_cast_fp16 = mul(x = var_2334_cast_fp16, y = var_2337_cast_fp16)[name = tensor<string, []>("op_2338_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_93_cast_fp16 = add(x = var_2338_cast_fp16, y = var_2331_cast_fp16_1)[name = tensor<string, []>("xt_93_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2341_to_fp16 = const()[name = tensor<string, []>("op_2341_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47844864)))]; |
| tensor<fp16, [1, 128, ?]> var_2342_cast_fp16 = mul(x = xt_93_cast_fp16, y = var_2341_to_fp16)[name = tensor<string, []>("op_2342_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_63_cast_fp16 = cos(x = var_2342_cast_fp16)[name = tensor<string, []>("cv_63_cast_fp16")]; |
| tensor<fp16, []> var_2344_to_fp16 = const()[name = tensor<string, []>("op_2344_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2345_cast_fp16 = mul(x = cv_63_cast_fp16, y = var_2344_to_fp16)[name = tensor<string, []>("op_2345_cast_fp16")]; |
| tensor<fp16, []> var_2346_to_fp16 = const()[name = tensor<string, []>("op_2346_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2347_cast_fp16 = add(x = var_2345_cast_fp16, y = var_2346_to_fp16)[name = tensor<string, []>("op_2347_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2348_to_fp16 = const()[name = tensor<string, []>("op_2348_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47845184)))]; |
| tensor<fp16, [1, 128, ?]> var_2351_cast_fp16 = mul(x = var_2347_cast_fp16, y = var_2348_to_fp16)[name = tensor<string, []>("op_2351_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_215_cast_fp16 = add(x = xt_93_cast_fp16, y = var_2351_cast_fp16)[name = tensor<string, []>("input_215_cast_fp16")]; |
| tensor<string, []> xt_95_pad_type_0 = const()[name = tensor<string, []>("xt_95_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_95_pad_0 = const()[name = tensor<string, []>("xt_95_pad_0"), val = tensor<int32, [2]>([5, 5])]; |
| tensor<int32, [1]> xt_95_strides_0 = const()[name = tensor<string, []>("xt_95_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_95_dilations_0 = const()[name = tensor<string, []>("xt_95_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_95_groups_0 = const()[name = tensor<string, []>("xt_95_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 11]> weight_183_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [180224]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47845504))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48025792))), name = tensor<string, []>("weight_183_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 11])]; |
| tensor<fp16, [128]> resblocks_5_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_5_convs2_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48026368)))]; |
| tensor<fp16, [1, 128, ?]> xt_95_cast_fp16 = conv(bias = resblocks_5_convs2_0_bias_to_fp16, dilations = xt_95_dilations_0, groups = xt_95_groups_0, pad = xt_95_pad_0, pad_type = xt_95_pad_type_0, strides = xt_95_strides_0, weight = weight_183_to_fp16_palettized, x = input_215_cast_fp16)[name = tensor<string, []>("xt_95_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_217_cast_fp16 = add(x = xt_95_cast_fp16, y = input_165_cast_fp16)[name = tensor<string, []>("input_217_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_5_adain1_1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48026688))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48059520))), name = tensor<string, []>("resblocks_5_adain1_1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_5_adain1_1_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_5_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48060096)))]; |
| tensor<fp16, [1, 256]> linear_42_cast_fp16 = linear(bias = resblocks_5_adain1_1_fc_bias_to_fp16, weight = resblocks_5_adain1_1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_42_cast_fp16")]; |
| tensor<int32, [3]> var_2368 = const()[name = tensor<string, []>("op_2368"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_171_cast_fp16 = reshape(shape = var_2368, x = linear_42_cast_fp16)[name = tensor<string, []>("h_171_cast_fp16")]; |
