program(1.3)
[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}, {"coremltools-component-torch", "2.11.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0"}})]
{
    func main<ios18>(tensor<fp32, [1, 1, ?]> har_source, tensor<fp32, [1, 128]> ref, tensor<fp32, [1, 512, ?]> x_pre) [FlexibleShapeInformation = tuple<tuple<string, dict<string, tensor<int32, [?]>>>, tuple<string, dict<string, list<tensor<int32, [2]>, ?>>>>((("DefaultShapes", {{"har_source", [1, 1, 88200]}, {"x_pre", [1, 512, 294]}}), ("RangeDims", {{"har_source", [[1, 1], [1, 1], [600, 1228800]]}, {"x_pre", [[1, 1], [512, 512], [2, 4096]]}})))] {
            string ref_to_fp16_dtype_0 = const()[name = string("ref_to_fp16_dtype_0"), val = string("fp16")];
            tensor<fp16, [1, 512, 1]> generator_alphas_0_to_fp16 = const()[name = string("generator_alphas_0_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            string x_pre_to_fp16_dtype_0 = const()[name = string("x_pre_to_fp16_dtype_0"), val = string("fp16")];
            tensor<fp16, [1, 512, ?]> x_pre_to_fp16 = cast(dtype = x_pre_to_fp16_dtype_0, x = x_pre)[name = string("cast_106")];
            tensor<fp16, [1, 512, ?]> var_87_cast_fp16 = mul(x = generator_alphas_0_to_fp16, y = x_pre_to_fp16)[name = string("op_87_cast_fp16")];
            tensor<fp16, [1, 512, ?]> var_88_cast_fp16 = sin(x = var_87_cast_fp16)[name = string("op_88_cast_fp16")];
            fp16 var_24_promoted_to_fp16 = const()[name = string("op_24_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 512, ?]> var_89_cast_fp16 = pow(x = var_88_cast_fp16, y = var_24_promoted_to_fp16)[name = string("op_89_cast_fp16")];
            tensor<fp16, [1, 512, 1]> var_84_to_fp16 = const()[name = string("op_84_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1152)))];
            tensor<fp16, [1, 512, ?]> var_90_cast_fp16 = mul(x = var_84_to_fp16, y = var_89_cast_fp16)[name = string("op_90_cast_fp16")];
            tensor<fp16, [1, 512, ?]> input_27_cast_fp16 = add(x = x_pre_to_fp16, y = var_90_cast_fp16)[name = string("input_27_cast_fp16")];
            string input_3_pad_type_0 = const()[name = string("input_3_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [2]>([15, 15])];
            tensor<int32, [1]> input_3_strides_0 = const()[name = string("input_3_strides_0"), val = tensor<int32, [1]>([30])];
            tensor<int32, [1]> input_3_dilations_0 = const()[name = string("input_3_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_3_groups_0 = const()[name = string("input_3_groups_0"), val = int32(1)];
            string har_source_to_fp16_dtype_0 = const()[name = string("har_source_to_fp16_dtype_0"), val = string("fp16")];
            tensor<fp16, [256, 1, 60]> generator_noise_convs_0_weight_to_fp16 = const()[name = string("generator_noise_convs_0_weight_to_fp16"), val = tensor<fp16, [256, 1, 60]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2240)))];
            tensor<fp16, [256]> generator_noise_convs_0_bias_to_fp16 = const()[name = string("generator_noise_convs_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33024)))];
            tensor<fp16, [1, 1, ?]> har_source_to_fp16 = cast(dtype = har_source_to_fp16_dtype_0, x = har_source)[name = string("cast_105")];
            tensor<fp16, [1, 256, ?]> input_3_cast_fp16 = conv(bias = generator_noise_convs_0_bias_to_fp16, dilations = input_3_dilations_0, groups = input_3_groups_0, pad = input_3_pad_0, pad_type = input_3_pad_type_0, strides = input_3_strides_0, weight = generator_noise_convs_0_weight_to_fp16, x = har_source_to_fp16)[name = string("input_3_cast_fp16")];
            tensor<fp16, [512, 128]> generator_noise_res_0_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_noise_res_0_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33600)))];
            tensor<fp16, [512]> generator_noise_res_0_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_noise_res_0_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(164736)))];
            tensor<fp16, [1, 128]> ref_to_fp16 = cast(dtype = ref_to_fp16_dtype_0, x = ref)[name = string("cast_107")];
            tensor<fp16, [1, 512]> linear_0_cast_fp16 = linear(bias = generator_noise_res_0_adain1_0_fc_bias_to_fp16, weight = generator_noise_res_0_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_0_cast_fp16")];
            tensor<int32, [3]> var_141 = const()[name = string("op_141"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_3_cast_fp16 = reshape(shape = var_141, x = linear_0_cast_fp16)[name = string("h_3_cast_fp16")];
            tensor<int32, [2]> var_143_split_sizes_0 = const()[name = string("op_143_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_143_axis_0 = const()[name = string("op_143_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_143_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_143_cast_fp16_1 = split(axis = var_143_axis_0, split_sizes = var_143_split_sizes_0, x = h_3_cast_fp16)[name = string("op_143_cast_fp16")];
            fp16 var_145_promoted_to_fp16 = const()[name = string("op_145_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_146_cast_fp16 = add(x = var_143_cast_fp16_0, y = var_145_promoted_to_fp16)[name = string("op_146_cast_fp16")];
            fp16 var_14_to_fp16 = const()[name = string("op_14_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 256, ?]> var_147_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_3_cast_fp16)[name = string("op_147_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_148_cast_fp16 = mul(x = var_146_cast_fp16, y = var_147_cast_fp16)[name = string("op_148_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_1_cast_fp16 = add(x = var_148_cast_fp16, y = var_143_cast_fp16_1)[name = string("xt_1_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_noise_res_0_alpha1_0_to_fp16 = const()[name = string("generator_noise_res_0_alpha1_0_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(165824)))];
            tensor<fp16, [1, 256, ?]> var_153_cast_fp16 = mul(x = generator_noise_res_0_alpha1_0_to_fp16, y = xt_1_cast_fp16)[name = string("op_153_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_154_cast_fp16 = sin(x = var_153_cast_fp16)[name = string("op_154_cast_fp16")];
            fp16 var_24_promoted_1_to_fp16 = const()[name = string("op_24_promoted_1_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_155_cast_fp16 = pow(x = var_154_cast_fp16, y = var_24_promoted_1_to_fp16)[name = string("op_155_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_150_to_fp16 = const()[name = string("op_150_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(166400)))];
            tensor<fp16, [1, 256, ?]> var_156_cast_fp16 = mul(x = var_150_to_fp16, y = var_155_cast_fp16)[name = string("op_156_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_5_cast_fp16 = add(x = xt_1_cast_fp16, y = var_156_cast_fp16)[name = string("input_5_cast_fp16")];
            string input_7_pad_type_0 = const()[name = string("input_7_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_7_pad_0 = const()[name = string("input_7_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> input_7_strides_0 = const()[name = string("input_7_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_7_dilations_0 = const()[name = string("input_7_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_7_groups_0 = const()[name = string("input_7_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 7]> generator_noise_res_0_convs1_0_weight_to_fp16 = const()[name = string("generator_noise_res_0_convs1_0_weight_to_fp16"), val = tensor<fp16, [256, 256, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(166976)))];
            tensor<fp16, [256]> generator_noise_res_0_convs1_0_bias_to_fp16 = const()[name = string("generator_noise_res_0_convs1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1084544)))];
            tensor<fp16, [1, 256, ?]> input_7_cast_fp16 = conv(bias = generator_noise_res_0_convs1_0_bias_to_fp16, dilations = input_7_dilations_0, groups = input_7_groups_0, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = input_7_strides_0, weight = generator_noise_res_0_convs1_0_weight_to_fp16, x = input_5_cast_fp16)[name = string("input_7_cast_fp16")];
            tensor<fp16, [512, 128]> generator_noise_res_0_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_noise_res_0_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1085120)))];
            tensor<fp16, [512]> generator_noise_res_0_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_noise_res_0_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1216256)))];
            tensor<fp16, [1, 512]> linear_1_cast_fp16 = linear(bias = generator_noise_res_0_adain2_0_fc_bias_to_fp16, weight = generator_noise_res_0_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_1_cast_fp16")];
            tensor<int32, [3]> var_171 = const()[name = string("op_171"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_7_cast_fp16 = reshape(shape = var_171, x = linear_1_cast_fp16)[name = string("h_7_cast_fp16")];
            tensor<int32, [2]> var_173_split_sizes_0 = const()[name = string("op_173_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_173_axis_0 = const()[name = string("op_173_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_173_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_173_cast_fp16_1 = split(axis = var_173_axis_0, split_sizes = var_173_split_sizes_0, x = h_7_cast_fp16)[name = string("op_173_cast_fp16")];
            fp16 var_175_promoted_to_fp16 = const()[name = string("op_175_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_176_cast_fp16 = add(x = var_173_cast_fp16_0, y = var_175_promoted_to_fp16)[name = string("op_176_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_177_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_7_cast_fp16)[name = string("op_177_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_178_cast_fp16 = mul(x = var_176_cast_fp16, y = var_177_cast_fp16)[name = string("op_178_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_3_cast_fp16 = add(x = var_178_cast_fp16, y = var_173_cast_fp16_1)[name = string("xt_3_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_noise_res_0_alpha2_0_to_fp16 = const()[name = string("generator_noise_res_0_alpha2_0_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1217344)))];
            tensor<fp16, [1, 256, ?]> var_183_cast_fp16 = mul(x = generator_noise_res_0_alpha2_0_to_fp16, y = xt_3_cast_fp16)[name = string("op_183_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_184_cast_fp16 = sin(x = var_183_cast_fp16)[name = string("op_184_cast_fp16")];
            fp16 var_24_promoted_2_to_fp16 = const()[name = string("op_24_promoted_2_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_185_cast_fp16 = pow(x = var_184_cast_fp16, y = var_24_promoted_2_to_fp16)[name = string("op_185_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_180_to_fp16 = const()[name = string("op_180_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1217920)))];
            tensor<fp16, [1, 256, ?]> var_186_cast_fp16 = mul(x = var_180_to_fp16, y = var_185_cast_fp16)[name = string("op_186_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_9_cast_fp16 = add(x = xt_3_cast_fp16, y = var_186_cast_fp16)[name = string("input_9_cast_fp16")];
            string xt_5_pad_type_0 = const()[name = string("xt_5_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_5_pad_0 = const()[name = string("xt_5_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_5_strides_0 = const()[name = string("xt_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_5_dilations_0 = const()[name = string("xt_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_5_groups_0 = const()[name = string("xt_5_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 7]> generator_noise_res_0_convs2_0_weight_to_fp16 = const()[name = string("generator_noise_res_0_convs2_0_weight_to_fp16"), val = tensor<fp16, [256, 256, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1218496)))];
            tensor<fp16, [256]> generator_noise_res_0_convs2_0_bias_to_fp16 = const()[name = string("generator_noise_res_0_convs2_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2136064)))];
            tensor<fp16, [1, 256, ?]> xt_5_cast_fp16 = conv(bias = generator_noise_res_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 = generator_noise_res_0_convs2_0_weight_to_fp16, x = input_9_cast_fp16)[name = string("xt_5_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_11_cast_fp16 = add(x = xt_5_cast_fp16, y = input_3_cast_fp16)[name = string("input_11_cast_fp16")];
            tensor<fp16, [512, 128]> generator_noise_res_0_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_noise_res_0_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2136640)))];
            tensor<fp16, [512]> generator_noise_res_0_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_noise_res_0_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2267776)))];
            tensor<fp16, [1, 512]> linear_2_cast_fp16 = linear(bias = generator_noise_res_0_adain1_1_fc_bias_to_fp16, weight = generator_noise_res_0_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_2_cast_fp16")];
            tensor<int32, [3]> var_202 = const()[name = string("op_202"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_11_cast_fp16 = reshape(shape = var_202, x = linear_2_cast_fp16)[name = string("h_11_cast_fp16")];
            tensor<int32, [2]> var_204_split_sizes_0 = const()[name = string("op_204_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_204_axis_0 = const()[name = string("op_204_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_204_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_204_cast_fp16_1 = split(axis = var_204_axis_0, split_sizes = var_204_split_sizes_0, x = h_11_cast_fp16)[name = string("op_204_cast_fp16")];
            fp16 var_206_promoted_to_fp16 = const()[name = string("op_206_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_207_cast_fp16 = add(x = var_204_cast_fp16_0, y = var_206_promoted_to_fp16)[name = string("op_207_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_208_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_11_cast_fp16)[name = string("op_208_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_209_cast_fp16 = mul(x = var_207_cast_fp16, y = var_208_cast_fp16)[name = string("op_209_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_7_cast_fp16 = add(x = var_209_cast_fp16, y = var_204_cast_fp16_1)[name = string("xt_7_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_noise_res_0_alpha1_1_to_fp16 = const()[name = string("generator_noise_res_0_alpha1_1_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2268864)))];
            tensor<fp16, [1, 256, ?]> var_214_cast_fp16 = mul(x = generator_noise_res_0_alpha1_1_to_fp16, y = xt_7_cast_fp16)[name = string("op_214_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_215_cast_fp16 = sin(x = var_214_cast_fp16)[name = string("op_215_cast_fp16")];
            fp16 var_24_promoted_3_to_fp16 = const()[name = string("op_24_promoted_3_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_216_cast_fp16 = pow(x = var_215_cast_fp16, y = var_24_promoted_3_to_fp16)[name = string("op_216_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_211_to_fp16 = const()[name = string("op_211_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2269440)))];
            tensor<fp16, [1, 256, ?]> var_217_cast_fp16 = mul(x = var_211_to_fp16, y = var_216_cast_fp16)[name = string("op_217_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_13_cast_fp16 = add(x = xt_7_cast_fp16, y = var_217_cast_fp16)[name = string("input_13_cast_fp16")];
            string input_15_pad_type_0 = const()[name = string("input_15_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_15_pad_0 = const()[name = string("input_15_pad_0"), val = tensor<int32, [2]>([9, 9])];
            tensor<int32, [1]> input_15_dilations_0 = const()[name = string("input_15_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_15_strides_0 = const()[name = string("input_15_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_15_groups_0 = const()[name = string("input_15_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 7]> generator_noise_res_0_convs1_1_weight_to_fp16 = const()[name = string("generator_noise_res_0_convs1_1_weight_to_fp16"), val = tensor<fp16, [256, 256, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2270016)))];
            tensor<fp16, [256]> generator_noise_res_0_convs1_1_bias_to_fp16 = const()[name = string("generator_noise_res_0_convs1_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3187584)))];
            tensor<fp16, [1, 256, ?]> input_15_cast_fp16 = conv(bias = generator_noise_res_0_convs1_1_bias_to_fp16, dilations = input_15_dilations_0, groups = input_15_groups_0, pad = input_15_pad_0, pad_type = input_15_pad_type_0, strides = input_15_strides_0, weight = generator_noise_res_0_convs1_1_weight_to_fp16, x = input_13_cast_fp16)[name = string("input_15_cast_fp16")];
            tensor<fp16, [512, 128]> generator_noise_res_0_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_noise_res_0_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3188160)))];
            tensor<fp16, [512]> generator_noise_res_0_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_noise_res_0_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3319296)))];
            tensor<fp16, [1, 512]> linear_3_cast_fp16 = linear(bias = generator_noise_res_0_adain2_1_fc_bias_to_fp16, weight = generator_noise_res_0_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_3_cast_fp16")];
            tensor<int32, [3]> var_232 = const()[name = string("op_232"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_15_cast_fp16 = reshape(shape = var_232, x = linear_3_cast_fp16)[name = string("h_15_cast_fp16")];
            tensor<int32, [2]> var_234_split_sizes_0 = const()[name = string("op_234_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_234_axis_0 = const()[name = string("op_234_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_234_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_234_cast_fp16_1 = split(axis = var_234_axis_0, split_sizes = var_234_split_sizes_0, x = h_15_cast_fp16)[name = string("op_234_cast_fp16")];
            fp16 var_236_promoted_to_fp16 = const()[name = string("op_236_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_237_cast_fp16 = add(x = var_234_cast_fp16_0, y = var_236_promoted_to_fp16)[name = string("op_237_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_238_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_15_cast_fp16)[name = string("op_238_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_239_cast_fp16 = mul(x = var_237_cast_fp16, y = var_238_cast_fp16)[name = string("op_239_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_9_cast_fp16 = add(x = var_239_cast_fp16, y = var_234_cast_fp16_1)[name = string("xt_9_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_noise_res_0_alpha2_1_to_fp16 = const()[name = string("generator_noise_res_0_alpha2_1_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3320384)))];
            tensor<fp16, [1, 256, ?]> var_244_cast_fp16 = mul(x = generator_noise_res_0_alpha2_1_to_fp16, y = xt_9_cast_fp16)[name = string("op_244_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_245_cast_fp16 = sin(x = var_244_cast_fp16)[name = string("op_245_cast_fp16")];
            fp16 var_24_promoted_4_to_fp16 = const()[name = string("op_24_promoted_4_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_246_cast_fp16 = pow(x = var_245_cast_fp16, y = var_24_promoted_4_to_fp16)[name = string("op_246_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_241_to_fp16 = const()[name = string("op_241_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3320960)))];
            tensor<fp16, [1, 256, ?]> var_247_cast_fp16 = mul(x = var_241_to_fp16, y = var_246_cast_fp16)[name = string("op_247_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_17_cast_fp16 = add(x = xt_9_cast_fp16, y = var_247_cast_fp16)[name = string("input_17_cast_fp16")];
            string xt_11_pad_type_0 = const()[name = string("xt_11_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_11_pad_0 = const()[name = string("xt_11_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_11_strides_0 = const()[name = string("xt_11_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_11_dilations_0 = const()[name = string("xt_11_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_11_groups_0 = const()[name = string("xt_11_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 7]> generator_noise_res_0_convs2_1_weight_to_fp16 = const()[name = string("generator_noise_res_0_convs2_1_weight_to_fp16"), val = tensor<fp16, [256, 256, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3321536)))];
            tensor<fp16, [256]> generator_noise_res_0_convs2_1_bias_to_fp16 = const()[name = string("generator_noise_res_0_convs2_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4239104)))];
            tensor<fp16, [1, 256, ?]> xt_11_cast_fp16 = conv(bias = generator_noise_res_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 = generator_noise_res_0_convs2_1_weight_to_fp16, x = input_17_cast_fp16)[name = string("xt_11_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_19_cast_fp16 = add(x = xt_11_cast_fp16, y = input_11_cast_fp16)[name = string("input_19_cast_fp16")];
            tensor<fp16, [512, 128]> generator_noise_res_0_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_noise_res_0_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4239680)))];
            tensor<fp16, [512]> generator_noise_res_0_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_noise_res_0_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4370816)))];
            tensor<fp16, [1, 512]> linear_4_cast_fp16 = linear(bias = generator_noise_res_0_adain1_2_fc_bias_to_fp16, weight = generator_noise_res_0_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_4_cast_fp16")];
            tensor<int32, [3]> var_263 = const()[name = string("op_263"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_19_cast_fp16 = reshape(shape = var_263, x = linear_4_cast_fp16)[name = string("h_19_cast_fp16")];
            tensor<int32, [2]> var_265_split_sizes_0 = const()[name = string("op_265_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_265_axis_0 = const()[name = string("op_265_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_265_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_265_cast_fp16_1 = split(axis = var_265_axis_0, split_sizes = var_265_split_sizes_0, x = h_19_cast_fp16)[name = string("op_265_cast_fp16")];
            fp16 var_267_promoted_to_fp16 = const()[name = string("op_267_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_268_cast_fp16 = add(x = var_265_cast_fp16_0, y = var_267_promoted_to_fp16)[name = string("op_268_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_269_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_19_cast_fp16)[name = string("op_269_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_270_cast_fp16 = mul(x = var_268_cast_fp16, y = var_269_cast_fp16)[name = string("op_270_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_13_cast_fp16 = add(x = var_270_cast_fp16, y = var_265_cast_fp16_1)[name = string("xt_13_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_noise_res_0_alpha1_2_to_fp16 = const()[name = string("generator_noise_res_0_alpha1_2_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4371904)))];
            tensor<fp16, [1, 256, ?]> var_275_cast_fp16 = mul(x = generator_noise_res_0_alpha1_2_to_fp16, y = xt_13_cast_fp16)[name = string("op_275_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_276_cast_fp16 = sin(x = var_275_cast_fp16)[name = string("op_276_cast_fp16")];
            fp16 var_24_promoted_5_to_fp16 = const()[name = string("op_24_promoted_5_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_277_cast_fp16 = pow(x = var_276_cast_fp16, y = var_24_promoted_5_to_fp16)[name = string("op_277_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_272_to_fp16 = const()[name = string("op_272_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4372480)))];
            tensor<fp16, [1, 256, ?]> var_278_cast_fp16 = mul(x = var_272_to_fp16, y = var_277_cast_fp16)[name = string("op_278_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_21_cast_fp16 = add(x = xt_13_cast_fp16, y = var_278_cast_fp16)[name = string("input_21_cast_fp16")];
            string input_23_pad_type_0 = const()[name = string("input_23_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_23_pad_0 = const()[name = string("input_23_pad_0"), val = tensor<int32, [2]>([15, 15])];
            tensor<int32, [1]> input_23_dilations_0 = const()[name = string("input_23_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_23_strides_0 = const()[name = string("input_23_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_23_groups_0 = const()[name = string("input_23_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 7]> generator_noise_res_0_convs1_2_weight_to_fp16 = const()[name = string("generator_noise_res_0_convs1_2_weight_to_fp16"), val = tensor<fp16, [256, 256, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4373056)))];
            tensor<fp16, [256]> generator_noise_res_0_convs1_2_bias_to_fp16 = const()[name = string("generator_noise_res_0_convs1_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5290624)))];
            tensor<fp16, [1, 256, ?]> input_23_cast_fp16 = conv(bias = generator_noise_res_0_convs1_2_bias_to_fp16, dilations = input_23_dilations_0, groups = input_23_groups_0, pad = input_23_pad_0, pad_type = input_23_pad_type_0, strides = input_23_strides_0, weight = generator_noise_res_0_convs1_2_weight_to_fp16, x = input_21_cast_fp16)[name = string("input_23_cast_fp16")];
            tensor<fp16, [512, 128]> generator_noise_res_0_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_noise_res_0_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5291200)))];
            tensor<fp16, [512]> generator_noise_res_0_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_noise_res_0_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5422336)))];
            tensor<fp16, [1, 512]> linear_5_cast_fp16 = linear(bias = generator_noise_res_0_adain2_2_fc_bias_to_fp16, weight = generator_noise_res_0_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_5_cast_fp16")];
            tensor<int32, [3]> var_293 = const()[name = string("op_293"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_23_cast_fp16 = reshape(shape = var_293, x = linear_5_cast_fp16)[name = string("h_23_cast_fp16")];
            tensor<int32, [2]> var_295_split_sizes_0 = const()[name = string("op_295_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_295_axis_0 = const()[name = string("op_295_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_295_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_295_cast_fp16_1 = split(axis = var_295_axis_0, split_sizes = var_295_split_sizes_0, x = h_23_cast_fp16)[name = string("op_295_cast_fp16")];
            fp16 var_297_promoted_to_fp16 = const()[name = string("op_297_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_298_cast_fp16 = add(x = var_295_cast_fp16_0, y = var_297_promoted_to_fp16)[name = string("op_298_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_299_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_23_cast_fp16)[name = string("op_299_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_300_cast_fp16 = mul(x = var_298_cast_fp16, y = var_299_cast_fp16)[name = string("op_300_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_15_cast_fp16 = add(x = var_300_cast_fp16, y = var_295_cast_fp16_1)[name = string("xt_15_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_noise_res_0_alpha2_2_to_fp16 = const()[name = string("generator_noise_res_0_alpha2_2_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5423424)))];
            tensor<fp16, [1, 256, ?]> var_305_cast_fp16 = mul(x = generator_noise_res_0_alpha2_2_to_fp16, y = xt_15_cast_fp16)[name = string("op_305_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_306_cast_fp16 = sin(x = var_305_cast_fp16)[name = string("op_306_cast_fp16")];
            fp16 var_24_promoted_6_to_fp16 = const()[name = string("op_24_promoted_6_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_307_cast_fp16 = pow(x = var_306_cast_fp16, y = var_24_promoted_6_to_fp16)[name = string("op_307_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_302_to_fp16 = const()[name = string("op_302_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5424000)))];
            tensor<fp16, [1, 256, ?]> var_308_cast_fp16 = mul(x = var_302_to_fp16, y = var_307_cast_fp16)[name = string("op_308_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_25_cast_fp16 = add(x = xt_15_cast_fp16, y = var_308_cast_fp16)[name = string("input_25_cast_fp16")];
            string xt_17_pad_type_0 = const()[name = string("xt_17_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_17_pad_0 = const()[name = string("xt_17_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_17_strides_0 = const()[name = string("xt_17_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_17_dilations_0 = const()[name = string("xt_17_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_17_groups_0 = const()[name = string("xt_17_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 7]> generator_noise_res_0_convs2_2_weight_to_fp16 = const()[name = string("generator_noise_res_0_convs2_2_weight_to_fp16"), val = tensor<fp16, [256, 256, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5424576)))];
            tensor<fp16, [256]> generator_noise_res_0_convs2_2_bias_to_fp16 = const()[name = string("generator_noise_res_0_convs2_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6342144)))];
            tensor<fp16, [1, 256, ?]> xt_17_cast_fp16 = conv(bias = generator_noise_res_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 = generator_noise_res_0_convs2_2_weight_to_fp16, x = input_25_cast_fp16)[name = string("xt_17_cast_fp16")];
            tensor<fp16, [1, 256, ?]> x_source_1_cast_fp16 = add(x = xt_17_cast_fp16, y = input_19_cast_fp16)[name = string("x_source_1_cast_fp16")];
            string x_1_pad_type_0 = const()[name = string("x_1_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> x_1_pad_0 = const()[name = string("x_1_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> x_1_strides_0 = const()[name = string("x_1_strides_0"), val = tensor<int32, [1]>([10])];
            tensor<int32, [1]> x_1_dilations_0 = const()[name = string("x_1_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_1_groups_0 = const()[name = string("x_1_groups_0"), val = int32(1)];
            tensor<fp16, [512, 256, 20]> generator_ups_0_weight_to_fp16 = const()[name = string("generator_ups_0_weight_to_fp16"), val = tensor<fp16, [512, 256, 20]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6342720)))];
            tensor<fp16, [256]> generator_ups_0_bias_to_fp16 = const()[name = string("generator_ups_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11585664)))];
            tensor<fp16, [1, 256, ?]> x_1_cast_fp16 = conv_transpose(bias = generator_ups_0_bias_to_fp16, dilations = x_1_dilations_0, groups = x_1_groups_0, pad = x_1_pad_0, pad_type = x_1_pad_type_0, strides = x_1_strides_0, weight = generator_ups_0_weight_to_fp16, x = input_27_cast_fp16)[name = string("x_1_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_29_cast_fp16 = add(x = x_1_cast_fp16, y = x_source_1_cast_fp16)[name = string("input_29_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_0_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_0_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11586240)))];
            tensor<fp16, [512]> generator_resblocks_0_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_0_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11717376)))];
            tensor<fp16, [1, 512]> linear_6_cast_fp16 = linear(bias = generator_resblocks_0_adain1_0_fc_bias_to_fp16, weight = generator_resblocks_0_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_6_cast_fp16")];
            tensor<int32, [3]> var_368 = const()[name = string("op_368"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_27_cast_fp16 = reshape(shape = var_368, x = linear_6_cast_fp16)[name = string("h_27_cast_fp16")];
            tensor<int32, [2]> var_370_split_sizes_0 = const()[name = string("op_370_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_370_axis_0 = const()[name = string("op_370_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_370_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_370_cast_fp16_1 = split(axis = var_370_axis_0, split_sizes = var_370_split_sizes_0, x = h_27_cast_fp16)[name = string("op_370_cast_fp16")];
            fp16 var_372_promoted_to_fp16 = const()[name = string("op_372_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_373_cast_fp16 = add(x = var_370_cast_fp16_0, y = var_372_promoted_to_fp16)[name = string("op_373_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_374_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_29_cast_fp16)[name = string("op_374_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_375_cast_fp16 = mul(x = var_373_cast_fp16, y = var_374_cast_fp16)[name = string("op_375_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_19_cast_fp16 = add(x = var_375_cast_fp16, y = var_370_cast_fp16_1)[name = string("xt_19_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_0_alpha1_0_to_fp16 = const()[name = string("generator_resblocks_0_alpha1_0_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11718464)))];
            tensor<fp16, [1, 256, ?]> var_380_cast_fp16 = mul(x = generator_resblocks_0_alpha1_0_to_fp16, y = xt_19_cast_fp16)[name = string("op_380_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_381_cast_fp16 = sin(x = var_380_cast_fp16)[name = string("op_381_cast_fp16")];
            fp16 var_24_promoted_7_to_fp16 = const()[name = string("op_24_promoted_7_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_382_cast_fp16 = pow(x = var_381_cast_fp16, y = var_24_promoted_7_to_fp16)[name = string("op_382_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_377_to_fp16 = const()[name = string("op_377_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11719040)))];
            tensor<fp16, [1, 256, ?]> var_383_cast_fp16 = mul(x = var_377_to_fp16, y = var_382_cast_fp16)[name = string("op_383_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_31_cast_fp16 = add(x = xt_19_cast_fp16, y = var_383_cast_fp16)[name = string("input_31_cast_fp16")];
            string input_33_pad_type_0 = const()[name = string("input_33_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_33_pad_0 = const()[name = string("input_33_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> input_33_strides_0 = const()[name = string("input_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_33_dilations_0 = const()[name = string("input_33_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_33_groups_0 = const()[name = string("input_33_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 3]> generator_resblocks_0_convs1_0_weight_to_fp16 = const()[name = string("generator_resblocks_0_convs1_0_weight_to_fp16"), val = tensor<fp16, [256, 256, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11719616)))];
            tensor<fp16, [256]> generator_resblocks_0_convs1_0_bias_to_fp16 = const()[name = string("generator_resblocks_0_convs1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12112896)))];
            tensor<fp16, [1, 256, ?]> input_33_cast_fp16 = conv(bias = generator_resblocks_0_convs1_0_bias_to_fp16, dilations = input_33_dilations_0, groups = input_33_groups_0, pad = input_33_pad_0, pad_type = input_33_pad_type_0, strides = input_33_strides_0, weight = generator_resblocks_0_convs1_0_weight_to_fp16, x = input_31_cast_fp16)[name = string("input_33_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_0_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_0_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12113472)))];
            tensor<fp16, [512]> generator_resblocks_0_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_0_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12244608)))];
            tensor<fp16, [1, 512]> linear_7_cast_fp16 = linear(bias = generator_resblocks_0_adain2_0_fc_bias_to_fp16, weight = generator_resblocks_0_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_7_cast_fp16")];
            tensor<int32, [3]> var_398 = const()[name = string("op_398"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_31_cast_fp16 = reshape(shape = var_398, x = linear_7_cast_fp16)[name = string("h_31_cast_fp16")];
            tensor<int32, [2]> var_400_split_sizes_0 = const()[name = string("op_400_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_400_axis_0 = const()[name = string("op_400_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_400_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_400_cast_fp16_1 = split(axis = var_400_axis_0, split_sizes = var_400_split_sizes_0, x = h_31_cast_fp16)[name = string("op_400_cast_fp16")];
            fp16 var_402_promoted_to_fp16 = const()[name = string("op_402_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_403_cast_fp16 = add(x = var_400_cast_fp16_0, y = var_402_promoted_to_fp16)[name = string("op_403_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_404_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_33_cast_fp16)[name = string("op_404_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_405_cast_fp16 = mul(x = var_403_cast_fp16, y = var_404_cast_fp16)[name = string("op_405_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_21_cast_fp16 = add(x = var_405_cast_fp16, y = var_400_cast_fp16_1)[name = string("xt_21_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_0_alpha2_0_to_fp16 = const()[name = string("generator_resblocks_0_alpha2_0_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12245696)))];
            tensor<fp16, [1, 256, ?]> var_410_cast_fp16 = mul(x = generator_resblocks_0_alpha2_0_to_fp16, y = xt_21_cast_fp16)[name = string("op_410_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_411_cast_fp16 = sin(x = var_410_cast_fp16)[name = string("op_411_cast_fp16")];
            fp16 var_24_promoted_8_to_fp16 = const()[name = string("op_24_promoted_8_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_412_cast_fp16 = pow(x = var_411_cast_fp16, y = var_24_promoted_8_to_fp16)[name = string("op_412_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_407_to_fp16 = const()[name = string("op_407_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12246272)))];
            tensor<fp16, [1, 256, ?]> var_413_cast_fp16 = mul(x = var_407_to_fp16, y = var_412_cast_fp16)[name = string("op_413_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_35_cast_fp16 = add(x = xt_21_cast_fp16, y = var_413_cast_fp16)[name = string("input_35_cast_fp16")];
            string xt_23_pad_type_0 = const()[name = string("xt_23_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_23_pad_0 = const()[name = string("xt_23_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> xt_23_strides_0 = const()[name = string("xt_23_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_23_dilations_0 = const()[name = string("xt_23_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_23_groups_0 = const()[name = string("xt_23_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 3]> generator_resblocks_0_convs2_0_weight_to_fp16 = const()[name = string("generator_resblocks_0_convs2_0_weight_to_fp16"), val = tensor<fp16, [256, 256, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12246848)))];
            tensor<fp16, [256]> generator_resblocks_0_convs2_0_bias_to_fp16 = const()[name = string("generator_resblocks_0_convs2_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12640128)))];
            tensor<fp16, [1, 256, ?]> xt_23_cast_fp16 = conv(bias = generator_resblocks_0_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 = generator_resblocks_0_convs2_0_weight_to_fp16, x = input_35_cast_fp16)[name = string("xt_23_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_37_cast_fp16 = add(x = xt_23_cast_fp16, y = input_29_cast_fp16)[name = string("input_37_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_0_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_0_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12640704)))];
            tensor<fp16, [512]> generator_resblocks_0_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_0_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12771840)))];
            tensor<fp16, [1, 512]> linear_8_cast_fp16 = linear(bias = generator_resblocks_0_adain1_1_fc_bias_to_fp16, weight = generator_resblocks_0_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_8_cast_fp16")];
            tensor<int32, [3]> var_429 = const()[name = string("op_429"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_35_cast_fp16 = reshape(shape = var_429, x = linear_8_cast_fp16)[name = string("h_35_cast_fp16")];
            tensor<int32, [2]> var_431_split_sizes_0 = const()[name = string("op_431_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_431_axis_0 = const()[name = string("op_431_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_431_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_431_cast_fp16_1 = split(axis = var_431_axis_0, split_sizes = var_431_split_sizes_0, x = h_35_cast_fp16)[name = string("op_431_cast_fp16")];
            fp16 var_433_promoted_to_fp16 = const()[name = string("op_433_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_434_cast_fp16 = add(x = var_431_cast_fp16_0, y = var_433_promoted_to_fp16)[name = string("op_434_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_435_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_37_cast_fp16)[name = string("op_435_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_436_cast_fp16 = mul(x = var_434_cast_fp16, y = var_435_cast_fp16)[name = string("op_436_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_25_cast_fp16 = add(x = var_436_cast_fp16, y = var_431_cast_fp16_1)[name = string("xt_25_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_0_alpha1_1_to_fp16 = const()[name = string("generator_resblocks_0_alpha1_1_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12772928)))];
            tensor<fp16, [1, 256, ?]> var_441_cast_fp16 = mul(x = generator_resblocks_0_alpha1_1_to_fp16, y = xt_25_cast_fp16)[name = string("op_441_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_442_cast_fp16 = sin(x = var_441_cast_fp16)[name = string("op_442_cast_fp16")];
            fp16 var_24_promoted_9_to_fp16 = const()[name = string("op_24_promoted_9_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_443_cast_fp16 = pow(x = var_442_cast_fp16, y = var_24_promoted_9_to_fp16)[name = string("op_443_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_438_to_fp16 = const()[name = string("op_438_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12773504)))];
            tensor<fp16, [1, 256, ?]> var_444_cast_fp16 = mul(x = var_438_to_fp16, y = var_443_cast_fp16)[name = string("op_444_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_39_cast_fp16 = add(x = xt_25_cast_fp16, y = var_444_cast_fp16)[name = string("input_39_cast_fp16")];
            string input_41_pad_type_0 = const()[name = string("input_41_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_41_pad_0 = const()[name = string("input_41_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> input_41_dilations_0 = const()[name = string("input_41_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_41_strides_0 = const()[name = string("input_41_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_41_groups_0 = const()[name = string("input_41_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 3]> generator_resblocks_0_convs1_1_weight_to_fp16 = const()[name = string("generator_resblocks_0_convs1_1_weight_to_fp16"), val = tensor<fp16, [256, 256, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12774080)))];
            tensor<fp16, [256]> generator_resblocks_0_convs1_1_bias_to_fp16 = const()[name = string("generator_resblocks_0_convs1_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13167360)))];
            tensor<fp16, [1, 256, ?]> input_41_cast_fp16 = conv(bias = generator_resblocks_0_convs1_1_bias_to_fp16, dilations = input_41_dilations_0, groups = input_41_groups_0, pad = input_41_pad_0, pad_type = input_41_pad_type_0, strides = input_41_strides_0, weight = generator_resblocks_0_convs1_1_weight_to_fp16, x = input_39_cast_fp16)[name = string("input_41_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_0_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_0_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13167936)))];
            tensor<fp16, [512]> generator_resblocks_0_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_0_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13299072)))];
            tensor<fp16, [1, 512]> linear_9_cast_fp16 = linear(bias = generator_resblocks_0_adain2_1_fc_bias_to_fp16, weight = generator_resblocks_0_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_9_cast_fp16")];
            tensor<int32, [3]> var_459 = const()[name = string("op_459"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_39_cast_fp16 = reshape(shape = var_459, x = linear_9_cast_fp16)[name = string("h_39_cast_fp16")];
            tensor<int32, [2]> var_461_split_sizes_0 = const()[name = string("op_461_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_461_axis_0 = const()[name = string("op_461_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_461_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_461_cast_fp16_1 = split(axis = var_461_axis_0, split_sizes = var_461_split_sizes_0, x = h_39_cast_fp16)[name = string("op_461_cast_fp16")];
            fp16 var_463_promoted_to_fp16 = const()[name = string("op_463_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_464_cast_fp16 = add(x = var_461_cast_fp16_0, y = var_463_promoted_to_fp16)[name = string("op_464_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_465_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_41_cast_fp16)[name = string("op_465_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_466_cast_fp16 = mul(x = var_464_cast_fp16, y = var_465_cast_fp16)[name = string("op_466_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_27_cast_fp16 = add(x = var_466_cast_fp16, y = var_461_cast_fp16_1)[name = string("xt_27_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_0_alpha2_1_to_fp16 = const()[name = string("generator_resblocks_0_alpha2_1_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13300160)))];
            tensor<fp16, [1, 256, ?]> var_471_cast_fp16 = mul(x = generator_resblocks_0_alpha2_1_to_fp16, y = xt_27_cast_fp16)[name = string("op_471_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_472_cast_fp16 = sin(x = var_471_cast_fp16)[name = string("op_472_cast_fp16")];
            fp16 var_24_promoted_10_to_fp16 = const()[name = string("op_24_promoted_10_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_473_cast_fp16 = pow(x = var_472_cast_fp16, y = var_24_promoted_10_to_fp16)[name = string("op_473_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_468_to_fp16 = const()[name = string("op_468_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13300736)))];
            tensor<fp16, [1, 256, ?]> var_474_cast_fp16 = mul(x = var_468_to_fp16, y = var_473_cast_fp16)[name = string("op_474_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_43_cast_fp16 = add(x = xt_27_cast_fp16, y = var_474_cast_fp16)[name = string("input_43_cast_fp16")];
            string xt_29_pad_type_0 = const()[name = string("xt_29_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_29_pad_0 = const()[name = string("xt_29_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> xt_29_strides_0 = const()[name = string("xt_29_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_29_dilations_0 = const()[name = string("xt_29_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_29_groups_0 = const()[name = string("xt_29_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 3]> generator_resblocks_0_convs2_1_weight_to_fp16 = const()[name = string("generator_resblocks_0_convs2_1_weight_to_fp16"), val = tensor<fp16, [256, 256, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13301312)))];
            tensor<fp16, [256]> generator_resblocks_0_convs2_1_bias_to_fp16 = const()[name = string("generator_resblocks_0_convs2_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13694592)))];
            tensor<fp16, [1, 256, ?]> xt_29_cast_fp16 = conv(bias = generator_resblocks_0_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 = generator_resblocks_0_convs2_1_weight_to_fp16, x = input_43_cast_fp16)[name = string("xt_29_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_45_cast_fp16 = add(x = xt_29_cast_fp16, y = input_37_cast_fp16)[name = string("input_45_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_0_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_0_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13695168)))];
            tensor<fp16, [512]> generator_resblocks_0_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_0_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13826304)))];
            tensor<fp16, [1, 512]> linear_10_cast_fp16 = linear(bias = generator_resblocks_0_adain1_2_fc_bias_to_fp16, weight = generator_resblocks_0_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_10_cast_fp16")];
            tensor<int32, [3]> var_490 = const()[name = string("op_490"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_43_cast_fp16 = reshape(shape = var_490, x = linear_10_cast_fp16)[name = string("h_43_cast_fp16")];
            tensor<int32, [2]> var_492_split_sizes_0 = const()[name = string("op_492_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_492_axis_0 = const()[name = string("op_492_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_492_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_492_cast_fp16_1 = split(axis = var_492_axis_0, split_sizes = var_492_split_sizes_0, x = h_43_cast_fp16)[name = string("op_492_cast_fp16")];
            fp16 var_494_promoted_to_fp16 = const()[name = string("op_494_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_495_cast_fp16 = add(x = var_492_cast_fp16_0, y = var_494_promoted_to_fp16)[name = string("op_495_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_496_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_45_cast_fp16)[name = string("op_496_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_497_cast_fp16 = mul(x = var_495_cast_fp16, y = var_496_cast_fp16)[name = string("op_497_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_31_cast_fp16 = add(x = var_497_cast_fp16, y = var_492_cast_fp16_1)[name = string("xt_31_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_0_alpha1_2_to_fp16 = const()[name = string("generator_resblocks_0_alpha1_2_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13827392)))];
            tensor<fp16, [1, 256, ?]> var_502_cast_fp16 = mul(x = generator_resblocks_0_alpha1_2_to_fp16, y = xt_31_cast_fp16)[name = string("op_502_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_503_cast_fp16 = sin(x = var_502_cast_fp16)[name = string("op_503_cast_fp16")];
            fp16 var_24_promoted_11_to_fp16 = const()[name = string("op_24_promoted_11_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_504_cast_fp16 = pow(x = var_503_cast_fp16, y = var_24_promoted_11_to_fp16)[name = string("op_504_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_499_to_fp16 = const()[name = string("op_499_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13827968)))];
            tensor<fp16, [1, 256, ?]> var_505_cast_fp16 = mul(x = var_499_to_fp16, y = var_504_cast_fp16)[name = string("op_505_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_47_cast_fp16 = add(x = xt_31_cast_fp16, y = var_505_cast_fp16)[name = string("input_47_cast_fp16")];
            string input_49_pad_type_0 = const()[name = string("input_49_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_49_pad_0 = const()[name = string("input_49_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> input_49_dilations_0 = const()[name = string("input_49_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_49_strides_0 = const()[name = string("input_49_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_49_groups_0 = const()[name = string("input_49_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 3]> generator_resblocks_0_convs1_2_weight_to_fp16 = const()[name = string("generator_resblocks_0_convs1_2_weight_to_fp16"), val = tensor<fp16, [256, 256, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13828544)))];
            tensor<fp16, [256]> generator_resblocks_0_convs1_2_bias_to_fp16 = const()[name = string("generator_resblocks_0_convs1_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14221824)))];
            tensor<fp16, [1, 256, ?]> input_49_cast_fp16 = conv(bias = generator_resblocks_0_convs1_2_bias_to_fp16, dilations = input_49_dilations_0, groups = input_49_groups_0, pad = input_49_pad_0, pad_type = input_49_pad_type_0, strides = input_49_strides_0, weight = generator_resblocks_0_convs1_2_weight_to_fp16, x = input_47_cast_fp16)[name = string("input_49_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_0_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_0_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14222400)))];
            tensor<fp16, [512]> generator_resblocks_0_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_0_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14353536)))];
            tensor<fp16, [1, 512]> linear_11_cast_fp16 = linear(bias = generator_resblocks_0_adain2_2_fc_bias_to_fp16, weight = generator_resblocks_0_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_11_cast_fp16")];
            tensor<int32, [3]> var_520 = const()[name = string("op_520"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_47_cast_fp16 = reshape(shape = var_520, x = linear_11_cast_fp16)[name = string("h_47_cast_fp16")];
            tensor<int32, [2]> var_522_split_sizes_0 = const()[name = string("op_522_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_522_axis_0 = const()[name = string("op_522_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_522_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_522_cast_fp16_1 = split(axis = var_522_axis_0, split_sizes = var_522_split_sizes_0, x = h_47_cast_fp16)[name = string("op_522_cast_fp16")];
            fp16 var_524_promoted_to_fp16 = const()[name = string("op_524_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_525_cast_fp16 = add(x = var_522_cast_fp16_0, y = var_524_promoted_to_fp16)[name = string("op_525_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_526_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_49_cast_fp16)[name = string("op_526_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_527_cast_fp16 = mul(x = var_525_cast_fp16, y = var_526_cast_fp16)[name = string("op_527_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_33_cast_fp16 = add(x = var_527_cast_fp16, y = var_522_cast_fp16_1)[name = string("xt_33_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_0_alpha2_2_to_fp16 = const()[name = string("generator_resblocks_0_alpha2_2_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14354624)))];