| tensor<int32, [2]> var_2370_split_sizes_0 = const()[name = tensor<string, []>("op_2370_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_2370_axis_0 = const()[name = tensor<string, []>("op_2370_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_2370_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_2370_cast_fp16_1 = split(axis = var_2370_axis_0, split_sizes = var_2370_split_sizes_0, x = h_171_cast_fp16)[name = tensor<string, []>("op_2370_cast_fp16")]; |
| tensor<fp16, []> var_2372_promoted_to_fp16 = const()[name = tensor<string, []>("op_2372_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_2373_cast_fp16 = add(x = var_2370_cast_fp16_0, y = var_2372_promoted_to_fp16)[name = tensor<string, []>("op_2373_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2376_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_2208_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_217_cast_fp16)[name = tensor<string, []>("op_2376_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2377_cast_fp16 = mul(x = var_2373_cast_fp16, y = var_2376_cast_fp16)[name = tensor<string, []>("op_2377_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_97_cast_fp16 = add(x = var_2377_cast_fp16, y = var_2370_cast_fp16_1)[name = tensor<string, []>("xt_97_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2380_to_fp16 = const()[name = tensor<string, []>("op_2380_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48060672)))]; |
| tensor<fp16, [1, 128, ?]> var_2381_cast_fp16 = mul(x = xt_97_cast_fp16, y = var_2380_to_fp16)[name = tensor<string, []>("op_2381_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_65_cast_fp16 = cos(x = var_2381_cast_fp16)[name = tensor<string, []>("cv_65_cast_fp16")]; |
| tensor<fp16, []> var_2383_to_fp16 = const()[name = tensor<string, []>("op_2383_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2384_cast_fp16 = mul(x = cv_65_cast_fp16, y = var_2383_to_fp16)[name = tensor<string, []>("op_2384_cast_fp16")]; |
| tensor<fp16, []> var_2385_to_fp16 = const()[name = tensor<string, []>("op_2385_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2386_cast_fp16 = add(x = var_2384_cast_fp16, y = var_2385_to_fp16)[name = tensor<string, []>("op_2386_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2387_to_fp16 = const()[name = tensor<string, []>("op_2387_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48060992)))]; |
| tensor<fp16, [1, 128, ?]> var_2390_cast_fp16 = mul(x = var_2386_cast_fp16, y = var_2387_to_fp16)[name = tensor<string, []>("op_2390_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_219_cast_fp16 = add(x = xt_97_cast_fp16, y = var_2390_cast_fp16)[name = tensor<string, []>("input_219_cast_fp16")]; |
| tensor<string, []> input_221_pad_type_0 = const()[name = tensor<string, []>("input_221_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_221_pad_0 = const()[name = tensor<string, []>("input_221_pad_0"), val = tensor<int32, [2]>([15, 15])]; |
| tensor<int32, [1]> input_221_dilations_0 = const()[name = tensor<string, []>("input_221_dilations_0"), val = tensor<int32, [1]>([3])]; |
| tensor<int32, [1]> input_221_strides_0 = const()[name = tensor<string, []>("input_221_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_221_groups_0 = const()[name = tensor<string, []>("input_221_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 11]> weight_187_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [180224]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48061312))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48241600))), name = tensor<string, []>("weight_187_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 11])]; |
| tensor<fp16, [128]> resblocks_5_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_5_convs1_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48242176)))]; |
| tensor<fp16, [1, 128, ?]> input_221_cast_fp16 = conv(bias = resblocks_5_convs1_1_bias_to_fp16, dilations = input_221_dilations_0, groups = input_221_groups_0, pad = input_221_pad_0, pad_type = input_221_pad_type_0, strides = input_221_strides_0, weight = weight_187_to_fp16_palettized, x = input_219_cast_fp16)[name = tensor<string, []>("input_221_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_5_adain2_1_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48242496))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48275328))), name = tensor<string, []>("resblocks_5_adain2_1_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_5_adain2_1_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_5_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48275904)))]; |