            tensor<fp16, [1, 256, ?]> var_532_cast_fp16 = mul(x = generator_resblocks_0_alpha2_2_to_fp16, y = xt_33_cast_fp16)[name = string("op_532_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_533_cast_fp16 = sin(x = var_532_cast_fp16)[name = string("op_533_cast_fp16")];
            fp16 var_24_promoted_12_to_fp16 = const()[name = string("op_24_promoted_12_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_534_cast_fp16 = pow(x = var_533_cast_fp16, y = var_24_promoted_12_to_fp16)[name = string("op_534_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_529_to_fp16 = const()[name = string("op_529_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14355200)))];
            tensor<fp16, [1, 256, ?]> var_535_cast_fp16 = mul(x = var_529_to_fp16, y = var_534_cast_fp16)[name = string("op_535_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_51_cast_fp16 = add(x = xt_33_cast_fp16, y = var_535_cast_fp16)[name = string("input_51_cast_fp16")];
            string xt_35_pad_type_0 = const()[name = string("xt_35_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_35_pad_0 = const()[name = string("xt_35_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> xt_35_strides_0 = const()[name = string("xt_35_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_35_dilations_0 = const()[name = string("xt_35_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_35_groups_0 = const()[name = string("xt_35_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 3]> generator_resblocks_0_convs2_2_weight_to_fp16 = const()[name = string("generator_resblocks_0_convs2_2_weight_to_fp16"), val = tensor<fp16, [256, 256, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14355776)))];
            tensor<fp16, [256]> generator_resblocks_0_convs2_2_bias_to_fp16 = const()[name = string("generator_resblocks_0_convs2_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14749056)))];
            tensor<fp16, [1, 256, ?]> xt_35_cast_fp16 = conv(bias = generator_resblocks_0_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 = generator_resblocks_0_convs2_2_weight_to_fp16, x = input_51_cast_fp16)[name = string("xt_35_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xs_1_cast_fp16 = add(x = xt_35_cast_fp16, y = input_45_cast_fp16)[name = string("xs_1_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_1_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_1_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14749632)))];
            tensor<fp16, [512]> generator_resblocks_1_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_1_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14880768)))];
            tensor<fp16, [1, 512]> linear_12_cast_fp16 = linear(bias = generator_resblocks_1_adain1_0_fc_bias_to_fp16, weight = generator_resblocks_1_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_12_cast_fp16")];
            tensor<int32, [3]> var_587 = const()[name = string("op_587"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_51_cast_fp16 = reshape(shape = var_587, x = linear_12_cast_fp16)[name = string("h_51_cast_fp16")];
            tensor<int32, [2]> var_589_split_sizes_0 = const()[name = string("op_589_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_589_axis_0 = const()[name = string("op_589_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_589_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_589_cast_fp16_1 = split(axis = var_589_axis_0, split_sizes = var_589_split_sizes_0, x = h_51_cast_fp16)[name = string("op_589_cast_fp16")];
            fp16 var_591_promoted_to_fp16 = const()[name = string("op_591_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_592_cast_fp16 = add(x = var_589_cast_fp16_0, y = var_591_promoted_to_fp16)[name = string("op_592_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_594_cast_fp16 = mul(x = var_592_cast_fp16, y = var_374_cast_fp16)[name = string("op_594_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_37_cast_fp16 = add(x = var_594_cast_fp16, y = var_589_cast_fp16_1)[name = string("xt_37_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_1_alpha1_0_to_fp16 = const()[name = string("generator_resblocks_1_alpha1_0_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14881856)))];
            tensor<fp16, [1, 256, ?]> var_599_cast_fp16 = mul(x = generator_resblocks_1_alpha1_0_to_fp16, y = xt_37_cast_fp16)[name = string("op_599_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_600_cast_fp16 = sin(x = var_599_cast_fp16)[name = string("op_600_cast_fp16")];
            fp16 var_24_promoted_13_to_fp16 = const()[name = string("op_24_promoted_13_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_601_cast_fp16 = pow(x = var_600_cast_fp16, y = var_24_promoted_13_to_fp16)[name = string("op_601_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_596_to_fp16 = const()[name = string("op_596_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14882432)))];
            tensor<fp16, [1, 256, ?]> var_602_cast_fp16 = mul(x = var_596_to_fp16, y = var_601_cast_fp16)[name = string("op_602_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_53_cast_fp16 = add(x = xt_37_cast_fp16, y = var_602_cast_fp16)[name = string("input_53_cast_fp16")];
            string input_55_pad_type_0 = const()[name = string("input_55_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_55_pad_0 = const()[name = string("input_55_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> input_55_strides_0 = const()[name = string("input_55_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_55_dilations_0 = const()[name = string("input_55_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_55_groups_0 = const()[name = string("input_55_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 7]> generator_resblocks_1_convs1_0_weight_to_fp16 = const()[name = string("generator_resblocks_1_convs1_0_weight_to_fp16"), val = tensor<fp16, [256, 256, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14883008)))];
            tensor<fp16, [256]> generator_resblocks_1_convs1_0_bias_to_fp16 = const()[name = string("generator_resblocks_1_convs1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15800576)))];
            tensor<fp16, [1, 256, ?]> input_55_cast_fp16 = conv(bias = generator_resblocks_1_convs1_0_bias_to_fp16, dilations = input_55_dilations_0, groups = input_55_groups_0, pad = input_55_pad_0, pad_type = input_55_pad_type_0, strides = input_55_strides_0, weight = generator_resblocks_1_convs1_0_weight_to_fp16, x = input_53_cast_fp16)[name = string("input_55_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_1_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_1_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15801152)))];
            tensor<fp16, [512]> generator_resblocks_1_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_1_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15932288)))];
            tensor<fp16, [1, 512]> linear_13_cast_fp16 = linear(bias = generator_resblocks_1_adain2_0_fc_bias_to_fp16, weight = generator_resblocks_1_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_13_cast_fp16")];
            tensor<int32, [3]> var_617 = const()[name = string("op_617"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_55_cast_fp16 = reshape(shape = var_617, x = linear_13_cast_fp16)[name = string("h_55_cast_fp16")];
            tensor<int32, [2]> var_619_split_sizes_0 = const()[name = string("op_619_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_619_axis_0 = const()[name = string("op_619_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_619_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_619_cast_fp16_1 = split(axis = var_619_axis_0, split_sizes = var_619_split_sizes_0, x = h_55_cast_fp16)[name = string("op_619_cast_fp16")];
            fp16 var_621_promoted_to_fp16 = const()[name = string("op_621_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_622_cast_fp16 = add(x = var_619_cast_fp16_0, y = var_621_promoted_to_fp16)[name = string("op_622_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_623_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_55_cast_fp16)[name = string("op_623_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_624_cast_fp16 = mul(x = var_622_cast_fp16, y = var_623_cast_fp16)[name = string("op_624_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_39_cast_fp16 = add(x = var_624_cast_fp16, y = var_619_cast_fp16_1)[name = string("xt_39_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_1_alpha2_0_to_fp16 = const()[name = string("generator_resblocks_1_alpha2_0_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15933376)))];
            tensor<fp16, [1, 256, ?]> var_629_cast_fp16 = mul(x = generator_resblocks_1_alpha2_0_to_fp16, y = xt_39_cast_fp16)[name = string("op_629_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_630_cast_fp16 = sin(x = var_629_cast_fp16)[name = string("op_630_cast_fp16")];
            fp16 var_24_promoted_14_to_fp16 = const()[name = string("op_24_promoted_14_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_631_cast_fp16 = pow(x = var_630_cast_fp16, y = var_24_promoted_14_to_fp16)[name = string("op_631_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_626_to_fp16 = const()[name = string("op_626_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15933952)))];
            tensor<fp16, [1, 256, ?]> var_632_cast_fp16 = mul(x = var_626_to_fp16, y = var_631_cast_fp16)[name = string("op_632_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_57_cast_fp16 = add(x = xt_39_cast_fp16, y = var_632_cast_fp16)[name = string("input_57_cast_fp16")];
            string xt_41_pad_type_0 = const()[name = string("xt_41_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_41_pad_0 = const()[name = string("xt_41_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_41_strides_0 = const()[name = string("xt_41_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_41_dilations_0 = const()[name = string("xt_41_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_41_groups_0 = const()[name = string("xt_41_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 7]> generator_resblocks_1_convs2_0_weight_to_fp16 = const()[name = string("generator_resblocks_1_convs2_0_weight_to_fp16"), val = tensor<fp16, [256, 256, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15934528)))];
            tensor<fp16, [256]> generator_resblocks_1_convs2_0_bias_to_fp16 = const()[name = string("generator_resblocks_1_convs2_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16852096)))];
            tensor<fp16, [1, 256, ?]> xt_41_cast_fp16 = conv(bias = generator_resblocks_1_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 = generator_resblocks_1_convs2_0_weight_to_fp16, x = input_57_cast_fp16)[name = string("xt_41_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_59_cast_fp16 = add(x = xt_41_cast_fp16, y = input_29_cast_fp16)[name = string("input_59_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_1_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_1_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16852672)))];
            tensor<fp16, [512]> generator_resblocks_1_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_1_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16983808)))];
            tensor<fp16, [1, 512]> linear_14_cast_fp16 = linear(bias = generator_resblocks_1_adain1_1_fc_bias_to_fp16, weight = generator_resblocks_1_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_14_cast_fp16")];
            tensor<int32, [3]> var_648 = const()[name = string("op_648"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_59_cast_fp16 = reshape(shape = var_648, x = linear_14_cast_fp16)[name = string("h_59_cast_fp16")];
            tensor<int32, [2]> var_650_split_sizes_0 = const()[name = string("op_650_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_650_axis_0 = const()[name = string("op_650_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_650_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_650_cast_fp16_1 = split(axis = var_650_axis_0, split_sizes = var_650_split_sizes_0, x = h_59_cast_fp16)[name = string("op_650_cast_fp16")];
            fp16 var_652_promoted_to_fp16 = const()[name = string("op_652_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_653_cast_fp16 = add(x = var_650_cast_fp16_0, y = var_652_promoted_to_fp16)[name = string("op_653_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_654_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_59_cast_fp16)[name = string("op_654_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_655_cast_fp16 = mul(x = var_653_cast_fp16, y = var_654_cast_fp16)[name = string("op_655_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_43_cast_fp16 = add(x = var_655_cast_fp16, y = var_650_cast_fp16_1)[name = string("xt_43_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_1_alpha1_1_to_fp16 = const()[name = string("generator_resblocks_1_alpha1_1_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16984896)))];
            tensor<fp16, [1, 256, ?]> var_660_cast_fp16 = mul(x = generator_resblocks_1_alpha1_1_to_fp16, y = xt_43_cast_fp16)[name = string("op_660_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_661_cast_fp16 = sin(x = var_660_cast_fp16)[name = string("op_661_cast_fp16")];
            fp16 var_24_promoted_15_to_fp16 = const()[name = string("op_24_promoted_15_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_662_cast_fp16 = pow(x = var_661_cast_fp16, y = var_24_promoted_15_to_fp16)[name = string("op_662_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_657_to_fp16 = const()[name = string("op_657_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16985472)))];
            tensor<fp16, [1, 256, ?]> var_663_cast_fp16 = mul(x = var_657_to_fp16, y = var_662_cast_fp16)[name = string("op_663_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_61_cast_fp16 = add(x = xt_43_cast_fp16, y = var_663_cast_fp16)[name = string("input_61_cast_fp16")];
            string input_63_pad_type_0 = const()[name = string("input_63_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_63_pad_0 = const()[name = string("input_63_pad_0"), val = tensor<int32, [2]>([9, 9])];
            tensor<int32, [1]> input_63_dilations_0 = const()[name = string("input_63_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_63_strides_0 = const()[name = string("input_63_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_63_groups_0 = const()[name = string("input_63_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 7]> generator_resblocks_1_convs1_1_weight_to_fp16 = const()[name = string("generator_resblocks_1_convs1_1_weight_to_fp16"), val = tensor<fp16, [256, 256, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16986048)))];
            tensor<fp16, [256]> generator_resblocks_1_convs1_1_bias_to_fp16 = const()[name = string("generator_resblocks_1_convs1_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17903616)))];
            tensor<fp16, [1, 256, ?]> input_63_cast_fp16 = conv(bias = generator_resblocks_1_convs1_1_bias_to_fp16, dilations = input_63_dilations_0, groups = input_63_groups_0, pad = input_63_pad_0, pad_type = input_63_pad_type_0, strides = input_63_strides_0, weight = generator_resblocks_1_convs1_1_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_63_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_1_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_1_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17904192)))];
            tensor<fp16, [512]> generator_resblocks_1_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_1_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18035328)))];
            tensor<fp16, [1, 512]> linear_15_cast_fp16 = linear(bias = generator_resblocks_1_adain2_1_fc_bias_to_fp16, weight = generator_resblocks_1_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_15_cast_fp16")];
            tensor<int32, [3]> var_678 = const()[name = string("op_678"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_63_cast_fp16 = reshape(shape = var_678, x = linear_15_cast_fp16)[name = string("h_63_cast_fp16")];
            tensor<int32, [2]> var_680_split_sizes_0 = const()[name = string("op_680_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_680_axis_0 = const()[name = string("op_680_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_680_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_680_cast_fp16_1 = split(axis = var_680_axis_0, split_sizes = var_680_split_sizes_0, x = h_63_cast_fp16)[name = string("op_680_cast_fp16")];
            fp16 var_682_promoted_to_fp16 = const()[name = string("op_682_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_683_cast_fp16 = add(x = var_680_cast_fp16_0, y = var_682_promoted_to_fp16)[name = string("op_683_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_684_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_63_cast_fp16)[name = string("op_684_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_685_cast_fp16 = mul(x = var_683_cast_fp16, y = var_684_cast_fp16)[name = string("op_685_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_45_cast_fp16 = add(x = var_685_cast_fp16, y = var_680_cast_fp16_1)[name = string("xt_45_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_1_alpha2_1_to_fp16 = const()[name = string("generator_resblocks_1_alpha2_1_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18036416)))];
            tensor<fp16, [1, 256, ?]> var_690_cast_fp16 = mul(x = generator_resblocks_1_alpha2_1_to_fp16, y = xt_45_cast_fp16)[name = string("op_690_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_691_cast_fp16 = sin(x = var_690_cast_fp16)[name = string("op_691_cast_fp16")];
            fp16 var_24_promoted_16_to_fp16 = const()[name = string("op_24_promoted_16_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_692_cast_fp16 = pow(x = var_691_cast_fp16, y = var_24_promoted_16_to_fp16)[name = string("op_692_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_687_to_fp16 = const()[name = string("op_687_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18036992)))];
            tensor<fp16, [1, 256, ?]> var_693_cast_fp16 = mul(x = var_687_to_fp16, y = var_692_cast_fp16)[name = string("op_693_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_65_cast_fp16 = add(x = xt_45_cast_fp16, y = var_693_cast_fp16)[name = string("input_65_cast_fp16")];
            string xt_47_pad_type_0 = const()[name = string("xt_47_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_47_pad_0 = const()[name = string("xt_47_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_47_strides_0 = const()[name = string("xt_47_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_47_dilations_0 = const()[name = string("xt_47_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_47_groups_0 = const()[name = string("xt_47_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 7]> generator_resblocks_1_convs2_1_weight_to_fp16 = const()[name = string("generator_resblocks_1_convs2_1_weight_to_fp16"), val = tensor<fp16, [256, 256, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18037568)))];
            tensor<fp16, [256]> generator_resblocks_1_convs2_1_bias_to_fp16 = const()[name = string("generator_resblocks_1_convs2_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18955136)))];
            tensor<fp16, [1, 256, ?]> xt_47_cast_fp16 = conv(bias = generator_resblocks_1_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 = generator_resblocks_1_convs2_1_weight_to_fp16, x = input_65_cast_fp16)[name = string("xt_47_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_67_cast_fp16 = add(x = xt_47_cast_fp16, y = input_59_cast_fp16)[name = string("input_67_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_1_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_1_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18955712)))];
            tensor<fp16, [512]> generator_resblocks_1_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_1_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19086848)))];
            tensor<fp16, [1, 512]> linear_16_cast_fp16 = linear(bias = generator_resblocks_1_adain1_2_fc_bias_to_fp16, weight = generator_resblocks_1_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_16_cast_fp16")];
            tensor<int32, [3]> var_709 = const()[name = string("op_709"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_67_cast_fp16 = reshape(shape = var_709, x = linear_16_cast_fp16)[name = string("h_67_cast_fp16")];
            tensor<int32, [2]> var_711_split_sizes_0 = const()[name = string("op_711_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_711_axis_0 = const()[name = string("op_711_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_711_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_711_cast_fp16_1 = split(axis = var_711_axis_0, split_sizes = var_711_split_sizes_0, x = h_67_cast_fp16)[name = string("op_711_cast_fp16")];
            fp16 var_713_promoted_to_fp16 = const()[name = string("op_713_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_714_cast_fp16 = add(x = var_711_cast_fp16_0, y = var_713_promoted_to_fp16)[name = string("op_714_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_715_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_67_cast_fp16)[name = string("op_715_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_716_cast_fp16 = mul(x = var_714_cast_fp16, y = var_715_cast_fp16)[name = string("op_716_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_49_cast_fp16 = add(x = var_716_cast_fp16, y = var_711_cast_fp16_1)[name = string("xt_49_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_1_alpha1_2_to_fp16 = const()[name = string("generator_resblocks_1_alpha1_2_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19087936)))];
            tensor<fp16, [1, 256, ?]> var_721_cast_fp16 = mul(x = generator_resblocks_1_alpha1_2_to_fp16, y = xt_49_cast_fp16)[name = string("op_721_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_722_cast_fp16 = sin(x = var_721_cast_fp16)[name = string("op_722_cast_fp16")];
            fp16 var_24_promoted_17_to_fp16 = const()[name = string("op_24_promoted_17_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_723_cast_fp16 = pow(x = var_722_cast_fp16, y = var_24_promoted_17_to_fp16)[name = string("op_723_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_718_to_fp16 = const()[name = string("op_718_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19088512)))];
            tensor<fp16, [1, 256, ?]> var_724_cast_fp16 = mul(x = var_718_to_fp16, y = var_723_cast_fp16)[name = string("op_724_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_69_cast_fp16 = add(x = xt_49_cast_fp16, y = var_724_cast_fp16)[name = string("input_69_cast_fp16")];
            string input_71_pad_type_0 = const()[name = string("input_71_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_71_pad_0 = const()[name = string("input_71_pad_0"), val = tensor<int32, [2]>([15, 15])];
            tensor<int32, [1]> input_71_dilations_0 = const()[name = string("input_71_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_71_strides_0 = const()[name = string("input_71_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_71_groups_0 = const()[name = string("input_71_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 7]> generator_resblocks_1_convs1_2_weight_to_fp16 = const()[name = string("generator_resblocks_1_convs1_2_weight_to_fp16"), val = tensor<fp16, [256, 256, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19089088)))];
            tensor<fp16, [256]> generator_resblocks_1_convs1_2_bias_to_fp16 = const()[name = string("generator_resblocks_1_convs1_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20006656)))];
            tensor<fp16, [1, 256, ?]> input_71_cast_fp16 = conv(bias = generator_resblocks_1_convs1_2_bias_to_fp16, dilations = input_71_dilations_0, groups = input_71_groups_0, pad = input_71_pad_0, pad_type = input_71_pad_type_0, strides = input_71_strides_0, weight = generator_resblocks_1_convs1_2_weight_to_fp16, x = input_69_cast_fp16)[name = string("input_71_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_1_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_1_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20007232)))];
            tensor<fp16, [512]> generator_resblocks_1_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_1_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20138368)))];
            tensor<fp16, [1, 512]> linear_17_cast_fp16 = linear(bias = generator_resblocks_1_adain2_2_fc_bias_to_fp16, weight = generator_resblocks_1_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_17_cast_fp16")];
            tensor<int32, [3]> var_739 = const()[name = string("op_739"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_71_cast_fp16 = reshape(shape = var_739, x = linear_17_cast_fp16)[name = string("h_71_cast_fp16")];
            tensor<int32, [2]> var_741_split_sizes_0 = const()[name = string("op_741_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_741_axis_0 = const()[name = string("op_741_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_741_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_741_cast_fp16_1 = split(axis = var_741_axis_0, split_sizes = var_741_split_sizes_0, x = h_71_cast_fp16)[name = string("op_741_cast_fp16")];
            fp16 var_743_promoted_to_fp16 = const()[name = string("op_743_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_744_cast_fp16 = add(x = var_741_cast_fp16_0, y = var_743_promoted_to_fp16)[name = string("op_744_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_745_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_71_cast_fp16)[name = string("op_745_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_746_cast_fp16 = mul(x = var_744_cast_fp16, y = var_745_cast_fp16)[name = string("op_746_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_51_cast_fp16 = add(x = var_746_cast_fp16, y = var_741_cast_fp16_1)[name = string("xt_51_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_1_alpha2_2_to_fp16 = const()[name = string("generator_resblocks_1_alpha2_2_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20139456)))];
            tensor<fp16, [1, 256, ?]> var_751_cast_fp16 = mul(x = generator_resblocks_1_alpha2_2_to_fp16, y = xt_51_cast_fp16)[name = string("op_751_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_752_cast_fp16 = sin(x = var_751_cast_fp16)[name = string("op_752_cast_fp16")];
            fp16 var_24_promoted_18_to_fp16 = const()[name = string("op_24_promoted_18_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_753_cast_fp16 = pow(x = var_752_cast_fp16, y = var_24_promoted_18_to_fp16)[name = string("op_753_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_748_to_fp16 = const()[name = string("op_748_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20140032)))];
            tensor<fp16, [1, 256, ?]> var_754_cast_fp16 = mul(x = var_748_to_fp16, y = var_753_cast_fp16)[name = string("op_754_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_73_cast_fp16 = add(x = xt_51_cast_fp16, y = var_754_cast_fp16)[name = string("input_73_cast_fp16")];
            string xt_53_pad_type_0 = const()[name = string("xt_53_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_53_pad_0 = const()[name = string("xt_53_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_53_strides_0 = const()[name = string("xt_53_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_53_dilations_0 = const()[name = string("xt_53_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_53_groups_0 = const()[name = string("xt_53_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 7]> generator_resblocks_1_convs2_2_weight_to_fp16 = const()[name = string("generator_resblocks_1_convs2_2_weight_to_fp16"), val = tensor<fp16, [256, 256, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20140608)))];
            tensor<fp16, [256]> generator_resblocks_1_convs2_2_bias_to_fp16 = const()[name = string("generator_resblocks_1_convs2_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21058176)))];
            tensor<fp16, [1, 256, ?]> xt_53_cast_fp16 = conv(bias = generator_resblocks_1_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 = generator_resblocks_1_convs2_2_weight_to_fp16, x = input_73_cast_fp16)[name = string("xt_53_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_763_cast_fp16 = add(x = xt_53_cast_fp16, y = input_67_cast_fp16)[name = string("op_763_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xs_3_cast_fp16 = add(x = xs_1_cast_fp16, y = var_763_cast_fp16)[name = string("xs_3_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_2_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_2_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21058752)))];
            tensor<fp16, [512]> generator_resblocks_2_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_2_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21189888)))];
            tensor<fp16, [1, 512]> linear_18_cast_fp16 = linear(bias = generator_resblocks_2_adain1_0_fc_bias_to_fp16, weight = generator_resblocks_2_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_18_cast_fp16")];
            tensor<int32, [3]> var_807 = const()[name = string("op_807"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_75_cast_fp16 = reshape(shape = var_807, x = linear_18_cast_fp16)[name = string("h_75_cast_fp16")];
            tensor<int32, [2]> var_809_split_sizes_0 = const()[name = string("op_809_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_809_axis_0 = const()[name = string("op_809_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_809_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_809_cast_fp16_1 = split(axis = var_809_axis_0, split_sizes = var_809_split_sizes_0, x = h_75_cast_fp16)[name = string("op_809_cast_fp16")];
            fp16 var_811_promoted_to_fp16 = const()[name = string("op_811_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_812_cast_fp16 = add(x = var_809_cast_fp16_0, y = var_811_promoted_to_fp16)[name = string("op_812_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_814_cast_fp16 = mul(x = var_812_cast_fp16, y = var_374_cast_fp16)[name = string("op_814_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_55_cast_fp16 = add(x = var_814_cast_fp16, y = var_809_cast_fp16_1)[name = string("xt_55_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_2_alpha1_0_to_fp16 = const()[name = string("generator_resblocks_2_alpha1_0_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21190976)))];
            tensor<fp16, [1, 256, ?]> var_819_cast_fp16 = mul(x = generator_resblocks_2_alpha1_0_to_fp16, y = xt_55_cast_fp16)[name = string("op_819_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_820_cast_fp16 = sin(x = var_819_cast_fp16)[name = string("op_820_cast_fp16")];
            fp16 var_24_promoted_19_to_fp16 = const()[name = string("op_24_promoted_19_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_821_cast_fp16 = pow(x = var_820_cast_fp16, y = var_24_promoted_19_to_fp16)[name = string("op_821_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_816_to_fp16 = const()[name = string("op_816_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21191552)))];
            tensor<fp16, [1, 256, ?]> var_822_cast_fp16 = mul(x = var_816_to_fp16, y = var_821_cast_fp16)[name = string("op_822_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_75_cast_fp16 = add(x = xt_55_cast_fp16, y = var_822_cast_fp16)[name = string("input_75_cast_fp16")];
            string input_77_pad_type_0 = const()[name = string("input_77_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_77_pad_0 = const()[name = string("input_77_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> input_77_strides_0 = const()[name = string("input_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_77_dilations_0 = const()[name = string("input_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_77_groups_0 = const()[name = string("input_77_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 11]> generator_resblocks_2_convs1_0_weight_to_fp16 = const()[name = string("generator_resblocks_2_convs1_0_weight_to_fp16"), val = tensor<fp16, [256, 256, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21192128)))];
            tensor<fp16, [256]> generator_resblocks_2_convs1_0_bias_to_fp16 = const()[name = string("generator_resblocks_2_convs1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22633984)))];
            tensor<fp16, [1, 256, ?]> input_77_cast_fp16 = conv(bias = generator_resblocks_2_convs1_0_bias_to_fp16, dilations = input_77_dilations_0, groups = input_77_groups_0, pad = input_77_pad_0, pad_type = input_77_pad_type_0, strides = input_77_strides_0, weight = generator_resblocks_2_convs1_0_weight_to_fp16, x = input_75_cast_fp16)[name = string("input_77_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_2_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_2_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22634560)))];
            tensor<fp16, [512]> generator_resblocks_2_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_2_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22765696)))];
            tensor<fp16, [1, 512]> linear_19_cast_fp16 = linear(bias = generator_resblocks_2_adain2_0_fc_bias_to_fp16, weight = generator_resblocks_2_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_19_cast_fp16")];
            tensor<int32, [3]> var_837 = const()[name = string("op_837"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_79_cast_fp16 = reshape(shape = var_837, x = linear_19_cast_fp16)[name = string("h_79_cast_fp16")];
            tensor<int32, [2]> var_839_split_sizes_0 = const()[name = string("op_839_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_839_axis_0 = const()[name = string("op_839_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_839_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_839_cast_fp16_1 = split(axis = var_839_axis_0, split_sizes = var_839_split_sizes_0, x = h_79_cast_fp16)[name = string("op_839_cast_fp16")];
            fp16 var_841_promoted_to_fp16 = const()[name = string("op_841_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_842_cast_fp16 = add(x = var_839_cast_fp16_0, y = var_841_promoted_to_fp16)[name = string("op_842_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_843_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_77_cast_fp16)[name = string("op_843_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_844_cast_fp16 = mul(x = var_842_cast_fp16, y = var_843_cast_fp16)[name = string("op_844_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_57_cast_fp16 = add(x = var_844_cast_fp16, y = var_839_cast_fp16_1)[name = string("xt_57_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_2_alpha2_0_to_fp16 = const()[name = string("generator_resblocks_2_alpha2_0_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22766784)))];
            tensor<fp16, [1, 256, ?]> var_849_cast_fp16 = mul(x = generator_resblocks_2_alpha2_0_to_fp16, y = xt_57_cast_fp16)[name = string("op_849_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_850_cast_fp16 = sin(x = var_849_cast_fp16)[name = string("op_850_cast_fp16")];
            fp16 var_24_promoted_20_to_fp16 = const()[name = string("op_24_promoted_20_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_851_cast_fp16 = pow(x = var_850_cast_fp16, y = var_24_promoted_20_to_fp16)[name = string("op_851_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_846_to_fp16 = const()[name = string("op_846_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22767360)))];
            tensor<fp16, [1, 256, ?]> var_852_cast_fp16 = mul(x = var_846_to_fp16, y = var_851_cast_fp16)[name = string("op_852_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_79_cast_fp16 = add(x = xt_57_cast_fp16, y = var_852_cast_fp16)[name = string("input_79_cast_fp16")];
            string xt_59_pad_type_0 = const()[name = string("xt_59_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_59_pad_0 = const()[name = string("xt_59_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_59_strides_0 = const()[name = string("xt_59_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_59_dilations_0 = const()[name = string("xt_59_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_59_groups_0 = const()[name = string("xt_59_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 11]> generator_resblocks_2_convs2_0_weight_to_fp16 = const()[name = string("generator_resblocks_2_convs2_0_weight_to_fp16"), val = tensor<fp16, [256, 256, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22767936)))];
            tensor<fp16, [256]> generator_resblocks_2_convs2_0_bias_to_fp16 = const()[name = string("generator_resblocks_2_convs2_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(24209792)))];
            tensor<fp16, [1, 256, ?]> xt_59_cast_fp16 = conv(bias = generator_resblocks_2_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 = generator_resblocks_2_convs2_0_weight_to_fp16, x = input_79_cast_fp16)[name = string("xt_59_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_81_cast_fp16 = add(x = xt_59_cast_fp16, y = input_29_cast_fp16)[name = string("input_81_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_2_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_2_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(24210368)))];
            tensor<fp16, [512]> generator_resblocks_2_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_2_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(24341504)))];
            tensor<fp16, [1, 512]> linear_20_cast_fp16 = linear(bias = generator_resblocks_2_adain1_1_fc_bias_to_fp16, weight = generator_resblocks_2_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_20_cast_fp16")];
            tensor<int32, [3]> var_868 = const()[name = string("op_868"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_83_cast_fp16 = reshape(shape = var_868, x = linear_20_cast_fp16)[name = string("h_83_cast_fp16")];
            tensor<int32, [2]> var_870_split_sizes_0 = const()[name = string("op_870_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_870_axis_0 = const()[name = string("op_870_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_870_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_870_cast_fp16_1 = split(axis = var_870_axis_0, split_sizes = var_870_split_sizes_0, x = h_83_cast_fp16)[name = string("op_870_cast_fp16")];
            fp16 var_872_promoted_to_fp16 = const()[name = string("op_872_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_873_cast_fp16 = add(x = var_870_cast_fp16_0, y = var_872_promoted_to_fp16)[name = string("op_873_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_874_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_81_cast_fp16)[name = string("op_874_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_875_cast_fp16 = mul(x = var_873_cast_fp16, y = var_874_cast_fp16)[name = string("op_875_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_61_cast_fp16 = add(x = var_875_cast_fp16, y = var_870_cast_fp16_1)[name = string("xt_61_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_2_alpha1_1_to_fp16 = const()[name = string("generator_resblocks_2_alpha1_1_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(24342592)))];
            tensor<fp16, [1, 256, ?]> var_880_cast_fp16 = mul(x = generator_resblocks_2_alpha1_1_to_fp16, y = xt_61_cast_fp16)[name = string("op_880_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_881_cast_fp16 = sin(x = var_880_cast_fp16)[name = string("op_881_cast_fp16")];
            fp16 var_24_promoted_21_to_fp16 = const()[name = string("op_24_promoted_21_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_882_cast_fp16 = pow(x = var_881_cast_fp16, y = var_24_promoted_21_to_fp16)[name = string("op_882_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_877_to_fp16 = const()[name = string("op_877_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(24343168)))];
            tensor<fp16, [1, 256, ?]> var_883_cast_fp16 = mul(x = var_877_to_fp16, y = var_882_cast_fp16)[name = string("op_883_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_83_cast_fp16 = add(x = xt_61_cast_fp16, y = var_883_cast_fp16)[name = string("input_83_cast_fp16")];
            string input_85_pad_type_0 = const()[name = string("input_85_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_85_pad_0 = const()[name = string("input_85_pad_0"), val = tensor<int32, [2]>([15, 15])];
            tensor<int32, [1]> input_85_dilations_0 = const()[name = string("input_85_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_85_strides_0 = const()[name = string("input_85_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_85_groups_0 = const()[name = string("input_85_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 11]> generator_resblocks_2_convs1_1_weight_to_fp16 = const()[name = string("generator_resblocks_2_convs1_1_weight_to_fp16"), val = tensor<fp16, [256, 256, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(24343744)))];
            tensor<fp16, [256]> generator_resblocks_2_convs1_1_bias_to_fp16 = const()[name = string("generator_resblocks_2_convs1_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25785600)))];
            tensor<fp16, [1, 256, ?]> input_85_cast_fp16 = conv(bias = generator_resblocks_2_convs1_1_bias_to_fp16, dilations = input_85_dilations_0, groups = input_85_groups_0, pad = input_85_pad_0, pad_type = input_85_pad_type_0, strides = input_85_strides_0, weight = generator_resblocks_2_convs1_1_weight_to_fp16, x = input_83_cast_fp16)[name = string("input_85_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_2_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_2_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25786176)))];
            tensor<fp16, [512]> generator_resblocks_2_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_2_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25917312)))];
            tensor<fp16, [1, 512]> linear_21_cast_fp16 = linear(bias = generator_resblocks_2_adain2_1_fc_bias_to_fp16, weight = generator_resblocks_2_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_21_cast_fp16")];
            tensor<int32, [3]> var_898 = const()[name = string("op_898"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_87_cast_fp16 = reshape(shape = var_898, x = linear_21_cast_fp16)[name = string("h_87_cast_fp16")];
            tensor<int32, [2]> var_900_split_sizes_0 = const()[name = string("op_900_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_900_axis_0 = const()[name = string("op_900_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_900_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_900_cast_fp16_1 = split(axis = var_900_axis_0, split_sizes = var_900_split_sizes_0, x = h_87_cast_fp16)[name = string("op_900_cast_fp16")];
            fp16 var_902_promoted_to_fp16 = const()[name = string("op_902_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_903_cast_fp16 = add(x = var_900_cast_fp16_0, y = var_902_promoted_to_fp16)[name = string("op_903_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_904_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_85_cast_fp16)[name = string("op_904_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_905_cast_fp16 = mul(x = var_903_cast_fp16, y = var_904_cast_fp16)[name = string("op_905_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_63_cast_fp16 = add(x = var_905_cast_fp16, y = var_900_cast_fp16_1)[name = string("xt_63_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_2_alpha2_1_to_fp16 = const()[name = string("generator_resblocks_2_alpha2_1_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25918400)))];
            tensor<fp16, [1, 256, ?]> var_910_cast_fp16 = mul(x = generator_resblocks_2_alpha2_1_to_fp16, y = xt_63_cast_fp16)[name = string("op_910_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_911_cast_fp16 = sin(x = var_910_cast_fp16)[name = string("op_911_cast_fp16")];
            fp16 var_24_promoted_22_to_fp16 = const()[name = string("op_24_promoted_22_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_912_cast_fp16 = pow(x = var_911_cast_fp16, y = var_24_promoted_22_to_fp16)[name = string("op_912_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_907_to_fp16 = const()[name = string("op_907_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25918976)))];
            tensor<fp16, [1, 256, ?]> var_913_cast_fp16 = mul(x = var_907_to_fp16, y = var_912_cast_fp16)[name = string("op_913_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_87_cast_fp16 = add(x = xt_63_cast_fp16, y = var_913_cast_fp16)[name = string("input_87_cast_fp16")];
            string xt_65_pad_type_0 = const()[name = string("xt_65_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_65_pad_0 = const()[name = string("xt_65_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_65_strides_0 = const()[name = string("xt_65_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_65_dilations_0 = const()[name = string("xt_65_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_65_groups_0 = const()[name = string("xt_65_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 11]> generator_resblocks_2_convs2_1_weight_to_fp16 = const()[name = string("generator_resblocks_2_convs2_1_weight_to_fp16"), val = tensor<fp16, [256, 256, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25919552)))];
            tensor<fp16, [256]> generator_resblocks_2_convs2_1_bias_to_fp16 = const()[name = string("generator_resblocks_2_convs2_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27361408)))];
            tensor<fp16, [1, 256, ?]> xt_65_cast_fp16 = conv(bias = generator_resblocks_2_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 = generator_resblocks_2_convs2_1_weight_to_fp16, x = input_87_cast_fp16)[name = string("xt_65_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_89_cast_fp16 = add(x = xt_65_cast_fp16, y = input_81_cast_fp16)[name = string("input_89_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_2_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_2_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27361984)))];
            tensor<fp16, [512]> generator_resblocks_2_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_2_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27493120)))];
            tensor<fp16, [1, 512]> linear_22_cast_fp16 = linear(bias = generator_resblocks_2_adain1_2_fc_bias_to_fp16, weight = generator_resblocks_2_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_22_cast_fp16")];
            tensor<int32, [3]> var_929 = const()[name = string("op_929"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_91_cast_fp16 = reshape(shape = var_929, x = linear_22_cast_fp16)[name = string("h_91_cast_fp16")];
            tensor<int32, [2]> var_931_split_sizes_0 = const()[name = string("op_931_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_931_axis_0 = const()[name = string("op_931_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_931_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_931_cast_fp16_1 = split(axis = var_931_axis_0, split_sizes = var_931_split_sizes_0, x = h_91_cast_fp16)[name = string("op_931_cast_fp16")];
            fp16 var_933_promoted_to_fp16 = const()[name = string("op_933_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_934_cast_fp16 = add(x = var_931_cast_fp16_0, y = var_933_promoted_to_fp16)[name = string("op_934_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_935_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_89_cast_fp16)[name = string("op_935_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_936_cast_fp16 = mul(x = var_934_cast_fp16, y = var_935_cast_fp16)[name = string("op_936_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_67_cast_fp16 = add(x = var_936_cast_fp16, y = var_931_cast_fp16_1)[name = string("xt_67_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_2_alpha1_2_to_fp16 = const()[name = string("generator_resblocks_2_alpha1_2_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27494208)))];
            tensor<fp16, [1, 256, ?]> var_941_cast_fp16 = mul(x = generator_resblocks_2_alpha1_2_to_fp16, y = xt_67_cast_fp16)[name = string("op_941_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_942_cast_fp16 = sin(x = var_941_cast_fp16)[name = string("op_942_cast_fp16")];
            fp16 var_24_promoted_23_to_fp16 = const()[name = string("op_24_promoted_23_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_943_cast_fp16 = pow(x = var_942_cast_fp16, y = var_24_promoted_23_to_fp16)[name = string("op_943_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_938_to_fp16 = const()[name = string("op_938_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27494784)))];
            tensor<fp16, [1, 256, ?]> var_944_cast_fp16 = mul(x = var_938_to_fp16, y = var_943_cast_fp16)[name = string("op_944_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_91_cast_fp16 = add(x = xt_67_cast_fp16, y = var_944_cast_fp16)[name = string("input_91_cast_fp16")];
            string input_93_pad_type_0 = const()[name = string("input_93_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_93_pad_0 = const()[name = string("input_93_pad_0"), val = tensor<int32, [2]>([25, 25])];
            tensor<int32, [1]> input_93_dilations_0 = const()[name = string("input_93_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_93_strides_0 = const()[name = string("input_93_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_93_groups_0 = const()[name = string("input_93_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 11]> generator_resblocks_2_convs1_2_weight_to_fp16 = const()[name = string("generator_resblocks_2_convs1_2_weight_to_fp16"), val = tensor<fp16, [256, 256, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27495360)))];
            tensor<fp16, [256]> generator_resblocks_2_convs1_2_bias_to_fp16 = const()[name = string("generator_resblocks_2_convs1_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28937216)))];
            tensor<fp16, [1, 256, ?]> input_93_cast_fp16 = conv(bias = generator_resblocks_2_convs1_2_bias_to_fp16, dilations = input_93_dilations_0, groups = input_93_groups_0, pad = input_93_pad_0, pad_type = input_93_pad_type_0, strides = input_93_strides_0, weight = generator_resblocks_2_convs1_2_weight_to_fp16, x = input_91_cast_fp16)[name = string("input_93_cast_fp16")];
            tensor<fp16, [512, 128]> generator_resblocks_2_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_2_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [512, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28937792)))];
            tensor<fp16, [512]> generator_resblocks_2_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_2_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29068928)))];
            tensor<fp16, [1, 512]> linear_23_cast_fp16 = linear(bias = generator_resblocks_2_adain2_2_fc_bias_to_fp16, weight = generator_resblocks_2_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_23_cast_fp16")];
            tensor<int32, [3]> var_959 = const()[name = string("op_959"), val = tensor<int32, [3]>([1, 512, 1])];
            tensor<fp16, [1, 512, 1]> h_95_cast_fp16 = reshape(shape = var_959, x = linear_23_cast_fp16)[name = string("h_95_cast_fp16")];
            tensor<int32, [2]> var_961_split_sizes_0 = const()[name = string("op_961_split_sizes_0"), val = tensor<int32, [2]>([256, 256])];
            int32 var_961_axis_0 = const()[name = string("op_961_axis_0"), val = int32(1)];
            tensor<fp16, [1, 256, 1]> var_961_cast_fp16_0, tensor<fp16, [1, 256, 1]> var_961_cast_fp16_1 = split(axis = var_961_axis_0, split_sizes = var_961_split_sizes_0, x = h_95_cast_fp16)[name = string("op_961_cast_fp16")];
            fp16 var_963_promoted_to_fp16 = const()[name = string("op_963_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256, 1]> var_964_cast_fp16 = add(x = var_961_cast_fp16_0, y = var_963_promoted_to_fp16)[name = string("op_964_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_965_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_93_cast_fp16)[name = string("op_965_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_966_cast_fp16 = mul(x = var_964_cast_fp16, y = var_965_cast_fp16)[name = string("op_966_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xt_69_cast_fp16 = add(x = var_966_cast_fp16, y = var_961_cast_fp16_1)[name = string("xt_69_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_resblocks_2_alpha2_2_to_fp16 = const()[name = string("generator_resblocks_2_alpha2_2_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29070016)))];
            tensor<fp16, [1, 256, ?]> var_971_cast_fp16 = mul(x = generator_resblocks_2_alpha2_2_to_fp16, y = xt_69_cast_fp16)[name = string("op_971_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_972_cast_fp16 = sin(x = var_971_cast_fp16)[name = string("op_972_cast_fp16")];
            fp16 var_24_promoted_24_to_fp16 = const()[name = string("op_24_promoted_24_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_973_cast_fp16 = pow(x = var_972_cast_fp16, y = var_24_promoted_24_to_fp16)[name = string("op_973_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_968_to_fp16 = const()[name = string("op_968_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29070592)))];
            tensor<fp16, [1, 256, ?]> var_974_cast_fp16 = mul(x = var_968_to_fp16, y = var_973_cast_fp16)[name = string("op_974_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_95_cast_fp16 = add(x = xt_69_cast_fp16, y = var_974_cast_fp16)[name = string("input_95_cast_fp16")];
            string xt_71_pad_type_0 = const()[name = string("xt_71_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_71_pad_0 = const()[name = string("xt_71_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_71_strides_0 = const()[name = string("xt_71_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_71_dilations_0 = const()[name = string("xt_71_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_71_groups_0 = const()[name = string("xt_71_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 11]> generator_resblocks_2_convs2_2_weight_to_fp16 = const()[name = string("generator_resblocks_2_convs2_2_weight_to_fp16"), val = tensor<fp16, [256, 256, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29071168)))];
            tensor<fp16, [256]> generator_resblocks_2_convs2_2_bias_to_fp16 = const()[name = string("generator_resblocks_2_convs2_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30513024)))];
            tensor<fp16, [1, 256, ?]> xt_71_cast_fp16 = conv(bias = generator_resblocks_2_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 = generator_resblocks_2_convs2_2_weight_to_fp16, x = input_95_cast_fp16)[name = string("xt_71_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_983_cast_fp16 = add(x = xt_71_cast_fp16, y = input_89_cast_fp16)[name = string("op_983_cast_fp16")];
            tensor<fp16, [1, 256, ?]> xs_5_cast_fp16 = add(x = xs_3_cast_fp16, y = var_983_cast_fp16)[name = string("xs_5_cast_fp16")];
            fp16 _inversed_x_3_y_0_to_fp16 = const()[name = string("_inversed_x_3_y_0_to_fp16"), val = fp16(0x1.554p-2)];
            tensor<fp16, [1, 256, ?]> _inversed_x_3_cast_fp16 = mul(x = xs_5_cast_fp16, y = _inversed_x_3_y_0_to_fp16)[name = string("_inversed_x_3_cast_fp16")];
            tensor<fp16, [1, 256, 1]> generator_alphas_1_to_fp16 = const()[name = string("generator_alphas_1_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30513600)))];
            tensor<fp16, [1, 256, ?]> var_990_cast_fp16 = mul(x = generator_alphas_1_to_fp16, y = _inversed_x_3_cast_fp16)[name = string("op_990_cast_fp16")];