| tensor<fp16, [1, 256]> linear_43_cast_fp16 = linear(bias = resblocks_5_adain2_1_fc_bias_to_fp16, weight = resblocks_5_adain2_1_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_43_cast_fp16")]; |
| tensor<int32, [3]> var_2406 = const()[name = tensor<string, []>("op_2406"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_175_cast_fp16 = reshape(shape = var_2406, x = linear_43_cast_fp16)[name = tensor<string, []>("h_175_cast_fp16")]; |
| tensor<int32, [2]> var_2408_split_sizes_0 = const()[name = tensor<string, []>("op_2408_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_2408_axis_0 = const()[name = tensor<string, []>("op_2408_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_2408_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_2408_cast_fp16_1 = split(axis = var_2408_axis_0, split_sizes = var_2408_split_sizes_0, x = h_175_cast_fp16)[name = tensor<string, []>("op_2408_cast_fp16")]; |
| tensor<fp16, []> var_2410_promoted_to_fp16 = const()[name = tensor<string, []>("op_2410_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_2411_cast_fp16 = add(x = var_2408_cast_fp16_0, y = var_2410_promoted_to_fp16)[name = tensor<string, []>("op_2411_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2414_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_2208_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_221_cast_fp16)[name = tensor<string, []>("op_2414_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2415_cast_fp16 = mul(x = var_2411_cast_fp16, y = var_2414_cast_fp16)[name = tensor<string, []>("op_2415_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_99_cast_fp16 = add(x = var_2415_cast_fp16, y = var_2408_cast_fp16_1)[name = tensor<string, []>("xt_99_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2418_to_fp16 = const()[name = tensor<string, []>("op_2418_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48276480)))]; |
| tensor<fp16, [1, 128, ?]> var_2419_cast_fp16 = mul(x = xt_99_cast_fp16, y = var_2418_to_fp16)[name = tensor<string, []>("op_2419_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_67_cast_fp16 = cos(x = var_2419_cast_fp16)[name = tensor<string, []>("cv_67_cast_fp16")]; |
| tensor<fp16, []> var_2421_to_fp16 = const()[name = tensor<string, []>("op_2421_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2422_cast_fp16 = mul(x = cv_67_cast_fp16, y = var_2421_to_fp16)[name = tensor<string, []>("op_2422_cast_fp16")]; |
| tensor<fp16, []> var_2423_to_fp16 = const()[name = tensor<string, []>("op_2423_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2424_cast_fp16 = add(x = var_2422_cast_fp16, y = var_2423_to_fp16)[name = tensor<string, []>("op_2424_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2425_to_fp16 = const()[name = tensor<string, []>("op_2425_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48276800)))]; |
| tensor<fp16, [1, 128, ?]> var_2428_cast_fp16 = mul(x = var_2424_cast_fp16, y = var_2425_to_fp16)[name = tensor<string, []>("op_2428_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_223_cast_fp16 = add(x = xt_99_cast_fp16, y = var_2428_cast_fp16)[name = tensor<string, []>("input_223_cast_fp16")]; |
| tensor<string, []> xt_101_pad_type_0 = const()[name = tensor<string, []>("xt_101_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_101_pad_0 = const()[name = tensor<string, []>("xt_101_pad_0"), val = tensor<int32, [2]>([5, 5])]; |
| tensor<int32, [1]> xt_101_strides_0 = const()[name = tensor<string, []>("xt_101_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_101_dilations_0 = const()[name = tensor<string, []>("xt_101_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_101_groups_0 = const()[name = tensor<string, []>("xt_101_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 11]> weight_191_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [180224]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48277120))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48457408))), name = tensor<string, []>("weight_191_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 11])]; |