            tensor<fp16, [1, 256, ?]> var_991_cast_fp16 = sin(x = var_990_cast_fp16)[name = string("op_991_cast_fp16")];
            fp16 var_24_promoted_25_to_fp16 = const()[name = string("op_24_promoted_25_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, ?]> var_992_cast_fp16 = pow(x = var_991_cast_fp16, y = var_24_promoted_25_to_fp16)[name = string("op_992_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_987_to_fp16 = const()[name = string("op_987_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30514176)))];
            tensor<fp16, [1, 256, ?]> var_993_cast_fp16 = mul(x = var_987_to_fp16, y = var_992_cast_fp16)[name = string("op_993_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_121_cast_fp16 = add(x = _inversed_x_3_cast_fp16, y = var_993_cast_fp16)[name = string("input_121_cast_fp16")];
            string input_97_pad_type_0 = const()[name = string("input_97_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_97_pad_0 = const()[name = string("input_97_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> input_97_strides_0 = const()[name = string("input_97_strides_0"), val = tensor<int32, [1]>([6])];
            tensor<int32, [1]> input_97_dilations_0 = const()[name = string("input_97_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_97_groups_0 = const()[name = string("input_97_groups_0"), val = int32(1)];
            tensor<fp16, [128, 1, 12]> generator_noise_convs_1_weight_to_fp16 = const()[name = string("generator_noise_convs_1_weight_to_fp16"), val = tensor<fp16, [128, 1, 12]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30514752)))];
            tensor<fp16, [128]> generator_noise_convs_1_bias_to_fp16 = const()[name = string("generator_noise_convs_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30517888)))];
            tensor<fp16, [1, 128, ?]> input_97_cast_fp16 = conv(bias = generator_noise_convs_1_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 = generator_noise_convs_1_weight_to_fp16, x = har_source_to_fp16)[name = string("input_97_cast_fp16")];
            tensor<fp16, [256, 128]> generator_noise_res_1_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_noise_res_1_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30518208)))];
            tensor<fp16, [256]> generator_noise_res_1_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_noise_res_1_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30583808)))];
            tensor<fp16, [1, 256]> linear_24_cast_fp16 = linear(bias = generator_noise_res_1_adain1_0_fc_bias_to_fp16, weight = generator_noise_res_1_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_24_cast_fp16")];
            tensor<int32, [3]> var_1044 = const()[name = string("op_1044"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_99_cast_fp16 = reshape(shape = var_1044, x = linear_24_cast_fp16)[name = string("h_99_cast_fp16")];
            tensor<int32, [2]> var_1046_split_sizes_0 = const()[name = string("op_1046_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1046_axis_0 = const()[name = string("op_1046_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1046_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1046_cast_fp16_1 = split(axis = var_1046_axis_0, split_sizes = var_1046_split_sizes_0, x = h_99_cast_fp16)[name = string("op_1046_cast_fp16")];
            fp16 var_1048_promoted_to_fp16 = const()[name = string("op_1048_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1049_cast_fp16 = add(x = var_1046_cast_fp16_0, y = var_1048_promoted_to_fp16)[name = string("op_1049_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1050_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_97_cast_fp16)[name = string("op_1050_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1051_cast_fp16 = mul(x = var_1049_cast_fp16, y = var_1050_cast_fp16)[name = string("op_1051_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_73_cast_fp16 = add(x = var_1051_cast_fp16, y = var_1046_cast_fp16_1)[name = string("xt_73_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_noise_res_1_alpha1_0_to_fp16 = const()[name = string("generator_noise_res_1_alpha1_0_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30584384)))];
            tensor<fp16, [1, 128, ?]> var_1056_cast_fp16 = mul(x = generator_noise_res_1_alpha1_0_to_fp16, y = xt_73_cast_fp16)[name = string("op_1056_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1057_cast_fp16 = sin(x = var_1056_cast_fp16)[name = string("op_1057_cast_fp16")];
            fp16 var_24_promoted_26_to_fp16 = const()[name = string("op_24_promoted_26_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1058_cast_fp16 = pow(x = var_1057_cast_fp16, y = var_24_promoted_26_to_fp16)[name = string("op_1058_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1053_to_fp16 = const()[name = string("op_1053_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30584704)))];
            tensor<fp16, [1, 128, ?]> var_1059_cast_fp16 = mul(x = var_1053_to_fp16, y = var_1058_cast_fp16)[name = string("op_1059_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_99_cast_fp16 = add(x = xt_73_cast_fp16, y = var_1059_cast_fp16)[name = string("input_99_cast_fp16")];
            string input_101_pad_type_0 = const()[name = string("input_101_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_101_pad_0 = const()[name = string("input_101_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> input_101_strides_0 = const()[name = string("input_101_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_101_dilations_0 = const()[name = string("input_101_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_101_groups_0 = const()[name = string("input_101_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 7]> generator_noise_res_1_convs1_0_weight_to_fp16 = const()[name = string("generator_noise_res_1_convs1_0_weight_to_fp16"), val = tensor<fp16, [128, 128, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30585024)))];
            tensor<fp16, [128]> generator_noise_res_1_convs1_0_bias_to_fp16 = const()[name = string("generator_noise_res_1_convs1_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30814464)))];
            tensor<fp16, [1, 128, ?]> input_101_cast_fp16 = conv(bias = generator_noise_res_1_convs1_0_bias_to_fp16, dilations = input_101_dilations_0, groups = input_101_groups_0, pad = input_101_pad_0, pad_type = input_101_pad_type_0, strides = input_101_strides_0, weight = generator_noise_res_1_convs1_0_weight_to_fp16, x = input_99_cast_fp16)[name = string("input_101_cast_fp16")];
            tensor<fp16, [256, 128]> generator_noise_res_1_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_noise_res_1_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30814784)))];
            tensor<fp16, [256]> generator_noise_res_1_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_noise_res_1_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30880384)))];
            tensor<fp16, [1, 256]> linear_25_cast_fp16 = linear(bias = generator_noise_res_1_adain2_0_fc_bias_to_fp16, weight = generator_noise_res_1_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_25_cast_fp16")];
            tensor<int32, [3]> var_1074 = const()[name = string("op_1074"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_103_cast_fp16 = reshape(shape = var_1074, x = linear_25_cast_fp16)[name = string("h_103_cast_fp16")];
            tensor<int32, [2]> var_1076_split_sizes_0 = const()[name = string("op_1076_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1076_axis_0 = const()[name = string("op_1076_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1076_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1076_cast_fp16_1 = split(axis = var_1076_axis_0, split_sizes = var_1076_split_sizes_0, x = h_103_cast_fp16)[name = string("op_1076_cast_fp16")];
            fp16 var_1078_promoted_to_fp16 = const()[name = string("op_1078_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1079_cast_fp16 = add(x = var_1076_cast_fp16_0, y = var_1078_promoted_to_fp16)[name = string("op_1079_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1080_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_101_cast_fp16)[name = string("op_1080_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1081_cast_fp16 = mul(x = var_1079_cast_fp16, y = var_1080_cast_fp16)[name = string("op_1081_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_75_cast_fp16 = add(x = var_1081_cast_fp16, y = var_1076_cast_fp16_1)[name = string("xt_75_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_noise_res_1_alpha2_0_to_fp16 = const()[name = string("generator_noise_res_1_alpha2_0_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30880960)))];
            tensor<fp16, [1, 128, ?]> var_1086_cast_fp16 = mul(x = generator_noise_res_1_alpha2_0_to_fp16, y = xt_75_cast_fp16)[name = string("op_1086_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1087_cast_fp16 = sin(x = var_1086_cast_fp16)[name = string("op_1087_cast_fp16")];
            fp16 var_24_promoted_27_to_fp16 = const()[name = string("op_24_promoted_27_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1088_cast_fp16 = pow(x = var_1087_cast_fp16, y = var_24_promoted_27_to_fp16)[name = string("op_1088_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1083_to_fp16 = const()[name = string("op_1083_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30881280)))];
            tensor<fp16, [1, 128, ?]> var_1089_cast_fp16 = mul(x = var_1083_to_fp16, y = var_1088_cast_fp16)[name = string("op_1089_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_103_cast_fp16 = add(x = xt_75_cast_fp16, y = var_1089_cast_fp16)[name = string("input_103_cast_fp16")];
            string xt_77_pad_type_0 = const()[name = string("xt_77_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_77_pad_0 = const()[name = string("xt_77_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_77_strides_0 = const()[name = string("xt_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_77_dilations_0 = const()[name = string("xt_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_77_groups_0 = const()[name = string("xt_77_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 7]> generator_noise_res_1_convs2_0_weight_to_fp16 = const()[name = string("generator_noise_res_1_convs2_0_weight_to_fp16"), val = tensor<fp16, [128, 128, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30881600)))];
            tensor<fp16, [128]> generator_noise_res_1_convs2_0_bias_to_fp16 = const()[name = string("generator_noise_res_1_convs2_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31111040)))];
            tensor<fp16, [1, 128, ?]> xt_77_cast_fp16 = conv(bias = generator_noise_res_1_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 = generator_noise_res_1_convs2_0_weight_to_fp16, x = input_103_cast_fp16)[name = string("xt_77_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_105_cast_fp16 = add(x = xt_77_cast_fp16, y = input_97_cast_fp16)[name = string("input_105_cast_fp16")];
            tensor<fp16, [256, 128]> generator_noise_res_1_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_noise_res_1_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31111360)))];
            tensor<fp16, [256]> generator_noise_res_1_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_noise_res_1_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31176960)))];
            tensor<fp16, [1, 256]> linear_26_cast_fp16 = linear(bias = generator_noise_res_1_adain1_1_fc_bias_to_fp16, weight = generator_noise_res_1_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_26_cast_fp16")];
            tensor<int32, [3]> var_1105 = const()[name = string("op_1105"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_107_cast_fp16 = reshape(shape = var_1105, x = linear_26_cast_fp16)[name = string("h_107_cast_fp16")];
            tensor<int32, [2]> var_1107_split_sizes_0 = const()[name = string("op_1107_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1107_axis_0 = const()[name = string("op_1107_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1107_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1107_cast_fp16_1 = split(axis = var_1107_axis_0, split_sizes = var_1107_split_sizes_0, x = h_107_cast_fp16)[name = string("op_1107_cast_fp16")];
            fp16 var_1109_promoted_to_fp16 = const()[name = string("op_1109_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1110_cast_fp16 = add(x = var_1107_cast_fp16_0, y = var_1109_promoted_to_fp16)[name = string("op_1110_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1111_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_105_cast_fp16)[name = string("op_1111_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1112_cast_fp16 = mul(x = var_1110_cast_fp16, y = var_1111_cast_fp16)[name = string("op_1112_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_79_cast_fp16 = add(x = var_1112_cast_fp16, y = var_1107_cast_fp16_1)[name = string("xt_79_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_noise_res_1_alpha1_1_to_fp16 = const()[name = string("generator_noise_res_1_alpha1_1_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31177536)))];
            tensor<fp16, [1, 128, ?]> var_1117_cast_fp16 = mul(x = generator_noise_res_1_alpha1_1_to_fp16, y = xt_79_cast_fp16)[name = string("op_1117_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1118_cast_fp16 = sin(x = var_1117_cast_fp16)[name = string("op_1118_cast_fp16")];
            fp16 var_24_promoted_28_to_fp16 = const()[name = string("op_24_promoted_28_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1119_cast_fp16 = pow(x = var_1118_cast_fp16, y = var_24_promoted_28_to_fp16)[name = string("op_1119_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1114_to_fp16 = const()[name = string("op_1114_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31177856)))];
            tensor<fp16, [1, 128, ?]> var_1120_cast_fp16 = mul(x = var_1114_to_fp16, y = var_1119_cast_fp16)[name = string("op_1120_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_107_cast_fp16 = add(x = xt_79_cast_fp16, y = var_1120_cast_fp16)[name = string("input_107_cast_fp16")];
            string input_109_pad_type_0 = const()[name = string("input_109_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_109_pad_0 = const()[name = string("input_109_pad_0"), val = tensor<int32, [2]>([9, 9])];
            tensor<int32, [1]> input_109_dilations_0 = const()[name = string("input_109_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_109_strides_0 = const()[name = string("input_109_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_109_groups_0 = const()[name = string("input_109_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 7]> generator_noise_res_1_convs1_1_weight_to_fp16 = const()[name = string("generator_noise_res_1_convs1_1_weight_to_fp16"), val = tensor<fp16, [128, 128, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31178176)))];
            tensor<fp16, [128]> generator_noise_res_1_convs1_1_bias_to_fp16 = const()[name = string("generator_noise_res_1_convs1_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31407616)))];
            tensor<fp16, [1, 128, ?]> input_109_cast_fp16 = conv(bias = generator_noise_res_1_convs1_1_bias_to_fp16, dilations = input_109_dilations_0, groups = input_109_groups_0, pad = input_109_pad_0, pad_type = input_109_pad_type_0, strides = input_109_strides_0, weight = generator_noise_res_1_convs1_1_weight_to_fp16, x = input_107_cast_fp16)[name = string("input_109_cast_fp16")];
            tensor<fp16, [256, 128]> generator_noise_res_1_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_noise_res_1_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31407936)))];
            tensor<fp16, [256]> generator_noise_res_1_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_noise_res_1_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31473536)))];
            tensor<fp16, [1, 256]> linear_27_cast_fp16 = linear(bias = generator_noise_res_1_adain2_1_fc_bias_to_fp16, weight = generator_noise_res_1_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_27_cast_fp16")];
            tensor<int32, [3]> var_1135 = const()[name = string("op_1135"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_111_cast_fp16 = reshape(shape = var_1135, x = linear_27_cast_fp16)[name = string("h_111_cast_fp16")];
            tensor<int32, [2]> var_1137_split_sizes_0 = const()[name = string("op_1137_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1137_axis_0 = const()[name = string("op_1137_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1137_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1137_cast_fp16_1 = split(axis = var_1137_axis_0, split_sizes = var_1137_split_sizes_0, x = h_111_cast_fp16)[name = string("op_1137_cast_fp16")];
            fp16 var_1139_promoted_to_fp16 = const()[name = string("op_1139_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1140_cast_fp16 = add(x = var_1137_cast_fp16_0, y = var_1139_promoted_to_fp16)[name = string("op_1140_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1141_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_109_cast_fp16)[name = string("op_1141_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1142_cast_fp16 = mul(x = var_1140_cast_fp16, y = var_1141_cast_fp16)[name = string("op_1142_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_81_cast_fp16 = add(x = var_1142_cast_fp16, y = var_1137_cast_fp16_1)[name = string("xt_81_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_noise_res_1_alpha2_1_to_fp16 = const()[name = string("generator_noise_res_1_alpha2_1_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31474112)))];
            tensor<fp16, [1, 128, ?]> var_1147_cast_fp16 = mul(x = generator_noise_res_1_alpha2_1_to_fp16, y = xt_81_cast_fp16)[name = string("op_1147_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1148_cast_fp16 = sin(x = var_1147_cast_fp16)[name = string("op_1148_cast_fp16")];
            fp16 var_24_promoted_29_to_fp16 = const()[name = string("op_24_promoted_29_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1149_cast_fp16 = pow(x = var_1148_cast_fp16, y = var_24_promoted_29_to_fp16)[name = string("op_1149_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1144_to_fp16 = const()[name = string("op_1144_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31474432)))];
            tensor<fp16, [1, 128, ?]> var_1150_cast_fp16 = mul(x = var_1144_to_fp16, y = var_1149_cast_fp16)[name = string("op_1150_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_111_cast_fp16 = add(x = xt_81_cast_fp16, y = var_1150_cast_fp16)[name = string("input_111_cast_fp16")];
            string xt_83_pad_type_0 = const()[name = string("xt_83_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_83_pad_0 = const()[name = string("xt_83_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_83_strides_0 = const()[name = string("xt_83_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_83_dilations_0 = const()[name = string("xt_83_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_83_groups_0 = const()[name = string("xt_83_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 7]> generator_noise_res_1_convs2_1_weight_to_fp16 = const()[name = string("generator_noise_res_1_convs2_1_weight_to_fp16"), val = tensor<fp16, [128, 128, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31474752)))];
            tensor<fp16, [128]> generator_noise_res_1_convs2_1_bias_to_fp16 = const()[name = string("generator_noise_res_1_convs2_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31704192)))];
            tensor<fp16, [1, 128, ?]> xt_83_cast_fp16 = conv(bias = generator_noise_res_1_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 = generator_noise_res_1_convs2_1_weight_to_fp16, x = input_111_cast_fp16)[name = string("xt_83_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_113_cast_fp16 = add(x = xt_83_cast_fp16, y = input_105_cast_fp16)[name = string("input_113_cast_fp16")];
            tensor<fp16, [256, 128]> generator_noise_res_1_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_noise_res_1_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31704512)))];
            tensor<fp16, [256]> generator_noise_res_1_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_noise_res_1_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31770112)))];
            tensor<fp16, [1, 256]> linear_28_cast_fp16 = linear(bias = generator_noise_res_1_adain1_2_fc_bias_to_fp16, weight = generator_noise_res_1_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_28_cast_fp16")];
            tensor<int32, [3]> var_1166 = const()[name = string("op_1166"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_115_cast_fp16 = reshape(shape = var_1166, x = linear_28_cast_fp16)[name = string("h_115_cast_fp16")];
            tensor<int32, [2]> var_1168_split_sizes_0 = const()[name = string("op_1168_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1168_axis_0 = const()[name = string("op_1168_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1168_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1168_cast_fp16_1 = split(axis = var_1168_axis_0, split_sizes = var_1168_split_sizes_0, x = h_115_cast_fp16)[name = string("op_1168_cast_fp16")];
            fp16 var_1170_promoted_to_fp16 = const()[name = string("op_1170_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1171_cast_fp16 = add(x = var_1168_cast_fp16_0, y = var_1170_promoted_to_fp16)[name = string("op_1171_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1172_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_113_cast_fp16)[name = string("op_1172_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1173_cast_fp16 = mul(x = var_1171_cast_fp16, y = var_1172_cast_fp16)[name = string("op_1173_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_85_cast_fp16 = add(x = var_1173_cast_fp16, y = var_1168_cast_fp16_1)[name = string("xt_85_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_noise_res_1_alpha1_2_to_fp16 = const()[name = string("generator_noise_res_1_alpha1_2_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31770688)))];
            tensor<fp16, [1, 128, ?]> var_1178_cast_fp16 = mul(x = generator_noise_res_1_alpha1_2_to_fp16, y = xt_85_cast_fp16)[name = string("op_1178_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1179_cast_fp16 = sin(x = var_1178_cast_fp16)[name = string("op_1179_cast_fp16")];
            fp16 var_24_promoted_30_to_fp16 = const()[name = string("op_24_promoted_30_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1180_cast_fp16 = pow(x = var_1179_cast_fp16, y = var_24_promoted_30_to_fp16)[name = string("op_1180_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1175_to_fp16 = const()[name = string("op_1175_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31771008)))];
            tensor<fp16, [1, 128, ?]> var_1181_cast_fp16 = mul(x = var_1175_to_fp16, y = var_1180_cast_fp16)[name = string("op_1181_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_115_cast_fp16 = add(x = xt_85_cast_fp16, y = var_1181_cast_fp16)[name = string("input_115_cast_fp16")];
            string input_117_pad_type_0 = const()[name = string("input_117_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_117_pad_0 = const()[name = string("input_117_pad_0"), val = tensor<int32, [2]>([15, 15])];
            tensor<int32, [1]> input_117_dilations_0 = const()[name = string("input_117_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_117_strides_0 = const()[name = string("input_117_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_117_groups_0 = const()[name = string("input_117_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 7]> generator_noise_res_1_convs1_2_weight_to_fp16 = const()[name = string("generator_noise_res_1_convs1_2_weight_to_fp16"), val = tensor<fp16, [128, 128, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31771328)))];
            tensor<fp16, [128]> generator_noise_res_1_convs1_2_bias_to_fp16 = const()[name = string("generator_noise_res_1_convs1_2_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32000768)))];
            tensor<fp16, [1, 128, ?]> input_117_cast_fp16 = conv(bias = generator_noise_res_1_convs1_2_bias_to_fp16, dilations = input_117_dilations_0, groups = input_117_groups_0, pad = input_117_pad_0, pad_type = input_117_pad_type_0, strides = input_117_strides_0, weight = generator_noise_res_1_convs1_2_weight_to_fp16, x = input_115_cast_fp16)[name = string("input_117_cast_fp16")];
            tensor<fp16, [256, 128]> generator_noise_res_1_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_noise_res_1_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32001088)))];
            tensor<fp16, [256]> generator_noise_res_1_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_noise_res_1_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32066688)))];
            tensor<fp16, [1, 256]> linear_29_cast_fp16 = linear(bias = generator_noise_res_1_adain2_2_fc_bias_to_fp16, weight = generator_noise_res_1_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_29_cast_fp16")];
            tensor<int32, [3]> var_1196 = const()[name = string("op_1196"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_119_cast_fp16 = reshape(shape = var_1196, x = linear_29_cast_fp16)[name = string("h_119_cast_fp16")];
            tensor<int32, [2]> var_1198_split_sizes_0 = const()[name = string("op_1198_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1198_axis_0 = const()[name = string("op_1198_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1198_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1198_cast_fp16_1 = split(axis = var_1198_axis_0, split_sizes = var_1198_split_sizes_0, x = h_119_cast_fp16)[name = string("op_1198_cast_fp16")];
            fp16 var_1200_promoted_to_fp16 = const()[name = string("op_1200_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1201_cast_fp16 = add(x = var_1198_cast_fp16_0, y = var_1200_promoted_to_fp16)[name = string("op_1201_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1202_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_117_cast_fp16)[name = string("op_1202_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1203_cast_fp16 = mul(x = var_1201_cast_fp16, y = var_1202_cast_fp16)[name = string("op_1203_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_87_cast_fp16 = add(x = var_1203_cast_fp16, y = var_1198_cast_fp16_1)[name = string("xt_87_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_noise_res_1_alpha2_2_to_fp16 = const()[name = string("generator_noise_res_1_alpha2_2_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32067264)))];
            tensor<fp16, [1, 128, ?]> var_1208_cast_fp16 = mul(x = generator_noise_res_1_alpha2_2_to_fp16, y = xt_87_cast_fp16)[name = string("op_1208_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1209_cast_fp16 = sin(x = var_1208_cast_fp16)[name = string("op_1209_cast_fp16")];
            fp16 var_24_promoted_31_to_fp16 = const()[name = string("op_24_promoted_31_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1210_cast_fp16 = pow(x = var_1209_cast_fp16, y = var_24_promoted_31_to_fp16)[name = string("op_1210_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1205_to_fp16 = const()[name = string("op_1205_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32067584)))];
            tensor<fp16, [1, 128, ?]> var_1211_cast_fp16 = mul(x = var_1205_to_fp16, y = var_1210_cast_fp16)[name = string("op_1211_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_119_cast_fp16 = add(x = xt_87_cast_fp16, y = var_1211_cast_fp16)[name = string("input_119_cast_fp16")];
            string xt_89_pad_type_0 = const()[name = string("xt_89_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_89_pad_0 = const()[name = string("xt_89_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_89_strides_0 = const()[name = string("xt_89_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_89_dilations_0 = const()[name = string("xt_89_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_89_groups_0 = const()[name = string("xt_89_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 7]> generator_noise_res_1_convs2_2_weight_to_fp16 = const()[name = string("generator_noise_res_1_convs2_2_weight_to_fp16"), val = tensor<fp16, [128, 128, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32067904)))];
            tensor<fp16, [128]> generator_noise_res_1_convs2_2_bias_to_fp16 = const()[name = string("generator_noise_res_1_convs2_2_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32297344)))];
            tensor<fp16, [1, 128, ?]> xt_89_cast_fp16 = conv(bias = generator_noise_res_1_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 = generator_noise_res_1_convs2_2_weight_to_fp16, x = input_119_cast_fp16)[name = string("xt_89_cast_fp16")];
            tensor<fp16, [1, 128, ?]> x_source_3_cast_fp16 = add(x = xt_89_cast_fp16, y = input_113_cast_fp16)[name = string("x_source_3_cast_fp16")];
            string conv_transpose_0_pad_type_0 = const()[name = string("conv_transpose_0_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_transpose_0_pad_0 = const()[name = string("conv_transpose_0_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_transpose_0_strides_0 = const()[name = string("conv_transpose_0_strides_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> conv_transpose_0_dilations_0 = const()[name = string("conv_transpose_0_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_transpose_0_groups_0 = const()[name = string("conv_transpose_0_groups_0"), val = int32(1)];
            tensor<fp16, [256, 128, 10]> generator_ups_1_weight_to_fp16 = const()[name = string("generator_ups_1_weight_to_fp16"), val = tensor<fp16, [256, 128, 10]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32297664)))];
            tensor<fp16, [128]> generator_ups_1_bias_to_fp16 = const()[name = string("generator_ups_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32953088)))];
            tensor<fp16, [1, 128, ?]> conv_transpose_0_cast_fp16 = conv_transpose(bias = generator_ups_1_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 = generator_ups_1_weight_to_fp16, x = input_121_cast_fp16)[name = string("conv_transpose_0_cast_fp16")];
            tensor<int32, [3]> x_5_begin_0 = const()[name = string("x_5_begin_0"), val = tensor<int32, [3]>([0, 0, 3])];
            tensor<int32, [3]> x_5_end_0 = const()[name = string("x_5_end_0"), val = tensor<int32, [3]>([0, 0, -2])];
            tensor<bool, [3]> x_5_begin_mask_0 = const()[name = string("x_5_begin_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<bool, [3]> x_5_end_mask_0 = const()[name = string("x_5_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> x_5_cast_fp16 = slice_by_index(begin = x_5_begin_0, begin_mask = x_5_begin_mask_0, end = x_5_end_0, end_mask = x_5_end_mask_0, x = conv_transpose_0_cast_fp16)[name = string("x_5_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_123_cast_fp16 = add(x = x_5_cast_fp16, y = x_source_3_cast_fp16)[name = string("input_123_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_3_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_3_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32953408)))];
            tensor<fp16, [256]> generator_resblocks_3_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_3_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33019008)))];
            tensor<fp16, [1, 256]> linear_30_cast_fp16 = linear(bias = generator_resblocks_3_adain1_0_fc_bias_to_fp16, weight = generator_resblocks_3_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_30_cast_fp16")];
            tensor<int32, [3]> var_1271 = const()[name = string("op_1271"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_123_cast_fp16 = reshape(shape = var_1271, x = linear_30_cast_fp16)[name = string("h_123_cast_fp16")];
            tensor<int32, [2]> var_1273_split_sizes_0 = const()[name = string("op_1273_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1273_axis_0 = const()[name = string("op_1273_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1273_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1273_cast_fp16_1 = split(axis = var_1273_axis_0, split_sizes = var_1273_split_sizes_0, x = h_123_cast_fp16)[name = string("op_1273_cast_fp16")];
            fp16 var_1275_promoted_to_fp16 = const()[name = string("op_1275_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1276_cast_fp16 = add(x = var_1273_cast_fp16_0, y = var_1275_promoted_to_fp16)[name = string("op_1276_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1277_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_123_cast_fp16)[name = string("op_1277_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1278_cast_fp16 = mul(x = var_1276_cast_fp16, y = var_1277_cast_fp16)[name = string("op_1278_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_91_cast_fp16 = add(x = var_1278_cast_fp16, y = var_1273_cast_fp16_1)[name = string("xt_91_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_3_alpha1_0_to_fp16 = const()[name = string("generator_resblocks_3_alpha1_0_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33019584)))];
            tensor<fp16, [1, 128, ?]> var_1283_cast_fp16 = mul(x = generator_resblocks_3_alpha1_0_to_fp16, y = xt_91_cast_fp16)[name = string("op_1283_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1284_cast_fp16 = sin(x = var_1283_cast_fp16)[name = string("op_1284_cast_fp16")];
            fp16 var_24_promoted_32_to_fp16 = const()[name = string("op_24_promoted_32_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1285_cast_fp16 = pow(x = var_1284_cast_fp16, y = var_24_promoted_32_to_fp16)[name = string("op_1285_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1280_to_fp16 = const()[name = string("op_1280_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33019904)))];
            tensor<fp16, [1, 128, ?]> var_1286_cast_fp16 = mul(x = var_1280_to_fp16, y = var_1285_cast_fp16)[name = string("op_1286_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_125_cast_fp16 = add(x = xt_91_cast_fp16, y = var_1286_cast_fp16)[name = string("input_125_cast_fp16")];
            string input_127_pad_type_0 = const()[name = string("input_127_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_127_pad_0 = const()[name = string("input_127_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> input_127_strides_0 = const()[name = string("input_127_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_127_dilations_0 = const()[name = string("input_127_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_127_groups_0 = const()[name = string("input_127_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 3]> generator_resblocks_3_convs1_0_weight_to_fp16 = const()[name = string("generator_resblocks_3_convs1_0_weight_to_fp16"), val = tensor<fp16, [128, 128, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33020224)))];
            tensor<fp16, [128]> generator_resblocks_3_convs1_0_bias_to_fp16 = const()[name = string("generator_resblocks_3_convs1_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33118592)))];
            tensor<fp16, [1, 128, ?]> input_127_cast_fp16 = conv(bias = generator_resblocks_3_convs1_0_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 = generator_resblocks_3_convs1_0_weight_to_fp16, x = input_125_cast_fp16)[name = string("input_127_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_3_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_3_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33118912)))];
            tensor<fp16, [256]> generator_resblocks_3_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_3_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33184512)))];
            tensor<fp16, [1, 256]> linear_31_cast_fp16 = linear(bias = generator_resblocks_3_adain2_0_fc_bias_to_fp16, weight = generator_resblocks_3_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_31_cast_fp16")];
            tensor<int32, [3]> var_1301 = const()[name = string("op_1301"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_127_cast_fp16 = reshape(shape = var_1301, x = linear_31_cast_fp16)[name = string("h_127_cast_fp16")];
            tensor<int32, [2]> var_1303_split_sizes_0 = const()[name = string("op_1303_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1303_axis_0 = const()[name = string("op_1303_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1303_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1303_cast_fp16_1 = split(axis = var_1303_axis_0, split_sizes = var_1303_split_sizes_0, x = h_127_cast_fp16)[name = string("op_1303_cast_fp16")];
            fp16 var_1305_promoted_to_fp16 = const()[name = string("op_1305_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1306_cast_fp16 = add(x = var_1303_cast_fp16_0, y = var_1305_promoted_to_fp16)[name = string("op_1306_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1307_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_127_cast_fp16)[name = string("op_1307_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1308_cast_fp16 = mul(x = var_1306_cast_fp16, y = var_1307_cast_fp16)[name = string("op_1308_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_93_cast_fp16 = add(x = var_1308_cast_fp16, y = var_1303_cast_fp16_1)[name = string("xt_93_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_3_alpha2_0_to_fp16 = const()[name = string("generator_resblocks_3_alpha2_0_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33185088)))];
            tensor<fp16, [1, 128, ?]> var_1313_cast_fp16 = mul(x = generator_resblocks_3_alpha2_0_to_fp16, y = xt_93_cast_fp16)[name = string("op_1313_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1314_cast_fp16 = sin(x = var_1313_cast_fp16)[name = string("op_1314_cast_fp16")];
            fp16 var_24_promoted_33_to_fp16 = const()[name = string("op_24_promoted_33_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1315_cast_fp16 = pow(x = var_1314_cast_fp16, y = var_24_promoted_33_to_fp16)[name = string("op_1315_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1310_to_fp16 = const()[name = string("op_1310_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33185408)))];
            tensor<fp16, [1, 128, ?]> var_1316_cast_fp16 = mul(x = var_1310_to_fp16, y = var_1315_cast_fp16)[name = string("op_1316_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_129_cast_fp16 = add(x = xt_93_cast_fp16, y = var_1316_cast_fp16)[name = string("input_129_cast_fp16")];
            string xt_95_pad_type_0 = const()[name = string("xt_95_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_95_pad_0 = const()[name = string("xt_95_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> xt_95_strides_0 = const()[name = string("xt_95_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_95_dilations_0 = const()[name = string("xt_95_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_95_groups_0 = const()[name = string("xt_95_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 3]> generator_resblocks_3_convs2_0_weight_to_fp16 = const()[name = string("generator_resblocks_3_convs2_0_weight_to_fp16"), val = tensor<fp16, [128, 128, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33185728)))];
            tensor<fp16, [128]> generator_resblocks_3_convs2_0_bias_to_fp16 = const()[name = string("generator_resblocks_3_convs2_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33284096)))];
            tensor<fp16, [1, 128, ?]> xt_95_cast_fp16 = conv(bias = generator_resblocks_3_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 = generator_resblocks_3_convs2_0_weight_to_fp16, x = input_129_cast_fp16)[name = string("xt_95_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_131_cast_fp16 = add(x = xt_95_cast_fp16, y = input_123_cast_fp16)[name = string("input_131_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_3_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_3_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33284416)))];
            tensor<fp16, [256]> generator_resblocks_3_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_3_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33350016)))];
            tensor<fp16, [1, 256]> linear_32_cast_fp16 = linear(bias = generator_resblocks_3_adain1_1_fc_bias_to_fp16, weight = generator_resblocks_3_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_32_cast_fp16")];
            tensor<int32, [3]> var_1332 = const()[name = string("op_1332"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_131_cast_fp16 = reshape(shape = var_1332, x = linear_32_cast_fp16)[name = string("h_131_cast_fp16")];
            tensor<int32, [2]> var_1334_split_sizes_0 = const()[name = string("op_1334_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1334_axis_0 = const()[name = string("op_1334_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1334_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1334_cast_fp16_1 = split(axis = var_1334_axis_0, split_sizes = var_1334_split_sizes_0, x = h_131_cast_fp16)[name = string("op_1334_cast_fp16")];
            fp16 var_1336_promoted_to_fp16 = const()[name = string("op_1336_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1337_cast_fp16 = add(x = var_1334_cast_fp16_0, y = var_1336_promoted_to_fp16)[name = string("op_1337_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1338_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_131_cast_fp16)[name = string("op_1338_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1339_cast_fp16 = mul(x = var_1337_cast_fp16, y = var_1338_cast_fp16)[name = string("op_1339_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_97_cast_fp16 = add(x = var_1339_cast_fp16, y = var_1334_cast_fp16_1)[name = string("xt_97_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_3_alpha1_1_to_fp16 = const()[name = string("generator_resblocks_3_alpha1_1_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33350592)))];
            tensor<fp16, [1, 128, ?]> var_1344_cast_fp16 = mul(x = generator_resblocks_3_alpha1_1_to_fp16, y = xt_97_cast_fp16)[name = string("op_1344_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1345_cast_fp16 = sin(x = var_1344_cast_fp16)[name = string("op_1345_cast_fp16")];
            fp16 var_24_promoted_34_to_fp16 = const()[name = string("op_24_promoted_34_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1346_cast_fp16 = pow(x = var_1345_cast_fp16, y = var_24_promoted_34_to_fp16)[name = string("op_1346_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1341_to_fp16 = const()[name = string("op_1341_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33350912)))];
            tensor<fp16, [1, 128, ?]> var_1347_cast_fp16 = mul(x = var_1341_to_fp16, y = var_1346_cast_fp16)[name = string("op_1347_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_133_cast_fp16 = add(x = xt_97_cast_fp16, y = var_1347_cast_fp16)[name = string("input_133_cast_fp16")];
            string input_135_pad_type_0 = const()[name = string("input_135_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_135_pad_0 = const()[name = string("input_135_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> input_135_dilations_0 = const()[name = string("input_135_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_135_strides_0 = const()[name = string("input_135_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_135_groups_0 = const()[name = string("input_135_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 3]> generator_resblocks_3_convs1_1_weight_to_fp16 = const()[name = string("generator_resblocks_3_convs1_1_weight_to_fp16"), val = tensor<fp16, [128, 128, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33351232)))];
            tensor<fp16, [128]> generator_resblocks_3_convs1_1_bias_to_fp16 = const()[name = string("generator_resblocks_3_convs1_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33449600)))];
            tensor<fp16, [1, 128, ?]> input_135_cast_fp16 = conv(bias = generator_resblocks_3_convs1_1_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 = generator_resblocks_3_convs1_1_weight_to_fp16, x = input_133_cast_fp16)[name = string("input_135_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_3_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_3_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33449920)))];
            tensor<fp16, [256]> generator_resblocks_3_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_3_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33515520)))];
            tensor<fp16, [1, 256]> linear_33_cast_fp16 = linear(bias = generator_resblocks_3_adain2_1_fc_bias_to_fp16, weight = generator_resblocks_3_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_33_cast_fp16")];
            tensor<int32, [3]> var_1362 = const()[name = string("op_1362"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_135_cast_fp16 = reshape(shape = var_1362, x = linear_33_cast_fp16)[name = string("h_135_cast_fp16")];
            tensor<int32, [2]> var_1364_split_sizes_0 = const()[name = string("op_1364_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1364_axis_0 = const()[name = string("op_1364_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1364_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1364_cast_fp16_1 = split(axis = var_1364_axis_0, split_sizes = var_1364_split_sizes_0, x = h_135_cast_fp16)[name = string("op_1364_cast_fp16")];
            fp16 var_1366_promoted_to_fp16 = const()[name = string("op_1366_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1367_cast_fp16 = add(x = var_1364_cast_fp16_0, y = var_1366_promoted_to_fp16)[name = string("op_1367_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1368_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_135_cast_fp16)[name = string("op_1368_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1369_cast_fp16 = mul(x = var_1367_cast_fp16, y = var_1368_cast_fp16)[name = string("op_1369_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_99_cast_fp16 = add(x = var_1369_cast_fp16, y = var_1364_cast_fp16_1)[name = string("xt_99_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_3_alpha2_1_to_fp16 = const()[name = string("generator_resblocks_3_alpha2_1_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33516096)))];
            tensor<fp16, [1, 128, ?]> var_1374_cast_fp16 = mul(x = generator_resblocks_3_alpha2_1_to_fp16, y = xt_99_cast_fp16)[name = string("op_1374_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1375_cast_fp16 = sin(x = var_1374_cast_fp16)[name = string("op_1375_cast_fp16")];
            fp16 var_24_promoted_35_to_fp16 = const()[name = string("op_24_promoted_35_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1376_cast_fp16 = pow(x = var_1375_cast_fp16, y = var_24_promoted_35_to_fp16)[name = string("op_1376_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1371_to_fp16 = const()[name = string("op_1371_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33516416)))];
            tensor<fp16, [1, 128, ?]> var_1377_cast_fp16 = mul(x = var_1371_to_fp16, y = var_1376_cast_fp16)[name = string("op_1377_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_137_cast_fp16 = add(x = xt_99_cast_fp16, y = var_1377_cast_fp16)[name = string("input_137_cast_fp16")];
            string xt_101_pad_type_0 = const()[name = string("xt_101_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_101_pad_0 = const()[name = string("xt_101_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> xt_101_strides_0 = const()[name = string("xt_101_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_101_dilations_0 = const()[name = string("xt_101_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_101_groups_0 = const()[name = string("xt_101_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 3]> generator_resblocks_3_convs2_1_weight_to_fp16 = const()[name = string("generator_resblocks_3_convs2_1_weight_to_fp16"), val = tensor<fp16, [128, 128, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33516736)))];
            tensor<fp16, [128]> generator_resblocks_3_convs2_1_bias_to_fp16 = const()[name = string("generator_resblocks_3_convs2_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33615104)))];
            tensor<fp16, [1, 128, ?]> xt_101_cast_fp16 = conv(bias = generator_resblocks_3_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 = generator_resblocks_3_convs2_1_weight_to_fp16, x = input_137_cast_fp16)[name = string("xt_101_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_139_cast_fp16 = add(x = xt_101_cast_fp16, y = input_131_cast_fp16)[name = string("input_139_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_3_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_3_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33615424)))];
            tensor<fp16, [256]> generator_resblocks_3_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_3_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33681024)))];
            tensor<fp16, [1, 256]> linear_34_cast_fp16 = linear(bias = generator_resblocks_3_adain1_2_fc_bias_to_fp16, weight = generator_resblocks_3_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_34_cast_fp16")];
            tensor<int32, [3]> var_1393 = const()[name = string("op_1393"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_139_cast_fp16 = reshape(shape = var_1393, x = linear_34_cast_fp16)[name = string("h_139_cast_fp16")];
            tensor<int32, [2]> var_1395_split_sizes_0 = const()[name = string("op_1395_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1395_axis_0 = const()[name = string("op_1395_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1395_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1395_cast_fp16_1 = split(axis = var_1395_axis_0, split_sizes = var_1395_split_sizes_0, x = h_139_cast_fp16)[name = string("op_1395_cast_fp16")];
            fp16 var_1397_promoted_to_fp16 = const()[name = string("op_1397_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1398_cast_fp16 = add(x = var_1395_cast_fp16_0, y = var_1397_promoted_to_fp16)[name = string("op_1398_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1399_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_139_cast_fp16)[name = string("op_1399_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1400_cast_fp16 = mul(x = var_1398_cast_fp16, y = var_1399_cast_fp16)[name = string("op_1400_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_103_cast_fp16 = add(x = var_1400_cast_fp16, y = var_1395_cast_fp16_1)[name = string("xt_103_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_3_alpha1_2_to_fp16 = const()[name = string("generator_resblocks_3_alpha1_2_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33681600)))];
            tensor<fp16, [1, 128, ?]> var_1405_cast_fp16 = mul(x = generator_resblocks_3_alpha1_2_to_fp16, y = xt_103_cast_fp16)[name = string("op_1405_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1406_cast_fp16 = sin(x = var_1405_cast_fp16)[name = string("op_1406_cast_fp16")];
            fp16 var_24_promoted_36_to_fp16 = const()[name = string("op_24_promoted_36_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1407_cast_fp16 = pow(x = var_1406_cast_fp16, y = var_24_promoted_36_to_fp16)[name = string("op_1407_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1402_to_fp16 = const()[name = string("op_1402_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33681920)))];
            tensor<fp16, [1, 128, ?]> var_1408_cast_fp16 = mul(x = var_1402_to_fp16, y = var_1407_cast_fp16)[name = string("op_1408_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_141_cast_fp16 = add(x = xt_103_cast_fp16, y = var_1408_cast_fp16)[name = string("input_141_cast_fp16")];
            string input_143_pad_type_0 = const()[name = string("input_143_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_143_pad_0 = const()[name = string("input_143_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> input_143_dilations_0 = const()[name = string("input_143_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_143_strides_0 = const()[name = string("input_143_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_143_groups_0 = const()[name = string("input_143_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 3]> generator_resblocks_3_convs1_2_weight_to_fp16 = const()[name = string("generator_resblocks_3_convs1_2_weight_to_fp16"), val = tensor<fp16, [128, 128, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33682240)))];
            tensor<fp16, [128]> generator_resblocks_3_convs1_2_bias_to_fp16 = const()[name = string("generator_resblocks_3_convs1_2_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33780608)))];
            tensor<fp16, [1, 128, ?]> input_143_cast_fp16 = conv(bias = generator_resblocks_3_convs1_2_bias_to_fp16, dilations = input_143_dilations_0, groups = input_143_groups_0, pad = input_143_pad_0, pad_type = input_143_pad_type_0, strides = input_143_strides_0, weight = generator_resblocks_3_convs1_2_weight_to_fp16, x = input_141_cast_fp16)[name = string("input_143_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_3_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_3_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33780928)))];
            tensor<fp16, [256]> generator_resblocks_3_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_3_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33846528)))];
            tensor<fp16, [1, 256]> linear_35_cast_fp16 = linear(bias = generator_resblocks_3_adain2_2_fc_bias_to_fp16, weight = generator_resblocks_3_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_35_cast_fp16")];
            tensor<int32, [3]> var_1423 = const()[name = string("op_1423"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_143_cast_fp16 = reshape(shape = var_1423, x = linear_35_cast_fp16)[name = string("h_143_cast_fp16")];
            tensor<int32, [2]> var_1425_split_sizes_0 = const()[name = string("op_1425_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1425_axis_0 = const()[name = string("op_1425_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1425_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1425_cast_fp16_1 = split(axis = var_1425_axis_0, split_sizes = var_1425_split_sizes_0, x = h_143_cast_fp16)[name = string("op_1425_cast_fp16")];
            fp16 var_1427_promoted_to_fp16 = const()[name = string("op_1427_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1428_cast_fp16 = add(x = var_1425_cast_fp16_0, y = var_1427_promoted_to_fp16)[name = string("op_1428_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1429_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_143_cast_fp16)[name = string("op_1429_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1430_cast_fp16 = mul(x = var_1428_cast_fp16, y = var_1429_cast_fp16)[name = string("op_1430_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_105_cast_fp16 = add(x = var_1430_cast_fp16, y = var_1425_cast_fp16_1)[name = string("xt_105_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_3_alpha2_2_to_fp16 = const()[name = string("generator_resblocks_3_alpha2_2_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33847104)))];
            tensor<fp16, [1, 128, ?]> var_1435_cast_fp16 = mul(x = generator_resblocks_3_alpha2_2_to_fp16, y = xt_105_cast_fp16)[name = string("op_1435_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1436_cast_fp16 = sin(x = var_1435_cast_fp16)[name = string("op_1436_cast_fp16")];
            fp16 var_24_promoted_37_to_fp16 = const()[name = string("op_24_promoted_37_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1437_cast_fp16 = pow(x = var_1436_cast_fp16, y = var_24_promoted_37_to_fp16)[name = string("op_1437_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1432_to_fp16 = const()[name = string("op_1432_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33847424)))];
            tensor<fp16, [1, 128, ?]> var_1438_cast_fp16 = mul(x = var_1432_to_fp16, y = var_1437_cast_fp16)[name = string("op_1438_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_145_cast_fp16 = add(x = xt_105_cast_fp16, y = var_1438_cast_fp16)[name = string("input_145_cast_fp16")];
            string xt_107_pad_type_0 = const()[name = string("xt_107_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_107_pad_0 = const()[name = string("xt_107_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> xt_107_strides_0 = const()[name = string("xt_107_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_107_dilations_0 = const()[name = string("xt_107_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_107_groups_0 = const()[name = string("xt_107_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 3]> generator_resblocks_3_convs2_2_weight_to_fp16 = const()[name = string("generator_resblocks_3_convs2_2_weight_to_fp16"), val = tensor<fp16, [128, 128, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33847744)))];
            tensor<fp16, [128]> generator_resblocks_3_convs2_2_bias_to_fp16 = const()[name = string("generator_resblocks_3_convs2_2_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33946112)))];
            tensor<fp16, [1, 128, ?]> xt_107_cast_fp16 = conv(bias = generator_resblocks_3_convs2_2_bias_to_fp16, dilations = xt_107_dilations_0, groups = xt_107_groups_0, pad = xt_107_pad_0, pad_type = xt_107_pad_type_0, strides = xt_107_strides_0, weight = generator_resblocks_3_convs2_2_weight_to_fp16, x = input_145_cast_fp16)[name = string("xt_107_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xs_7_cast_fp16 = add(x = xt_107_cast_fp16, y = input_139_cast_fp16)[name = string("xs_7_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_4_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_4_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33946432)))];
            tensor<fp16, [256]> generator_resblocks_4_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_4_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34012032)))];
            tensor<fp16, [1, 256]> linear_36_cast_fp16 = linear(bias = generator_resblocks_4_adain1_0_fc_bias_to_fp16, weight = generator_resblocks_4_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_36_cast_fp16")];
            tensor<int32, [3]> var_1490 = const()[name = string("op_1490"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_147_cast_fp16 = reshape(shape = var_1490, x = linear_36_cast_fp16)[name = string("h_147_cast_fp16")];
            tensor<int32, [2]> var_1492_split_sizes_0 = const()[name = string("op_1492_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1492_axis_0 = const()[name = string("op_1492_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1492_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1492_cast_fp16_1 = split(axis = var_1492_axis_0, split_sizes = var_1492_split_sizes_0, x = h_147_cast_fp16)[name = string("op_1492_cast_fp16")];
            fp16 var_1494_promoted_to_fp16 = const()[name = string("op_1494_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1495_cast_fp16 = add(x = var_1492_cast_fp16_0, y = var_1494_promoted_to_fp16)[name = string("op_1495_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1497_cast_fp16 = mul(x = var_1495_cast_fp16, y = var_1277_cast_fp16)[name = string("op_1497_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_109_cast_fp16 = add(x = var_1497_cast_fp16, y = var_1492_cast_fp16_1)[name = string("xt_109_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_4_alpha1_0_to_fp16 = const()[name = string("generator_resblocks_4_alpha1_0_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34012608)))];
            tensor<fp16, [1, 128, ?]> var_1502_cast_fp16 = mul(x = generator_resblocks_4_alpha1_0_to_fp16, y = xt_109_cast_fp16)[name = string("op_1502_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1503_cast_fp16 = sin(x = var_1502_cast_fp16)[name = string("op_1503_cast_fp16")];
            fp16 var_24_promoted_38_to_fp16 = const()[name = string("op_24_promoted_38_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1504_cast_fp16 = pow(x = var_1503_cast_fp16, y = var_24_promoted_38_to_fp16)[name = string("op_1504_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1499_to_fp16 = const()[name = string("op_1499_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34012928)))];
            tensor<fp16, [1, 128, ?]> var_1505_cast_fp16 = mul(x = var_1499_to_fp16, y = var_1504_cast_fp16)[name = string("op_1505_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_147_cast_fp16 = add(x = xt_109_cast_fp16, y = var_1505_cast_fp16)[name = string("input_147_cast_fp16")];
            string input_149_pad_type_0 = const()[name = string("input_149_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_149_pad_0 = const()[name = string("input_149_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> input_149_strides_0 = const()[name = string("input_149_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_149_dilations_0 = const()[name = string("input_149_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_149_groups_0 = const()[name = string("input_149_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 7]> generator_resblocks_4_convs1_0_weight_to_fp16 = const()[name = string("generator_resblocks_4_convs1_0_weight_to_fp16"), val = tensor<fp16, [128, 128, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34013248)))];
            tensor<fp16, [128]> generator_resblocks_4_convs1_0_bias_to_fp16 = const()[name = string("generator_resblocks_4_convs1_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34242688)))];
            tensor<fp16, [1, 128, ?]> input_149_cast_fp16 = conv(bias = generator_resblocks_4_convs1_0_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 = generator_resblocks_4_convs1_0_weight_to_fp16, x = input_147_cast_fp16)[name = string("input_149_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_4_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_4_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34243008)))];
            tensor<fp16, [256]> generator_resblocks_4_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_4_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34308608)))];
            tensor<fp16, [1, 256]> linear_37_cast_fp16 = linear(bias = generator_resblocks_4_adain2_0_fc_bias_to_fp16, weight = generator_resblocks_4_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_37_cast_fp16")];
            tensor<int32, [3]> var_1520 = const()[name = string("op_1520"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_151_cast_fp16 = reshape(shape = var_1520, x = linear_37_cast_fp16)[name = string("h_151_cast_fp16")];
            tensor<int32, [2]> var_1522_split_sizes_0 = const()[name = string("op_1522_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1522_axis_0 = const()[name = string("op_1522_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1522_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1522_cast_fp16_1 = split(axis = var_1522_axis_0, split_sizes = var_1522_split_sizes_0, x = h_151_cast_fp16)[name = string("op_1522_cast_fp16")];
            fp16 var_1524_promoted_to_fp16 = const()[name = string("op_1524_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1525_cast_fp16 = add(x = var_1522_cast_fp16_0, y = var_1524_promoted_to_fp16)[name = string("op_1525_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1526_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_149_cast_fp16)[name = string("op_1526_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1527_cast_fp16 = mul(x = var_1525_cast_fp16, y = var_1526_cast_fp16)[name = string("op_1527_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_111_cast_fp16 = add(x = var_1527_cast_fp16, y = var_1522_cast_fp16_1)[name = string("xt_111_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_4_alpha2_0_to_fp16 = const()[name = string("generator_resblocks_4_alpha2_0_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34309184)))];
            tensor<fp16, [1, 128, ?]> var_1532_cast_fp16 = mul(x = generator_resblocks_4_alpha2_0_to_fp16, y = xt_111_cast_fp16)[name = string("op_1532_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1533_cast_fp16 = sin(x = var_1532_cast_fp16)[name = string("op_1533_cast_fp16")];
            fp16 var_24_promoted_39_to_fp16 = const()[name = string("op_24_promoted_39_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1534_cast_fp16 = pow(x = var_1533_cast_fp16, y = var_24_promoted_39_to_fp16)[name = string("op_1534_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1529_to_fp16 = const()[name = string("op_1529_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34309504)))];
            tensor<fp16, [1, 128, ?]> var_1535_cast_fp16 = mul(x = var_1529_to_fp16, y = var_1534_cast_fp16)[name = string("op_1535_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_151_cast_fp16 = add(x = xt_111_cast_fp16, y = var_1535_cast_fp16)[name = string("input_151_cast_fp16")];
            string xt_113_pad_type_0 = const()[name = string("xt_113_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_113_pad_0 = const()[name = string("xt_113_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_113_strides_0 = const()[name = string("xt_113_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_113_dilations_0 = const()[name = string("xt_113_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_113_groups_0 = const()[name = string("xt_113_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 7]> generator_resblocks_4_convs2_0_weight_to_fp16 = const()[name = string("generator_resblocks_4_convs2_0_weight_to_fp16"), val = tensor<fp16, [128, 128, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34309824)))];
            tensor<fp16, [128]> generator_resblocks_4_convs2_0_bias_to_fp16 = const()[name = string("generator_resblocks_4_convs2_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34539264)))];
            tensor<fp16, [1, 128, ?]> xt_113_cast_fp16 = conv(bias = generator_resblocks_4_convs2_0_bias_to_fp16, dilations = xt_113_dilations_0, groups = xt_113_groups_0, pad = xt_113_pad_0, pad_type = xt_113_pad_type_0, strides = xt_113_strides_0, weight = generator_resblocks_4_convs2_0_weight_to_fp16, x = input_151_cast_fp16)[name = string("xt_113_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_153_cast_fp16 = add(x = xt_113_cast_fp16, y = input_123_cast_fp16)[name = string("input_153_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_4_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_4_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34539584)))];
            tensor<fp16, [256]> generator_resblocks_4_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_4_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34605184)))];
            tensor<fp16, [1, 256]> linear_38_cast_fp16 = linear(bias = generator_resblocks_4_adain1_1_fc_bias_to_fp16, weight = generator_resblocks_4_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_38_cast_fp16")];
            tensor<int32, [3]> var_1551 = const()[name = string("op_1551"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_155_cast_fp16 = reshape(shape = var_1551, x = linear_38_cast_fp16)[name = string("h_155_cast_fp16")];
            tensor<int32, [2]> var_1553_split_sizes_0 = const()[name = string("op_1553_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1553_axis_0 = const()[name = string("op_1553_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1553_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1553_cast_fp16_1 = split(axis = var_1553_axis_0, split_sizes = var_1553_split_sizes_0, x = h_155_cast_fp16)[name = string("op_1553_cast_fp16")];
            fp16 var_1555_promoted_to_fp16 = const()[name = string("op_1555_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1556_cast_fp16 = add(x = var_1553_cast_fp16_0, y = var_1555_promoted_to_fp16)[name = string("op_1556_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1557_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_153_cast_fp16)[name = string("op_1557_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1558_cast_fp16 = mul(x = var_1556_cast_fp16, y = var_1557_cast_fp16)[name = string("op_1558_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_115_cast_fp16 = add(x = var_1558_cast_fp16, y = var_1553_cast_fp16_1)[name = string("xt_115_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_4_alpha1_1_to_fp16 = const()[name = string("generator_resblocks_4_alpha1_1_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34605760)))];
            tensor<fp16, [1, 128, ?]> var_1563_cast_fp16 = mul(x = generator_resblocks_4_alpha1_1_to_fp16, y = xt_115_cast_fp16)[name = string("op_1563_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1564_cast_fp16 = sin(x = var_1563_cast_fp16)[name = string("op_1564_cast_fp16")];
            fp16 var_24_promoted_40_to_fp16 = const()[name = string("op_24_promoted_40_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1565_cast_fp16 = pow(x = var_1564_cast_fp16, y = var_24_promoted_40_to_fp16)[name = string("op_1565_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1560_to_fp16 = const()[name = string("op_1560_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34606080)))];
            tensor<fp16, [1, 128, ?]> var_1566_cast_fp16 = mul(x = var_1560_to_fp16, y = var_1565_cast_fp16)[name = string("op_1566_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_155_cast_fp16 = add(x = xt_115_cast_fp16, y = var_1566_cast_fp16)[name = string("input_155_cast_fp16")];
            string input_157_pad_type_0 = const()[name = string("input_157_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_157_pad_0 = const()[name = string("input_157_pad_0"), val = tensor<int32, [2]>([9, 9])];
            tensor<int32, [1]> input_157_dilations_0 = const()[name = string("input_157_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_157_strides_0 = const()[name = string("input_157_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_157_groups_0 = const()[name = string("input_157_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 7]> generator_resblocks_4_convs1_1_weight_to_fp16 = const()[name = string("generator_resblocks_4_convs1_1_weight_to_fp16"), val = tensor<fp16, [128, 128, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34606400)))];
            tensor<fp16, [128]> generator_resblocks_4_convs1_1_bias_to_fp16 = const()[name = string("generator_resblocks_4_convs1_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34835840)))];
            tensor<fp16, [1, 128, ?]> input_157_cast_fp16 = conv(bias = generator_resblocks_4_convs1_1_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 = generator_resblocks_4_convs1_1_weight_to_fp16, x = input_155_cast_fp16)[name = string("input_157_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_4_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_4_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34836160)))];
            tensor<fp16, [256]> generator_resblocks_4_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_4_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34901760)))];
            tensor<fp16, [1, 256]> linear_39_cast_fp16 = linear(bias = generator_resblocks_4_adain2_1_fc_bias_to_fp16, weight = generator_resblocks_4_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_39_cast_fp16")];
            tensor<int32, [3]> var_1581 = const()[name = string("op_1581"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_159_cast_fp16 = reshape(shape = var_1581, x = linear_39_cast_fp16)[name = string("h_159_cast_fp16")];
            tensor<int32, [2]> var_1583_split_sizes_0 = const()[name = string("op_1583_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1583_axis_0 = const()[name = string("op_1583_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1583_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1583_cast_fp16_1 = split(axis = var_1583_axis_0, split_sizes = var_1583_split_sizes_0, x = h_159_cast_fp16)[name = string("op_1583_cast_fp16")];
            fp16 var_1585_promoted_to_fp16 = const()[name = string("op_1585_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1586_cast_fp16 = add(x = var_1583_cast_fp16_0, y = var_1585_promoted_to_fp16)[name = string("op_1586_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1587_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_157_cast_fp16)[name = string("op_1587_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1588_cast_fp16 = mul(x = var_1586_cast_fp16, y = var_1587_cast_fp16)[name = string("op_1588_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_117_cast_fp16 = add(x = var_1588_cast_fp16, y = var_1583_cast_fp16_1)[name = string("xt_117_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_4_alpha2_1_to_fp16 = const()[name = string("generator_resblocks_4_alpha2_1_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34902336)))];
            tensor<fp16, [1, 128, ?]> var_1593_cast_fp16 = mul(x = generator_resblocks_4_alpha2_1_to_fp16, y = xt_117_cast_fp16)[name = string("op_1593_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1594_cast_fp16 = sin(x = var_1593_cast_fp16)[name = string("op_1594_cast_fp16")];
            fp16 var_24_promoted_41_to_fp16 = const()[name = string("op_24_promoted_41_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1595_cast_fp16 = pow(x = var_1594_cast_fp16, y = var_24_promoted_41_to_fp16)[name = string("op_1595_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1590_to_fp16 = const()[name = string("op_1590_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34902656)))];
            tensor<fp16, [1, 128, ?]> var_1596_cast_fp16 = mul(x = var_1590_to_fp16, y = var_1595_cast_fp16)[name = string("op_1596_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_159_cast_fp16 = add(x = xt_117_cast_fp16, y = var_1596_cast_fp16)[name = string("input_159_cast_fp16")];
            string xt_119_pad_type_0 = const()[name = string("xt_119_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_119_pad_0 = const()[name = string("xt_119_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_119_strides_0 = const()[name = string("xt_119_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_119_dilations_0 = const()[name = string("xt_119_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_119_groups_0 = const()[name = string("xt_119_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 7]> generator_resblocks_4_convs2_1_weight_to_fp16 = const()[name = string("generator_resblocks_4_convs2_1_weight_to_fp16"), val = tensor<fp16, [128, 128, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34902976)))];
            tensor<fp16, [128]> generator_resblocks_4_convs2_1_bias_to_fp16 = const()[name = string("generator_resblocks_4_convs2_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35132416)))];
            tensor<fp16, [1, 128, ?]> xt_119_cast_fp16 = conv(bias = generator_resblocks_4_convs2_1_bias_to_fp16, dilations = xt_119_dilations_0, groups = xt_119_groups_0, pad = xt_119_pad_0, pad_type = xt_119_pad_type_0, strides = xt_119_strides_0, weight = generator_resblocks_4_convs2_1_weight_to_fp16, x = input_159_cast_fp16)[name = string("xt_119_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_161_cast_fp16 = add(x = xt_119_cast_fp16, y = input_153_cast_fp16)[name = string("input_161_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_4_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_4_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35132736)))];
            tensor<fp16, [256]> generator_resblocks_4_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_4_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35198336)))];
            tensor<fp16, [1, 256]> linear_40_cast_fp16 = linear(bias = generator_resblocks_4_adain1_2_fc_bias_to_fp16, weight = generator_resblocks_4_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_40_cast_fp16")];
            tensor<int32, [3]> var_1612 = const()[name = string("op_1612"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_163_cast_fp16 = reshape(shape = var_1612, x = linear_40_cast_fp16)[name = string("h_163_cast_fp16")];
            tensor<int32, [2]> var_1614_split_sizes_0 = const()[name = string("op_1614_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1614_axis_0 = const()[name = string("op_1614_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1614_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1614_cast_fp16_1 = split(axis = var_1614_axis_0, split_sizes = var_1614_split_sizes_0, x = h_163_cast_fp16)[name = string("op_1614_cast_fp16")];
            fp16 var_1616_promoted_to_fp16 = const()[name = string("op_1616_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1617_cast_fp16 = add(x = var_1614_cast_fp16_0, y = var_1616_promoted_to_fp16)[name = string("op_1617_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1618_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_161_cast_fp16)[name = string("op_1618_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1619_cast_fp16 = mul(x = var_1617_cast_fp16, y = var_1618_cast_fp16)[name = string("op_1619_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_121_cast_fp16 = add(x = var_1619_cast_fp16, y = var_1614_cast_fp16_1)[name = string("xt_121_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_4_alpha1_2_to_fp16 = const()[name = string("generator_resblocks_4_alpha1_2_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35198912)))];
            tensor<fp16, [1, 128, ?]> var_1624_cast_fp16 = mul(x = generator_resblocks_4_alpha1_2_to_fp16, y = xt_121_cast_fp16)[name = string("op_1624_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1625_cast_fp16 = sin(x = var_1624_cast_fp16)[name = string("op_1625_cast_fp16")];
            fp16 var_24_promoted_42_to_fp16 = const()[name = string("op_24_promoted_42_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1626_cast_fp16 = pow(x = var_1625_cast_fp16, y = var_24_promoted_42_to_fp16)[name = string("op_1626_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1621_to_fp16 = const()[name = string("op_1621_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35199232)))];
            tensor<fp16, [1, 128, ?]> var_1627_cast_fp16 = mul(x = var_1621_to_fp16, y = var_1626_cast_fp16)[name = string("op_1627_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_163_cast_fp16 = add(x = xt_121_cast_fp16, y = var_1627_cast_fp16)[name = string("input_163_cast_fp16")];
            string input_165_pad_type_0 = const()[name = string("input_165_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_165_pad_0 = const()[name = string("input_165_pad_0"), val = tensor<int32, [2]>([15, 15])];
            tensor<int32, [1]> input_165_dilations_0 = const()[name = string("input_165_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_165_strides_0 = const()[name = string("input_165_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_165_groups_0 = const()[name = string("input_165_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 7]> generator_resblocks_4_convs1_2_weight_to_fp16 = const()[name = string("generator_resblocks_4_convs1_2_weight_to_fp16"), val = tensor<fp16, [128, 128, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35199552)))];
            tensor<fp16, [128]> generator_resblocks_4_convs1_2_bias_to_fp16 = const()[name = string("generator_resblocks_4_convs1_2_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35428992)))];
            tensor<fp16, [1, 128, ?]> input_165_cast_fp16 = conv(bias = generator_resblocks_4_convs1_2_bias_to_fp16, dilations = input_165_dilations_0, groups = input_165_groups_0, pad = input_165_pad_0, pad_type = input_165_pad_type_0, strides = input_165_strides_0, weight = generator_resblocks_4_convs1_2_weight_to_fp16, x = input_163_cast_fp16)[name = string("input_165_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_4_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_4_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35429312)))];
            tensor<fp16, [256]> generator_resblocks_4_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_4_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35494912)))];
            tensor<fp16, [1, 256]> linear_41_cast_fp16 = linear(bias = generator_resblocks_4_adain2_2_fc_bias_to_fp16, weight = generator_resblocks_4_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_41_cast_fp16")];
            tensor<int32, [3]> var_1642 = const()[name = string("op_1642"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_167_cast_fp16 = reshape(shape = var_1642, x = linear_41_cast_fp16)[name = string("h_167_cast_fp16")];
            tensor<int32, [2]> var_1644_split_sizes_0 = const()[name = string("op_1644_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1644_axis_0 = const()[name = string("op_1644_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1644_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1644_cast_fp16_1 = split(axis = var_1644_axis_0, split_sizes = var_1644_split_sizes_0, x = h_167_cast_fp16)[name = string("op_1644_cast_fp16")];
            fp16 var_1646_promoted_to_fp16 = const()[name = string("op_1646_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1647_cast_fp16 = add(x = var_1644_cast_fp16_0, y = var_1646_promoted_to_fp16)[name = string("op_1647_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1648_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_165_cast_fp16)[name = string("op_1648_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1649_cast_fp16 = mul(x = var_1647_cast_fp16, y = var_1648_cast_fp16)[name = string("op_1649_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_123_cast_fp16 = add(x = var_1649_cast_fp16, y = var_1644_cast_fp16_1)[name = string("xt_123_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_4_alpha2_2_to_fp16 = const()[name = string("generator_resblocks_4_alpha2_2_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35495488)))];
            tensor<fp16, [1, 128, ?]> var_1654_cast_fp16 = mul(x = generator_resblocks_4_alpha2_2_to_fp16, y = xt_123_cast_fp16)[name = string("op_1654_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1655_cast_fp16 = sin(x = var_1654_cast_fp16)[name = string("op_1655_cast_fp16")];
            fp16 var_24_promoted_43_to_fp16 = const()[name = string("op_24_promoted_43_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1656_cast_fp16 = pow(x = var_1655_cast_fp16, y = var_24_promoted_43_to_fp16)[name = string("op_1656_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1651_to_fp16 = const()[name = string("op_1651_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35495808)))];
            tensor<fp16, [1, 128, ?]> var_1657_cast_fp16 = mul(x = var_1651_to_fp16, y = var_1656_cast_fp16)[name = string("op_1657_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_167_cast_fp16 = add(x = xt_123_cast_fp16, y = var_1657_cast_fp16)[name = string("input_167_cast_fp16")];
            string xt_125_pad_type_0 = const()[name = string("xt_125_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_125_pad_0 = const()[name = string("xt_125_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_125_strides_0 = const()[name = string("xt_125_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_125_dilations_0 = const()[name = string("xt_125_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_125_groups_0 = const()[name = string("xt_125_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 7]> generator_resblocks_4_convs2_2_weight_to_fp16 = const()[name = string("generator_resblocks_4_convs2_2_weight_to_fp16"), val = tensor<fp16, [128, 128, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35496128)))];
            tensor<fp16, [128]> generator_resblocks_4_convs2_2_bias_to_fp16 = const()[name = string("generator_resblocks_4_convs2_2_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35725568)))];
            tensor<fp16, [1, 128, ?]> xt_125_cast_fp16 = conv(bias = generator_resblocks_4_convs2_2_bias_to_fp16, dilations = xt_125_dilations_0, groups = xt_125_groups_0, pad = xt_125_pad_0, pad_type = xt_125_pad_type_0, strides = xt_125_strides_0, weight = generator_resblocks_4_convs2_2_weight_to_fp16, x = input_167_cast_fp16)[name = string("xt_125_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1666_cast_fp16 = add(x = xt_125_cast_fp16, y = input_161_cast_fp16)[name = string("op_1666_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xs_9_cast_fp16 = add(x = xs_7_cast_fp16, y = var_1666_cast_fp16)[name = string("xs_9_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_5_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_5_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35725888)))];
            tensor<fp16, [256]> generator_resblocks_5_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_5_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35791488)))];
            tensor<fp16, [1, 256]> linear_42_cast_fp16 = linear(bias = generator_resblocks_5_adain1_0_fc_bias_to_fp16, weight = generator_resblocks_5_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_42_cast_fp16")];
            tensor<int32, [3]> var_1710 = const()[name = string("op_1710"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_171_cast_fp16 = reshape(shape = var_1710, x = linear_42_cast_fp16)[name = string("h_171_cast_fp16")];
            tensor<int32, [2]> var_1712_split_sizes_0 = const()[name = string("op_1712_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1712_axis_0 = const()[name = string("op_1712_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1712_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1712_cast_fp16_1 = split(axis = var_1712_axis_0, split_sizes = var_1712_split_sizes_0, x = h_171_cast_fp16)[name = string("op_1712_cast_fp16")];
            fp16 var_1714_promoted_to_fp16 = const()[name = string("op_1714_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1715_cast_fp16 = add(x = var_1712_cast_fp16_0, y = var_1714_promoted_to_fp16)[name = string("op_1715_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1717_cast_fp16 = mul(x = var_1715_cast_fp16, y = var_1277_cast_fp16)[name = string("op_1717_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_127_cast_fp16 = add(x = var_1717_cast_fp16, y = var_1712_cast_fp16_1)[name = string("xt_127_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_5_alpha1_0_to_fp16 = const()[name = string("generator_resblocks_5_alpha1_0_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35792064)))];
            tensor<fp16, [1, 128, ?]> var_1722_cast_fp16 = mul(x = generator_resblocks_5_alpha1_0_to_fp16, y = xt_127_cast_fp16)[name = string("op_1722_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1723_cast_fp16 = sin(x = var_1722_cast_fp16)[name = string("op_1723_cast_fp16")];
            fp16 var_24_promoted_44_to_fp16 = const()[name = string("op_24_promoted_44_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1724_cast_fp16 = pow(x = var_1723_cast_fp16, y = var_24_promoted_44_to_fp16)[name = string("op_1724_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1719_to_fp16 = const()[name = string("op_1719_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35792384)))];
            tensor<fp16, [1, 128, ?]> var_1725_cast_fp16 = mul(x = var_1719_to_fp16, y = var_1724_cast_fp16)[name = string("op_1725_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_169_cast_fp16 = add(x = xt_127_cast_fp16, y = var_1725_cast_fp16)[name = string("input_169_cast_fp16")];
            string input_171_pad_type_0 = const()[name = string("input_171_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_171_pad_0 = const()[name = string("input_171_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> input_171_strides_0 = const()[name = string("input_171_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_171_dilations_0 = const()[name = string("input_171_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_171_groups_0 = const()[name = string("input_171_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 11]> generator_resblocks_5_convs1_0_weight_to_fp16 = const()[name = string("generator_resblocks_5_convs1_0_weight_to_fp16"), val = tensor<fp16, [128, 128, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35792704)))];
            tensor<fp16, [128]> generator_resblocks_5_convs1_0_bias_to_fp16 = const()[name = string("generator_resblocks_5_convs1_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36153216)))];
            tensor<fp16, [1, 128, ?]> input_171_cast_fp16 = conv(bias = generator_resblocks_5_convs1_0_bias_to_fp16, dilations = input_171_dilations_0, groups = input_171_groups_0, pad = input_171_pad_0, pad_type = input_171_pad_type_0, strides = input_171_strides_0, weight = generator_resblocks_5_convs1_0_weight_to_fp16, x = input_169_cast_fp16)[name = string("input_171_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_5_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_5_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36153536)))];
            tensor<fp16, [256]> generator_resblocks_5_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_5_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36219136)))];
            tensor<fp16, [1, 256]> linear_43_cast_fp16 = linear(bias = generator_resblocks_5_adain2_0_fc_bias_to_fp16, weight = generator_resblocks_5_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_43_cast_fp16")];
            tensor<int32, [3]> var_1740 = const()[name = string("op_1740"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_175_cast_fp16 = reshape(shape = var_1740, x = linear_43_cast_fp16)[name = string("h_175_cast_fp16")];
            tensor<int32, [2]> var_1742_split_sizes_0 = const()[name = string("op_1742_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1742_axis_0 = const()[name = string("op_1742_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1742_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1742_cast_fp16_1 = split(axis = var_1742_axis_0, split_sizes = var_1742_split_sizes_0, x = h_175_cast_fp16)[name = string("op_1742_cast_fp16")];
            fp16 var_1744_promoted_to_fp16 = const()[name = string("op_1744_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1745_cast_fp16 = add(x = var_1742_cast_fp16_0, y = var_1744_promoted_to_fp16)[name = string("op_1745_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1746_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_171_cast_fp16)[name = string("op_1746_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1747_cast_fp16 = mul(x = var_1745_cast_fp16, y = var_1746_cast_fp16)[name = string("op_1747_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_129_cast_fp16 = add(x = var_1747_cast_fp16, y = var_1742_cast_fp16_1)[name = string("xt_129_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_5_alpha2_0_to_fp16 = const()[name = string("generator_resblocks_5_alpha2_0_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36219712)))];
            tensor<fp16, [1, 128, ?]> var_1752_cast_fp16 = mul(x = generator_resblocks_5_alpha2_0_to_fp16, y = xt_129_cast_fp16)[name = string("op_1752_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1753_cast_fp16 = sin(x = var_1752_cast_fp16)[name = string("op_1753_cast_fp16")];
            fp16 var_24_promoted_45_to_fp16 = const()[name = string("op_24_promoted_45_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1754_cast_fp16 = pow(x = var_1753_cast_fp16, y = var_24_promoted_45_to_fp16)[name = string("op_1754_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1749_to_fp16 = const()[name = string("op_1749_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36220032)))];
            tensor<fp16, [1, 128, ?]> var_1755_cast_fp16 = mul(x = var_1749_to_fp16, y = var_1754_cast_fp16)[name = string("op_1755_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_173_cast_fp16 = add(x = xt_129_cast_fp16, y = var_1755_cast_fp16)[name = string("input_173_cast_fp16")];
            string xt_131_pad_type_0 = const()[name = string("xt_131_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_131_pad_0 = const()[name = string("xt_131_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_131_strides_0 = const()[name = string("xt_131_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_131_dilations_0 = const()[name = string("xt_131_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_131_groups_0 = const()[name = string("xt_131_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 11]> generator_resblocks_5_convs2_0_weight_to_fp16 = const()[name = string("generator_resblocks_5_convs2_0_weight_to_fp16"), val = tensor<fp16, [128, 128, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36220352)))];
            tensor<fp16, [128]> generator_resblocks_5_convs2_0_bias_to_fp16 = const()[name = string("generator_resblocks_5_convs2_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36580864)))];
            tensor<fp16, [1, 128, ?]> xt_131_cast_fp16 = conv(bias = generator_resblocks_5_convs2_0_bias_to_fp16, dilations = xt_131_dilations_0, groups = xt_131_groups_0, pad = xt_131_pad_0, pad_type = xt_131_pad_type_0, strides = xt_131_strides_0, weight = generator_resblocks_5_convs2_0_weight_to_fp16, x = input_173_cast_fp16)[name = string("xt_131_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_175_cast_fp16 = add(x = xt_131_cast_fp16, y = input_123_cast_fp16)[name = string("input_175_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_5_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_5_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36581184)))];
            tensor<fp16, [256]> generator_resblocks_5_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_5_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36646784)))];
            tensor<fp16, [1, 256]> linear_44_cast_fp16 = linear(bias = generator_resblocks_5_adain1_1_fc_bias_to_fp16, weight = generator_resblocks_5_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_44_cast_fp16")];
            tensor<int32, [3]> var_1771 = const()[name = string("op_1771"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_179_cast_fp16 = reshape(shape = var_1771, x = linear_44_cast_fp16)[name = string("h_179_cast_fp16")];
            tensor<int32, [2]> var_1773_split_sizes_0 = const()[name = string("op_1773_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1773_axis_0 = const()[name = string("op_1773_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1773_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1773_cast_fp16_1 = split(axis = var_1773_axis_0, split_sizes = var_1773_split_sizes_0, x = h_179_cast_fp16)[name = string("op_1773_cast_fp16")];
            fp16 var_1775_promoted_to_fp16 = const()[name = string("op_1775_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1776_cast_fp16 = add(x = var_1773_cast_fp16_0, y = var_1775_promoted_to_fp16)[name = string("op_1776_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1777_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_175_cast_fp16)[name = string("op_1777_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1778_cast_fp16 = mul(x = var_1776_cast_fp16, y = var_1777_cast_fp16)[name = string("op_1778_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_133_cast_fp16 = add(x = var_1778_cast_fp16, y = var_1773_cast_fp16_1)[name = string("xt_133_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_5_alpha1_1_to_fp16 = const()[name = string("generator_resblocks_5_alpha1_1_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36647360)))];
            tensor<fp16, [1, 128, ?]> var_1783_cast_fp16 = mul(x = generator_resblocks_5_alpha1_1_to_fp16, y = xt_133_cast_fp16)[name = string("op_1783_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1784_cast_fp16 = sin(x = var_1783_cast_fp16)[name = string("op_1784_cast_fp16")];
            fp16 var_24_promoted_46_to_fp16 = const()[name = string("op_24_promoted_46_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1785_cast_fp16 = pow(x = var_1784_cast_fp16, y = var_24_promoted_46_to_fp16)[name = string("op_1785_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1780_to_fp16 = const()[name = string("op_1780_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36647680)))];
            tensor<fp16, [1, 128, ?]> var_1786_cast_fp16 = mul(x = var_1780_to_fp16, y = var_1785_cast_fp16)[name = string("op_1786_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_177_cast_fp16 = add(x = xt_133_cast_fp16, y = var_1786_cast_fp16)[name = string("input_177_cast_fp16")];
            string input_179_pad_type_0 = const()[name = string("input_179_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_179_pad_0 = const()[name = string("input_179_pad_0"), val = tensor<int32, [2]>([15, 15])];
            tensor<int32, [1]> input_179_dilations_0 = const()[name = string("input_179_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_179_strides_0 = const()[name = string("input_179_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_179_groups_0 = const()[name = string("input_179_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 11]> generator_resblocks_5_convs1_1_weight_to_fp16 = const()[name = string("generator_resblocks_5_convs1_1_weight_to_fp16"), val = tensor<fp16, [128, 128, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36648000)))];
            tensor<fp16, [128]> generator_resblocks_5_convs1_1_bias_to_fp16 = const()[name = string("generator_resblocks_5_convs1_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37008512)))];
            tensor<fp16, [1, 128, ?]> input_179_cast_fp16 = conv(bias = generator_resblocks_5_convs1_1_bias_to_fp16, dilations = input_179_dilations_0, groups = input_179_groups_0, pad = input_179_pad_0, pad_type = input_179_pad_type_0, strides = input_179_strides_0, weight = generator_resblocks_5_convs1_1_weight_to_fp16, x = input_177_cast_fp16)[name = string("input_179_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_5_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_5_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37008832)))];
            tensor<fp16, [256]> generator_resblocks_5_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_5_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37074432)))];
            tensor<fp16, [1, 256]> linear_45_cast_fp16 = linear(bias = generator_resblocks_5_adain2_1_fc_bias_to_fp16, weight = generator_resblocks_5_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_45_cast_fp16")];
            tensor<int32, [3]> var_1801 = const()[name = string("op_1801"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_183_cast_fp16 = reshape(shape = var_1801, x = linear_45_cast_fp16)[name = string("h_183_cast_fp16")];
            tensor<int32, [2]> var_1803_split_sizes_0 = const()[name = string("op_1803_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1803_axis_0 = const()[name = string("op_1803_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1803_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1803_cast_fp16_1 = split(axis = var_1803_axis_0, split_sizes = var_1803_split_sizes_0, x = h_183_cast_fp16)[name = string("op_1803_cast_fp16")];
            fp16 var_1805_promoted_to_fp16 = const()[name = string("op_1805_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1806_cast_fp16 = add(x = var_1803_cast_fp16_0, y = var_1805_promoted_to_fp16)[name = string("op_1806_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1807_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_179_cast_fp16)[name = string("op_1807_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1808_cast_fp16 = mul(x = var_1806_cast_fp16, y = var_1807_cast_fp16)[name = string("op_1808_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_135_cast_fp16 = add(x = var_1808_cast_fp16, y = var_1803_cast_fp16_1)[name = string("xt_135_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_5_alpha2_1_to_fp16 = const()[name = string("generator_resblocks_5_alpha2_1_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37075008)))];
            tensor<fp16, [1, 128, ?]> var_1813_cast_fp16 = mul(x = generator_resblocks_5_alpha2_1_to_fp16, y = xt_135_cast_fp16)[name = string("op_1813_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1814_cast_fp16 = sin(x = var_1813_cast_fp16)[name = string("op_1814_cast_fp16")];
            fp16 var_24_promoted_47_to_fp16 = const()[name = string("op_24_promoted_47_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1815_cast_fp16 = pow(x = var_1814_cast_fp16, y = var_24_promoted_47_to_fp16)[name = string("op_1815_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1810_to_fp16 = const()[name = string("op_1810_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37075328)))];
            tensor<fp16, [1, 128, ?]> var_1816_cast_fp16 = mul(x = var_1810_to_fp16, y = var_1815_cast_fp16)[name = string("op_1816_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_181_cast_fp16 = add(x = xt_135_cast_fp16, y = var_1816_cast_fp16)[name = string("input_181_cast_fp16")];
            string xt_137_pad_type_0 = const()[name = string("xt_137_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_137_pad_0 = const()[name = string("xt_137_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_137_strides_0 = const()[name = string("xt_137_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_137_dilations_0 = const()[name = string("xt_137_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_137_groups_0 = const()[name = string("xt_137_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 11]> generator_resblocks_5_convs2_1_weight_to_fp16 = const()[name = string("generator_resblocks_5_convs2_1_weight_to_fp16"), val = tensor<fp16, [128, 128, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37075648)))];
            tensor<fp16, [128]> generator_resblocks_5_convs2_1_bias_to_fp16 = const()[name = string("generator_resblocks_5_convs2_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37436160)))];
            tensor<fp16, [1, 128, ?]> xt_137_cast_fp16 = conv(bias = generator_resblocks_5_convs2_1_bias_to_fp16, dilations = xt_137_dilations_0, groups = xt_137_groups_0, pad = xt_137_pad_0, pad_type = xt_137_pad_type_0, strides = xt_137_strides_0, weight = generator_resblocks_5_convs2_1_weight_to_fp16, x = input_181_cast_fp16)[name = string("xt_137_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_183_cast_fp16 = add(x = xt_137_cast_fp16, y = input_175_cast_fp16)[name = string("input_183_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_5_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_5_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37436480)))];
            tensor<fp16, [256]> generator_resblocks_5_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_5_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37502080)))];
            tensor<fp16, [1, 256]> linear_46_cast_fp16 = linear(bias = generator_resblocks_5_adain1_2_fc_bias_to_fp16, weight = generator_resblocks_5_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_46_cast_fp16")];
            tensor<int32, [3]> var_1832 = const()[name = string("op_1832"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_187_cast_fp16 = reshape(shape = var_1832, x = linear_46_cast_fp16)[name = string("h_187_cast_fp16")];
            tensor<int32, [2]> var_1834_split_sizes_0 = const()[name = string("op_1834_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1834_axis_0 = const()[name = string("op_1834_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1834_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1834_cast_fp16_1 = split(axis = var_1834_axis_0, split_sizes = var_1834_split_sizes_0, x = h_187_cast_fp16)[name = string("op_1834_cast_fp16")];
            fp16 var_1836_promoted_to_fp16 = const()[name = string("op_1836_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1837_cast_fp16 = add(x = var_1834_cast_fp16_0, y = var_1836_promoted_to_fp16)[name = string("op_1837_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1838_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_183_cast_fp16)[name = string("op_1838_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1839_cast_fp16 = mul(x = var_1837_cast_fp16, y = var_1838_cast_fp16)[name = string("op_1839_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_139_cast_fp16 = add(x = var_1839_cast_fp16, y = var_1834_cast_fp16_1)[name = string("xt_139_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_5_alpha1_2_to_fp16 = const()[name = string("generator_resblocks_5_alpha1_2_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37502656)))];
            tensor<fp16, [1, 128, ?]> var_1844_cast_fp16 = mul(x = generator_resblocks_5_alpha1_2_to_fp16, y = xt_139_cast_fp16)[name = string("op_1844_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1845_cast_fp16 = sin(x = var_1844_cast_fp16)[name = string("op_1845_cast_fp16")];
            fp16 var_24_promoted_48_to_fp16 = const()[name = string("op_24_promoted_48_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1846_cast_fp16 = pow(x = var_1845_cast_fp16, y = var_24_promoted_48_to_fp16)[name = string("op_1846_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1841_to_fp16 = const()[name = string("op_1841_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37502976)))];
            tensor<fp16, [1, 128, ?]> var_1847_cast_fp16 = mul(x = var_1841_to_fp16, y = var_1846_cast_fp16)[name = string("op_1847_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_185_cast_fp16 = add(x = xt_139_cast_fp16, y = var_1847_cast_fp16)[name = string("input_185_cast_fp16")];
            string input_187_pad_type_0 = const()[name = string("input_187_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_187_pad_0 = const()[name = string("input_187_pad_0"), val = tensor<int32, [2]>([25, 25])];
            tensor<int32, [1]> input_187_dilations_0 = const()[name = string("input_187_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_187_strides_0 = const()[name = string("input_187_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_187_groups_0 = const()[name = string("input_187_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 11]> generator_resblocks_5_convs1_2_weight_to_fp16 = const()[name = string("generator_resblocks_5_convs1_2_weight_to_fp16"), val = tensor<fp16, [128, 128, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37503296)))];
            tensor<fp16, [128]> generator_resblocks_5_convs1_2_bias_to_fp16 = const()[name = string("generator_resblocks_5_convs1_2_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37863808)))];
            tensor<fp16, [1, 128, ?]> input_187_cast_fp16 = conv(bias = generator_resblocks_5_convs1_2_bias_to_fp16, dilations = input_187_dilations_0, groups = input_187_groups_0, pad = input_187_pad_0, pad_type = input_187_pad_type_0, strides = input_187_strides_0, weight = generator_resblocks_5_convs1_2_weight_to_fp16, x = input_185_cast_fp16)[name = string("input_187_cast_fp16")];
            tensor<fp16, [256, 128]> generator_resblocks_5_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_5_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37864128)))];
            tensor<fp16, [256]> generator_resblocks_5_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_5_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37929728)))];
            tensor<fp16, [1, 256]> linear_47_cast_fp16 = linear(bias = generator_resblocks_5_adain2_2_fc_bias_to_fp16, weight = generator_resblocks_5_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_47_cast_fp16")];
            tensor<int32, [3]> var_1862 = const()[name = string("op_1862"), val = tensor<int32, [3]>([1, 256, 1])];
            tensor<fp16, [1, 256, 1]> h_191_cast_fp16 = reshape(shape = var_1862, x = linear_47_cast_fp16)[name = string("h_191_cast_fp16")];
            tensor<int32, [2]> var_1864_split_sizes_0 = const()[name = string("op_1864_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 var_1864_axis_0 = const()[name = string("op_1864_axis_0"), val = int32(1)];
            tensor<fp16, [1, 128, 1]> var_1864_cast_fp16_0, tensor<fp16, [1, 128, 1]> var_1864_cast_fp16_1 = split(axis = var_1864_axis_0, split_sizes = var_1864_split_sizes_0, x = h_191_cast_fp16)[name = string("op_1864_cast_fp16")];
            fp16 var_1866_promoted_to_fp16 = const()[name = string("op_1866_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 128, 1]> var_1867_cast_fp16 = add(x = var_1864_cast_fp16_0, y = var_1866_promoted_to_fp16)[name = string("op_1867_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1868_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_187_cast_fp16)[name = string("op_1868_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1869_cast_fp16 = mul(x = var_1867_cast_fp16, y = var_1868_cast_fp16)[name = string("op_1869_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xt_141_cast_fp16 = add(x = var_1869_cast_fp16, y = var_1864_cast_fp16_1)[name = string("xt_141_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_resblocks_5_alpha2_2_to_fp16 = const()[name = string("generator_resblocks_5_alpha2_2_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37930304)))];
            tensor<fp16, [1, 128, ?]> var_1874_cast_fp16 = mul(x = generator_resblocks_5_alpha2_2_to_fp16, y = xt_141_cast_fp16)[name = string("op_1874_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1875_cast_fp16 = sin(x = var_1874_cast_fp16)[name = string("op_1875_cast_fp16")];
            fp16 var_24_promoted_49_to_fp16 = const()[name = string("op_24_promoted_49_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1876_cast_fp16 = pow(x = var_1875_cast_fp16, y = var_24_promoted_49_to_fp16)[name = string("op_1876_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1871_to_fp16 = const()[name = string("op_1871_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37930624)))];
            tensor<fp16, [1, 128, ?]> var_1877_cast_fp16 = mul(x = var_1871_to_fp16, y = var_1876_cast_fp16)[name = string("op_1877_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_189_cast_fp16 = add(x = xt_141_cast_fp16, y = var_1877_cast_fp16)[name = string("input_189_cast_fp16")];
            string xt_143_pad_type_0 = const()[name = string("xt_143_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_143_pad_0 = const()[name = string("xt_143_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_143_strides_0 = const()[name = string("xt_143_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_143_dilations_0 = const()[name = string("xt_143_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_143_groups_0 = const()[name = string("xt_143_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 11]> generator_resblocks_5_convs2_2_weight_to_fp16 = const()[name = string("generator_resblocks_5_convs2_2_weight_to_fp16"), val = tensor<fp16, [128, 128, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37930944)))];
            tensor<fp16, [128]> generator_resblocks_5_convs2_2_bias_to_fp16 = const()[name = string("generator_resblocks_5_convs2_2_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38291456)))];
            tensor<fp16, [1, 128, ?]> xt_143_cast_fp16 = conv(bias = generator_resblocks_5_convs2_2_bias_to_fp16, dilations = xt_143_dilations_0, groups = xt_143_groups_0, pad = xt_143_pad_0, pad_type = xt_143_pad_type_0, strides = xt_143_strides_0, weight = generator_resblocks_5_convs2_2_weight_to_fp16, x = input_189_cast_fp16)[name = string("xt_143_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1886_cast_fp16 = add(x = xt_143_cast_fp16, y = input_183_cast_fp16)[name = string("op_1886_cast_fp16")];
            tensor<fp16, [1, 128, ?]> xs_11_cast_fp16 = add(x = xs_9_cast_fp16, y = var_1886_cast_fp16)[name = string("xs_11_cast_fp16")];