| tensor<fp16, [128]> resblocks_5_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_5_convs2_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48457984)))]; |
| tensor<fp16, [1, 128, ?]> xt_101_cast_fp16 = conv(bias = resblocks_5_convs2_1_bias_to_fp16, dilations = xt_101_dilations_0, groups = xt_101_groups_0, pad = xt_101_pad_0, pad_type = xt_101_pad_type_0, strides = xt_101_strides_0, weight = weight_191_to_fp16_palettized, x = input_223_cast_fp16)[name = tensor<string, []>("xt_101_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_225_cast_fp16 = add(x = xt_101_cast_fp16, y = input_217_cast_fp16)[name = tensor<string, []>("input_225_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_5_adain1_2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48458304))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48491136))), name = tensor<string, []>("resblocks_5_adain1_2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_5_adain1_2_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_5_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48491712)))]; |
| tensor<fp16, [1, 256]> linear_44_cast_fp16 = linear(bias = resblocks_5_adain1_2_fc_bias_to_fp16, weight = resblocks_5_adain1_2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_44_cast_fp16")]; |
| tensor<int32, [3]> var_2445 = const()[name = tensor<string, []>("op_2445"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_179_cast_fp16 = reshape(shape = var_2445, x = linear_44_cast_fp16)[name = tensor<string, []>("h_179_cast_fp16")]; |
| tensor<int32, [2]> var_2447_split_sizes_0 = const()[name = tensor<string, []>("op_2447_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_2447_axis_0 = const()[name = tensor<string, []>("op_2447_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_2447_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_2447_cast_fp16_1 = split(axis = var_2447_axis_0, split_sizes = var_2447_split_sizes_0, x = h_179_cast_fp16)[name = tensor<string, []>("op_2447_cast_fp16")]; |
| tensor<fp16, []> var_2449_promoted_to_fp16 = const()[name = tensor<string, []>("op_2449_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_2450_cast_fp16 = add(x = var_2447_cast_fp16_0, y = var_2449_promoted_to_fp16)[name = tensor<string, []>("op_2450_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2453_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_2208_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_225_cast_fp16)[name = tensor<string, []>("op_2453_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2454_cast_fp16 = mul(x = var_2450_cast_fp16, y = var_2453_cast_fp16)[name = tensor<string, []>("op_2454_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_103_cast_fp16 = add(x = var_2454_cast_fp16, y = var_2447_cast_fp16_1)[name = tensor<string, []>("xt_103_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2457_to_fp16 = const()[name = tensor<string, []>("op_2457_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48492288)))]; |
| tensor<fp16, [1, 128, ?]> var_2458_cast_fp16 = mul(x = xt_103_cast_fp16, y = var_2457_to_fp16)[name = tensor<string, []>("op_2458_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_69_cast_fp16 = cos(x = var_2458_cast_fp16)[name = tensor<string, []>("cv_69_cast_fp16")]; |
| tensor<fp16, []> var_2460_to_fp16 = const()[name = tensor<string, []>("op_2460_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2461_cast_fp16 = mul(x = cv_69_cast_fp16, y = var_2460_to_fp16)[name = tensor<string, []>("op_2461_cast_fp16")]; |
| tensor<fp16, []> var_2462_to_fp16 = const()[name = tensor<string, []>("op_2462_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2463_cast_fp16 = add(x = var_2461_cast_fp16, y = var_2462_to_fp16)[name = tensor<string, []>("op_2463_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2464_to_fp16 = const()[name = tensor<string, []>("op_2464_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48492608)))]; |
| tensor<fp16, [1, 128, ?]> var_2467_cast_fp16 = mul(x = var_2463_cast_fp16, y = var_2464_to_fp16)[name = tensor<string, []>("op_2467_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_227_cast_fp16 = add(x = xt_103_cast_fp16, y = var_2467_cast_fp16)[name = tensor<string, []>("input_227_cast_fp16")]; |