            fp16 _inversed_x_7_y_0_to_fp16 = const()[name = string("_inversed_x_7_y_0_to_fp16"), val = fp16(0x1.554p-2)];
            tensor<fp16, [1, 128, ?]> _inversed_x_7_cast_fp16 = mul(x = xs_11_cast_fp16, y = _inversed_x_7_y_0_to_fp16)[name = string("_inversed_x_7_cast_fp16")];
            tensor<fp16, [1, 128, 1]> generator_alphas_2_to_fp16 = const()[name = string("generator_alphas_2_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38291776)))];
            tensor<fp16, [1, 128, ?]> var_1893_cast_fp16 = mul(x = generator_alphas_2_to_fp16, y = _inversed_x_7_cast_fp16)[name = string("op_1893_cast_fp16")];
            tensor<fp16, [1, 128, ?]> var_1894_cast_fp16 = sin(x = var_1893_cast_fp16)[name = string("op_1894_cast_fp16")];
            fp16 var_24_promoted_50_to_fp16 = const()[name = string("op_24_promoted_50_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, ?]> var_1895_cast_fp16 = pow(x = var_1894_cast_fp16, y = var_24_promoted_50_to_fp16)[name = string("op_1895_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_1890_to_fp16 = const()[name = string("op_1890_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38292096)))];
            tensor<fp16, [1, 128, ?]> var_1896_cast_fp16 = mul(x = var_1890_to_fp16, y = var_1895_cast_fp16)[name = string("op_1896_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_215_cast_fp16 = add(x = _inversed_x_7_cast_fp16, y = var_1896_cast_fp16)[name = string("input_215_cast_fp16")];
            string input_191_pad_type_0 = const()[name = string("input_191_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_191_pad_0 = const()[name = string("input_191_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> input_191_strides_0 = const()[name = string("input_191_strides_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> input_191_dilations_0 = const()[name = string("input_191_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_191_groups_0 = const()[name = string("input_191_groups_0"), val = int32(1)];
            tensor<fp16, [64, 1, 4]> generator_noise_convs_2_weight_to_fp16 = const()[name = string("generator_noise_convs_2_weight_to_fp16"), val = tensor<fp16, [64, 1, 4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38292416)))];
            tensor<fp16, [64]> generator_noise_convs_2_bias_to_fp16 = const()[name = string("generator_noise_convs_2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38292992)))];
            tensor<fp16, [1, 64, ?]> input_191_cast_fp16 = conv(bias = generator_noise_convs_2_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 = generator_noise_convs_2_weight_to_fp16, x = har_source_to_fp16)[name = string("input_191_cast_fp16")];
            tensor<fp16, [128, 128]> generator_noise_res_2_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_noise_res_2_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38293184)))];
            tensor<fp16, [128]> generator_noise_res_2_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_noise_res_2_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38326016)))];
            tensor<fp16, [1, 128]> linear_48_cast_fp16 = linear(bias = generator_noise_res_2_adain1_0_fc_bias_to_fp16, weight = generator_noise_res_2_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_48_cast_fp16")];
            tensor<int32, [3]> var_1947 = const()[name = string("op_1947"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_195_cast_fp16 = reshape(shape = var_1947, x = linear_48_cast_fp16)[name = string("h_195_cast_fp16")];
            tensor<int32, [2]> var_1949_split_sizes_0 = const()[name = string("op_1949_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_1949_axis_0 = const()[name = string("op_1949_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_1949_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_1949_cast_fp16_1 = split(axis = var_1949_axis_0, split_sizes = var_1949_split_sizes_0, x = h_195_cast_fp16)[name = string("op_1949_cast_fp16")];
            fp16 var_1951_promoted_to_fp16 = const()[name = string("op_1951_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_1952_cast_fp16 = add(x = var_1949_cast_fp16_0, y = var_1951_promoted_to_fp16)[name = string("op_1952_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_1953_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_191_cast_fp16)[name = string("op_1953_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_1954_cast_fp16 = mul(x = var_1952_cast_fp16, y = var_1953_cast_fp16)[name = string("op_1954_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_145_cast_fp16 = add(x = var_1954_cast_fp16, y = var_1949_cast_fp16_1)[name = string("xt_145_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_noise_res_2_alpha1_0_to_fp16 = const()[name = string("generator_noise_res_2_alpha1_0_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38326336)))];
            tensor<fp16, [1, 64, ?]> var_1959_cast_fp16 = mul(x = generator_noise_res_2_alpha1_0_to_fp16, y = xt_145_cast_fp16)[name = string("op_1959_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_1960_cast_fp16 = sin(x = var_1959_cast_fp16)[name = string("op_1960_cast_fp16")];
            fp16 var_24_promoted_51_to_fp16 = const()[name = string("op_24_promoted_51_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_1961_cast_fp16 = pow(x = var_1960_cast_fp16, y = var_24_promoted_51_to_fp16)[name = string("op_1961_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_1956_to_fp16 = const()[name = string("op_1956_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38326528)))];
            tensor<fp16, [1, 64, ?]> var_1962_cast_fp16 = mul(x = var_1956_to_fp16, y = var_1961_cast_fp16)[name = string("op_1962_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_193_cast_fp16 = add(x = xt_145_cast_fp16, y = var_1962_cast_fp16)[name = string("input_193_cast_fp16")];
            string input_195_pad_type_0 = const()[name = string("input_195_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_195_pad_0 = const()[name = string("input_195_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> input_195_strides_0 = const()[name = string("input_195_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_195_dilations_0 = const()[name = string("input_195_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_195_groups_0 = const()[name = string("input_195_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 7]> generator_noise_res_2_convs1_0_weight_to_fp16 = const()[name = string("generator_noise_res_2_convs1_0_weight_to_fp16"), val = tensor<fp16, [64, 64, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38326720)))];
            tensor<fp16, [64]> generator_noise_res_2_convs1_0_bias_to_fp16 = const()[name = string("generator_noise_res_2_convs1_0_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38384128)))];
            tensor<fp16, [1, 64, ?]> input_195_cast_fp16 = conv(bias = generator_noise_res_2_convs1_0_bias_to_fp16, dilations = input_195_dilations_0, groups = input_195_groups_0, pad = input_195_pad_0, pad_type = input_195_pad_type_0, strides = input_195_strides_0, weight = generator_noise_res_2_convs1_0_weight_to_fp16, x = input_193_cast_fp16)[name = string("input_195_cast_fp16")];
            tensor<fp16, [128, 128]> generator_noise_res_2_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_noise_res_2_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38384320)))];
            tensor<fp16, [128]> generator_noise_res_2_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_noise_res_2_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38417152)))];
            tensor<fp16, [1, 128]> linear_49_cast_fp16 = linear(bias = generator_noise_res_2_adain2_0_fc_bias_to_fp16, weight = generator_noise_res_2_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_49_cast_fp16")];
            tensor<int32, [3]> var_1977 = const()[name = string("op_1977"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_199_cast_fp16 = reshape(shape = var_1977, x = linear_49_cast_fp16)[name = string("h_199_cast_fp16")];
            tensor<int32, [2]> var_1979_split_sizes_0 = const()[name = string("op_1979_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_1979_axis_0 = const()[name = string("op_1979_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_1979_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_1979_cast_fp16_1 = split(axis = var_1979_axis_0, split_sizes = var_1979_split_sizes_0, x = h_199_cast_fp16)[name = string("op_1979_cast_fp16")];
            fp16 var_1981_promoted_to_fp16 = const()[name = string("op_1981_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_1982_cast_fp16 = add(x = var_1979_cast_fp16_0, y = var_1981_promoted_to_fp16)[name = string("op_1982_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_1983_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_195_cast_fp16)[name = string("op_1983_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_1984_cast_fp16 = mul(x = var_1982_cast_fp16, y = var_1983_cast_fp16)[name = string("op_1984_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_147_cast_fp16 = add(x = var_1984_cast_fp16, y = var_1979_cast_fp16_1)[name = string("xt_147_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_noise_res_2_alpha2_0_to_fp16 = const()[name = string("generator_noise_res_2_alpha2_0_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38417472)))];
            tensor<fp16, [1, 64, ?]> var_1989_cast_fp16 = mul(x = generator_noise_res_2_alpha2_0_to_fp16, y = xt_147_cast_fp16)[name = string("op_1989_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_1990_cast_fp16 = sin(x = var_1989_cast_fp16)[name = string("op_1990_cast_fp16")];
            fp16 var_24_promoted_52_to_fp16 = const()[name = string("op_24_promoted_52_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_1991_cast_fp16 = pow(x = var_1990_cast_fp16, y = var_24_promoted_52_to_fp16)[name = string("op_1991_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_1986_to_fp16 = const()[name = string("op_1986_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38417664)))];
            tensor<fp16, [1, 64, ?]> var_1992_cast_fp16 = mul(x = var_1986_to_fp16, y = var_1991_cast_fp16)[name = string("op_1992_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_197_cast_fp16 = add(x = xt_147_cast_fp16, y = var_1992_cast_fp16)[name = string("input_197_cast_fp16")];
            string xt_149_pad_type_0 = const()[name = string("xt_149_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_149_pad_0 = const()[name = string("xt_149_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_149_strides_0 = const()[name = string("xt_149_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_149_dilations_0 = const()[name = string("xt_149_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_149_groups_0 = const()[name = string("xt_149_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 7]> generator_noise_res_2_convs2_0_weight_to_fp16 = const()[name = string("generator_noise_res_2_convs2_0_weight_to_fp16"), val = tensor<fp16, [64, 64, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38417856)))];
            tensor<fp16, [64]> generator_noise_res_2_convs2_0_bias_to_fp16 = const()[name = string("generator_noise_res_2_convs2_0_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38475264)))];
            tensor<fp16, [1, 64, ?]> xt_149_cast_fp16 = conv(bias = generator_noise_res_2_convs2_0_bias_to_fp16, dilations = xt_149_dilations_0, groups = xt_149_groups_0, pad = xt_149_pad_0, pad_type = xt_149_pad_type_0, strides = xt_149_strides_0, weight = generator_noise_res_2_convs2_0_weight_to_fp16, x = input_197_cast_fp16)[name = string("xt_149_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_199_cast_fp16 = add(x = xt_149_cast_fp16, y = input_191_cast_fp16)[name = string("input_199_cast_fp16")];
            tensor<fp16, [128, 128]> generator_noise_res_2_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_noise_res_2_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38475456)))];
            tensor<fp16, [128]> generator_noise_res_2_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_noise_res_2_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38508288)))];
            tensor<fp16, [1, 128]> linear_50_cast_fp16 = linear(bias = generator_noise_res_2_adain1_1_fc_bias_to_fp16, weight = generator_noise_res_2_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_50_cast_fp16")];
            tensor<int32, [3]> var_2008 = const()[name = string("op_2008"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_203_cast_fp16 = reshape(shape = var_2008, x = linear_50_cast_fp16)[name = string("h_203_cast_fp16")];
            tensor<int32, [2]> var_2010_split_sizes_0 = const()[name = string("op_2010_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2010_axis_0 = const()[name = string("op_2010_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2010_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2010_cast_fp16_1 = split(axis = var_2010_axis_0, split_sizes = var_2010_split_sizes_0, x = h_203_cast_fp16)[name = string("op_2010_cast_fp16")];
            fp16 var_2012_promoted_to_fp16 = const()[name = string("op_2012_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2013_cast_fp16 = add(x = var_2010_cast_fp16_0, y = var_2012_promoted_to_fp16)[name = string("op_2013_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2014_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_199_cast_fp16)[name = string("op_2014_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2015_cast_fp16 = mul(x = var_2013_cast_fp16, y = var_2014_cast_fp16)[name = string("op_2015_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_151_cast_fp16 = add(x = var_2015_cast_fp16, y = var_2010_cast_fp16_1)[name = string("xt_151_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_noise_res_2_alpha1_1_to_fp16 = const()[name = string("generator_noise_res_2_alpha1_1_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38508608)))];
            tensor<fp16, [1, 64, ?]> var_2020_cast_fp16 = mul(x = generator_noise_res_2_alpha1_1_to_fp16, y = xt_151_cast_fp16)[name = string("op_2020_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2021_cast_fp16 = sin(x = var_2020_cast_fp16)[name = string("op_2021_cast_fp16")];
            fp16 var_24_promoted_53_to_fp16 = const()[name = string("op_24_promoted_53_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2022_cast_fp16 = pow(x = var_2021_cast_fp16, y = var_24_promoted_53_to_fp16)[name = string("op_2022_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2017_to_fp16 = const()[name = string("op_2017_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38508800)))];
            tensor<fp16, [1, 64, ?]> var_2023_cast_fp16 = mul(x = var_2017_to_fp16, y = var_2022_cast_fp16)[name = string("op_2023_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_201_cast_fp16 = add(x = xt_151_cast_fp16, y = var_2023_cast_fp16)[name = string("input_201_cast_fp16")];
            string input_203_pad_type_0 = const()[name = string("input_203_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_203_pad_0 = const()[name = string("input_203_pad_0"), val = tensor<int32, [2]>([9, 9])];
            tensor<int32, [1]> input_203_dilations_0 = const()[name = string("input_203_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_203_strides_0 = const()[name = string("input_203_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_203_groups_0 = const()[name = string("input_203_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 7]> generator_noise_res_2_convs1_1_weight_to_fp16 = const()[name = string("generator_noise_res_2_convs1_1_weight_to_fp16"), val = tensor<fp16, [64, 64, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38508992)))];
            tensor<fp16, [64]> generator_noise_res_2_convs1_1_bias_to_fp16 = const()[name = string("generator_noise_res_2_convs1_1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38566400)))];
            tensor<fp16, [1, 64, ?]> input_203_cast_fp16 = conv(bias = generator_noise_res_2_convs1_1_bias_to_fp16, dilations = input_203_dilations_0, groups = input_203_groups_0, pad = input_203_pad_0, pad_type = input_203_pad_type_0, strides = input_203_strides_0, weight = generator_noise_res_2_convs1_1_weight_to_fp16, x = input_201_cast_fp16)[name = string("input_203_cast_fp16")];
            tensor<fp16, [128, 128]> generator_noise_res_2_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_noise_res_2_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38566592)))];
            tensor<fp16, [128]> generator_noise_res_2_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_noise_res_2_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38599424)))];
            tensor<fp16, [1, 128]> linear_51_cast_fp16 = linear(bias = generator_noise_res_2_adain2_1_fc_bias_to_fp16, weight = generator_noise_res_2_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_51_cast_fp16")];
            tensor<int32, [3]> var_2038 = const()[name = string("op_2038"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_207_cast_fp16 = reshape(shape = var_2038, x = linear_51_cast_fp16)[name = string("h_207_cast_fp16")];
            tensor<int32, [2]> var_2040_split_sizes_0 = const()[name = string("op_2040_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2040_axis_0 = const()[name = string("op_2040_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2040_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2040_cast_fp16_1 = split(axis = var_2040_axis_0, split_sizes = var_2040_split_sizes_0, x = h_207_cast_fp16)[name = string("op_2040_cast_fp16")];
            fp16 var_2042_promoted_to_fp16 = const()[name = string("op_2042_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2043_cast_fp16 = add(x = var_2040_cast_fp16_0, y = var_2042_promoted_to_fp16)[name = string("op_2043_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2044_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_203_cast_fp16)[name = string("op_2044_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2045_cast_fp16 = mul(x = var_2043_cast_fp16, y = var_2044_cast_fp16)[name = string("op_2045_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_153_cast_fp16 = add(x = var_2045_cast_fp16, y = var_2040_cast_fp16_1)[name = string("xt_153_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_noise_res_2_alpha2_1_to_fp16 = const()[name = string("generator_noise_res_2_alpha2_1_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38599744)))];
            tensor<fp16, [1, 64, ?]> var_2050_cast_fp16 = mul(x = generator_noise_res_2_alpha2_1_to_fp16, y = xt_153_cast_fp16)[name = string("op_2050_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2051_cast_fp16 = sin(x = var_2050_cast_fp16)[name = string("op_2051_cast_fp16")];
            fp16 var_24_promoted_54_to_fp16 = const()[name = string("op_24_promoted_54_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2052_cast_fp16 = pow(x = var_2051_cast_fp16, y = var_24_promoted_54_to_fp16)[name = string("op_2052_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2047_to_fp16 = const()[name = string("op_2047_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38599936)))];
            tensor<fp16, [1, 64, ?]> var_2053_cast_fp16 = mul(x = var_2047_to_fp16, y = var_2052_cast_fp16)[name = string("op_2053_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_205_cast_fp16 = add(x = xt_153_cast_fp16, y = var_2053_cast_fp16)[name = string("input_205_cast_fp16")];
            string xt_155_pad_type_0 = const()[name = string("xt_155_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_155_pad_0 = const()[name = string("xt_155_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_155_strides_0 = const()[name = string("xt_155_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_155_dilations_0 = const()[name = string("xt_155_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_155_groups_0 = const()[name = string("xt_155_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 7]> generator_noise_res_2_convs2_1_weight_to_fp16 = const()[name = string("generator_noise_res_2_convs2_1_weight_to_fp16"), val = tensor<fp16, [64, 64, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38600128)))];
            tensor<fp16, [64]> generator_noise_res_2_convs2_1_bias_to_fp16 = const()[name = string("generator_noise_res_2_convs2_1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38657536)))];
            tensor<fp16, [1, 64, ?]> xt_155_cast_fp16 = conv(bias = generator_noise_res_2_convs2_1_bias_to_fp16, dilations = xt_155_dilations_0, groups = xt_155_groups_0, pad = xt_155_pad_0, pad_type = xt_155_pad_type_0, strides = xt_155_strides_0, weight = generator_noise_res_2_convs2_1_weight_to_fp16, x = input_205_cast_fp16)[name = string("xt_155_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_207_cast_fp16 = add(x = xt_155_cast_fp16, y = input_199_cast_fp16)[name = string("input_207_cast_fp16")];
            tensor<fp16, [128, 128]> generator_noise_res_2_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_noise_res_2_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38657728)))];
            tensor<fp16, [128]> generator_noise_res_2_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_noise_res_2_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38690560)))];
            tensor<fp16, [1, 128]> linear_52_cast_fp16 = linear(bias = generator_noise_res_2_adain1_2_fc_bias_to_fp16, weight = generator_noise_res_2_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_52_cast_fp16")];
            tensor<int32, [3]> var_2069 = const()[name = string("op_2069"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_211_cast_fp16 = reshape(shape = var_2069, x = linear_52_cast_fp16)[name = string("h_211_cast_fp16")];
            tensor<int32, [2]> var_2071_split_sizes_0 = const()[name = string("op_2071_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2071_axis_0 = const()[name = string("op_2071_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2071_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2071_cast_fp16_1 = split(axis = var_2071_axis_0, split_sizes = var_2071_split_sizes_0, x = h_211_cast_fp16)[name = string("op_2071_cast_fp16")];
            fp16 var_2073_promoted_to_fp16 = const()[name = string("op_2073_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2074_cast_fp16 = add(x = var_2071_cast_fp16_0, y = var_2073_promoted_to_fp16)[name = string("op_2074_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2075_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_207_cast_fp16)[name = string("op_2075_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2076_cast_fp16 = mul(x = var_2074_cast_fp16, y = var_2075_cast_fp16)[name = string("op_2076_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_157_cast_fp16 = add(x = var_2076_cast_fp16, y = var_2071_cast_fp16_1)[name = string("xt_157_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_noise_res_2_alpha1_2_to_fp16 = const()[name = string("generator_noise_res_2_alpha1_2_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38690880)))];
            tensor<fp16, [1, 64, ?]> var_2081_cast_fp16 = mul(x = generator_noise_res_2_alpha1_2_to_fp16, y = xt_157_cast_fp16)[name = string("op_2081_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2082_cast_fp16 = sin(x = var_2081_cast_fp16)[name = string("op_2082_cast_fp16")];
            fp16 var_24_promoted_55_to_fp16 = const()[name = string("op_24_promoted_55_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2083_cast_fp16 = pow(x = var_2082_cast_fp16, y = var_24_promoted_55_to_fp16)[name = string("op_2083_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2078_to_fp16 = const()[name = string("op_2078_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38691072)))];
            tensor<fp16, [1, 64, ?]> var_2084_cast_fp16 = mul(x = var_2078_to_fp16, y = var_2083_cast_fp16)[name = string("op_2084_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_209_cast_fp16 = add(x = xt_157_cast_fp16, y = var_2084_cast_fp16)[name = string("input_209_cast_fp16")];
            string input_211_pad_type_0 = const()[name = string("input_211_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_211_pad_0 = const()[name = string("input_211_pad_0"), val = tensor<int32, [2]>([15, 15])];
            tensor<int32, [1]> input_211_dilations_0 = const()[name = string("input_211_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_211_strides_0 = const()[name = string("input_211_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_211_groups_0 = const()[name = string("input_211_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 7]> generator_noise_res_2_convs1_2_weight_to_fp16 = const()[name = string("generator_noise_res_2_convs1_2_weight_to_fp16"), val = tensor<fp16, [64, 64, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38691264)))];
            tensor<fp16, [64]> generator_noise_res_2_convs1_2_bias_to_fp16 = const()[name = string("generator_noise_res_2_convs1_2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38748672)))];
            tensor<fp16, [1, 64, ?]> input_211_cast_fp16 = conv(bias = generator_noise_res_2_convs1_2_bias_to_fp16, dilations = input_211_dilations_0, groups = input_211_groups_0, pad = input_211_pad_0, pad_type = input_211_pad_type_0, strides = input_211_strides_0, weight = generator_noise_res_2_convs1_2_weight_to_fp16, x = input_209_cast_fp16)[name = string("input_211_cast_fp16")];
            tensor<fp16, [128, 128]> generator_noise_res_2_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_noise_res_2_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38748864)))];
            tensor<fp16, [128]> generator_noise_res_2_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_noise_res_2_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38781696)))];
            tensor<fp16, [1, 128]> linear_53_cast_fp16 = linear(bias = generator_noise_res_2_adain2_2_fc_bias_to_fp16, weight = generator_noise_res_2_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_53_cast_fp16")];
            tensor<int32, [3]> var_2099 = const()[name = string("op_2099"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_215_cast_fp16 = reshape(shape = var_2099, x = linear_53_cast_fp16)[name = string("h_215_cast_fp16")];
            tensor<int32, [2]> var_2101_split_sizes_0 = const()[name = string("op_2101_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2101_axis_0 = const()[name = string("op_2101_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2101_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2101_cast_fp16_1 = split(axis = var_2101_axis_0, split_sizes = var_2101_split_sizes_0, x = h_215_cast_fp16)[name = string("op_2101_cast_fp16")];
            fp16 var_2103_promoted_to_fp16 = const()[name = string("op_2103_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2104_cast_fp16 = add(x = var_2101_cast_fp16_0, y = var_2103_promoted_to_fp16)[name = string("op_2104_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2105_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_211_cast_fp16)[name = string("op_2105_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2106_cast_fp16 = mul(x = var_2104_cast_fp16, y = var_2105_cast_fp16)[name = string("op_2106_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_159_cast_fp16 = add(x = var_2106_cast_fp16, y = var_2101_cast_fp16_1)[name = string("xt_159_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_noise_res_2_alpha2_2_to_fp16 = const()[name = string("generator_noise_res_2_alpha2_2_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38782016)))];
            tensor<fp16, [1, 64, ?]> var_2111_cast_fp16 = mul(x = generator_noise_res_2_alpha2_2_to_fp16, y = xt_159_cast_fp16)[name = string("op_2111_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2112_cast_fp16 = sin(x = var_2111_cast_fp16)[name = string("op_2112_cast_fp16")];
            fp16 var_24_promoted_56_to_fp16 = const()[name = string("op_24_promoted_56_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2113_cast_fp16 = pow(x = var_2112_cast_fp16, y = var_24_promoted_56_to_fp16)[name = string("op_2113_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2108_to_fp16 = const()[name = string("op_2108_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38782208)))];
            tensor<fp16, [1, 64, ?]> var_2114_cast_fp16 = mul(x = var_2108_to_fp16, y = var_2113_cast_fp16)[name = string("op_2114_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_213_cast_fp16 = add(x = xt_159_cast_fp16, y = var_2114_cast_fp16)[name = string("input_213_cast_fp16")];
            string xt_161_pad_type_0 = const()[name = string("xt_161_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_161_pad_0 = const()[name = string("xt_161_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_161_strides_0 = const()[name = string("xt_161_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_161_dilations_0 = const()[name = string("xt_161_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_161_groups_0 = const()[name = string("xt_161_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 7]> generator_noise_res_2_convs2_2_weight_to_fp16 = const()[name = string("generator_noise_res_2_convs2_2_weight_to_fp16"), val = tensor<fp16, [64, 64, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38782400)))];
            tensor<fp16, [64]> generator_noise_res_2_convs2_2_bias_to_fp16 = const()[name = string("generator_noise_res_2_convs2_2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38839808)))];
            tensor<fp16, [1, 64, ?]> xt_161_cast_fp16 = conv(bias = generator_noise_res_2_convs2_2_bias_to_fp16, dilations = xt_161_dilations_0, groups = xt_161_groups_0, pad = xt_161_pad_0, pad_type = xt_161_pad_type_0, strides = xt_161_strides_0, weight = generator_noise_res_2_convs2_2_weight_to_fp16, x = input_213_cast_fp16)[name = string("xt_161_cast_fp16")];
            tensor<fp16, [1, 64, ?]> x_source_5_cast_fp16 = add(x = xt_161_cast_fp16, y = input_207_cast_fp16)[name = string("x_source_5_cast_fp16")];
            string conv_transpose_1_pad_type_0 = const()[name = string("conv_transpose_1_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_transpose_1_pad_0 = const()[name = string("conv_transpose_1_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_transpose_1_strides_0 = const()[name = string("conv_transpose_1_strides_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> conv_transpose_1_dilations_0 = const()[name = string("conv_transpose_1_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_transpose_1_groups_0 = const()[name = string("conv_transpose_1_groups_0"), val = int32(1)];
            tensor<fp16, [128, 64, 6]> generator_ups_2_weight_to_fp16 = const()[name = string("generator_ups_2_weight_to_fp16"), val = tensor<fp16, [128, 64, 6]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38840000)))];
            tensor<fp16, [64]> generator_ups_2_bias_to_fp16 = const()[name = string("generator_ups_2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38938368)))];
            tensor<fp16, [1, 64, ?]> conv_transpose_1_cast_fp16 = conv_transpose(bias = generator_ups_2_bias_to_fp16, dilations = conv_transpose_1_dilations_0, groups = conv_transpose_1_groups_0, pad = conv_transpose_1_pad_0, pad_type = conv_transpose_1_pad_type_0, strides = conv_transpose_1_strides_0, weight = generator_ups_2_weight_to_fp16, x = input_215_cast_fp16)[name = string("conv_transpose_1_cast_fp16")];
            tensor<int32, [3]> x_9_begin_0 = const()[name = string("x_9_begin_0"), val = tensor<int32, [3]>([0, 0, 2])];
            tensor<int32, [3]> x_9_end_0 = const()[name = string("x_9_end_0"), val = tensor<int32, [3]>([0, 0, -1])];
            tensor<bool, [3]> x_9_begin_mask_0 = const()[name = string("x_9_begin_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<bool, [3]> x_9_end_mask_0 = const()[name = string("x_9_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 64, ?]> x_9_cast_fp16 = slice_by_index(begin = x_9_begin_0, begin_mask = x_9_begin_mask_0, end = x_9_end_0, end_mask = x_9_end_mask_0, x = conv_transpose_1_cast_fp16)[name = string("x_9_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_217_cast_fp16 = add(x = x_9_cast_fp16, y = x_source_5_cast_fp16)[name = string("input_217_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_6_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_6_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38938560)))];
            tensor<fp16, [128]> generator_resblocks_6_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_6_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38971392)))];
            tensor<fp16, [1, 128]> linear_54_cast_fp16 = linear(bias = generator_resblocks_6_adain1_0_fc_bias_to_fp16, weight = generator_resblocks_6_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_54_cast_fp16")];
            tensor<int32, [3]> var_2174 = const()[name = string("op_2174"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_219_cast_fp16 = reshape(shape = var_2174, x = linear_54_cast_fp16)[name = string("h_219_cast_fp16")];
            tensor<int32, [2]> var_2176_split_sizes_0 = const()[name = string("op_2176_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2176_axis_0 = const()[name = string("op_2176_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2176_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2176_cast_fp16_1 = split(axis = var_2176_axis_0, split_sizes = var_2176_split_sizes_0, x = h_219_cast_fp16)[name = string("op_2176_cast_fp16")];
            fp16 var_2178_promoted_to_fp16 = const()[name = string("op_2178_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2179_cast_fp16 = add(x = var_2176_cast_fp16_0, y = var_2178_promoted_to_fp16)[name = string("op_2179_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2180_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_217_cast_fp16)[name = string("op_2180_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2181_cast_fp16 = mul(x = var_2179_cast_fp16, y = var_2180_cast_fp16)[name = string("op_2181_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_163_cast_fp16 = add(x = var_2181_cast_fp16, y = var_2176_cast_fp16_1)[name = string("xt_163_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_6_alpha1_0_to_fp16 = const()[name = string("generator_resblocks_6_alpha1_0_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38971712)))];
            tensor<fp16, [1, 64, ?]> var_2186_cast_fp16 = mul(x = generator_resblocks_6_alpha1_0_to_fp16, y = xt_163_cast_fp16)[name = string("op_2186_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2187_cast_fp16 = sin(x = var_2186_cast_fp16)[name = string("op_2187_cast_fp16")];
            fp16 var_24_promoted_57_to_fp16 = const()[name = string("op_24_promoted_57_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2188_cast_fp16 = pow(x = var_2187_cast_fp16, y = var_24_promoted_57_to_fp16)[name = string("op_2188_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2183_to_fp16 = const()[name = string("op_2183_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38971904)))];
            tensor<fp16, [1, 64, ?]> var_2189_cast_fp16 = mul(x = var_2183_to_fp16, y = var_2188_cast_fp16)[name = string("op_2189_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_219_cast_fp16 = add(x = xt_163_cast_fp16, y = var_2189_cast_fp16)[name = string("input_219_cast_fp16")];
            string input_221_pad_type_0 = const()[name = string("input_221_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_221_pad_0 = const()[name = string("input_221_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> input_221_strides_0 = const()[name = string("input_221_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_221_dilations_0 = const()[name = string("input_221_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_221_groups_0 = const()[name = string("input_221_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3]> generator_resblocks_6_convs1_0_weight_to_fp16 = const()[name = string("generator_resblocks_6_convs1_0_weight_to_fp16"), val = tensor<fp16, [64, 64, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38972096)))];
            tensor<fp16, [64]> generator_resblocks_6_convs1_0_bias_to_fp16 = const()[name = string("generator_resblocks_6_convs1_0_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38996736)))];
            tensor<fp16, [1, 64, ?]> input_221_cast_fp16 = conv(bias = generator_resblocks_6_convs1_0_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 = generator_resblocks_6_convs1_0_weight_to_fp16, x = input_219_cast_fp16)[name = string("input_221_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_6_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_6_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38996928)))];
            tensor<fp16, [128]> generator_resblocks_6_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_6_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39029760)))];
            tensor<fp16, [1, 128]> linear_55_cast_fp16 = linear(bias = generator_resblocks_6_adain2_0_fc_bias_to_fp16, weight = generator_resblocks_6_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_55_cast_fp16")];
            tensor<int32, [3]> var_2204 = const()[name = string("op_2204"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_223_cast_fp16 = reshape(shape = var_2204, x = linear_55_cast_fp16)[name = string("h_223_cast_fp16")];
            tensor<int32, [2]> var_2206_split_sizes_0 = const()[name = string("op_2206_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2206_axis_0 = const()[name = string("op_2206_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2206_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2206_cast_fp16_1 = split(axis = var_2206_axis_0, split_sizes = var_2206_split_sizes_0, x = h_223_cast_fp16)[name = string("op_2206_cast_fp16")];
            fp16 var_2208_promoted_to_fp16 = const()[name = string("op_2208_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2209_cast_fp16 = add(x = var_2206_cast_fp16_0, y = var_2208_promoted_to_fp16)[name = string("op_2209_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2210_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_221_cast_fp16)[name = string("op_2210_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2211_cast_fp16 = mul(x = var_2209_cast_fp16, y = var_2210_cast_fp16)[name = string("op_2211_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_165_cast_fp16 = add(x = var_2211_cast_fp16, y = var_2206_cast_fp16_1)[name = string("xt_165_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_6_alpha2_0_to_fp16 = const()[name = string("generator_resblocks_6_alpha2_0_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39030080)))];
            tensor<fp16, [1, 64, ?]> var_2216_cast_fp16 = mul(x = generator_resblocks_6_alpha2_0_to_fp16, y = xt_165_cast_fp16)[name = string("op_2216_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2217_cast_fp16 = sin(x = var_2216_cast_fp16)[name = string("op_2217_cast_fp16")];
            fp16 var_24_promoted_58_to_fp16 = const()[name = string("op_24_promoted_58_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2218_cast_fp16 = pow(x = var_2217_cast_fp16, y = var_24_promoted_58_to_fp16)[name = string("op_2218_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2213_to_fp16 = const()[name = string("op_2213_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39030272)))];
            tensor<fp16, [1, 64, ?]> var_2219_cast_fp16 = mul(x = var_2213_to_fp16, y = var_2218_cast_fp16)[name = string("op_2219_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_223_cast_fp16 = add(x = xt_165_cast_fp16, y = var_2219_cast_fp16)[name = string("input_223_cast_fp16")];
            string xt_167_pad_type_0 = const()[name = string("xt_167_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_167_pad_0 = const()[name = string("xt_167_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> xt_167_strides_0 = const()[name = string("xt_167_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_167_dilations_0 = const()[name = string("xt_167_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_167_groups_0 = const()[name = string("xt_167_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3]> generator_resblocks_6_convs2_0_weight_to_fp16 = const()[name = string("generator_resblocks_6_convs2_0_weight_to_fp16"), val = tensor<fp16, [64, 64, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39030464)))];
            tensor<fp16, [64]> generator_resblocks_6_convs2_0_bias_to_fp16 = const()[name = string("generator_resblocks_6_convs2_0_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39055104)))];
            tensor<fp16, [1, 64, ?]> xt_167_cast_fp16 = conv(bias = generator_resblocks_6_convs2_0_bias_to_fp16, dilations = xt_167_dilations_0, groups = xt_167_groups_0, pad = xt_167_pad_0, pad_type = xt_167_pad_type_0, strides = xt_167_strides_0, weight = generator_resblocks_6_convs2_0_weight_to_fp16, x = input_223_cast_fp16)[name = string("xt_167_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_225_cast_fp16 = add(x = xt_167_cast_fp16, y = input_217_cast_fp16)[name = string("input_225_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_6_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_6_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39055296)))];
            tensor<fp16, [128]> generator_resblocks_6_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_6_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39088128)))];
            tensor<fp16, [1, 128]> linear_56_cast_fp16 = linear(bias = generator_resblocks_6_adain1_1_fc_bias_to_fp16, weight = generator_resblocks_6_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_56_cast_fp16")];
            tensor<int32, [3]> var_2235 = const()[name = string("op_2235"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_227_cast_fp16 = reshape(shape = var_2235, x = linear_56_cast_fp16)[name = string("h_227_cast_fp16")];
            tensor<int32, [2]> var_2237_split_sizes_0 = const()[name = string("op_2237_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2237_axis_0 = const()[name = string("op_2237_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2237_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2237_cast_fp16_1 = split(axis = var_2237_axis_0, split_sizes = var_2237_split_sizes_0, x = h_227_cast_fp16)[name = string("op_2237_cast_fp16")];
            fp16 var_2239_promoted_to_fp16 = const()[name = string("op_2239_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2240_cast_fp16 = add(x = var_2237_cast_fp16_0, y = var_2239_promoted_to_fp16)[name = string("op_2240_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2241_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_225_cast_fp16)[name = string("op_2241_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2242_cast_fp16 = mul(x = var_2240_cast_fp16, y = var_2241_cast_fp16)[name = string("op_2242_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_169_cast_fp16 = add(x = var_2242_cast_fp16, y = var_2237_cast_fp16_1)[name = string("xt_169_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_6_alpha1_1_to_fp16 = const()[name = string("generator_resblocks_6_alpha1_1_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39088448)))];
            tensor<fp16, [1, 64, ?]> var_2247_cast_fp16 = mul(x = generator_resblocks_6_alpha1_1_to_fp16, y = xt_169_cast_fp16)[name = string("op_2247_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2248_cast_fp16 = sin(x = var_2247_cast_fp16)[name = string("op_2248_cast_fp16")];
            fp16 var_24_promoted_59_to_fp16 = const()[name = string("op_24_promoted_59_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2249_cast_fp16 = pow(x = var_2248_cast_fp16, y = var_24_promoted_59_to_fp16)[name = string("op_2249_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2244_to_fp16 = const()[name = string("op_2244_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39088640)))];
            tensor<fp16, [1, 64, ?]> var_2250_cast_fp16 = mul(x = var_2244_to_fp16, y = var_2249_cast_fp16)[name = string("op_2250_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_227_cast_fp16 = add(x = xt_169_cast_fp16, y = var_2250_cast_fp16)[name = string("input_227_cast_fp16")];
            string input_229_pad_type_0 = const()[name = string("input_229_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_229_pad_0 = const()[name = string("input_229_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> input_229_dilations_0 = const()[name = string("input_229_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_229_strides_0 = const()[name = string("input_229_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_229_groups_0 = const()[name = string("input_229_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3]> generator_resblocks_6_convs1_1_weight_to_fp16 = const()[name = string("generator_resblocks_6_convs1_1_weight_to_fp16"), val = tensor<fp16, [64, 64, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39088832)))];
            tensor<fp16, [64]> generator_resblocks_6_convs1_1_bias_to_fp16 = const()[name = string("generator_resblocks_6_convs1_1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39113472)))];
            tensor<fp16, [1, 64, ?]> input_229_cast_fp16 = conv(bias = generator_resblocks_6_convs1_1_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 = generator_resblocks_6_convs1_1_weight_to_fp16, x = input_227_cast_fp16)[name = string("input_229_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_6_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_6_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39113664)))];
            tensor<fp16, [128]> generator_resblocks_6_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_6_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39146496)))];
            tensor<fp16, [1, 128]> linear_57_cast_fp16 = linear(bias = generator_resblocks_6_adain2_1_fc_bias_to_fp16, weight = generator_resblocks_6_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_57_cast_fp16")];
            tensor<int32, [3]> var_2265 = const()[name = string("op_2265"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_231_cast_fp16 = reshape(shape = var_2265, x = linear_57_cast_fp16)[name = string("h_231_cast_fp16")];
            tensor<int32, [2]> var_2267_split_sizes_0 = const()[name = string("op_2267_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2267_axis_0 = const()[name = string("op_2267_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2267_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2267_cast_fp16_1 = split(axis = var_2267_axis_0, split_sizes = var_2267_split_sizes_0, x = h_231_cast_fp16)[name = string("op_2267_cast_fp16")];
            fp16 var_2269_promoted_to_fp16 = const()[name = string("op_2269_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2270_cast_fp16 = add(x = var_2267_cast_fp16_0, y = var_2269_promoted_to_fp16)[name = string("op_2270_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2271_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_229_cast_fp16)[name = string("op_2271_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2272_cast_fp16 = mul(x = var_2270_cast_fp16, y = var_2271_cast_fp16)[name = string("op_2272_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_171_cast_fp16 = add(x = var_2272_cast_fp16, y = var_2267_cast_fp16_1)[name = string("xt_171_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_6_alpha2_1_to_fp16 = const()[name = string("generator_resblocks_6_alpha2_1_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39146816)))];
            tensor<fp16, [1, 64, ?]> var_2277_cast_fp16 = mul(x = generator_resblocks_6_alpha2_1_to_fp16, y = xt_171_cast_fp16)[name = string("op_2277_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2278_cast_fp16 = sin(x = var_2277_cast_fp16)[name = string("op_2278_cast_fp16")];
            fp16 var_24_promoted_60_to_fp16 = const()[name = string("op_24_promoted_60_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2279_cast_fp16 = pow(x = var_2278_cast_fp16, y = var_24_promoted_60_to_fp16)[name = string("op_2279_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2274_to_fp16 = const()[name = string("op_2274_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39147008)))];
            tensor<fp16, [1, 64, ?]> var_2280_cast_fp16 = mul(x = var_2274_to_fp16, y = var_2279_cast_fp16)[name = string("op_2280_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_231_cast_fp16 = add(x = xt_171_cast_fp16, y = var_2280_cast_fp16)[name = string("input_231_cast_fp16")];
            string xt_173_pad_type_0 = const()[name = string("xt_173_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_173_pad_0 = const()[name = string("xt_173_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> xt_173_strides_0 = const()[name = string("xt_173_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_173_dilations_0 = const()[name = string("xt_173_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_173_groups_0 = const()[name = string("xt_173_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3]> generator_resblocks_6_convs2_1_weight_to_fp16 = const()[name = string("generator_resblocks_6_convs2_1_weight_to_fp16"), val = tensor<fp16, [64, 64, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39147200)))];
            tensor<fp16, [64]> generator_resblocks_6_convs2_1_bias_to_fp16 = const()[name = string("generator_resblocks_6_convs2_1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39171840)))];
            tensor<fp16, [1, 64, ?]> xt_173_cast_fp16 = conv(bias = generator_resblocks_6_convs2_1_bias_to_fp16, dilations = xt_173_dilations_0, groups = xt_173_groups_0, pad = xt_173_pad_0, pad_type = xt_173_pad_type_0, strides = xt_173_strides_0, weight = generator_resblocks_6_convs2_1_weight_to_fp16, x = input_231_cast_fp16)[name = string("xt_173_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_233_cast_fp16 = add(x = xt_173_cast_fp16, y = input_225_cast_fp16)[name = string("input_233_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_6_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_6_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39172032)))];
            tensor<fp16, [128]> generator_resblocks_6_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_6_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39204864)))];
            tensor<fp16, [1, 128]> linear_58_cast_fp16 = linear(bias = generator_resblocks_6_adain1_2_fc_bias_to_fp16, weight = generator_resblocks_6_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_58_cast_fp16")];
            tensor<int32, [3]> var_2296 = const()[name = string("op_2296"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_235_cast_fp16 = reshape(shape = var_2296, x = linear_58_cast_fp16)[name = string("h_235_cast_fp16")];
            tensor<int32, [2]> var_2298_split_sizes_0 = const()[name = string("op_2298_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2298_axis_0 = const()[name = string("op_2298_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2298_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2298_cast_fp16_1 = split(axis = var_2298_axis_0, split_sizes = var_2298_split_sizes_0, x = h_235_cast_fp16)[name = string("op_2298_cast_fp16")];
            fp16 var_2300_promoted_to_fp16 = const()[name = string("op_2300_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2301_cast_fp16 = add(x = var_2298_cast_fp16_0, y = var_2300_promoted_to_fp16)[name = string("op_2301_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2302_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_233_cast_fp16)[name = string("op_2302_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2303_cast_fp16 = mul(x = var_2301_cast_fp16, y = var_2302_cast_fp16)[name = string("op_2303_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_175_cast_fp16 = add(x = var_2303_cast_fp16, y = var_2298_cast_fp16_1)[name = string("xt_175_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_6_alpha1_2_to_fp16 = const()[name = string("generator_resblocks_6_alpha1_2_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39205184)))];
            tensor<fp16, [1, 64, ?]> var_2308_cast_fp16 = mul(x = generator_resblocks_6_alpha1_2_to_fp16, y = xt_175_cast_fp16)[name = string("op_2308_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2309_cast_fp16 = sin(x = var_2308_cast_fp16)[name = string("op_2309_cast_fp16")];
            fp16 var_24_promoted_61_to_fp16 = const()[name = string("op_24_promoted_61_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2310_cast_fp16 = pow(x = var_2309_cast_fp16, y = var_24_promoted_61_to_fp16)[name = string("op_2310_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2305_to_fp16 = const()[name = string("op_2305_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39205376)))];
            tensor<fp16, [1, 64, ?]> var_2311_cast_fp16 = mul(x = var_2305_to_fp16, y = var_2310_cast_fp16)[name = string("op_2311_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_235_cast_fp16 = add(x = xt_175_cast_fp16, y = var_2311_cast_fp16)[name = string("input_235_cast_fp16")];
            string input_237_pad_type_0 = const()[name = string("input_237_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_237_pad_0 = const()[name = string("input_237_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> input_237_dilations_0 = const()[name = string("input_237_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_237_strides_0 = const()[name = string("input_237_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_237_groups_0 = const()[name = string("input_237_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3]> generator_resblocks_6_convs1_2_weight_to_fp16 = const()[name = string("generator_resblocks_6_convs1_2_weight_to_fp16"), val = tensor<fp16, [64, 64, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39205568)))];
            tensor<fp16, [64]> generator_resblocks_6_convs1_2_bias_to_fp16 = const()[name = string("generator_resblocks_6_convs1_2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39230208)))];
            tensor<fp16, [1, 64, ?]> input_237_cast_fp16 = conv(bias = generator_resblocks_6_convs1_2_bias_to_fp16, dilations = input_237_dilations_0, groups = input_237_groups_0, pad = input_237_pad_0, pad_type = input_237_pad_type_0, strides = input_237_strides_0, weight = generator_resblocks_6_convs1_2_weight_to_fp16, x = input_235_cast_fp16)[name = string("input_237_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_6_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_6_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39230400)))];
            tensor<fp16, [128]> generator_resblocks_6_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_6_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39263232)))];
            tensor<fp16, [1, 128]> linear_59_cast_fp16 = linear(bias = generator_resblocks_6_adain2_2_fc_bias_to_fp16, weight = generator_resblocks_6_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_59_cast_fp16")];
            tensor<int32, [3]> var_2326 = const()[name = string("op_2326"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_239_cast_fp16 = reshape(shape = var_2326, x = linear_59_cast_fp16)[name = string("h_239_cast_fp16")];
            tensor<int32, [2]> var_2328_split_sizes_0 = const()[name = string("op_2328_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2328_axis_0 = const()[name = string("op_2328_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2328_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2328_cast_fp16_1 = split(axis = var_2328_axis_0, split_sizes = var_2328_split_sizes_0, x = h_239_cast_fp16)[name = string("op_2328_cast_fp16")];
            fp16 var_2330_promoted_to_fp16 = const()[name = string("op_2330_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2331_cast_fp16 = add(x = var_2328_cast_fp16_0, y = var_2330_promoted_to_fp16)[name = string("op_2331_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2332_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_237_cast_fp16)[name = string("op_2332_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2333_cast_fp16 = mul(x = var_2331_cast_fp16, y = var_2332_cast_fp16)[name = string("op_2333_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_177_cast_fp16 = add(x = var_2333_cast_fp16, y = var_2328_cast_fp16_1)[name = string("xt_177_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_6_alpha2_2_to_fp16 = const()[name = string("generator_resblocks_6_alpha2_2_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39263552)))];
            tensor<fp16, [1, 64, ?]> var_2338_cast_fp16 = mul(x = generator_resblocks_6_alpha2_2_to_fp16, y = xt_177_cast_fp16)[name = string("op_2338_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2339_cast_fp16 = sin(x = var_2338_cast_fp16)[name = string("op_2339_cast_fp16")];
            fp16 var_24_promoted_62_to_fp16 = const()[name = string("op_24_promoted_62_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2340_cast_fp16 = pow(x = var_2339_cast_fp16, y = var_24_promoted_62_to_fp16)[name = string("op_2340_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2335_to_fp16 = const()[name = string("op_2335_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39263744)))];
            tensor<fp16, [1, 64, ?]> var_2341_cast_fp16 = mul(x = var_2335_to_fp16, y = var_2340_cast_fp16)[name = string("op_2341_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_239_cast_fp16 = add(x = xt_177_cast_fp16, y = var_2341_cast_fp16)[name = string("input_239_cast_fp16")];
            string xt_179_pad_type_0 = const()[name = string("xt_179_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_179_pad_0 = const()[name = string("xt_179_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> xt_179_strides_0 = const()[name = string("xt_179_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_179_dilations_0 = const()[name = string("xt_179_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_179_groups_0 = const()[name = string("xt_179_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 3]> generator_resblocks_6_convs2_2_weight_to_fp16 = const()[name = string("generator_resblocks_6_convs2_2_weight_to_fp16"), val = tensor<fp16, [64, 64, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39263936)))];
            tensor<fp16, [64]> generator_resblocks_6_convs2_2_bias_to_fp16 = const()[name = string("generator_resblocks_6_convs2_2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39288576)))];
            tensor<fp16, [1, 64, ?]> xt_179_cast_fp16 = conv(bias = generator_resblocks_6_convs2_2_bias_to_fp16, dilations = xt_179_dilations_0, groups = xt_179_groups_0, pad = xt_179_pad_0, pad_type = xt_179_pad_type_0, strides = xt_179_strides_0, weight = generator_resblocks_6_convs2_2_weight_to_fp16, x = input_239_cast_fp16)[name = string("xt_179_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xs_13_cast_fp16 = add(x = xt_179_cast_fp16, y = input_233_cast_fp16)[name = string("xs_13_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_7_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_7_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39288768)))];
            tensor<fp16, [128]> generator_resblocks_7_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_7_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39321600)))];
            tensor<fp16, [1, 128]> linear_60_cast_fp16 = linear(bias = generator_resblocks_7_adain1_0_fc_bias_to_fp16, weight = generator_resblocks_7_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_60_cast_fp16")];
            tensor<int32, [3]> var_2393 = const()[name = string("op_2393"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_243_cast_fp16 = reshape(shape = var_2393, x = linear_60_cast_fp16)[name = string("h_243_cast_fp16")];
            tensor<int32, [2]> var_2395_split_sizes_0 = const()[name = string("op_2395_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2395_axis_0 = const()[name = string("op_2395_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2395_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2395_cast_fp16_1 = split(axis = var_2395_axis_0, split_sizes = var_2395_split_sizes_0, x = h_243_cast_fp16)[name = string("op_2395_cast_fp16")];
            fp16 var_2397_promoted_to_fp16 = const()[name = string("op_2397_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2398_cast_fp16 = add(x = var_2395_cast_fp16_0, y = var_2397_promoted_to_fp16)[name = string("op_2398_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2400_cast_fp16 = mul(x = var_2398_cast_fp16, y = var_2180_cast_fp16)[name = string("op_2400_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_181_cast_fp16 = add(x = var_2400_cast_fp16, y = var_2395_cast_fp16_1)[name = string("xt_181_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_7_alpha1_0_to_fp16 = const()[name = string("generator_resblocks_7_alpha1_0_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39321920)))];
            tensor<fp16, [1, 64, ?]> var_2405_cast_fp16 = mul(x = generator_resblocks_7_alpha1_0_to_fp16, y = xt_181_cast_fp16)[name = string("op_2405_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2406_cast_fp16 = sin(x = var_2405_cast_fp16)[name = string("op_2406_cast_fp16")];
            fp16 var_24_promoted_63_to_fp16 = const()[name = string("op_24_promoted_63_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2407_cast_fp16 = pow(x = var_2406_cast_fp16, y = var_24_promoted_63_to_fp16)[name = string("op_2407_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2402_to_fp16 = const()[name = string("op_2402_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39322112)))];
            tensor<fp16, [1, 64, ?]> var_2408_cast_fp16 = mul(x = var_2402_to_fp16, y = var_2407_cast_fp16)[name = string("op_2408_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_241_cast_fp16 = add(x = xt_181_cast_fp16, y = var_2408_cast_fp16)[name = string("input_241_cast_fp16")];
            string input_243_pad_type_0 = const()[name = string("input_243_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_243_pad_0 = const()[name = string("input_243_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> input_243_strides_0 = const()[name = string("input_243_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_243_dilations_0 = const()[name = string("input_243_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_243_groups_0 = const()[name = string("input_243_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 7]> generator_resblocks_7_convs1_0_weight_to_fp16 = const()[name = string("generator_resblocks_7_convs1_0_weight_to_fp16"), val = tensor<fp16, [64, 64, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39322304)))];
            tensor<fp16, [64]> generator_resblocks_7_convs1_0_bias_to_fp16 = const()[name = string("generator_resblocks_7_convs1_0_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39379712)))];
            tensor<fp16, [1, 64, ?]> input_243_cast_fp16 = conv(bias = generator_resblocks_7_convs1_0_bias_to_fp16, dilations = input_243_dilations_0, groups = input_243_groups_0, pad = input_243_pad_0, pad_type = input_243_pad_type_0, strides = input_243_strides_0, weight = generator_resblocks_7_convs1_0_weight_to_fp16, x = input_241_cast_fp16)[name = string("input_243_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_7_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_7_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39379904)))];
            tensor<fp16, [128]> generator_resblocks_7_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_7_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39412736)))];
            tensor<fp16, [1, 128]> linear_61_cast_fp16 = linear(bias = generator_resblocks_7_adain2_0_fc_bias_to_fp16, weight = generator_resblocks_7_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_61_cast_fp16")];
            tensor<int32, [3]> var_2423 = const()[name = string("op_2423"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_247_cast_fp16 = reshape(shape = var_2423, x = linear_61_cast_fp16)[name = string("h_247_cast_fp16")];
            tensor<int32, [2]> var_2425_split_sizes_0 = const()[name = string("op_2425_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2425_axis_0 = const()[name = string("op_2425_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2425_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2425_cast_fp16_1 = split(axis = var_2425_axis_0, split_sizes = var_2425_split_sizes_0, x = h_247_cast_fp16)[name = string("op_2425_cast_fp16")];
            fp16 var_2427_promoted_to_fp16 = const()[name = string("op_2427_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2428_cast_fp16 = add(x = var_2425_cast_fp16_0, y = var_2427_promoted_to_fp16)[name = string("op_2428_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2429_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_243_cast_fp16)[name = string("op_2429_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2430_cast_fp16 = mul(x = var_2428_cast_fp16, y = var_2429_cast_fp16)[name = string("op_2430_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_183_cast_fp16 = add(x = var_2430_cast_fp16, y = var_2425_cast_fp16_1)[name = string("xt_183_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_7_alpha2_0_to_fp16 = const()[name = string("generator_resblocks_7_alpha2_0_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39413056)))];
            tensor<fp16, [1, 64, ?]> var_2435_cast_fp16 = mul(x = generator_resblocks_7_alpha2_0_to_fp16, y = xt_183_cast_fp16)[name = string("op_2435_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2436_cast_fp16 = sin(x = var_2435_cast_fp16)[name = string("op_2436_cast_fp16")];
            fp16 var_24_promoted_64_to_fp16 = const()[name = string("op_24_promoted_64_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2437_cast_fp16 = pow(x = var_2436_cast_fp16, y = var_24_promoted_64_to_fp16)[name = string("op_2437_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2432_to_fp16 = const()[name = string("op_2432_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39413248)))];
            tensor<fp16, [1, 64, ?]> var_2438_cast_fp16 = mul(x = var_2432_to_fp16, y = var_2437_cast_fp16)[name = string("op_2438_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_245_cast_fp16 = add(x = xt_183_cast_fp16, y = var_2438_cast_fp16)[name = string("input_245_cast_fp16")];
            string xt_185_pad_type_0 = const()[name = string("xt_185_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_185_pad_0 = const()[name = string("xt_185_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_185_strides_0 = const()[name = string("xt_185_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_185_dilations_0 = const()[name = string("xt_185_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_185_groups_0 = const()[name = string("xt_185_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 7]> generator_resblocks_7_convs2_0_weight_to_fp16 = const()[name = string("generator_resblocks_7_convs2_0_weight_to_fp16"), val = tensor<fp16, [64, 64, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39413440)))];
            tensor<fp16, [64]> generator_resblocks_7_convs2_0_bias_to_fp16 = const()[name = string("generator_resblocks_7_convs2_0_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39470848)))];
            tensor<fp16, [1, 64, ?]> xt_185_cast_fp16 = conv(bias = generator_resblocks_7_convs2_0_bias_to_fp16, dilations = xt_185_dilations_0, groups = xt_185_groups_0, pad = xt_185_pad_0, pad_type = xt_185_pad_type_0, strides = xt_185_strides_0, weight = generator_resblocks_7_convs2_0_weight_to_fp16, x = input_245_cast_fp16)[name = string("xt_185_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_247_cast_fp16 = add(x = xt_185_cast_fp16, y = input_217_cast_fp16)[name = string("input_247_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_7_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_7_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39471040)))];
            tensor<fp16, [128]> generator_resblocks_7_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_7_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39503872)))];
            tensor<fp16, [1, 128]> linear_62_cast_fp16 = linear(bias = generator_resblocks_7_adain1_1_fc_bias_to_fp16, weight = generator_resblocks_7_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_62_cast_fp16")];
            tensor<int32, [3]> var_2454 = const()[name = string("op_2454"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_251_cast_fp16 = reshape(shape = var_2454, x = linear_62_cast_fp16)[name = string("h_251_cast_fp16")];
            tensor<int32, [2]> var_2456_split_sizes_0 = const()[name = string("op_2456_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2456_axis_0 = const()[name = string("op_2456_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2456_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2456_cast_fp16_1 = split(axis = var_2456_axis_0, split_sizes = var_2456_split_sizes_0, x = h_251_cast_fp16)[name = string("op_2456_cast_fp16")];
            fp16 var_2458_promoted_to_fp16 = const()[name = string("op_2458_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2459_cast_fp16 = add(x = var_2456_cast_fp16_0, y = var_2458_promoted_to_fp16)[name = string("op_2459_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2460_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_247_cast_fp16)[name = string("op_2460_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2461_cast_fp16 = mul(x = var_2459_cast_fp16, y = var_2460_cast_fp16)[name = string("op_2461_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_187_cast_fp16 = add(x = var_2461_cast_fp16, y = var_2456_cast_fp16_1)[name = string("xt_187_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_7_alpha1_1_to_fp16 = const()[name = string("generator_resblocks_7_alpha1_1_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39504192)))];
            tensor<fp16, [1, 64, ?]> var_2466_cast_fp16 = mul(x = generator_resblocks_7_alpha1_1_to_fp16, y = xt_187_cast_fp16)[name = string("op_2466_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2467_cast_fp16 = sin(x = var_2466_cast_fp16)[name = string("op_2467_cast_fp16")];
            fp16 var_24_promoted_65_to_fp16 = const()[name = string("op_24_promoted_65_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2468_cast_fp16 = pow(x = var_2467_cast_fp16, y = var_24_promoted_65_to_fp16)[name = string("op_2468_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2463_to_fp16 = const()[name = string("op_2463_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39504384)))];
            tensor<fp16, [1, 64, ?]> var_2469_cast_fp16 = mul(x = var_2463_to_fp16, y = var_2468_cast_fp16)[name = string("op_2469_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_249_cast_fp16 = add(x = xt_187_cast_fp16, y = var_2469_cast_fp16)[name = string("input_249_cast_fp16")];
            string input_251_pad_type_0 = const()[name = string("input_251_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_251_pad_0 = const()[name = string("input_251_pad_0"), val = tensor<int32, [2]>([9, 9])];
            tensor<int32, [1]> input_251_dilations_0 = const()[name = string("input_251_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_251_strides_0 = const()[name = string("input_251_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_251_groups_0 = const()[name = string("input_251_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 7]> generator_resblocks_7_convs1_1_weight_to_fp16 = const()[name = string("generator_resblocks_7_convs1_1_weight_to_fp16"), val = tensor<fp16, [64, 64, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39504576)))];
            tensor<fp16, [64]> generator_resblocks_7_convs1_1_bias_to_fp16 = const()[name = string("generator_resblocks_7_convs1_1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39561984)))];
            tensor<fp16, [1, 64, ?]> input_251_cast_fp16 = conv(bias = generator_resblocks_7_convs1_1_bias_to_fp16, dilations = input_251_dilations_0, groups = input_251_groups_0, pad = input_251_pad_0, pad_type = input_251_pad_type_0, strides = input_251_strides_0, weight = generator_resblocks_7_convs1_1_weight_to_fp16, x = input_249_cast_fp16)[name = string("input_251_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_7_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_7_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39562176)))];
            tensor<fp16, [128]> generator_resblocks_7_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_7_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39595008)))];
            tensor<fp16, [1, 128]> linear_63_cast_fp16 = linear(bias = generator_resblocks_7_adain2_1_fc_bias_to_fp16, weight = generator_resblocks_7_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_63_cast_fp16")];
            tensor<int32, [3]> var_2484 = const()[name = string("op_2484"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_255_cast_fp16 = reshape(shape = var_2484, x = linear_63_cast_fp16)[name = string("h_255_cast_fp16")];
            tensor<int32, [2]> var_2486_split_sizes_0 = const()[name = string("op_2486_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2486_axis_0 = const()[name = string("op_2486_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2486_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2486_cast_fp16_1 = split(axis = var_2486_axis_0, split_sizes = var_2486_split_sizes_0, x = h_255_cast_fp16)[name = string("op_2486_cast_fp16")];
            fp16 var_2488_promoted_to_fp16 = const()[name = string("op_2488_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2489_cast_fp16 = add(x = var_2486_cast_fp16_0, y = var_2488_promoted_to_fp16)[name = string("op_2489_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2490_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_251_cast_fp16)[name = string("op_2490_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2491_cast_fp16 = mul(x = var_2489_cast_fp16, y = var_2490_cast_fp16)[name = string("op_2491_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_189_cast_fp16 = add(x = var_2491_cast_fp16, y = var_2486_cast_fp16_1)[name = string("xt_189_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_7_alpha2_1_to_fp16 = const()[name = string("generator_resblocks_7_alpha2_1_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39595328)))];
            tensor<fp16, [1, 64, ?]> var_2496_cast_fp16 = mul(x = generator_resblocks_7_alpha2_1_to_fp16, y = xt_189_cast_fp16)[name = string("op_2496_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2497_cast_fp16 = sin(x = var_2496_cast_fp16)[name = string("op_2497_cast_fp16")];
            fp16 var_24_promoted_66_to_fp16 = const()[name = string("op_24_promoted_66_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2498_cast_fp16 = pow(x = var_2497_cast_fp16, y = var_24_promoted_66_to_fp16)[name = string("op_2498_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2493_to_fp16 = const()[name = string("op_2493_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39595520)))];
            tensor<fp16, [1, 64, ?]> var_2499_cast_fp16 = mul(x = var_2493_to_fp16, y = var_2498_cast_fp16)[name = string("op_2499_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_253_cast_fp16 = add(x = xt_189_cast_fp16, y = var_2499_cast_fp16)[name = string("input_253_cast_fp16")];
            string xt_191_pad_type_0 = const()[name = string("xt_191_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_191_pad_0 = const()[name = string("xt_191_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_191_strides_0 = const()[name = string("xt_191_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_191_dilations_0 = const()[name = string("xt_191_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_191_groups_0 = const()[name = string("xt_191_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 7]> generator_resblocks_7_convs2_1_weight_to_fp16 = const()[name = string("generator_resblocks_7_convs2_1_weight_to_fp16"), val = tensor<fp16, [64, 64, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39595712)))];
            tensor<fp16, [64]> generator_resblocks_7_convs2_1_bias_to_fp16 = const()[name = string("generator_resblocks_7_convs2_1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39653120)))];
            tensor<fp16, [1, 64, ?]> xt_191_cast_fp16 = conv(bias = generator_resblocks_7_convs2_1_bias_to_fp16, dilations = xt_191_dilations_0, groups = xt_191_groups_0, pad = xt_191_pad_0, pad_type = xt_191_pad_type_0, strides = xt_191_strides_0, weight = generator_resblocks_7_convs2_1_weight_to_fp16, x = input_253_cast_fp16)[name = string("xt_191_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_255_cast_fp16 = add(x = xt_191_cast_fp16, y = input_247_cast_fp16)[name = string("input_255_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_7_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_7_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39653312)))];
            tensor<fp16, [128]> generator_resblocks_7_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_7_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39686144)))];
            tensor<fp16, [1, 128]> linear_64_cast_fp16 = linear(bias = generator_resblocks_7_adain1_2_fc_bias_to_fp16, weight = generator_resblocks_7_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_64_cast_fp16")];
            tensor<int32, [3]> var_2515 = const()[name = string("op_2515"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_259_cast_fp16 = reshape(shape = var_2515, x = linear_64_cast_fp16)[name = string("h_259_cast_fp16")];
            tensor<int32, [2]> var_2517_split_sizes_0 = const()[name = string("op_2517_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2517_axis_0 = const()[name = string("op_2517_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2517_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2517_cast_fp16_1 = split(axis = var_2517_axis_0, split_sizes = var_2517_split_sizes_0, x = h_259_cast_fp16)[name = string("op_2517_cast_fp16")];
            fp16 var_2519_promoted_to_fp16 = const()[name = string("op_2519_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2520_cast_fp16 = add(x = var_2517_cast_fp16_0, y = var_2519_promoted_to_fp16)[name = string("op_2520_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2521_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_255_cast_fp16)[name = string("op_2521_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2522_cast_fp16 = mul(x = var_2520_cast_fp16, y = var_2521_cast_fp16)[name = string("op_2522_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_193_cast_fp16 = add(x = var_2522_cast_fp16, y = var_2517_cast_fp16_1)[name = string("xt_193_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_7_alpha1_2_to_fp16 = const()[name = string("generator_resblocks_7_alpha1_2_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39686464)))];
            tensor<fp16, [1, 64, ?]> var_2527_cast_fp16 = mul(x = generator_resblocks_7_alpha1_2_to_fp16, y = xt_193_cast_fp16)[name = string("op_2527_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2528_cast_fp16 = sin(x = var_2527_cast_fp16)[name = string("op_2528_cast_fp16")];
            fp16 var_24_promoted_67_to_fp16 = const()[name = string("op_24_promoted_67_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2529_cast_fp16 = pow(x = var_2528_cast_fp16, y = var_24_promoted_67_to_fp16)[name = string("op_2529_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2524_to_fp16 = const()[name = string("op_2524_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39686656)))];
            tensor<fp16, [1, 64, ?]> var_2530_cast_fp16 = mul(x = var_2524_to_fp16, y = var_2529_cast_fp16)[name = string("op_2530_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_257_cast_fp16 = add(x = xt_193_cast_fp16, y = var_2530_cast_fp16)[name = string("input_257_cast_fp16")];
            string input_259_pad_type_0 = const()[name = string("input_259_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_259_pad_0 = const()[name = string("input_259_pad_0"), val = tensor<int32, [2]>([15, 15])];
            tensor<int32, [1]> input_259_dilations_0 = const()[name = string("input_259_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_259_strides_0 = const()[name = string("input_259_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_259_groups_0 = const()[name = string("input_259_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 7]> generator_resblocks_7_convs1_2_weight_to_fp16 = const()[name = string("generator_resblocks_7_convs1_2_weight_to_fp16"), val = tensor<fp16, [64, 64, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39686848)))];
            tensor<fp16, [64]> generator_resblocks_7_convs1_2_bias_to_fp16 = const()[name = string("generator_resblocks_7_convs1_2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39744256)))];
            tensor<fp16, [1, 64, ?]> input_259_cast_fp16 = conv(bias = generator_resblocks_7_convs1_2_bias_to_fp16, dilations = input_259_dilations_0, groups = input_259_groups_0, pad = input_259_pad_0, pad_type = input_259_pad_type_0, strides = input_259_strides_0, weight = generator_resblocks_7_convs1_2_weight_to_fp16, x = input_257_cast_fp16)[name = string("input_259_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_7_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_7_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39744448)))];
            tensor<fp16, [128]> generator_resblocks_7_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_7_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39777280)))];
            tensor<fp16, [1, 128]> linear_65_cast_fp16 = linear(bias = generator_resblocks_7_adain2_2_fc_bias_to_fp16, weight = generator_resblocks_7_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_65_cast_fp16")];
            tensor<int32, [3]> var_2545 = const()[name = string("op_2545"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_263_cast_fp16 = reshape(shape = var_2545, x = linear_65_cast_fp16)[name = string("h_263_cast_fp16")];
            tensor<int32, [2]> var_2547_split_sizes_0 = const()[name = string("op_2547_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2547_axis_0 = const()[name = string("op_2547_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2547_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2547_cast_fp16_1 = split(axis = var_2547_axis_0, split_sizes = var_2547_split_sizes_0, x = h_263_cast_fp16)[name = string("op_2547_cast_fp16")];
            fp16 var_2549_promoted_to_fp16 = const()[name = string("op_2549_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2550_cast_fp16 = add(x = var_2547_cast_fp16_0, y = var_2549_promoted_to_fp16)[name = string("op_2550_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2551_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_259_cast_fp16)[name = string("op_2551_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2552_cast_fp16 = mul(x = var_2550_cast_fp16, y = var_2551_cast_fp16)[name = string("op_2552_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_195_cast_fp16 = add(x = var_2552_cast_fp16, y = var_2547_cast_fp16_1)[name = string("xt_195_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_7_alpha2_2_to_fp16 = const()[name = string("generator_resblocks_7_alpha2_2_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39777600)))];
            tensor<fp16, [1, 64, ?]> var_2557_cast_fp16 = mul(x = generator_resblocks_7_alpha2_2_to_fp16, y = xt_195_cast_fp16)[name = string("op_2557_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2558_cast_fp16 = sin(x = var_2557_cast_fp16)[name = string("op_2558_cast_fp16")];
            fp16 var_24_promoted_68_to_fp16 = const()[name = string("op_24_promoted_68_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2559_cast_fp16 = pow(x = var_2558_cast_fp16, y = var_24_promoted_68_to_fp16)[name = string("op_2559_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2554_to_fp16 = const()[name = string("op_2554_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39777792)))];
            tensor<fp16, [1, 64, ?]> var_2560_cast_fp16 = mul(x = var_2554_to_fp16, y = var_2559_cast_fp16)[name = string("op_2560_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_261_cast_fp16 = add(x = xt_195_cast_fp16, y = var_2560_cast_fp16)[name = string("input_261_cast_fp16")];
            string xt_197_pad_type_0 = const()[name = string("xt_197_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_197_pad_0 = const()[name = string("xt_197_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_197_strides_0 = const()[name = string("xt_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_197_dilations_0 = const()[name = string("xt_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_197_groups_0 = const()[name = string("xt_197_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 7]> generator_resblocks_7_convs2_2_weight_to_fp16 = const()[name = string("generator_resblocks_7_convs2_2_weight_to_fp16"), val = tensor<fp16, [64, 64, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39777984)))];
            tensor<fp16, [64]> generator_resblocks_7_convs2_2_bias_to_fp16 = const()[name = string("generator_resblocks_7_convs2_2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39835392)))];
            tensor<fp16, [1, 64, ?]> xt_197_cast_fp16 = conv(bias = generator_resblocks_7_convs2_2_bias_to_fp16, dilations = xt_197_dilations_0, groups = xt_197_groups_0, pad = xt_197_pad_0, pad_type = xt_197_pad_type_0, strides = xt_197_strides_0, weight = generator_resblocks_7_convs2_2_weight_to_fp16, x = input_261_cast_fp16)[name = string("xt_197_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2569_cast_fp16 = add(x = xt_197_cast_fp16, y = input_255_cast_fp16)[name = string("op_2569_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xs_15_cast_fp16 = add(x = xs_13_cast_fp16, y = var_2569_cast_fp16)[name = string("xs_15_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_8_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_8_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39835584)))];
            tensor<fp16, [128]> generator_resblocks_8_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_8_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39868416)))];
            tensor<fp16, [1, 128]> linear_66_cast_fp16 = linear(bias = generator_resblocks_8_adain1_0_fc_bias_to_fp16, weight = generator_resblocks_8_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_66_cast_fp16")];
            tensor<int32, [3]> var_2613 = const()[name = string("op_2613"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_267_cast_fp16 = reshape(shape = var_2613, x = linear_66_cast_fp16)[name = string("h_267_cast_fp16")];
            tensor<int32, [2]> var_2615_split_sizes_0 = const()[name = string("op_2615_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2615_axis_0 = const()[name = string("op_2615_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2615_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2615_cast_fp16_1 = split(axis = var_2615_axis_0, split_sizes = var_2615_split_sizes_0, x = h_267_cast_fp16)[name = string("op_2615_cast_fp16")];
            fp16 var_2617_promoted_to_fp16 = const()[name = string("op_2617_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2618_cast_fp16 = add(x = var_2615_cast_fp16_0, y = var_2617_promoted_to_fp16)[name = string("op_2618_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2620_cast_fp16 = mul(x = var_2618_cast_fp16, y = var_2180_cast_fp16)[name = string("op_2620_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_199_cast_fp16 = add(x = var_2620_cast_fp16, y = var_2615_cast_fp16_1)[name = string("xt_199_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_8_alpha1_0_to_fp16 = const()[name = string("generator_resblocks_8_alpha1_0_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39868736)))];
            tensor<fp16, [1, 64, ?]> var_2625_cast_fp16 = mul(x = generator_resblocks_8_alpha1_0_to_fp16, y = xt_199_cast_fp16)[name = string("op_2625_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2626_cast_fp16 = sin(x = var_2625_cast_fp16)[name = string("op_2626_cast_fp16")];
            fp16 var_24_promoted_69_to_fp16 = const()[name = string("op_24_promoted_69_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2627_cast_fp16 = pow(x = var_2626_cast_fp16, y = var_24_promoted_69_to_fp16)[name = string("op_2627_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2622_to_fp16 = const()[name = string("op_2622_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39868928)))];
            tensor<fp16, [1, 64, ?]> var_2628_cast_fp16 = mul(x = var_2622_to_fp16, y = var_2627_cast_fp16)[name = string("op_2628_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_263_cast_fp16 = add(x = xt_199_cast_fp16, y = var_2628_cast_fp16)[name = string("input_263_cast_fp16")];
            string input_265_pad_type_0 = const()[name = string("input_265_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_265_pad_0 = const()[name = string("input_265_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> input_265_strides_0 = const()[name = string("input_265_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_265_dilations_0 = const()[name = string("input_265_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_265_groups_0 = const()[name = string("input_265_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 11]> generator_resblocks_8_convs1_0_weight_to_fp16 = const()[name = string("generator_resblocks_8_convs1_0_weight_to_fp16"), val = tensor<fp16, [64, 64, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39869120)))];
            tensor<fp16, [64]> generator_resblocks_8_convs1_0_bias_to_fp16 = const()[name = string("generator_resblocks_8_convs1_0_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39959296)))];
            tensor<fp16, [1, 64, ?]> input_265_cast_fp16 = conv(bias = generator_resblocks_8_convs1_0_bias_to_fp16, dilations = input_265_dilations_0, groups = input_265_groups_0, pad = input_265_pad_0, pad_type = input_265_pad_type_0, strides = input_265_strides_0, weight = generator_resblocks_8_convs1_0_weight_to_fp16, x = input_263_cast_fp16)[name = string("input_265_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_8_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_8_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39959488)))];
            tensor<fp16, [128]> generator_resblocks_8_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_8_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39992320)))];
            tensor<fp16, [1, 128]> linear_67_cast_fp16 = linear(bias = generator_resblocks_8_adain2_0_fc_bias_to_fp16, weight = generator_resblocks_8_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_67_cast_fp16")];
            tensor<int32, [3]> var_2643 = const()[name = string("op_2643"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_271_cast_fp16 = reshape(shape = var_2643, x = linear_67_cast_fp16)[name = string("h_271_cast_fp16")];
            tensor<int32, [2]> var_2645_split_sizes_0 = const()[name = string("op_2645_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2645_axis_0 = const()[name = string("op_2645_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2645_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2645_cast_fp16_1 = split(axis = var_2645_axis_0, split_sizes = var_2645_split_sizes_0, x = h_271_cast_fp16)[name = string("op_2645_cast_fp16")];
            fp16 var_2647_promoted_to_fp16 = const()[name = string("op_2647_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2648_cast_fp16 = add(x = var_2645_cast_fp16_0, y = var_2647_promoted_to_fp16)[name = string("op_2648_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2649_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_265_cast_fp16)[name = string("op_2649_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2650_cast_fp16 = mul(x = var_2648_cast_fp16, y = var_2649_cast_fp16)[name = string("op_2650_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_201_cast_fp16 = add(x = var_2650_cast_fp16, y = var_2645_cast_fp16_1)[name = string("xt_201_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_8_alpha2_0_to_fp16 = const()[name = string("generator_resblocks_8_alpha2_0_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39992640)))];
            tensor<fp16, [1, 64, ?]> var_2655_cast_fp16 = mul(x = generator_resblocks_8_alpha2_0_to_fp16, y = xt_201_cast_fp16)[name = string("op_2655_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2656_cast_fp16 = sin(x = var_2655_cast_fp16)[name = string("op_2656_cast_fp16")];
            fp16 var_24_promoted_70_to_fp16 = const()[name = string("op_24_promoted_70_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2657_cast_fp16 = pow(x = var_2656_cast_fp16, y = var_24_promoted_70_to_fp16)[name = string("op_2657_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2652_to_fp16 = const()[name = string("op_2652_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39992832)))];
            tensor<fp16, [1, 64, ?]> var_2658_cast_fp16 = mul(x = var_2652_to_fp16, y = var_2657_cast_fp16)[name = string("op_2658_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_267_cast_fp16 = add(x = xt_201_cast_fp16, y = var_2658_cast_fp16)[name = string("input_267_cast_fp16")];
            string xt_203_pad_type_0 = const()[name = string("xt_203_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_203_pad_0 = const()[name = string("xt_203_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_203_strides_0 = const()[name = string("xt_203_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_203_dilations_0 = const()[name = string("xt_203_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_203_groups_0 = const()[name = string("xt_203_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 11]> generator_resblocks_8_convs2_0_weight_to_fp16 = const()[name = string("generator_resblocks_8_convs2_0_weight_to_fp16"), val = tensor<fp16, [64, 64, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39993024)))];
            tensor<fp16, [64]> generator_resblocks_8_convs2_0_bias_to_fp16 = const()[name = string("generator_resblocks_8_convs2_0_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40083200)))];
            tensor<fp16, [1, 64, ?]> xt_203_cast_fp16 = conv(bias = generator_resblocks_8_convs2_0_bias_to_fp16, dilations = xt_203_dilations_0, groups = xt_203_groups_0, pad = xt_203_pad_0, pad_type = xt_203_pad_type_0, strides = xt_203_strides_0, weight = generator_resblocks_8_convs2_0_weight_to_fp16, x = input_267_cast_fp16)[name = string("xt_203_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_269_cast_fp16 = add(x = xt_203_cast_fp16, y = input_217_cast_fp16)[name = string("input_269_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_8_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_8_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40083392)))];
            tensor<fp16, [128]> generator_resblocks_8_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_8_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40116224)))];
            tensor<fp16, [1, 128]> linear_68_cast_fp16 = linear(bias = generator_resblocks_8_adain1_1_fc_bias_to_fp16, weight = generator_resblocks_8_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_68_cast_fp16")];
            tensor<int32, [3]> var_2674 = const()[name = string("op_2674"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_275_cast_fp16 = reshape(shape = var_2674, x = linear_68_cast_fp16)[name = string("h_275_cast_fp16")];
            tensor<int32, [2]> var_2676_split_sizes_0 = const()[name = string("op_2676_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2676_axis_0 = const()[name = string("op_2676_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2676_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2676_cast_fp16_1 = split(axis = var_2676_axis_0, split_sizes = var_2676_split_sizes_0, x = h_275_cast_fp16)[name = string("op_2676_cast_fp16")];
            fp16 var_2678_promoted_to_fp16 = const()[name = string("op_2678_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2679_cast_fp16 = add(x = var_2676_cast_fp16_0, y = var_2678_promoted_to_fp16)[name = string("op_2679_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2680_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_269_cast_fp16)[name = string("op_2680_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2681_cast_fp16 = mul(x = var_2679_cast_fp16, y = var_2680_cast_fp16)[name = string("op_2681_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_205_cast_fp16 = add(x = var_2681_cast_fp16, y = var_2676_cast_fp16_1)[name = string("xt_205_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_8_alpha1_1_to_fp16 = const()[name = string("generator_resblocks_8_alpha1_1_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40116544)))];
            tensor<fp16, [1, 64, ?]> var_2686_cast_fp16 = mul(x = generator_resblocks_8_alpha1_1_to_fp16, y = xt_205_cast_fp16)[name = string("op_2686_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2687_cast_fp16 = sin(x = var_2686_cast_fp16)[name = string("op_2687_cast_fp16")];
            fp16 var_24_promoted_71_to_fp16 = const()[name = string("op_24_promoted_71_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2688_cast_fp16 = pow(x = var_2687_cast_fp16, y = var_24_promoted_71_to_fp16)[name = string("op_2688_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2683_to_fp16 = const()[name = string("op_2683_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40116736)))];
            tensor<fp16, [1, 64, ?]> var_2689_cast_fp16 = mul(x = var_2683_to_fp16, y = var_2688_cast_fp16)[name = string("op_2689_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_271_cast_fp16 = add(x = xt_205_cast_fp16, y = var_2689_cast_fp16)[name = string("input_271_cast_fp16")];
            string input_273_pad_type_0 = const()[name = string("input_273_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_273_pad_0 = const()[name = string("input_273_pad_0"), val = tensor<int32, [2]>([15, 15])];
            tensor<int32, [1]> input_273_dilations_0 = const()[name = string("input_273_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_273_strides_0 = const()[name = string("input_273_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_273_groups_0 = const()[name = string("input_273_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 11]> generator_resblocks_8_convs1_1_weight_to_fp16 = const()[name = string("generator_resblocks_8_convs1_1_weight_to_fp16"), val = tensor<fp16, [64, 64, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40116928)))];
            tensor<fp16, [64]> generator_resblocks_8_convs1_1_bias_to_fp16 = const()[name = string("generator_resblocks_8_convs1_1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40207104)))];
            tensor<fp16, [1, 64, ?]> input_273_cast_fp16 = conv(bias = generator_resblocks_8_convs1_1_bias_to_fp16, dilations = input_273_dilations_0, groups = input_273_groups_0, pad = input_273_pad_0, pad_type = input_273_pad_type_0, strides = input_273_strides_0, weight = generator_resblocks_8_convs1_1_weight_to_fp16, x = input_271_cast_fp16)[name = string("input_273_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_8_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_8_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40207296)))];
            tensor<fp16, [128]> generator_resblocks_8_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_8_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40240128)))];
            tensor<fp16, [1, 128]> linear_69_cast_fp16 = linear(bias = generator_resblocks_8_adain2_1_fc_bias_to_fp16, weight = generator_resblocks_8_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_69_cast_fp16")];
            tensor<int32, [3]> var_2704 = const()[name = string("op_2704"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_279_cast_fp16 = reshape(shape = var_2704, x = linear_69_cast_fp16)[name = string("h_279_cast_fp16")];
            tensor<int32, [2]> var_2706_split_sizes_0 = const()[name = string("op_2706_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2706_axis_0 = const()[name = string("op_2706_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2706_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2706_cast_fp16_1 = split(axis = var_2706_axis_0, split_sizes = var_2706_split_sizes_0, x = h_279_cast_fp16)[name = string("op_2706_cast_fp16")];
            fp16 var_2708_promoted_to_fp16 = const()[name = string("op_2708_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2709_cast_fp16 = add(x = var_2706_cast_fp16_0, y = var_2708_promoted_to_fp16)[name = string("op_2709_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2710_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_273_cast_fp16)[name = string("op_2710_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2711_cast_fp16 = mul(x = var_2709_cast_fp16, y = var_2710_cast_fp16)[name = string("op_2711_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_207_cast_fp16 = add(x = var_2711_cast_fp16, y = var_2706_cast_fp16_1)[name = string("xt_207_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_8_alpha2_1_to_fp16 = const()[name = string("generator_resblocks_8_alpha2_1_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40240448)))];
            tensor<fp16, [1, 64, ?]> var_2716_cast_fp16 = mul(x = generator_resblocks_8_alpha2_1_to_fp16, y = xt_207_cast_fp16)[name = string("op_2716_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2717_cast_fp16 = sin(x = var_2716_cast_fp16)[name = string("op_2717_cast_fp16")];
            fp16 var_24_promoted_72_to_fp16 = const()[name = string("op_24_promoted_72_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2718_cast_fp16 = pow(x = var_2717_cast_fp16, y = var_24_promoted_72_to_fp16)[name = string("op_2718_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2713_to_fp16 = const()[name = string("op_2713_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40240640)))];
            tensor<fp16, [1, 64, ?]> var_2719_cast_fp16 = mul(x = var_2713_to_fp16, y = var_2718_cast_fp16)[name = string("op_2719_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_275_cast_fp16 = add(x = xt_207_cast_fp16, y = var_2719_cast_fp16)[name = string("input_275_cast_fp16")];
            string xt_209_pad_type_0 = const()[name = string("xt_209_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_209_pad_0 = const()[name = string("xt_209_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_209_strides_0 = const()[name = string("xt_209_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_209_dilations_0 = const()[name = string("xt_209_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_209_groups_0 = const()[name = string("xt_209_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 11]> generator_resblocks_8_convs2_1_weight_to_fp16 = const()[name = string("generator_resblocks_8_convs2_1_weight_to_fp16"), val = tensor<fp16, [64, 64, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40240832)))];
            tensor<fp16, [64]> generator_resblocks_8_convs2_1_bias_to_fp16 = const()[name = string("generator_resblocks_8_convs2_1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40331008)))];
            tensor<fp16, [1, 64, ?]> xt_209_cast_fp16 = conv(bias = generator_resblocks_8_convs2_1_bias_to_fp16, dilations = xt_209_dilations_0, groups = xt_209_groups_0, pad = xt_209_pad_0, pad_type = xt_209_pad_type_0, strides = xt_209_strides_0, weight = generator_resblocks_8_convs2_1_weight_to_fp16, x = input_275_cast_fp16)[name = string("xt_209_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_277_cast_fp16 = add(x = xt_209_cast_fp16, y = input_269_cast_fp16)[name = string("input_277_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_8_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_8_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40331200)))];
            tensor<fp16, [128]> generator_resblocks_8_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_8_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40364032)))];
            tensor<fp16, [1, 128]> linear_70_cast_fp16 = linear(bias = generator_resblocks_8_adain1_2_fc_bias_to_fp16, weight = generator_resblocks_8_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_70_cast_fp16")];
            tensor<int32, [3]> var_2735 = const()[name = string("op_2735"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_283_cast_fp16 = reshape(shape = var_2735, x = linear_70_cast_fp16)[name = string("h_283_cast_fp16")];
            tensor<int32, [2]> var_2737_split_sizes_0 = const()[name = string("op_2737_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2737_axis_0 = const()[name = string("op_2737_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2737_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2737_cast_fp16_1 = split(axis = var_2737_axis_0, split_sizes = var_2737_split_sizes_0, x = h_283_cast_fp16)[name = string("op_2737_cast_fp16")];
            fp16 var_2739_promoted_to_fp16 = const()[name = string("op_2739_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2740_cast_fp16 = add(x = var_2737_cast_fp16_0, y = var_2739_promoted_to_fp16)[name = string("op_2740_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2741_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_277_cast_fp16)[name = string("op_2741_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2742_cast_fp16 = mul(x = var_2740_cast_fp16, y = var_2741_cast_fp16)[name = string("op_2742_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_211_cast_fp16 = add(x = var_2742_cast_fp16, y = var_2737_cast_fp16_1)[name = string("xt_211_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_8_alpha1_2_to_fp16 = const()[name = string("generator_resblocks_8_alpha1_2_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40364352)))];
            tensor<fp16, [1, 64, ?]> var_2747_cast_fp16 = mul(x = generator_resblocks_8_alpha1_2_to_fp16, y = xt_211_cast_fp16)[name = string("op_2747_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2748_cast_fp16 = sin(x = var_2747_cast_fp16)[name = string("op_2748_cast_fp16")];
            fp16 var_24_promoted_73_to_fp16 = const()[name = string("op_24_promoted_73_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2749_cast_fp16 = pow(x = var_2748_cast_fp16, y = var_24_promoted_73_to_fp16)[name = string("op_2749_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2744_to_fp16 = const()[name = string("op_2744_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40364544)))];
            tensor<fp16, [1, 64, ?]> var_2750_cast_fp16 = mul(x = var_2744_to_fp16, y = var_2749_cast_fp16)[name = string("op_2750_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_279_cast_fp16 = add(x = xt_211_cast_fp16, y = var_2750_cast_fp16)[name = string("input_279_cast_fp16")];
            string input_281_pad_type_0 = const()[name = string("input_281_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_281_pad_0 = const()[name = string("input_281_pad_0"), val = tensor<int32, [2]>([25, 25])];
            tensor<int32, [1]> input_281_dilations_0 = const()[name = string("input_281_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_281_strides_0 = const()[name = string("input_281_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_281_groups_0 = const()[name = string("input_281_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 11]> generator_resblocks_8_convs1_2_weight_to_fp16 = const()[name = string("generator_resblocks_8_convs1_2_weight_to_fp16"), val = tensor<fp16, [64, 64, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40364736)))];
            tensor<fp16, [64]> generator_resblocks_8_convs1_2_bias_to_fp16 = const()[name = string("generator_resblocks_8_convs1_2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40454912)))];
            tensor<fp16, [1, 64, ?]> input_281_cast_fp16 = conv(bias = generator_resblocks_8_convs1_2_bias_to_fp16, dilations = input_281_dilations_0, groups = input_281_groups_0, pad = input_281_pad_0, pad_type = input_281_pad_type_0, strides = input_281_strides_0, weight = generator_resblocks_8_convs1_2_weight_to_fp16, x = input_279_cast_fp16)[name = string("input_281_cast_fp16")];
            tensor<fp16, [128, 128]> generator_resblocks_8_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_8_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40455104)))];
            tensor<fp16, [128]> generator_resblocks_8_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_8_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40487936)))];
            tensor<fp16, [1, 128]> linear_71_cast_fp16 = linear(bias = generator_resblocks_8_adain2_2_fc_bias_to_fp16, weight = generator_resblocks_8_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_71_cast_fp16")];
            tensor<int32, [3]> var_2765 = const()[name = string("op_2765"), val = tensor<int32, [3]>([1, 128, 1])];
            tensor<fp16, [1, 128, 1]> h_287_cast_fp16 = reshape(shape = var_2765, x = linear_71_cast_fp16)[name = string("h_287_cast_fp16")];
            tensor<int32, [2]> var_2767_split_sizes_0 = const()[name = string("op_2767_split_sizes_0"), val = tensor<int32, [2]>([64, 64])];
            int32 var_2767_axis_0 = const()[name = string("op_2767_axis_0"), val = int32(1)];
            tensor<fp16, [1, 64, 1]> var_2767_cast_fp16_0, tensor<fp16, [1, 64, 1]> var_2767_cast_fp16_1 = split(axis = var_2767_axis_0, split_sizes = var_2767_split_sizes_0, x = h_287_cast_fp16)[name = string("op_2767_cast_fp16")];
            fp16 var_2769_promoted_to_fp16 = const()[name = string("op_2769_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64, 1]> var_2770_cast_fp16 = add(x = var_2767_cast_fp16_0, y = var_2769_promoted_to_fp16)[name = string("op_2770_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2771_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_281_cast_fp16)[name = string("op_2771_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2772_cast_fp16 = mul(x = var_2770_cast_fp16, y = var_2771_cast_fp16)[name = string("op_2772_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xt_213_cast_fp16 = add(x = var_2772_cast_fp16, y = var_2767_cast_fp16_1)[name = string("xt_213_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_resblocks_8_alpha2_2_to_fp16 = const()[name = string("generator_resblocks_8_alpha2_2_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40488256)))];
            tensor<fp16, [1, 64, ?]> var_2777_cast_fp16 = mul(x = generator_resblocks_8_alpha2_2_to_fp16, y = xt_213_cast_fp16)[name = string("op_2777_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2778_cast_fp16 = sin(x = var_2777_cast_fp16)[name = string("op_2778_cast_fp16")];
            fp16 var_24_promoted_74_to_fp16 = const()[name = string("op_24_promoted_74_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2779_cast_fp16 = pow(x = var_2778_cast_fp16, y = var_24_promoted_74_to_fp16)[name = string("op_2779_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2774_to_fp16 = const()[name = string("op_2774_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40488448)))];
            tensor<fp16, [1, 64, ?]> var_2780_cast_fp16 = mul(x = var_2774_to_fp16, y = var_2779_cast_fp16)[name = string("op_2780_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_283_cast_fp16 = add(x = xt_213_cast_fp16, y = var_2780_cast_fp16)[name = string("input_283_cast_fp16")];