| tensor<string, []> input_229_pad_type_0 = const()[name = tensor<string, []>("input_229_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> input_229_pad_0 = const()[name = tensor<string, []>("input_229_pad_0"), val = tensor<int32, [2]>([25, 25])]; |
| tensor<int32, [1]> input_229_dilations_0 = const()[name = tensor<string, []>("input_229_dilations_0"), val = tensor<int32, [1]>([5])]; |
| tensor<int32, [1]> input_229_strides_0 = const()[name = tensor<string, []>("input_229_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> input_229_groups_0 = const()[name = tensor<string, []>("input_229_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 11]> weight_195_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [180224]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48492928))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48673216))), name = tensor<string, []>("weight_195_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 11])]; |
| tensor<fp16, [128]> resblocks_5_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_5_convs1_2_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48673792)))]; |
| tensor<fp16, [1, 128, ?]> input_229_cast_fp16 = conv(bias = resblocks_5_convs1_2_bias_to_fp16, dilations = input_229_dilations_0, groups = input_229_groups_0, pad = input_229_pad_0, pad_type = input_229_pad_type_0, strides = input_229_strides_0, weight = weight_195_to_fp16_palettized, x = input_227_cast_fp16)[name = tensor<string, []>("input_229_cast_fp16")]; |
| tensor<fp16, [256, 128]> resblocks_5_adain2_2_fc_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [32768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48674112))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48706944))), name = tensor<string, []>("resblocks_5_adain2_2_fc_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 128])]; |
| tensor<fp16, [256]> resblocks_5_adain2_2_fc_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_5_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48707520)))]; |
| tensor<fp16, [1, 256]> linear_45_cast_fp16 = linear(bias = resblocks_5_adain2_2_fc_bias_to_fp16, weight = resblocks_5_adain2_2_fc_weight_to_fp16_palettized, x = style_timbre)[name = tensor<string, []>("linear_45_cast_fp16")]; |
| tensor<int32, [3]> var_2483 = const()[name = tensor<string, []>("op_2483"), val = tensor<int32, [3]>([1, 256, 1])]; |
| tensor<fp16, [1, 256, 1]> h_cast_fp16 = reshape(shape = var_2483, x = linear_45_cast_fp16)[name = tensor<string, []>("h_cast_fp16")]; |
| tensor<int32, [2]> var_2485_split_sizes_0 = const()[name = tensor<string, []>("op_2485_split_sizes_0"), val = tensor<int32, [2]>([128, 128])]; |
| tensor<int32, []> var_2485_axis_0 = const()[name = tensor<string, []>("op_2485_axis_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [1, 128, 1]> var_2485_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_2485_cast_fp16_1 = split(axis = var_2485_axis_0, split_sizes = var_2485_split_sizes_0, x = h_cast_fp16)[name = tensor<string, []>("op_2485_cast_fp16")]; |
| tensor<fp16, []> var_2487_promoted_to_fp16 = const()[name = tensor<string, []>("op_2487_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| tensor<fp16, [1, 128, 1]> var_2488_cast_fp16 = add(x = var_2485_cast_fp16_0, y = var_2487_promoted_to_fp16)[name = tensor<string, []>("op_2488_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2491_cast_fp16 = instance_norm(beta = resblocks_3_adain1_0_norm_bias_to_fp16, epsilon = var_2208_to_fp16, gamma = resblocks_3_adain1_0_norm_weight_to_fp16, x = input_229_cast_fp16)[name = tensor<string, []>("op_2491_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2492_cast_fp16 = mul(x = var_2488_cast_fp16, y = var_2491_cast_fp16)[name = tensor<string, []>("op_2492_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xt_105_cast_fp16 = add(x = var_2492_cast_fp16, y = var_2485_cast_fp16_1)[name = tensor<string, []>("xt_105_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2495_to_fp16 = const()[name = tensor<string, []>("op_2495_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48708096)))]; |