            string xt_215_pad_type_0 = const()[name = string("xt_215_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_215_pad_0 = const()[name = string("xt_215_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_215_strides_0 = const()[name = string("xt_215_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_215_dilations_0 = const()[name = string("xt_215_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_215_groups_0 = const()[name = string("xt_215_groups_0"), val = int32(1)];
            tensor<fp16, [64, 64, 11]> generator_resblocks_8_convs2_2_weight_to_fp16 = const()[name = string("generator_resblocks_8_convs2_2_weight_to_fp16"), val = tensor<fp16, [64, 64, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40488640)))];
            tensor<fp16, [64]> generator_resblocks_8_convs2_2_bias_to_fp16 = const()[name = string("generator_resblocks_8_convs2_2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40578816)))];
            tensor<fp16, [1, 64, ?]> xt_215_cast_fp16 = conv(bias = generator_resblocks_8_convs2_2_bias_to_fp16, dilations = xt_215_dilations_0, groups = xt_215_groups_0, pad = xt_215_pad_0, pad_type = xt_215_pad_type_0, strides = xt_215_strides_0, weight = generator_resblocks_8_convs2_2_weight_to_fp16, x = input_283_cast_fp16)[name = string("xt_215_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2789_cast_fp16 = add(x = xt_215_cast_fp16, y = input_277_cast_fp16)[name = string("op_2789_cast_fp16")];
            tensor<fp16, [1, 64, ?]> xs_17_cast_fp16 = add(x = xs_15_cast_fp16, y = var_2789_cast_fp16)[name = string("xs_17_cast_fp16")];
            fp16 _inversed_x_11_y_0_to_fp16 = const()[name = string("_inversed_x_11_y_0_to_fp16"), val = fp16(0x1.554p-2)];
            tensor<fp16, [1, 64, ?]> _inversed_x_11_cast_fp16 = mul(x = xs_17_cast_fp16, y = _inversed_x_11_y_0_to_fp16)[name = string("_inversed_x_11_cast_fp16")];
            tensor<fp16, [1, 64, 1]> generator_alphas_3_to_fp16 = const()[name = string("generator_alphas_3_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40579008)))];
            tensor<fp16, [1, 64, ?]> var_2796_cast_fp16 = mul(x = generator_alphas_3_to_fp16, y = _inversed_x_11_cast_fp16)[name = string("op_2796_cast_fp16")];
            tensor<fp16, [1, 64, ?]> var_2797_cast_fp16 = sin(x = var_2796_cast_fp16)[name = string("op_2797_cast_fp16")];
            fp16 var_24_promoted_75_to_fp16 = const()[name = string("op_24_promoted_75_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 64, ?]> var_2798_cast_fp16 = pow(x = var_2797_cast_fp16, y = var_24_promoted_75_to_fp16)[name = string("op_2798_cast_fp16")];
            tensor<fp16, [1, 64, 1]> var_2793_to_fp16 = const()[name = string("op_2793_to_fp16"), val = tensor<fp16, [1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40579200)))];
            tensor<fp16, [1, 64, ?]> var_2799_cast_fp16 = mul(x = var_2793_to_fp16, y = var_2798_cast_fp16)[name = string("op_2799_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_309_cast_fp16 = add(x = _inversed_x_11_cast_fp16, y = var_2799_cast_fp16)[name = string("input_309_cast_fp16")];
            string input_285_pad_type_0 = const()[name = string("input_285_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_285_strides_0 = const()[name = string("input_285_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_285_pad_0 = const()[name = string("input_285_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_285_dilations_0 = const()[name = string("input_285_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_285_groups_0 = const()[name = string("input_285_groups_0"), val = int32(1)];
            tensor<fp16, [32, 1, 1]> generator_noise_convs_3_weight_to_fp16 = const()[name = string("generator_noise_convs_3_weight_to_fp16"), val = tensor<fp16, [32, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40579392)))];
            tensor<fp16, [32]> generator_noise_convs_3_bias_to_fp16 = const()[name = string("generator_noise_convs_3_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40579520)))];
            tensor<fp16, [1, 32, ?]> input_285_cast_fp16 = conv(bias = generator_noise_convs_3_bias_to_fp16, dilations = input_285_dilations_0, groups = input_285_groups_0, pad = input_285_pad_0, pad_type = input_285_pad_type_0, strides = input_285_strides_0, weight = generator_noise_convs_3_weight_to_fp16, x = har_source_to_fp16)[name = string("input_285_cast_fp16")];
            tensor<fp16, [64, 128]> generator_noise_res_3_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_noise_res_3_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40579648)))];
            tensor<fp16, [64]> generator_noise_res_3_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_noise_res_3_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40596096)))];
            tensor<fp16, [1, 64]> linear_72_cast_fp16 = linear(bias = generator_noise_res_3_adain1_0_fc_bias_to_fp16, weight = generator_noise_res_3_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_72_cast_fp16")];
            tensor<int32, [3]> var_2850 = const()[name = string("op_2850"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_291_cast_fp16 = reshape(shape = var_2850, x = linear_72_cast_fp16)[name = string("h_291_cast_fp16")];
            tensor<int32, [2]> var_2852_split_sizes_0 = const()[name = string("op_2852_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_2852_axis_0 = const()[name = string("op_2852_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_2852_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_2852_cast_fp16_1 = split(axis = var_2852_axis_0, split_sizes = var_2852_split_sizes_0, x = h_291_cast_fp16)[name = string("op_2852_cast_fp16")];
            fp16 var_2854_promoted_to_fp16 = const()[name = string("op_2854_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_2855_cast_fp16 = add(x = var_2852_cast_fp16_0, y = var_2854_promoted_to_fp16)[name = string("op_2855_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2856_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_285_cast_fp16)[name = string("op_2856_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2857_cast_fp16 = mul(x = var_2855_cast_fp16, y = var_2856_cast_fp16)[name = string("op_2857_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_217_cast_fp16 = add(x = var_2857_cast_fp16, y = var_2852_cast_fp16_1)[name = string("xt_217_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_noise_res_3_alpha1_0_to_fp16 = const()[name = string("generator_noise_res_3_alpha1_0_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40596288)))];
            tensor<fp16, [1, 32, ?]> var_2862_cast_fp16 = mul(x = generator_noise_res_3_alpha1_0_to_fp16, y = xt_217_cast_fp16)[name = string("op_2862_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2863_cast_fp16 = sin(x = var_2862_cast_fp16)[name = string("op_2863_cast_fp16")];
            fp16 var_24_promoted_76_to_fp16 = const()[name = string("op_24_promoted_76_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_2864_cast_fp16 = pow(x = var_2863_cast_fp16, y = var_24_promoted_76_to_fp16)[name = string("op_2864_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_2859_to_fp16 = const()[name = string("op_2859_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40596416)))];
            tensor<fp16, [1, 32, ?]> var_2865_cast_fp16 = mul(x = var_2859_to_fp16, y = var_2864_cast_fp16)[name = string("op_2865_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_287_cast_fp16 = add(x = xt_217_cast_fp16, y = var_2865_cast_fp16)[name = string("input_287_cast_fp16")];
            string input_289_pad_type_0 = const()[name = string("input_289_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_289_pad_0 = const()[name = string("input_289_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> input_289_strides_0 = const()[name = string("input_289_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_289_dilations_0 = const()[name = string("input_289_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_289_groups_0 = const()[name = string("input_289_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 11]> generator_noise_res_3_convs1_0_weight_to_fp16 = const()[name = string("generator_noise_res_3_convs1_0_weight_to_fp16"), val = tensor<fp16, [32, 32, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40596544)))];
            tensor<fp16, [32]> generator_noise_res_3_convs1_0_bias_to_fp16 = const()[name = string("generator_noise_res_3_convs1_0_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40619136)))];
            tensor<fp16, [1, 32, ?]> input_289_cast_fp16 = conv(bias = generator_noise_res_3_convs1_0_bias_to_fp16, dilations = input_289_dilations_0, groups = input_289_groups_0, pad = input_289_pad_0, pad_type = input_289_pad_type_0, strides = input_289_strides_0, weight = generator_noise_res_3_convs1_0_weight_to_fp16, x = input_287_cast_fp16)[name = string("input_289_cast_fp16")];
            tensor<fp16, [64, 128]> generator_noise_res_3_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_noise_res_3_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40619264)))];
            tensor<fp16, [64]> generator_noise_res_3_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_noise_res_3_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40635712)))];
            tensor<fp16, [1, 64]> linear_73_cast_fp16 = linear(bias = generator_noise_res_3_adain2_0_fc_bias_to_fp16, weight = generator_noise_res_3_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_73_cast_fp16")];
            tensor<int32, [3]> var_2880 = const()[name = string("op_2880"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_295_cast_fp16 = reshape(shape = var_2880, x = linear_73_cast_fp16)[name = string("h_295_cast_fp16")];
            tensor<int32, [2]> var_2882_split_sizes_0 = const()[name = string("op_2882_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_2882_axis_0 = const()[name = string("op_2882_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_2882_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_2882_cast_fp16_1 = split(axis = var_2882_axis_0, split_sizes = var_2882_split_sizes_0, x = h_295_cast_fp16)[name = string("op_2882_cast_fp16")];
            fp16 var_2884_promoted_to_fp16 = const()[name = string("op_2884_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_2885_cast_fp16 = add(x = var_2882_cast_fp16_0, y = var_2884_promoted_to_fp16)[name = string("op_2885_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2886_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_289_cast_fp16)[name = string("op_2886_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2887_cast_fp16 = mul(x = var_2885_cast_fp16, y = var_2886_cast_fp16)[name = string("op_2887_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_219_cast_fp16 = add(x = var_2887_cast_fp16, y = var_2882_cast_fp16_1)[name = string("xt_219_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_noise_res_3_alpha2_0_to_fp16 = const()[name = string("generator_noise_res_3_alpha2_0_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40635904)))];
            tensor<fp16, [1, 32, ?]> var_2892_cast_fp16 = mul(x = generator_noise_res_3_alpha2_0_to_fp16, y = xt_219_cast_fp16)[name = string("op_2892_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2893_cast_fp16 = sin(x = var_2892_cast_fp16)[name = string("op_2893_cast_fp16")];
            fp16 var_24_promoted_77_to_fp16 = const()[name = string("op_24_promoted_77_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_2894_cast_fp16 = pow(x = var_2893_cast_fp16, y = var_24_promoted_77_to_fp16)[name = string("op_2894_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_2889_to_fp16 = const()[name = string("op_2889_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40636032)))];
            tensor<fp16, [1, 32, ?]> var_2895_cast_fp16 = mul(x = var_2889_to_fp16, y = var_2894_cast_fp16)[name = string("op_2895_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_291_cast_fp16 = add(x = xt_219_cast_fp16, y = var_2895_cast_fp16)[name = string("input_291_cast_fp16")];
            string xt_221_pad_type_0 = const()[name = string("xt_221_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_221_pad_0 = const()[name = string("xt_221_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_221_strides_0 = const()[name = string("xt_221_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_221_dilations_0 = const()[name = string("xt_221_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_221_groups_0 = const()[name = string("xt_221_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 11]> generator_noise_res_3_convs2_0_weight_to_fp16 = const()[name = string("generator_noise_res_3_convs2_0_weight_to_fp16"), val = tensor<fp16, [32, 32, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40636160)))];
            tensor<fp16, [32]> generator_noise_res_3_convs2_0_bias_to_fp16 = const()[name = string("generator_noise_res_3_convs2_0_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40658752)))];
            tensor<fp16, [1, 32, ?]> xt_221_cast_fp16 = conv(bias = generator_noise_res_3_convs2_0_bias_to_fp16, dilations = xt_221_dilations_0, groups = xt_221_groups_0, pad = xt_221_pad_0, pad_type = xt_221_pad_type_0, strides = xt_221_strides_0, weight = generator_noise_res_3_convs2_0_weight_to_fp16, x = input_291_cast_fp16)[name = string("xt_221_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_293_cast_fp16 = add(x = xt_221_cast_fp16, y = input_285_cast_fp16)[name = string("input_293_cast_fp16")];
            tensor<fp16, [64, 128]> generator_noise_res_3_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_noise_res_3_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40658880)))];
            tensor<fp16, [64]> generator_noise_res_3_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_noise_res_3_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40675328)))];
            tensor<fp16, [1, 64]> linear_74_cast_fp16 = linear(bias = generator_noise_res_3_adain1_1_fc_bias_to_fp16, weight = generator_noise_res_3_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_74_cast_fp16")];
            tensor<int32, [3]> var_2911 = const()[name = string("op_2911"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_299_cast_fp16 = reshape(shape = var_2911, x = linear_74_cast_fp16)[name = string("h_299_cast_fp16")];
            tensor<int32, [2]> var_2913_split_sizes_0 = const()[name = string("op_2913_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_2913_axis_0 = const()[name = string("op_2913_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_2913_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_2913_cast_fp16_1 = split(axis = var_2913_axis_0, split_sizes = var_2913_split_sizes_0, x = h_299_cast_fp16)[name = string("op_2913_cast_fp16")];
            fp16 var_2915_promoted_to_fp16 = const()[name = string("op_2915_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_2916_cast_fp16 = add(x = var_2913_cast_fp16_0, y = var_2915_promoted_to_fp16)[name = string("op_2916_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2917_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_293_cast_fp16)[name = string("op_2917_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2918_cast_fp16 = mul(x = var_2916_cast_fp16, y = var_2917_cast_fp16)[name = string("op_2918_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_223_cast_fp16 = add(x = var_2918_cast_fp16, y = var_2913_cast_fp16_1)[name = string("xt_223_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_noise_res_3_alpha1_1_to_fp16 = const()[name = string("generator_noise_res_3_alpha1_1_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40675520)))];
            tensor<fp16, [1, 32, ?]> var_2923_cast_fp16 = mul(x = generator_noise_res_3_alpha1_1_to_fp16, y = xt_223_cast_fp16)[name = string("op_2923_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2924_cast_fp16 = sin(x = var_2923_cast_fp16)[name = string("op_2924_cast_fp16")];
            fp16 var_24_promoted_78_to_fp16 = const()[name = string("op_24_promoted_78_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_2925_cast_fp16 = pow(x = var_2924_cast_fp16, y = var_24_promoted_78_to_fp16)[name = string("op_2925_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_2920_to_fp16 = const()[name = string("op_2920_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40675648)))];
            tensor<fp16, [1, 32, ?]> var_2926_cast_fp16 = mul(x = var_2920_to_fp16, y = var_2925_cast_fp16)[name = string("op_2926_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_295_cast_fp16 = add(x = xt_223_cast_fp16, y = var_2926_cast_fp16)[name = string("input_295_cast_fp16")];
            string input_297_pad_type_0 = const()[name = string("input_297_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_297_pad_0 = const()[name = string("input_297_pad_0"), val = tensor<int32, [2]>([15, 15])];
            tensor<int32, [1]> input_297_dilations_0 = const()[name = string("input_297_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_297_strides_0 = const()[name = string("input_297_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_297_groups_0 = const()[name = string("input_297_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 11]> generator_noise_res_3_convs1_1_weight_to_fp16 = const()[name = string("generator_noise_res_3_convs1_1_weight_to_fp16"), val = tensor<fp16, [32, 32, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40675776)))];
            tensor<fp16, [32]> generator_noise_res_3_convs1_1_bias_to_fp16 = const()[name = string("generator_noise_res_3_convs1_1_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40698368)))];
            tensor<fp16, [1, 32, ?]> input_297_cast_fp16 = conv(bias = generator_noise_res_3_convs1_1_bias_to_fp16, dilations = input_297_dilations_0, groups = input_297_groups_0, pad = input_297_pad_0, pad_type = input_297_pad_type_0, strides = input_297_strides_0, weight = generator_noise_res_3_convs1_1_weight_to_fp16, x = input_295_cast_fp16)[name = string("input_297_cast_fp16")];
            tensor<fp16, [64, 128]> generator_noise_res_3_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_noise_res_3_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40698496)))];
            tensor<fp16, [64]> generator_noise_res_3_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_noise_res_3_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40714944)))];
            tensor<fp16, [1, 64]> linear_75_cast_fp16 = linear(bias = generator_noise_res_3_adain2_1_fc_bias_to_fp16, weight = generator_noise_res_3_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_75_cast_fp16")];
            tensor<int32, [3]> var_2941 = const()[name = string("op_2941"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_303_cast_fp16 = reshape(shape = var_2941, x = linear_75_cast_fp16)[name = string("h_303_cast_fp16")];
            tensor<int32, [2]> var_2943_split_sizes_0 = const()[name = string("op_2943_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_2943_axis_0 = const()[name = string("op_2943_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_2943_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_2943_cast_fp16_1 = split(axis = var_2943_axis_0, split_sizes = var_2943_split_sizes_0, x = h_303_cast_fp16)[name = string("op_2943_cast_fp16")];
            fp16 var_2945_promoted_to_fp16 = const()[name = string("op_2945_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_2946_cast_fp16 = add(x = var_2943_cast_fp16_0, y = var_2945_promoted_to_fp16)[name = string("op_2946_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2947_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_297_cast_fp16)[name = string("op_2947_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2948_cast_fp16 = mul(x = var_2946_cast_fp16, y = var_2947_cast_fp16)[name = string("op_2948_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_225_cast_fp16 = add(x = var_2948_cast_fp16, y = var_2943_cast_fp16_1)[name = string("xt_225_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_noise_res_3_alpha2_1_to_fp16 = const()[name = string("generator_noise_res_3_alpha2_1_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40715136)))];
            tensor<fp16, [1, 32, ?]> var_2953_cast_fp16 = mul(x = generator_noise_res_3_alpha2_1_to_fp16, y = xt_225_cast_fp16)[name = string("op_2953_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2954_cast_fp16 = sin(x = var_2953_cast_fp16)[name = string("op_2954_cast_fp16")];
            fp16 var_24_promoted_79_to_fp16 = const()[name = string("op_24_promoted_79_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_2955_cast_fp16 = pow(x = var_2954_cast_fp16, y = var_24_promoted_79_to_fp16)[name = string("op_2955_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_2950_to_fp16 = const()[name = string("op_2950_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40715264)))];
            tensor<fp16, [1, 32, ?]> var_2956_cast_fp16 = mul(x = var_2950_to_fp16, y = var_2955_cast_fp16)[name = string("op_2956_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_299_cast_fp16 = add(x = xt_225_cast_fp16, y = var_2956_cast_fp16)[name = string("input_299_cast_fp16")];
            string xt_227_pad_type_0 = const()[name = string("xt_227_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_227_pad_0 = const()[name = string("xt_227_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_227_strides_0 = const()[name = string("xt_227_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_227_dilations_0 = const()[name = string("xt_227_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_227_groups_0 = const()[name = string("xt_227_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 11]> generator_noise_res_3_convs2_1_weight_to_fp16 = const()[name = string("generator_noise_res_3_convs2_1_weight_to_fp16"), val = tensor<fp16, [32, 32, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40715392)))];
            tensor<fp16, [32]> generator_noise_res_3_convs2_1_bias_to_fp16 = const()[name = string("generator_noise_res_3_convs2_1_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40737984)))];
            tensor<fp16, [1, 32, ?]> xt_227_cast_fp16 = conv(bias = generator_noise_res_3_convs2_1_bias_to_fp16, dilations = xt_227_dilations_0, groups = xt_227_groups_0, pad = xt_227_pad_0, pad_type = xt_227_pad_type_0, strides = xt_227_strides_0, weight = generator_noise_res_3_convs2_1_weight_to_fp16, x = input_299_cast_fp16)[name = string("xt_227_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_301_cast_fp16 = add(x = xt_227_cast_fp16, y = input_293_cast_fp16)[name = string("input_301_cast_fp16")];
            tensor<fp16, [64, 128]> generator_noise_res_3_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_noise_res_3_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40738112)))];
            tensor<fp16, [64]> generator_noise_res_3_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_noise_res_3_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40754560)))];
            tensor<fp16, [1, 64]> linear_76_cast_fp16 = linear(bias = generator_noise_res_3_adain1_2_fc_bias_to_fp16, weight = generator_noise_res_3_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_76_cast_fp16")];
            tensor<int32, [3]> var_2972 = const()[name = string("op_2972"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_307_cast_fp16 = reshape(shape = var_2972, x = linear_76_cast_fp16)[name = string("h_307_cast_fp16")];
            tensor<int32, [2]> var_2974_split_sizes_0 = const()[name = string("op_2974_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_2974_axis_0 = const()[name = string("op_2974_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_2974_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_2974_cast_fp16_1 = split(axis = var_2974_axis_0, split_sizes = var_2974_split_sizes_0, x = h_307_cast_fp16)[name = string("op_2974_cast_fp16")];
            fp16 var_2976_promoted_to_fp16 = const()[name = string("op_2976_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_2977_cast_fp16 = add(x = var_2974_cast_fp16_0, y = var_2976_promoted_to_fp16)[name = string("op_2977_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2978_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_301_cast_fp16)[name = string("op_2978_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2979_cast_fp16 = mul(x = var_2977_cast_fp16, y = var_2978_cast_fp16)[name = string("op_2979_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_229_cast_fp16 = add(x = var_2979_cast_fp16, y = var_2974_cast_fp16_1)[name = string("xt_229_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_noise_res_3_alpha1_2_to_fp16 = const()[name = string("generator_noise_res_3_alpha1_2_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40754752)))];
            tensor<fp16, [1, 32, ?]> var_2984_cast_fp16 = mul(x = generator_noise_res_3_alpha1_2_to_fp16, y = xt_229_cast_fp16)[name = string("op_2984_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2985_cast_fp16 = sin(x = var_2984_cast_fp16)[name = string("op_2985_cast_fp16")];
            fp16 var_24_promoted_80_to_fp16 = const()[name = string("op_24_promoted_80_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_2986_cast_fp16 = pow(x = var_2985_cast_fp16, y = var_24_promoted_80_to_fp16)[name = string("op_2986_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_2981_to_fp16 = const()[name = string("op_2981_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40754880)))];
            tensor<fp16, [1, 32, ?]> var_2987_cast_fp16 = mul(x = var_2981_to_fp16, y = var_2986_cast_fp16)[name = string("op_2987_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_303_cast_fp16 = add(x = xt_229_cast_fp16, y = var_2987_cast_fp16)[name = string("input_303_cast_fp16")];
            string input_305_pad_type_0 = const()[name = string("input_305_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_305_pad_0 = const()[name = string("input_305_pad_0"), val = tensor<int32, [2]>([25, 25])];
            tensor<int32, [1]> input_305_dilations_0 = const()[name = string("input_305_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_305_strides_0 = const()[name = string("input_305_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_305_groups_0 = const()[name = string("input_305_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 11]> generator_noise_res_3_convs1_2_weight_to_fp16 = const()[name = string("generator_noise_res_3_convs1_2_weight_to_fp16"), val = tensor<fp16, [32, 32, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40755008)))];
            tensor<fp16, [32]> generator_noise_res_3_convs1_2_bias_to_fp16 = const()[name = string("generator_noise_res_3_convs1_2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40777600)))];
            tensor<fp16, [1, 32, ?]> input_305_cast_fp16 = conv(bias = generator_noise_res_3_convs1_2_bias_to_fp16, dilations = input_305_dilations_0, groups = input_305_groups_0, pad = input_305_pad_0, pad_type = input_305_pad_type_0, strides = input_305_strides_0, weight = generator_noise_res_3_convs1_2_weight_to_fp16, x = input_303_cast_fp16)[name = string("input_305_cast_fp16")];
            tensor<fp16, [64, 128]> generator_noise_res_3_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_noise_res_3_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40777728)))];
            tensor<fp16, [64]> generator_noise_res_3_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_noise_res_3_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40794176)))];
            tensor<fp16, [1, 64]> linear_77_cast_fp16 = linear(bias = generator_noise_res_3_adain2_2_fc_bias_to_fp16, weight = generator_noise_res_3_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_77_cast_fp16")];
            tensor<int32, [3]> var_3002 = const()[name = string("op_3002"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_311_cast_fp16 = reshape(shape = var_3002, x = linear_77_cast_fp16)[name = string("h_311_cast_fp16")];
            tensor<int32, [2]> var_3004_split_sizes_0 = const()[name = string("op_3004_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3004_axis_0 = const()[name = string("op_3004_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3004_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3004_cast_fp16_1 = split(axis = var_3004_axis_0, split_sizes = var_3004_split_sizes_0, x = h_311_cast_fp16)[name = string("op_3004_cast_fp16")];
            fp16 var_3006_promoted_to_fp16 = const()[name = string("op_3006_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3007_cast_fp16 = add(x = var_3004_cast_fp16_0, y = var_3006_promoted_to_fp16)[name = string("op_3007_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3008_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_305_cast_fp16)[name = string("op_3008_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3009_cast_fp16 = mul(x = var_3007_cast_fp16, y = var_3008_cast_fp16)[name = string("op_3009_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_231_cast_fp16 = add(x = var_3009_cast_fp16, y = var_3004_cast_fp16_1)[name = string("xt_231_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_noise_res_3_alpha2_2_to_fp16 = const()[name = string("generator_noise_res_3_alpha2_2_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40794368)))];
            tensor<fp16, [1, 32, ?]> var_3014_cast_fp16 = mul(x = generator_noise_res_3_alpha2_2_to_fp16, y = xt_231_cast_fp16)[name = string("op_3014_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3015_cast_fp16 = sin(x = var_3014_cast_fp16)[name = string("op_3015_cast_fp16")];
            fp16 var_24_promoted_81_to_fp16 = const()[name = string("op_24_promoted_81_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3016_cast_fp16 = pow(x = var_3015_cast_fp16, y = var_24_promoted_81_to_fp16)[name = string("op_3016_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3011_to_fp16 = const()[name = string("op_3011_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40794496)))];
            tensor<fp16, [1, 32, ?]> var_3017_cast_fp16 = mul(x = var_3011_to_fp16, y = var_3016_cast_fp16)[name = string("op_3017_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_307_cast_fp16 = add(x = xt_231_cast_fp16, y = var_3017_cast_fp16)[name = string("input_307_cast_fp16")];
            string xt_233_pad_type_0 = const()[name = string("xt_233_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_233_pad_0 = const()[name = string("xt_233_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_233_strides_0 = const()[name = string("xt_233_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_233_dilations_0 = const()[name = string("xt_233_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_233_groups_0 = const()[name = string("xt_233_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 11]> generator_noise_res_3_convs2_2_weight_to_fp16 = const()[name = string("generator_noise_res_3_convs2_2_weight_to_fp16"), val = tensor<fp16, [32, 32, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40794624)))];
            tensor<fp16, [32]> generator_noise_res_3_convs2_2_bias_to_fp16 = const()[name = string("generator_noise_res_3_convs2_2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40817216)))];
            tensor<fp16, [1, 32, ?]> xt_233_cast_fp16 = conv(bias = generator_noise_res_3_convs2_2_bias_to_fp16, dilations = xt_233_dilations_0, groups = xt_233_groups_0, pad = xt_233_pad_0, pad_type = xt_233_pad_type_0, strides = xt_233_strides_0, weight = generator_noise_res_3_convs2_2_weight_to_fp16, x = input_307_cast_fp16)[name = string("xt_233_cast_fp16")];
            tensor<fp16, [1, 32, ?]> x_source_cast_fp16 = add(x = xt_233_cast_fp16, y = input_301_cast_fp16)[name = string("x_source_cast_fp16")];
            string x_13_pad_type_0 = const()[name = string("x_13_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> x_13_pad_0 = const()[name = string("x_13_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> x_13_strides_0 = const()[name = string("x_13_strides_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> x_13_dilations_0 = const()[name = string("x_13_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_13_groups_0 = const()[name = string("x_13_groups_0"), val = int32(1)];
            tensor<fp16, [64, 32, 4]> generator_ups_3_weight_to_fp16 = const()[name = string("generator_ups_3_weight_to_fp16"), val = tensor<fp16, [64, 32, 4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40817344)))];
            tensor<fp16, [32]> generator_ups_3_bias_to_fp16 = const()[name = string("generator_ups_3_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40833792)))];
            tensor<fp16, [1, 32, ?]> x_13_cast_fp16 = conv_transpose(bias = generator_ups_3_bias_to_fp16, dilations = x_13_dilations_0, groups = x_13_groups_0, pad = x_13_pad_0, pad_type = x_13_pad_type_0, strides = x_13_strides_0, weight = generator_ups_3_weight_to_fp16, x = input_309_cast_fp16)[name = string("x_13_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_311_cast_fp16 = add(x = x_13_cast_fp16, y = x_source_cast_fp16)[name = string("input_311_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_9_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_9_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40833920)))];
            tensor<fp16, [64]> generator_resblocks_9_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_9_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40850368)))];
            tensor<fp16, [1, 64]> linear_78_cast_fp16 = linear(bias = generator_resblocks_9_adain1_0_fc_bias_to_fp16, weight = generator_resblocks_9_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_78_cast_fp16")];
            tensor<int32, [3]> var_3077 = const()[name = string("op_3077"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_315_cast_fp16 = reshape(shape = var_3077, x = linear_78_cast_fp16)[name = string("h_315_cast_fp16")];
            tensor<int32, [2]> var_3079_split_sizes_0 = const()[name = string("op_3079_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3079_axis_0 = const()[name = string("op_3079_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3079_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3079_cast_fp16_1 = split(axis = var_3079_axis_0, split_sizes = var_3079_split_sizes_0, x = h_315_cast_fp16)[name = string("op_3079_cast_fp16")];
            fp16 var_3081_promoted_to_fp16 = const()[name = string("op_3081_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3082_cast_fp16 = add(x = var_3079_cast_fp16_0, y = var_3081_promoted_to_fp16)[name = string("op_3082_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3083_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_311_cast_fp16)[name = string("op_3083_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3084_cast_fp16 = mul(x = var_3082_cast_fp16, y = var_3083_cast_fp16)[name = string("op_3084_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_235_cast_fp16 = add(x = var_3084_cast_fp16, y = var_3079_cast_fp16_1)[name = string("xt_235_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_9_alpha1_0_to_fp16 = const()[name = string("generator_resblocks_9_alpha1_0_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40850560)))];
            tensor<fp16, [1, 32, ?]> var_3089_cast_fp16 = mul(x = generator_resblocks_9_alpha1_0_to_fp16, y = xt_235_cast_fp16)[name = string("op_3089_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3090_cast_fp16 = sin(x = var_3089_cast_fp16)[name = string("op_3090_cast_fp16")];
            fp16 var_24_promoted_82_to_fp16 = const()[name = string("op_24_promoted_82_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3091_cast_fp16 = pow(x = var_3090_cast_fp16, y = var_24_promoted_82_to_fp16)[name = string("op_3091_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3086_to_fp16 = const()[name = string("op_3086_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40850688)))];
            tensor<fp16, [1, 32, ?]> var_3092_cast_fp16 = mul(x = var_3086_to_fp16, y = var_3091_cast_fp16)[name = string("op_3092_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_313_cast_fp16 = add(x = xt_235_cast_fp16, y = var_3092_cast_fp16)[name = string("input_313_cast_fp16")];
            string input_315_pad_type_0 = const()[name = string("input_315_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_315_pad_0 = const()[name = string("input_315_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> input_315_strides_0 = const()[name = string("input_315_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_315_dilations_0 = const()[name = string("input_315_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_315_groups_0 = const()[name = string("input_315_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 3]> generator_resblocks_9_convs1_0_weight_to_fp16 = const()[name = string("generator_resblocks_9_convs1_0_weight_to_fp16"), val = tensor<fp16, [32, 32, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40850816)))];
            tensor<fp16, [32]> generator_resblocks_9_convs1_0_bias_to_fp16 = const()[name = string("generator_resblocks_9_convs1_0_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40857024)))];
            tensor<fp16, [1, 32, ?]> input_315_cast_fp16 = conv(bias = generator_resblocks_9_convs1_0_bias_to_fp16, dilations = input_315_dilations_0, groups = input_315_groups_0, pad = input_315_pad_0, pad_type = input_315_pad_type_0, strides = input_315_strides_0, weight = generator_resblocks_9_convs1_0_weight_to_fp16, x = input_313_cast_fp16)[name = string("input_315_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_9_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_9_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40857152)))];
            tensor<fp16, [64]> generator_resblocks_9_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_9_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40873600)))];
            tensor<fp16, [1, 64]> linear_79_cast_fp16 = linear(bias = generator_resblocks_9_adain2_0_fc_bias_to_fp16, weight = generator_resblocks_9_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_79_cast_fp16")];
            tensor<int32, [3]> var_3107 = const()[name = string("op_3107"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_319_cast_fp16 = reshape(shape = var_3107, x = linear_79_cast_fp16)[name = string("h_319_cast_fp16")];
            tensor<int32, [2]> var_3109_split_sizes_0 = const()[name = string("op_3109_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3109_axis_0 = const()[name = string("op_3109_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3109_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3109_cast_fp16_1 = split(axis = var_3109_axis_0, split_sizes = var_3109_split_sizes_0, x = h_319_cast_fp16)[name = string("op_3109_cast_fp16")];
            fp16 var_3111_promoted_to_fp16 = const()[name = string("op_3111_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3112_cast_fp16 = add(x = var_3109_cast_fp16_0, y = var_3111_promoted_to_fp16)[name = string("op_3112_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3113_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_315_cast_fp16)[name = string("op_3113_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3114_cast_fp16 = mul(x = var_3112_cast_fp16, y = var_3113_cast_fp16)[name = string("op_3114_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_237_cast_fp16 = add(x = var_3114_cast_fp16, y = var_3109_cast_fp16_1)[name = string("xt_237_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_9_alpha2_0_to_fp16 = const()[name = string("generator_resblocks_9_alpha2_0_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40873792)))];
            tensor<fp16, [1, 32, ?]> var_3119_cast_fp16 = mul(x = generator_resblocks_9_alpha2_0_to_fp16, y = xt_237_cast_fp16)[name = string("op_3119_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3120_cast_fp16 = sin(x = var_3119_cast_fp16)[name = string("op_3120_cast_fp16")];
            fp16 var_24_promoted_83_to_fp16 = const()[name = string("op_24_promoted_83_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3121_cast_fp16 = pow(x = var_3120_cast_fp16, y = var_24_promoted_83_to_fp16)[name = string("op_3121_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3116_to_fp16 = const()[name = string("op_3116_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40873920)))];
            tensor<fp16, [1, 32, ?]> var_3122_cast_fp16 = mul(x = var_3116_to_fp16, y = var_3121_cast_fp16)[name = string("op_3122_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_317_cast_fp16 = add(x = xt_237_cast_fp16, y = var_3122_cast_fp16)[name = string("input_317_cast_fp16")];
            string xt_239_pad_type_0 = const()[name = string("xt_239_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_239_pad_0 = const()[name = string("xt_239_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> xt_239_strides_0 = const()[name = string("xt_239_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_239_dilations_0 = const()[name = string("xt_239_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_239_groups_0 = const()[name = string("xt_239_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 3]> generator_resblocks_9_convs2_0_weight_to_fp16 = const()[name = string("generator_resblocks_9_convs2_0_weight_to_fp16"), val = tensor<fp16, [32, 32, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40874048)))];
            tensor<fp16, [32]> generator_resblocks_9_convs2_0_bias_to_fp16 = const()[name = string("generator_resblocks_9_convs2_0_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40880256)))];
            tensor<fp16, [1, 32, ?]> xt_239_cast_fp16 = conv(bias = generator_resblocks_9_convs2_0_bias_to_fp16, dilations = xt_239_dilations_0, groups = xt_239_groups_0, pad = xt_239_pad_0, pad_type = xt_239_pad_type_0, strides = xt_239_strides_0, weight = generator_resblocks_9_convs2_0_weight_to_fp16, x = input_317_cast_fp16)[name = string("xt_239_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_319_cast_fp16 = add(x = xt_239_cast_fp16, y = input_311_cast_fp16)[name = string("input_319_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_9_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_9_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40880384)))];
            tensor<fp16, [64]> generator_resblocks_9_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_9_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40896832)))];
            tensor<fp16, [1, 64]> linear_80_cast_fp16 = linear(bias = generator_resblocks_9_adain1_1_fc_bias_to_fp16, weight = generator_resblocks_9_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_80_cast_fp16")];
            tensor<int32, [3]> var_3138 = const()[name = string("op_3138"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_323_cast_fp16 = reshape(shape = var_3138, x = linear_80_cast_fp16)[name = string("h_323_cast_fp16")];
            tensor<int32, [2]> var_3140_split_sizes_0 = const()[name = string("op_3140_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3140_axis_0 = const()[name = string("op_3140_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3140_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3140_cast_fp16_1 = split(axis = var_3140_axis_0, split_sizes = var_3140_split_sizes_0, x = h_323_cast_fp16)[name = string("op_3140_cast_fp16")];
            fp16 var_3142_promoted_to_fp16 = const()[name = string("op_3142_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3143_cast_fp16 = add(x = var_3140_cast_fp16_0, y = var_3142_promoted_to_fp16)[name = string("op_3143_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3144_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_319_cast_fp16)[name = string("op_3144_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3145_cast_fp16 = mul(x = var_3143_cast_fp16, y = var_3144_cast_fp16)[name = string("op_3145_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_241_cast_fp16 = add(x = var_3145_cast_fp16, y = var_3140_cast_fp16_1)[name = string("xt_241_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_9_alpha1_1_to_fp16 = const()[name = string("generator_resblocks_9_alpha1_1_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40897024)))];
            tensor<fp16, [1, 32, ?]> var_3150_cast_fp16 = mul(x = generator_resblocks_9_alpha1_1_to_fp16, y = xt_241_cast_fp16)[name = string("op_3150_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3151_cast_fp16 = sin(x = var_3150_cast_fp16)[name = string("op_3151_cast_fp16")];
            fp16 var_24_promoted_84_to_fp16 = const()[name = string("op_24_promoted_84_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3152_cast_fp16 = pow(x = var_3151_cast_fp16, y = var_24_promoted_84_to_fp16)[name = string("op_3152_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3147_to_fp16 = const()[name = string("op_3147_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40897152)))];
            tensor<fp16, [1, 32, ?]> var_3153_cast_fp16 = mul(x = var_3147_to_fp16, y = var_3152_cast_fp16)[name = string("op_3153_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_321_cast_fp16 = add(x = xt_241_cast_fp16, y = var_3153_cast_fp16)[name = string("input_321_cast_fp16")];
            string input_323_pad_type_0 = const()[name = string("input_323_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_323_pad_0 = const()[name = string("input_323_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> input_323_dilations_0 = const()[name = string("input_323_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_323_strides_0 = const()[name = string("input_323_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_323_groups_0 = const()[name = string("input_323_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 3]> generator_resblocks_9_convs1_1_weight_to_fp16 = const()[name = string("generator_resblocks_9_convs1_1_weight_to_fp16"), val = tensor<fp16, [32, 32, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40897280)))];
            tensor<fp16, [32]> generator_resblocks_9_convs1_1_bias_to_fp16 = const()[name = string("generator_resblocks_9_convs1_1_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40903488)))];
            tensor<fp16, [1, 32, ?]> input_323_cast_fp16 = conv(bias = generator_resblocks_9_convs1_1_bias_to_fp16, dilations = input_323_dilations_0, groups = input_323_groups_0, pad = input_323_pad_0, pad_type = input_323_pad_type_0, strides = input_323_strides_0, weight = generator_resblocks_9_convs1_1_weight_to_fp16, x = input_321_cast_fp16)[name = string("input_323_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_9_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_9_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40903616)))];
            tensor<fp16, [64]> generator_resblocks_9_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_9_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40920064)))];
            tensor<fp16, [1, 64]> linear_81_cast_fp16 = linear(bias = generator_resblocks_9_adain2_1_fc_bias_to_fp16, weight = generator_resblocks_9_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_81_cast_fp16")];
            tensor<int32, [3]> var_3168 = const()[name = string("op_3168"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_327_cast_fp16 = reshape(shape = var_3168, x = linear_81_cast_fp16)[name = string("h_327_cast_fp16")];
            tensor<int32, [2]> var_3170_split_sizes_0 = const()[name = string("op_3170_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3170_axis_0 = const()[name = string("op_3170_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3170_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3170_cast_fp16_1 = split(axis = var_3170_axis_0, split_sizes = var_3170_split_sizes_0, x = h_327_cast_fp16)[name = string("op_3170_cast_fp16")];
            fp16 var_3172_promoted_to_fp16 = const()[name = string("op_3172_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3173_cast_fp16 = add(x = var_3170_cast_fp16_0, y = var_3172_promoted_to_fp16)[name = string("op_3173_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3174_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_323_cast_fp16)[name = string("op_3174_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3175_cast_fp16 = mul(x = var_3173_cast_fp16, y = var_3174_cast_fp16)[name = string("op_3175_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_243_cast_fp16 = add(x = var_3175_cast_fp16, y = var_3170_cast_fp16_1)[name = string("xt_243_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_9_alpha2_1_to_fp16 = const()[name = string("generator_resblocks_9_alpha2_1_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40920256)))];
            tensor<fp16, [1, 32, ?]> var_3180_cast_fp16 = mul(x = generator_resblocks_9_alpha2_1_to_fp16, y = xt_243_cast_fp16)[name = string("op_3180_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3181_cast_fp16 = sin(x = var_3180_cast_fp16)[name = string("op_3181_cast_fp16")];
            fp16 var_24_promoted_85_to_fp16 = const()[name = string("op_24_promoted_85_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3182_cast_fp16 = pow(x = var_3181_cast_fp16, y = var_24_promoted_85_to_fp16)[name = string("op_3182_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3177_to_fp16 = const()[name = string("op_3177_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40920384)))];
            tensor<fp16, [1, 32, ?]> var_3183_cast_fp16 = mul(x = var_3177_to_fp16, y = var_3182_cast_fp16)[name = string("op_3183_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_325_cast_fp16 = add(x = xt_243_cast_fp16, y = var_3183_cast_fp16)[name = string("input_325_cast_fp16")];
            string xt_245_pad_type_0 = const()[name = string("xt_245_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_245_pad_0 = const()[name = string("xt_245_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> xt_245_strides_0 = const()[name = string("xt_245_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_245_dilations_0 = const()[name = string("xt_245_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_245_groups_0 = const()[name = string("xt_245_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 3]> generator_resblocks_9_convs2_1_weight_to_fp16 = const()[name = string("generator_resblocks_9_convs2_1_weight_to_fp16"), val = tensor<fp16, [32, 32, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40920512)))];
            tensor<fp16, [32]> generator_resblocks_9_convs2_1_bias_to_fp16 = const()[name = string("generator_resblocks_9_convs2_1_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40926720)))];
            tensor<fp16, [1, 32, ?]> xt_245_cast_fp16 = conv(bias = generator_resblocks_9_convs2_1_bias_to_fp16, dilations = xt_245_dilations_0, groups = xt_245_groups_0, pad = xt_245_pad_0, pad_type = xt_245_pad_type_0, strides = xt_245_strides_0, weight = generator_resblocks_9_convs2_1_weight_to_fp16, x = input_325_cast_fp16)[name = string("xt_245_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_327_cast_fp16 = add(x = xt_245_cast_fp16, y = input_319_cast_fp16)[name = string("input_327_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_9_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_9_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40926848)))];
            tensor<fp16, [64]> generator_resblocks_9_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_9_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40943296)))];
            tensor<fp16, [1, 64]> linear_82_cast_fp16 = linear(bias = generator_resblocks_9_adain1_2_fc_bias_to_fp16, weight = generator_resblocks_9_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_82_cast_fp16")];
            tensor<int32, [3]> var_3199 = const()[name = string("op_3199"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_331_cast_fp16 = reshape(shape = var_3199, x = linear_82_cast_fp16)[name = string("h_331_cast_fp16")];
            tensor<int32, [2]> var_3201_split_sizes_0 = const()[name = string("op_3201_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3201_axis_0 = const()[name = string("op_3201_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3201_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3201_cast_fp16_1 = split(axis = var_3201_axis_0, split_sizes = var_3201_split_sizes_0, x = h_331_cast_fp16)[name = string("op_3201_cast_fp16")];
            fp16 var_3203_promoted_to_fp16 = const()[name = string("op_3203_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3204_cast_fp16 = add(x = var_3201_cast_fp16_0, y = var_3203_promoted_to_fp16)[name = string("op_3204_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3205_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_327_cast_fp16)[name = string("op_3205_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3206_cast_fp16 = mul(x = var_3204_cast_fp16, y = var_3205_cast_fp16)[name = string("op_3206_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_247_cast_fp16 = add(x = var_3206_cast_fp16, y = var_3201_cast_fp16_1)[name = string("xt_247_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_9_alpha1_2_to_fp16 = const()[name = string("generator_resblocks_9_alpha1_2_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40943488)))];
            tensor<fp16, [1, 32, ?]> var_3211_cast_fp16 = mul(x = generator_resblocks_9_alpha1_2_to_fp16, y = xt_247_cast_fp16)[name = string("op_3211_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3212_cast_fp16 = sin(x = var_3211_cast_fp16)[name = string("op_3212_cast_fp16")];
            fp16 var_24_promoted_86_to_fp16 = const()[name = string("op_24_promoted_86_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3213_cast_fp16 = pow(x = var_3212_cast_fp16, y = var_24_promoted_86_to_fp16)[name = string("op_3213_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3208_to_fp16 = const()[name = string("op_3208_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40943616)))];
            tensor<fp16, [1, 32, ?]> var_3214_cast_fp16 = mul(x = var_3208_to_fp16, y = var_3213_cast_fp16)[name = string("op_3214_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_329_cast_fp16 = add(x = xt_247_cast_fp16, y = var_3214_cast_fp16)[name = string("input_329_cast_fp16")];
            string input_331_pad_type_0 = const()[name = string("input_331_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_331_pad_0 = const()[name = string("input_331_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> input_331_dilations_0 = const()[name = string("input_331_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_331_strides_0 = const()[name = string("input_331_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_331_groups_0 = const()[name = string("input_331_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 3]> generator_resblocks_9_convs1_2_weight_to_fp16 = const()[name = string("generator_resblocks_9_convs1_2_weight_to_fp16"), val = tensor<fp16, [32, 32, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40943744)))];
            tensor<fp16, [32]> generator_resblocks_9_convs1_2_bias_to_fp16 = const()[name = string("generator_resblocks_9_convs1_2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40949952)))];
            tensor<fp16, [1, 32, ?]> input_331_cast_fp16 = conv(bias = generator_resblocks_9_convs1_2_bias_to_fp16, dilations = input_331_dilations_0, groups = input_331_groups_0, pad = input_331_pad_0, pad_type = input_331_pad_type_0, strides = input_331_strides_0, weight = generator_resblocks_9_convs1_2_weight_to_fp16, x = input_329_cast_fp16)[name = string("input_331_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_9_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_9_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40950080)))];