| tensor<fp16, [1, 128, ?]> var_2496_cast_fp16 = mul(x = xt_105_cast_fp16, y = var_2495_to_fp16)[name = tensor<string, []>("op_2496_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> cv_cast_fp16 = cos(x = var_2496_cast_fp16)[name = tensor<string, []>("cv_cast_fp16")]; |
| tensor<fp16, []> var_2498_to_fp16 = const()[name = tensor<string, []>("op_2498_to_fp16"), val = tensor<fp16, []>(-0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2499_cast_fp16 = mul(x = cv_cast_fp16, y = var_2498_to_fp16)[name = tensor<string, []>("op_2499_cast_fp16")]; |
| tensor<fp16, []> var_2500_to_fp16 = const()[name = tensor<string, []>("op_2500_to_fp16"), val = tensor<fp16, []>(0x1p-1)]; |
| tensor<fp16, [1, 128, ?]> var_2501_cast_fp16 = add(x = var_2499_cast_fp16, y = var_2500_to_fp16)[name = tensor<string, []>("op_2501_cast_fp16")]; |
| tensor<fp16, [1, 128, 1]> var_2502_to_fp16 = const()[name = tensor<string, []>("op_2502_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48708416)))]; |
| tensor<fp16, [1, 128, ?]> var_2505_cast_fp16 = mul(x = var_2501_cast_fp16, y = var_2502_to_fp16)[name = tensor<string, []>("op_2505_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> input_231_cast_fp16 = add(x = xt_105_cast_fp16, y = var_2505_cast_fp16)[name = tensor<string, []>("input_231_cast_fp16")]; |
| tensor<string, []> xt_pad_type_0 = const()[name = tensor<string, []>("xt_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [2]> xt_pad_0 = const()[name = tensor<string, []>("xt_pad_0"), val = tensor<int32, [2]>([5, 5])]; |
| tensor<int32, [1]> xt_strides_0 = const()[name = tensor<string, []>("xt_strides_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, [1]> xt_dilations_0 = const()[name = tensor<string, []>("xt_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> xt_groups_0 = const()[name = tensor<string, []>("xt_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp16, [128, 128, 11]> weight_199_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [180224]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48708736))), lut = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48889024))), name = tensor<string, []>("weight_199_to_fp16_palettized"), shape = tensor<uint32, [3]>([128, 128, 11])]; |
| tensor<fp16, [128]> resblocks_5_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("resblocks_5_convs2_2_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48889600)))]; |
| tensor<fp16, [1, 128, ?]> xt_cast_fp16 = conv(bias = resblocks_5_convs2_2_bias_to_fp16, dilations = xt_dilations_0, groups = xt_groups_0, pad = xt_pad_0, pad_type = xt_pad_type_0, strides = xt_strides_0, weight = weight_199_to_fp16_palettized, x = input_231_cast_fp16)[name = tensor<string, []>("xt_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> var_2514_cast_fp16 = add(x = xt_cast_fp16, y = input_225_cast_fp16)[name = tensor<string, []>("op_2514_cast_fp16")]; |
| tensor<fp16, [1, 128, ?]> xs_cast_fp16 = add(x = xs_9_cast_fp16, y = var_2514_cast_fp16)[name = tensor<string, []>("xs_cast_fp16")]; |
| tensor<fp16, []> _inversed_input_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_input_y_0_to_fp16"), val = tensor<fp16, []>(0x1.554p-2)]; |
| tensor<fp16, [1, 128, ?]> _inversed_input_cast_fp16 = mul(x = xs_cast_fp16, y = _inversed_input_y_0_to_fp16)[name = tensor<string, []>("_inversed_input_cast_fp16")]; |
| tensor<fp32, []> var_2519 = const()[name = tensor<string, []>("op_2519"), val = tensor<fp32, []>(0x1.47ae14p-7)]; |
| tensor<fp16, [1, 128, ?]> x_pre = leaky_relu(alpha = var_2519, x = _inversed_input_cast_fp16)[name = tensor<string, []>("x_pre_cast_fp16")]; |
| tensor<bool, []> var_2522_keep_dims_0 = const()[name = tensor<string, []>("op_2522_keep_dims_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, []> var_2522_cast_fp16 = reduce_mean(keep_dims = var_2522_keep_dims_0, x = x_pre)[name = tensor<string, []>("op_2522_cast_fp16")]; |
| tensor<int32, [1]> var_2524_axes_0 = const()[name = tensor<string, []>("op_2524_axes_0"), val = tensor<int32, [1]>([0])]; |
| tensor<fp16, [1]> anchor = expand_dims(axes = var_2524_axes_0, x = var_2522_cast_fp16)[name = tensor<string, []>("op_2524_cast_fp16")]; |
| } -> (anchor, x_pre); |
| } |