            tensor<fp16, [64]> generator_resblocks_9_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_9_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40966528)))];
            tensor<fp16, [1, 64]> linear_83_cast_fp16 = linear(bias = generator_resblocks_9_adain2_2_fc_bias_to_fp16, weight = generator_resblocks_9_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_83_cast_fp16")];
            tensor<int32, [3]> var_3229 = const()[name = string("op_3229"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_335_cast_fp16 = reshape(shape = var_3229, x = linear_83_cast_fp16)[name = string("h_335_cast_fp16")];
            tensor<int32, [2]> var_3231_split_sizes_0 = const()[name = string("op_3231_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3231_axis_0 = const()[name = string("op_3231_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3231_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3231_cast_fp16_1 = split(axis = var_3231_axis_0, split_sizes = var_3231_split_sizes_0, x = h_335_cast_fp16)[name = string("op_3231_cast_fp16")];
            fp16 var_3233_promoted_to_fp16 = const()[name = string("op_3233_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3234_cast_fp16 = add(x = var_3231_cast_fp16_0, y = var_3233_promoted_to_fp16)[name = string("op_3234_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3235_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_331_cast_fp16)[name = string("op_3235_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3236_cast_fp16 = mul(x = var_3234_cast_fp16, y = var_3235_cast_fp16)[name = string("op_3236_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_249_cast_fp16 = add(x = var_3236_cast_fp16, y = var_3231_cast_fp16_1)[name = string("xt_249_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_9_alpha2_2_to_fp16 = const()[name = string("generator_resblocks_9_alpha2_2_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40966720)))];
            tensor<fp16, [1, 32, ?]> var_3241_cast_fp16 = mul(x = generator_resblocks_9_alpha2_2_to_fp16, y = xt_249_cast_fp16)[name = string("op_3241_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3242_cast_fp16 = sin(x = var_3241_cast_fp16)[name = string("op_3242_cast_fp16")];
            fp16 var_24_promoted_87_to_fp16 = const()[name = string("op_24_promoted_87_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3243_cast_fp16 = pow(x = var_3242_cast_fp16, y = var_24_promoted_87_to_fp16)[name = string("op_3243_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3238_to_fp16 = const()[name = string("op_3238_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40966848)))];
            tensor<fp16, [1, 32, ?]> var_3244_cast_fp16 = mul(x = var_3238_to_fp16, y = var_3243_cast_fp16)[name = string("op_3244_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_333_cast_fp16 = add(x = xt_249_cast_fp16, y = var_3244_cast_fp16)[name = string("input_333_cast_fp16")];
            string xt_251_pad_type_0 = const()[name = string("xt_251_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_251_pad_0 = const()[name = string("xt_251_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> xt_251_strides_0 = const()[name = string("xt_251_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_251_dilations_0 = const()[name = string("xt_251_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_251_groups_0 = const()[name = string("xt_251_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 3]> generator_resblocks_9_convs2_2_weight_to_fp16 = const()[name = string("generator_resblocks_9_convs2_2_weight_to_fp16"), val = tensor<fp16, [32, 32, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40966976)))];
            tensor<fp16, [32]> generator_resblocks_9_convs2_2_bias_to_fp16 = const()[name = string("generator_resblocks_9_convs2_2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40973184)))];
            tensor<fp16, [1, 32, ?]> xt_251_cast_fp16 = conv(bias = generator_resblocks_9_convs2_2_bias_to_fp16, dilations = xt_251_dilations_0, groups = xt_251_groups_0, pad = xt_251_pad_0, pad_type = xt_251_pad_type_0, strides = xt_251_strides_0, weight = generator_resblocks_9_convs2_2_weight_to_fp16, x = input_333_cast_fp16)[name = string("xt_251_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xs_19_cast_fp16 = add(x = xt_251_cast_fp16, y = input_327_cast_fp16)[name = string("xs_19_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_10_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_10_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40973312)))];
            tensor<fp16, [64]> generator_resblocks_10_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_10_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40989760)))];
            tensor<fp16, [1, 64]> linear_84_cast_fp16 = linear(bias = generator_resblocks_10_adain1_0_fc_bias_to_fp16, weight = generator_resblocks_10_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_84_cast_fp16")];
            tensor<int32, [3]> var_3296 = const()[name = string("op_3296"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_339_cast_fp16 = reshape(shape = var_3296, x = linear_84_cast_fp16)[name = string("h_339_cast_fp16")];
            tensor<int32, [2]> var_3298_split_sizes_0 = const()[name = string("op_3298_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3298_axis_0 = const()[name = string("op_3298_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3298_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3298_cast_fp16_1 = split(axis = var_3298_axis_0, split_sizes = var_3298_split_sizes_0, x = h_339_cast_fp16)[name = string("op_3298_cast_fp16")];
            fp16 var_3300_promoted_to_fp16 = const()[name = string("op_3300_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3301_cast_fp16 = add(x = var_3298_cast_fp16_0, y = var_3300_promoted_to_fp16)[name = string("op_3301_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3303_cast_fp16 = mul(x = var_3301_cast_fp16, y = var_3083_cast_fp16)[name = string("op_3303_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_253_cast_fp16 = add(x = var_3303_cast_fp16, y = var_3298_cast_fp16_1)[name = string("xt_253_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_10_alpha1_0_to_fp16 = const()[name = string("generator_resblocks_10_alpha1_0_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40989952)))];
            tensor<fp16, [1, 32, ?]> var_3308_cast_fp16 = mul(x = generator_resblocks_10_alpha1_0_to_fp16, y = xt_253_cast_fp16)[name = string("op_3308_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3309_cast_fp16 = sin(x = var_3308_cast_fp16)[name = string("op_3309_cast_fp16")];
            fp16 var_24_promoted_88_to_fp16 = const()[name = string("op_24_promoted_88_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3310_cast_fp16 = pow(x = var_3309_cast_fp16, y = var_24_promoted_88_to_fp16)[name = string("op_3310_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3305_to_fp16 = const()[name = string("op_3305_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40990080)))];
            tensor<fp16, [1, 32, ?]> var_3311_cast_fp16 = mul(x = var_3305_to_fp16, y = var_3310_cast_fp16)[name = string("op_3311_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_335_cast_fp16 = add(x = xt_253_cast_fp16, y = var_3311_cast_fp16)[name = string("input_335_cast_fp16")];
            string input_337_pad_type_0 = const()[name = string("input_337_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_337_pad_0 = const()[name = string("input_337_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> input_337_strides_0 = const()[name = string("input_337_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_337_dilations_0 = const()[name = string("input_337_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_337_groups_0 = const()[name = string("input_337_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 7]> generator_resblocks_10_convs1_0_weight_to_fp16 = const()[name = string("generator_resblocks_10_convs1_0_weight_to_fp16"), val = tensor<fp16, [32, 32, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40990208)))];
            tensor<fp16, [32]> generator_resblocks_10_convs1_0_bias_to_fp16 = const()[name = string("generator_resblocks_10_convs1_0_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41004608)))];
            tensor<fp16, [1, 32, ?]> input_337_cast_fp16 = conv(bias = generator_resblocks_10_convs1_0_bias_to_fp16, dilations = input_337_dilations_0, groups = input_337_groups_0, pad = input_337_pad_0, pad_type = input_337_pad_type_0, strides = input_337_strides_0, weight = generator_resblocks_10_convs1_0_weight_to_fp16, x = input_335_cast_fp16)[name = string("input_337_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_10_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_10_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41004736)))];
            tensor<fp16, [64]> generator_resblocks_10_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_10_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41021184)))];
            tensor<fp16, [1, 64]> linear_85_cast_fp16 = linear(bias = generator_resblocks_10_adain2_0_fc_bias_to_fp16, weight = generator_resblocks_10_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_85_cast_fp16")];
            tensor<int32, [3]> var_3326 = const()[name = string("op_3326"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_343_cast_fp16 = reshape(shape = var_3326, x = linear_85_cast_fp16)[name = string("h_343_cast_fp16")];
            tensor<int32, [2]> var_3328_split_sizes_0 = const()[name = string("op_3328_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3328_axis_0 = const()[name = string("op_3328_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3328_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3328_cast_fp16_1 = split(axis = var_3328_axis_0, split_sizes = var_3328_split_sizes_0, x = h_343_cast_fp16)[name = string("op_3328_cast_fp16")];
            fp16 var_3330_promoted_to_fp16 = const()[name = string("op_3330_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3331_cast_fp16 = add(x = var_3328_cast_fp16_0, y = var_3330_promoted_to_fp16)[name = string("op_3331_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3332_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_337_cast_fp16)[name = string("op_3332_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3333_cast_fp16 = mul(x = var_3331_cast_fp16, y = var_3332_cast_fp16)[name = string("op_3333_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_255_cast_fp16 = add(x = var_3333_cast_fp16, y = var_3328_cast_fp16_1)[name = string("xt_255_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_10_alpha2_0_to_fp16 = const()[name = string("generator_resblocks_10_alpha2_0_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41021376)))];
            tensor<fp16, [1, 32, ?]> var_3338_cast_fp16 = mul(x = generator_resblocks_10_alpha2_0_to_fp16, y = xt_255_cast_fp16)[name = string("op_3338_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3339_cast_fp16 = sin(x = var_3338_cast_fp16)[name = string("op_3339_cast_fp16")];
            fp16 var_24_promoted_89_to_fp16 = const()[name = string("op_24_promoted_89_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3340_cast_fp16 = pow(x = var_3339_cast_fp16, y = var_24_promoted_89_to_fp16)[name = string("op_3340_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3335_to_fp16 = const()[name = string("op_3335_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41021504)))];
            tensor<fp16, [1, 32, ?]> var_3341_cast_fp16 = mul(x = var_3335_to_fp16, y = var_3340_cast_fp16)[name = string("op_3341_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_339_cast_fp16 = add(x = xt_255_cast_fp16, y = var_3341_cast_fp16)[name = string("input_339_cast_fp16")];
            string xt_257_pad_type_0 = const()[name = string("xt_257_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_257_pad_0 = const()[name = string("xt_257_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_257_strides_0 = const()[name = string("xt_257_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_257_dilations_0 = const()[name = string("xt_257_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_257_groups_0 = const()[name = string("xt_257_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 7]> generator_resblocks_10_convs2_0_weight_to_fp16 = const()[name = string("generator_resblocks_10_convs2_0_weight_to_fp16"), val = tensor<fp16, [32, 32, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41021632)))];
            tensor<fp16, [32]> generator_resblocks_10_convs2_0_bias_to_fp16 = const()[name = string("generator_resblocks_10_convs2_0_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41036032)))];
            tensor<fp16, [1, 32, ?]> xt_257_cast_fp16 = conv(bias = generator_resblocks_10_convs2_0_bias_to_fp16, dilations = xt_257_dilations_0, groups = xt_257_groups_0, pad = xt_257_pad_0, pad_type = xt_257_pad_type_0, strides = xt_257_strides_0, weight = generator_resblocks_10_convs2_0_weight_to_fp16, x = input_339_cast_fp16)[name = string("xt_257_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_341_cast_fp16 = add(x = xt_257_cast_fp16, y = input_311_cast_fp16)[name = string("input_341_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_10_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_10_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41036160)))];
            tensor<fp16, [64]> generator_resblocks_10_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_10_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41052608)))];
            tensor<fp16, [1, 64]> linear_86_cast_fp16 = linear(bias = generator_resblocks_10_adain1_1_fc_bias_to_fp16, weight = generator_resblocks_10_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_86_cast_fp16")];
            tensor<int32, [3]> var_3357 = const()[name = string("op_3357"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_347_cast_fp16 = reshape(shape = var_3357, x = linear_86_cast_fp16)[name = string("h_347_cast_fp16")];
            tensor<int32, [2]> var_3359_split_sizes_0 = const()[name = string("op_3359_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3359_axis_0 = const()[name = string("op_3359_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3359_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3359_cast_fp16_1 = split(axis = var_3359_axis_0, split_sizes = var_3359_split_sizes_0, x = h_347_cast_fp16)[name = string("op_3359_cast_fp16")];
            fp16 var_3361_promoted_to_fp16 = const()[name = string("op_3361_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3362_cast_fp16 = add(x = var_3359_cast_fp16_0, y = var_3361_promoted_to_fp16)[name = string("op_3362_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3363_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_341_cast_fp16)[name = string("op_3363_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3364_cast_fp16 = mul(x = var_3362_cast_fp16, y = var_3363_cast_fp16)[name = string("op_3364_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_259_cast_fp16 = add(x = var_3364_cast_fp16, y = var_3359_cast_fp16_1)[name = string("xt_259_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_10_alpha1_1_to_fp16 = const()[name = string("generator_resblocks_10_alpha1_1_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41052800)))];
            tensor<fp16, [1, 32, ?]> var_3369_cast_fp16 = mul(x = generator_resblocks_10_alpha1_1_to_fp16, y = xt_259_cast_fp16)[name = string("op_3369_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3370_cast_fp16 = sin(x = var_3369_cast_fp16)[name = string("op_3370_cast_fp16")];
            fp16 var_24_promoted_90_to_fp16 = const()[name = string("op_24_promoted_90_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3371_cast_fp16 = pow(x = var_3370_cast_fp16, y = var_24_promoted_90_to_fp16)[name = string("op_3371_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3366_to_fp16 = const()[name = string("op_3366_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41052928)))];
            tensor<fp16, [1, 32, ?]> var_3372_cast_fp16 = mul(x = var_3366_to_fp16, y = var_3371_cast_fp16)[name = string("op_3372_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_343_cast_fp16 = add(x = xt_259_cast_fp16, y = var_3372_cast_fp16)[name = string("input_343_cast_fp16")];
            string input_345_pad_type_0 = const()[name = string("input_345_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_345_pad_0 = const()[name = string("input_345_pad_0"), val = tensor<int32, [2]>([9, 9])];
            tensor<int32, [1]> input_345_dilations_0 = const()[name = string("input_345_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_345_strides_0 = const()[name = string("input_345_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_345_groups_0 = const()[name = string("input_345_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 7]> generator_resblocks_10_convs1_1_weight_to_fp16 = const()[name = string("generator_resblocks_10_convs1_1_weight_to_fp16"), val = tensor<fp16, [32, 32, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41053056)))];
            tensor<fp16, [32]> generator_resblocks_10_convs1_1_bias_to_fp16 = const()[name = string("generator_resblocks_10_convs1_1_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41067456)))];
            tensor<fp16, [1, 32, ?]> input_345_cast_fp16 = conv(bias = generator_resblocks_10_convs1_1_bias_to_fp16, dilations = input_345_dilations_0, groups = input_345_groups_0, pad = input_345_pad_0, pad_type = input_345_pad_type_0, strides = input_345_strides_0, weight = generator_resblocks_10_convs1_1_weight_to_fp16, x = input_343_cast_fp16)[name = string("input_345_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_10_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_10_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41067584)))];
            tensor<fp16, [64]> generator_resblocks_10_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_10_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41084032)))];
            tensor<fp16, [1, 64]> linear_87_cast_fp16 = linear(bias = generator_resblocks_10_adain2_1_fc_bias_to_fp16, weight = generator_resblocks_10_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_87_cast_fp16")];
            tensor<int32, [3]> var_3387 = const()[name = string("op_3387"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_351_cast_fp16 = reshape(shape = var_3387, x = linear_87_cast_fp16)[name = string("h_351_cast_fp16")];
            tensor<int32, [2]> var_3389_split_sizes_0 = const()[name = string("op_3389_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3389_axis_0 = const()[name = string("op_3389_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3389_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3389_cast_fp16_1 = split(axis = var_3389_axis_0, split_sizes = var_3389_split_sizes_0, x = h_351_cast_fp16)[name = string("op_3389_cast_fp16")];
            fp16 var_3391_promoted_to_fp16 = const()[name = string("op_3391_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3392_cast_fp16 = add(x = var_3389_cast_fp16_0, y = var_3391_promoted_to_fp16)[name = string("op_3392_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3393_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_345_cast_fp16)[name = string("op_3393_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3394_cast_fp16 = mul(x = var_3392_cast_fp16, y = var_3393_cast_fp16)[name = string("op_3394_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_261_cast_fp16 = add(x = var_3394_cast_fp16, y = var_3389_cast_fp16_1)[name = string("xt_261_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_10_alpha2_1_to_fp16 = const()[name = string("generator_resblocks_10_alpha2_1_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41084224)))];
            tensor<fp16, [1, 32, ?]> var_3399_cast_fp16 = mul(x = generator_resblocks_10_alpha2_1_to_fp16, y = xt_261_cast_fp16)[name = string("op_3399_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3400_cast_fp16 = sin(x = var_3399_cast_fp16)[name = string("op_3400_cast_fp16")];
            fp16 var_24_promoted_91_to_fp16 = const()[name = string("op_24_promoted_91_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3401_cast_fp16 = pow(x = var_3400_cast_fp16, y = var_24_promoted_91_to_fp16)[name = string("op_3401_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3396_to_fp16 = const()[name = string("op_3396_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41084352)))];
            tensor<fp16, [1, 32, ?]> var_3402_cast_fp16 = mul(x = var_3396_to_fp16, y = var_3401_cast_fp16)[name = string("op_3402_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_347_cast_fp16 = add(x = xt_261_cast_fp16, y = var_3402_cast_fp16)[name = string("input_347_cast_fp16")];
            string xt_263_pad_type_0 = const()[name = string("xt_263_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_263_pad_0 = const()[name = string("xt_263_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_263_strides_0 = const()[name = string("xt_263_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_263_dilations_0 = const()[name = string("xt_263_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_263_groups_0 = const()[name = string("xt_263_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 7]> generator_resblocks_10_convs2_1_weight_to_fp16 = const()[name = string("generator_resblocks_10_convs2_1_weight_to_fp16"), val = tensor<fp16, [32, 32, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41084480)))];
            tensor<fp16, [32]> generator_resblocks_10_convs2_1_bias_to_fp16 = const()[name = string("generator_resblocks_10_convs2_1_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41098880)))];
            tensor<fp16, [1, 32, ?]> xt_263_cast_fp16 = conv(bias = generator_resblocks_10_convs2_1_bias_to_fp16, dilations = xt_263_dilations_0, groups = xt_263_groups_0, pad = xt_263_pad_0, pad_type = xt_263_pad_type_0, strides = xt_263_strides_0, weight = generator_resblocks_10_convs2_1_weight_to_fp16, x = input_347_cast_fp16)[name = string("xt_263_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_349_cast_fp16 = add(x = xt_263_cast_fp16, y = input_341_cast_fp16)[name = string("input_349_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_10_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_10_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41099008)))];
            tensor<fp16, [64]> generator_resblocks_10_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_10_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41115456)))];
            tensor<fp16, [1, 64]> linear_88_cast_fp16 = linear(bias = generator_resblocks_10_adain1_2_fc_bias_to_fp16, weight = generator_resblocks_10_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_88_cast_fp16")];
            tensor<int32, [3]> var_3418 = const()[name = string("op_3418"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_355_cast_fp16 = reshape(shape = var_3418, x = linear_88_cast_fp16)[name = string("h_355_cast_fp16")];
            tensor<int32, [2]> var_3420_split_sizes_0 = const()[name = string("op_3420_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3420_axis_0 = const()[name = string("op_3420_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3420_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3420_cast_fp16_1 = split(axis = var_3420_axis_0, split_sizes = var_3420_split_sizes_0, x = h_355_cast_fp16)[name = string("op_3420_cast_fp16")];
            fp16 var_3422_promoted_to_fp16 = const()[name = string("op_3422_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3423_cast_fp16 = add(x = var_3420_cast_fp16_0, y = var_3422_promoted_to_fp16)[name = string("op_3423_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3424_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_349_cast_fp16)[name = string("op_3424_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3425_cast_fp16 = mul(x = var_3423_cast_fp16, y = var_3424_cast_fp16)[name = string("op_3425_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_265_cast_fp16 = add(x = var_3425_cast_fp16, y = var_3420_cast_fp16_1)[name = string("xt_265_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_10_alpha1_2_to_fp16 = const()[name = string("generator_resblocks_10_alpha1_2_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41115648)))];
            tensor<fp16, [1, 32, ?]> var_3430_cast_fp16 = mul(x = generator_resblocks_10_alpha1_2_to_fp16, y = xt_265_cast_fp16)[name = string("op_3430_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3431_cast_fp16 = sin(x = var_3430_cast_fp16)[name = string("op_3431_cast_fp16")];
            fp16 var_24_promoted_92_to_fp16 = const()[name = string("op_24_promoted_92_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3432_cast_fp16 = pow(x = var_3431_cast_fp16, y = var_24_promoted_92_to_fp16)[name = string("op_3432_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3427_to_fp16 = const()[name = string("op_3427_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41115776)))];
            tensor<fp16, [1, 32, ?]> var_3433_cast_fp16 = mul(x = var_3427_to_fp16, y = var_3432_cast_fp16)[name = string("op_3433_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_351_cast_fp16 = add(x = xt_265_cast_fp16, y = var_3433_cast_fp16)[name = string("input_351_cast_fp16")];
            string input_353_pad_type_0 = const()[name = string("input_353_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_353_pad_0 = const()[name = string("input_353_pad_0"), val = tensor<int32, [2]>([15, 15])];
            tensor<int32, [1]> input_353_dilations_0 = const()[name = string("input_353_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_353_strides_0 = const()[name = string("input_353_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_353_groups_0 = const()[name = string("input_353_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 7]> generator_resblocks_10_convs1_2_weight_to_fp16 = const()[name = string("generator_resblocks_10_convs1_2_weight_to_fp16"), val = tensor<fp16, [32, 32, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41115904)))];
            tensor<fp16, [32]> generator_resblocks_10_convs1_2_bias_to_fp16 = const()[name = string("generator_resblocks_10_convs1_2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41130304)))];
            tensor<fp16, [1, 32, ?]> input_353_cast_fp16 = conv(bias = generator_resblocks_10_convs1_2_bias_to_fp16, dilations = input_353_dilations_0, groups = input_353_groups_0, pad = input_353_pad_0, pad_type = input_353_pad_type_0, strides = input_353_strides_0, weight = generator_resblocks_10_convs1_2_weight_to_fp16, x = input_351_cast_fp16)[name = string("input_353_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_10_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_10_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41130432)))];
            tensor<fp16, [64]> generator_resblocks_10_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_10_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41146880)))];
            tensor<fp16, [1, 64]> linear_89_cast_fp16 = linear(bias = generator_resblocks_10_adain2_2_fc_bias_to_fp16, weight = generator_resblocks_10_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_89_cast_fp16")];
            tensor<int32, [3]> var_3448 = const()[name = string("op_3448"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_359_cast_fp16 = reshape(shape = var_3448, x = linear_89_cast_fp16)[name = string("h_359_cast_fp16")];
            tensor<int32, [2]> var_3450_split_sizes_0 = const()[name = string("op_3450_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3450_axis_0 = const()[name = string("op_3450_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3450_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3450_cast_fp16_1 = split(axis = var_3450_axis_0, split_sizes = var_3450_split_sizes_0, x = h_359_cast_fp16)[name = string("op_3450_cast_fp16")];
            fp16 var_3452_promoted_to_fp16 = const()[name = string("op_3452_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3453_cast_fp16 = add(x = var_3450_cast_fp16_0, y = var_3452_promoted_to_fp16)[name = string("op_3453_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3454_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_353_cast_fp16)[name = string("op_3454_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3455_cast_fp16 = mul(x = var_3453_cast_fp16, y = var_3454_cast_fp16)[name = string("op_3455_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_267_cast_fp16 = add(x = var_3455_cast_fp16, y = var_3450_cast_fp16_1)[name = string("xt_267_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_10_alpha2_2_to_fp16 = const()[name = string("generator_resblocks_10_alpha2_2_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41147072)))];
            tensor<fp16, [1, 32, ?]> var_3460_cast_fp16 = mul(x = generator_resblocks_10_alpha2_2_to_fp16, y = xt_267_cast_fp16)[name = string("op_3460_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3461_cast_fp16 = sin(x = var_3460_cast_fp16)[name = string("op_3461_cast_fp16")];
            fp16 var_24_promoted_93_to_fp16 = const()[name = string("op_24_promoted_93_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3462_cast_fp16 = pow(x = var_3461_cast_fp16, y = var_24_promoted_93_to_fp16)[name = string("op_3462_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3457_to_fp16 = const()[name = string("op_3457_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41147200)))];
            tensor<fp16, [1, 32, ?]> var_3463_cast_fp16 = mul(x = var_3457_to_fp16, y = var_3462_cast_fp16)[name = string("op_3463_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_355_cast_fp16 = add(x = xt_267_cast_fp16, y = var_3463_cast_fp16)[name = string("input_355_cast_fp16")];
            string xt_269_pad_type_0 = const()[name = string("xt_269_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_269_pad_0 = const()[name = string("xt_269_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> xt_269_strides_0 = const()[name = string("xt_269_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_269_dilations_0 = const()[name = string("xt_269_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_269_groups_0 = const()[name = string("xt_269_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 7]> generator_resblocks_10_convs2_2_weight_to_fp16 = const()[name = string("generator_resblocks_10_convs2_2_weight_to_fp16"), val = tensor<fp16, [32, 32, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41147328)))];
            tensor<fp16, [32]> generator_resblocks_10_convs2_2_bias_to_fp16 = const()[name = string("generator_resblocks_10_convs2_2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41161728)))];
            tensor<fp16, [1, 32, ?]> xt_269_cast_fp16 = conv(bias = generator_resblocks_10_convs2_2_bias_to_fp16, dilations = xt_269_dilations_0, groups = xt_269_groups_0, pad = xt_269_pad_0, pad_type = xt_269_pad_type_0, strides = xt_269_strides_0, weight = generator_resblocks_10_convs2_2_weight_to_fp16, x = input_355_cast_fp16)[name = string("xt_269_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3472_cast_fp16 = add(x = xt_269_cast_fp16, y = input_349_cast_fp16)[name = string("op_3472_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xs_21_cast_fp16 = add(x = xs_19_cast_fp16, y = var_3472_cast_fp16)[name = string("xs_21_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_11_adain1_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_11_adain1_0_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41161856)))];
            tensor<fp16, [64]> generator_resblocks_11_adain1_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_11_adain1_0_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41178304)))];
            tensor<fp16, [1, 64]> linear_90_cast_fp16 = linear(bias = generator_resblocks_11_adain1_0_fc_bias_to_fp16, weight = generator_resblocks_11_adain1_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_90_cast_fp16")];
            tensor<int32, [3]> var_3516 = const()[name = string("op_3516"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_363_cast_fp16 = reshape(shape = var_3516, x = linear_90_cast_fp16)[name = string("h_363_cast_fp16")];
            tensor<int32, [2]> var_3518_split_sizes_0 = const()[name = string("op_3518_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3518_axis_0 = const()[name = string("op_3518_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3518_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3518_cast_fp16_1 = split(axis = var_3518_axis_0, split_sizes = var_3518_split_sizes_0, x = h_363_cast_fp16)[name = string("op_3518_cast_fp16")];
            fp16 var_3520_promoted_to_fp16 = const()[name = string("op_3520_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3521_cast_fp16 = add(x = var_3518_cast_fp16_0, y = var_3520_promoted_to_fp16)[name = string("op_3521_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3523_cast_fp16 = mul(x = var_3521_cast_fp16, y = var_3083_cast_fp16)[name = string("op_3523_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_271_cast_fp16 = add(x = var_3523_cast_fp16, y = var_3518_cast_fp16_1)[name = string("xt_271_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_11_alpha1_0_to_fp16 = const()[name = string("generator_resblocks_11_alpha1_0_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41178496)))];
            tensor<fp16, [1, 32, ?]> var_3528_cast_fp16 = mul(x = generator_resblocks_11_alpha1_0_to_fp16, y = xt_271_cast_fp16)[name = string("op_3528_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3529_cast_fp16 = sin(x = var_3528_cast_fp16)[name = string("op_3529_cast_fp16")];
            fp16 var_24_promoted_94_to_fp16 = const()[name = string("op_24_promoted_94_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3530_cast_fp16 = pow(x = var_3529_cast_fp16, y = var_24_promoted_94_to_fp16)[name = string("op_3530_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3525_to_fp16 = const()[name = string("op_3525_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41178624)))];
            tensor<fp16, [1, 32, ?]> var_3531_cast_fp16 = mul(x = var_3525_to_fp16, y = var_3530_cast_fp16)[name = string("op_3531_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_357_cast_fp16 = add(x = xt_271_cast_fp16, y = var_3531_cast_fp16)[name = string("input_357_cast_fp16")];
            string input_359_pad_type_0 = const()[name = string("input_359_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_359_pad_0 = const()[name = string("input_359_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> input_359_strides_0 = const()[name = string("input_359_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> input_359_dilations_0 = const()[name = string("input_359_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_359_groups_0 = const()[name = string("input_359_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 11]> generator_resblocks_11_convs1_0_weight_to_fp16 = const()[name = string("generator_resblocks_11_convs1_0_weight_to_fp16"), val = tensor<fp16, [32, 32, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41178752)))];
            tensor<fp16, [32]> generator_resblocks_11_convs1_0_bias_to_fp16 = const()[name = string("generator_resblocks_11_convs1_0_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41201344)))];
            tensor<fp16, [1, 32, ?]> input_359_cast_fp16 = conv(bias = generator_resblocks_11_convs1_0_bias_to_fp16, dilations = input_359_dilations_0, groups = input_359_groups_0, pad = input_359_pad_0, pad_type = input_359_pad_type_0, strides = input_359_strides_0, weight = generator_resblocks_11_convs1_0_weight_to_fp16, x = input_357_cast_fp16)[name = string("input_359_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_11_adain2_0_fc_weight_to_fp16 = const()[name = string("generator_resblocks_11_adain2_0_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41201472)))];
            tensor<fp16, [64]> generator_resblocks_11_adain2_0_fc_bias_to_fp16 = const()[name = string("generator_resblocks_11_adain2_0_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41217920)))];
            tensor<fp16, [1, 64]> linear_91_cast_fp16 = linear(bias = generator_resblocks_11_adain2_0_fc_bias_to_fp16, weight = generator_resblocks_11_adain2_0_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_91_cast_fp16")];
            tensor<int32, [3]> var_3546 = const()[name = string("op_3546"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_367_cast_fp16 = reshape(shape = var_3546, x = linear_91_cast_fp16)[name = string("h_367_cast_fp16")];
            tensor<int32, [2]> var_3548_split_sizes_0 = const()[name = string("op_3548_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3548_axis_0 = const()[name = string("op_3548_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3548_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3548_cast_fp16_1 = split(axis = var_3548_axis_0, split_sizes = var_3548_split_sizes_0, x = h_367_cast_fp16)[name = string("op_3548_cast_fp16")];
            fp16 var_3550_promoted_to_fp16 = const()[name = string("op_3550_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3551_cast_fp16 = add(x = var_3548_cast_fp16_0, y = var_3550_promoted_to_fp16)[name = string("op_3551_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3552_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_359_cast_fp16)[name = string("op_3552_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3553_cast_fp16 = mul(x = var_3551_cast_fp16, y = var_3552_cast_fp16)[name = string("op_3553_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_273_cast_fp16 = add(x = var_3553_cast_fp16, y = var_3548_cast_fp16_1)[name = string("xt_273_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_11_alpha2_0_to_fp16 = const()[name = string("generator_resblocks_11_alpha2_0_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41218112)))];
            tensor<fp16, [1, 32, ?]> var_3558_cast_fp16 = mul(x = generator_resblocks_11_alpha2_0_to_fp16, y = xt_273_cast_fp16)[name = string("op_3558_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3559_cast_fp16 = sin(x = var_3558_cast_fp16)[name = string("op_3559_cast_fp16")];
            fp16 var_24_promoted_95_to_fp16 = const()[name = string("op_24_promoted_95_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3560_cast_fp16 = pow(x = var_3559_cast_fp16, y = var_24_promoted_95_to_fp16)[name = string("op_3560_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3555_to_fp16 = const()[name = string("op_3555_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41218240)))];
            tensor<fp16, [1, 32, ?]> var_3561_cast_fp16 = mul(x = var_3555_to_fp16, y = var_3560_cast_fp16)[name = string("op_3561_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_361_cast_fp16 = add(x = xt_273_cast_fp16, y = var_3561_cast_fp16)[name = string("input_361_cast_fp16")];
            string xt_275_pad_type_0 = const()[name = string("xt_275_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_275_pad_0 = const()[name = string("xt_275_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_275_strides_0 = const()[name = string("xt_275_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_275_dilations_0 = const()[name = string("xt_275_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_275_groups_0 = const()[name = string("xt_275_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 11]> generator_resblocks_11_convs2_0_weight_to_fp16 = const()[name = string("generator_resblocks_11_convs2_0_weight_to_fp16"), val = tensor<fp16, [32, 32, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41218368)))];
            tensor<fp16, [32]> generator_resblocks_11_convs2_0_bias_to_fp16 = const()[name = string("generator_resblocks_11_convs2_0_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41240960)))];
            tensor<fp16, [1, 32, ?]> xt_275_cast_fp16 = conv(bias = generator_resblocks_11_convs2_0_bias_to_fp16, dilations = xt_275_dilations_0, groups = xt_275_groups_0, pad = xt_275_pad_0, pad_type = xt_275_pad_type_0, strides = xt_275_strides_0, weight = generator_resblocks_11_convs2_0_weight_to_fp16, x = input_361_cast_fp16)[name = string("xt_275_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_363_cast_fp16 = add(x = xt_275_cast_fp16, y = input_311_cast_fp16)[name = string("input_363_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_11_adain1_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_11_adain1_1_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41241088)))];
            tensor<fp16, [64]> generator_resblocks_11_adain1_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_11_adain1_1_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41257536)))];
            tensor<fp16, [1, 64]> linear_92_cast_fp16 = linear(bias = generator_resblocks_11_adain1_1_fc_bias_to_fp16, weight = generator_resblocks_11_adain1_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_92_cast_fp16")];
            tensor<int32, [3]> var_3577 = const()[name = string("op_3577"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_371_cast_fp16 = reshape(shape = var_3577, x = linear_92_cast_fp16)[name = string("h_371_cast_fp16")];
            tensor<int32, [2]> var_3579_split_sizes_0 = const()[name = string("op_3579_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3579_axis_0 = const()[name = string("op_3579_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3579_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3579_cast_fp16_1 = split(axis = var_3579_axis_0, split_sizes = var_3579_split_sizes_0, x = h_371_cast_fp16)[name = string("op_3579_cast_fp16")];
            fp16 var_3581_promoted_to_fp16 = const()[name = string("op_3581_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3582_cast_fp16 = add(x = var_3579_cast_fp16_0, y = var_3581_promoted_to_fp16)[name = string("op_3582_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3583_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_363_cast_fp16)[name = string("op_3583_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3584_cast_fp16 = mul(x = var_3582_cast_fp16, y = var_3583_cast_fp16)[name = string("op_3584_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_277_cast_fp16 = add(x = var_3584_cast_fp16, y = var_3579_cast_fp16_1)[name = string("xt_277_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_11_alpha1_1_to_fp16 = const()[name = string("generator_resblocks_11_alpha1_1_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41257728)))];
            tensor<fp16, [1, 32, ?]> var_3589_cast_fp16 = mul(x = generator_resblocks_11_alpha1_1_to_fp16, y = xt_277_cast_fp16)[name = string("op_3589_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3590_cast_fp16 = sin(x = var_3589_cast_fp16)[name = string("op_3590_cast_fp16")];
            fp16 var_24_promoted_96_to_fp16 = const()[name = string("op_24_promoted_96_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3591_cast_fp16 = pow(x = var_3590_cast_fp16, y = var_24_promoted_96_to_fp16)[name = string("op_3591_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3586_to_fp16 = const()[name = string("op_3586_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41257856)))];
            tensor<fp16, [1, 32, ?]> var_3592_cast_fp16 = mul(x = var_3586_to_fp16, y = var_3591_cast_fp16)[name = string("op_3592_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_365_cast_fp16 = add(x = xt_277_cast_fp16, y = var_3592_cast_fp16)[name = string("input_365_cast_fp16")];
            string input_367_pad_type_0 = const()[name = string("input_367_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_367_pad_0 = const()[name = string("input_367_pad_0"), val = tensor<int32, [2]>([15, 15])];
            tensor<int32, [1]> input_367_dilations_0 = const()[name = string("input_367_dilations_0"), val = tensor<int32, [1]>([3])];
            tensor<int32, [1]> input_367_strides_0 = const()[name = string("input_367_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_367_groups_0 = const()[name = string("input_367_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 11]> generator_resblocks_11_convs1_1_weight_to_fp16 = const()[name = string("generator_resblocks_11_convs1_1_weight_to_fp16"), val = tensor<fp16, [32, 32, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41257984)))];
            tensor<fp16, [32]> generator_resblocks_11_convs1_1_bias_to_fp16 = const()[name = string("generator_resblocks_11_convs1_1_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41280576)))];
            tensor<fp16, [1, 32, ?]> input_367_cast_fp16 = conv(bias = generator_resblocks_11_convs1_1_bias_to_fp16, dilations = input_367_dilations_0, groups = input_367_groups_0, pad = input_367_pad_0, pad_type = input_367_pad_type_0, strides = input_367_strides_0, weight = generator_resblocks_11_convs1_1_weight_to_fp16, x = input_365_cast_fp16)[name = string("input_367_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_11_adain2_1_fc_weight_to_fp16 = const()[name = string("generator_resblocks_11_adain2_1_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41280704)))];
            tensor<fp16, [64]> generator_resblocks_11_adain2_1_fc_bias_to_fp16 = const()[name = string("generator_resblocks_11_adain2_1_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41297152)))];
            tensor<fp16, [1, 64]> linear_93_cast_fp16 = linear(bias = generator_resblocks_11_adain2_1_fc_bias_to_fp16, weight = generator_resblocks_11_adain2_1_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_93_cast_fp16")];
            tensor<int32, [3]> var_3607 = const()[name = string("op_3607"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_375_cast_fp16 = reshape(shape = var_3607, x = linear_93_cast_fp16)[name = string("h_375_cast_fp16")];
            tensor<int32, [2]> var_3609_split_sizes_0 = const()[name = string("op_3609_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3609_axis_0 = const()[name = string("op_3609_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3609_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3609_cast_fp16_1 = split(axis = var_3609_axis_0, split_sizes = var_3609_split_sizes_0, x = h_375_cast_fp16)[name = string("op_3609_cast_fp16")];
            fp16 var_3611_promoted_to_fp16 = const()[name = string("op_3611_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3612_cast_fp16 = add(x = var_3609_cast_fp16_0, y = var_3611_promoted_to_fp16)[name = string("op_3612_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3613_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_367_cast_fp16)[name = string("op_3613_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3614_cast_fp16 = mul(x = var_3612_cast_fp16, y = var_3613_cast_fp16)[name = string("op_3614_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_279_cast_fp16 = add(x = var_3614_cast_fp16, y = var_3609_cast_fp16_1)[name = string("xt_279_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_11_alpha2_1_to_fp16 = const()[name = string("generator_resblocks_11_alpha2_1_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41297344)))];
            tensor<fp16, [1, 32, ?]> var_3619_cast_fp16 = mul(x = generator_resblocks_11_alpha2_1_to_fp16, y = xt_279_cast_fp16)[name = string("op_3619_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3620_cast_fp16 = sin(x = var_3619_cast_fp16)[name = string("op_3620_cast_fp16")];
            fp16 var_24_promoted_97_to_fp16 = const()[name = string("op_24_promoted_97_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3621_cast_fp16 = pow(x = var_3620_cast_fp16, y = var_24_promoted_97_to_fp16)[name = string("op_3621_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3616_to_fp16 = const()[name = string("op_3616_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41297472)))];
            tensor<fp16, [1, 32, ?]> var_3622_cast_fp16 = mul(x = var_3616_to_fp16, y = var_3621_cast_fp16)[name = string("op_3622_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_369_cast_fp16 = add(x = xt_279_cast_fp16, y = var_3622_cast_fp16)[name = string("input_369_cast_fp16")];
            string xt_281_pad_type_0 = const()[name = string("xt_281_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_281_pad_0 = const()[name = string("xt_281_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_281_strides_0 = const()[name = string("xt_281_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_281_dilations_0 = const()[name = string("xt_281_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_281_groups_0 = const()[name = string("xt_281_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 11]> generator_resblocks_11_convs2_1_weight_to_fp16 = const()[name = string("generator_resblocks_11_convs2_1_weight_to_fp16"), val = tensor<fp16, [32, 32, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41297600)))];
            tensor<fp16, [32]> generator_resblocks_11_convs2_1_bias_to_fp16 = const()[name = string("generator_resblocks_11_convs2_1_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41320192)))];
            tensor<fp16, [1, 32, ?]> xt_281_cast_fp16 = conv(bias = generator_resblocks_11_convs2_1_bias_to_fp16, dilations = xt_281_dilations_0, groups = xt_281_groups_0, pad = xt_281_pad_0, pad_type = xt_281_pad_type_0, strides = xt_281_strides_0, weight = generator_resblocks_11_convs2_1_weight_to_fp16, x = input_369_cast_fp16)[name = string("xt_281_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_371_cast_fp16 = add(x = xt_281_cast_fp16, y = input_363_cast_fp16)[name = string("input_371_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_11_adain1_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_11_adain1_2_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41320320)))];
            tensor<fp16, [64]> generator_resblocks_11_adain1_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_11_adain1_2_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41336768)))];
            tensor<fp16, [1, 64]> linear_94_cast_fp16 = linear(bias = generator_resblocks_11_adain1_2_fc_bias_to_fp16, weight = generator_resblocks_11_adain1_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_94_cast_fp16")];
            tensor<int32, [3]> var_3638 = const()[name = string("op_3638"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_379_cast_fp16 = reshape(shape = var_3638, x = linear_94_cast_fp16)[name = string("h_379_cast_fp16")];
            tensor<int32, [2]> var_3640_split_sizes_0 = const()[name = string("op_3640_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3640_axis_0 = const()[name = string("op_3640_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3640_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3640_cast_fp16_1 = split(axis = var_3640_axis_0, split_sizes = var_3640_split_sizes_0, x = h_379_cast_fp16)[name = string("op_3640_cast_fp16")];
            fp16 var_3642_promoted_to_fp16 = const()[name = string("op_3642_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3643_cast_fp16 = add(x = var_3640_cast_fp16_0, y = var_3642_promoted_to_fp16)[name = string("op_3643_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3644_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_371_cast_fp16)[name = string("op_3644_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3645_cast_fp16 = mul(x = var_3643_cast_fp16, y = var_3644_cast_fp16)[name = string("op_3645_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_283_cast_fp16 = add(x = var_3645_cast_fp16, y = var_3640_cast_fp16_1)[name = string("xt_283_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_11_alpha1_2_to_fp16 = const()[name = string("generator_resblocks_11_alpha1_2_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41336960)))];
            tensor<fp16, [1, 32, ?]> var_3650_cast_fp16 = mul(x = generator_resblocks_11_alpha1_2_to_fp16, y = xt_283_cast_fp16)[name = string("op_3650_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3651_cast_fp16 = sin(x = var_3650_cast_fp16)[name = string("op_3651_cast_fp16")];
            fp16 var_24_promoted_98_to_fp16 = const()[name = string("op_24_promoted_98_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3652_cast_fp16 = pow(x = var_3651_cast_fp16, y = var_24_promoted_98_to_fp16)[name = string("op_3652_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3647_to_fp16 = const()[name = string("op_3647_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41337088)))];
            tensor<fp16, [1, 32, ?]> var_3653_cast_fp16 = mul(x = var_3647_to_fp16, y = var_3652_cast_fp16)[name = string("op_3653_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_373_cast_fp16 = add(x = xt_283_cast_fp16, y = var_3653_cast_fp16)[name = string("input_373_cast_fp16")];
            string input_375_pad_type_0 = const()[name = string("input_375_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> input_375_pad_0 = const()[name = string("input_375_pad_0"), val = tensor<int32, [2]>([25, 25])];
            tensor<int32, [1]> input_375_dilations_0 = const()[name = string("input_375_dilations_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [1]> input_375_strides_0 = const()[name = string("input_375_strides_0"), val = tensor<int32, [1]>([1])];
            int32 input_375_groups_0 = const()[name = string("input_375_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 11]> generator_resblocks_11_convs1_2_weight_to_fp16 = const()[name = string("generator_resblocks_11_convs1_2_weight_to_fp16"), val = tensor<fp16, [32, 32, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41337216)))];
            tensor<fp16, [32]> generator_resblocks_11_convs1_2_bias_to_fp16 = const()[name = string("generator_resblocks_11_convs1_2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41359808)))];
            tensor<fp16, [1, 32, ?]> input_375_cast_fp16 = conv(bias = generator_resblocks_11_convs1_2_bias_to_fp16, dilations = input_375_dilations_0, groups = input_375_groups_0, pad = input_375_pad_0, pad_type = input_375_pad_type_0, strides = input_375_strides_0, weight = generator_resblocks_11_convs1_2_weight_to_fp16, x = input_373_cast_fp16)[name = string("input_375_cast_fp16")];
            tensor<fp16, [64, 128]> generator_resblocks_11_adain2_2_fc_weight_to_fp16 = const()[name = string("generator_resblocks_11_adain2_2_fc_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41359936)))];
            tensor<fp16, [64]> generator_resblocks_11_adain2_2_fc_bias_to_fp16 = const()[name = string("generator_resblocks_11_adain2_2_fc_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41376384)))];
            tensor<fp16, [1, 64]> linear_95_cast_fp16 = linear(bias = generator_resblocks_11_adain2_2_fc_bias_to_fp16, weight = generator_resblocks_11_adain2_2_fc_weight_to_fp16, x = ref_to_fp16)[name = string("linear_95_cast_fp16")];
            tensor<int32, [3]> var_3668 = const()[name = string("op_3668"), val = tensor<int32, [3]>([1, 64, 1])];
            tensor<fp16, [1, 64, 1]> h_cast_fp16 = reshape(shape = var_3668, x = linear_95_cast_fp16)[name = string("h_cast_fp16")];
            tensor<int32, [2]> var_3670_split_sizes_0 = const()[name = string("op_3670_split_sizes_0"), val = tensor<int32, [2]>([32, 32])];
            int32 var_3670_axis_0 = const()[name = string("op_3670_axis_0"), val = int32(1)];
            tensor<fp16, [1, 32, 1]> var_3670_cast_fp16_0, tensor<fp16, [1, 32, 1]> var_3670_cast_fp16_1 = split(axis = var_3670_axis_0, split_sizes = var_3670_split_sizes_0, x = h_cast_fp16)[name = string("op_3670_cast_fp16")];
            fp16 var_3672_promoted_to_fp16 = const()[name = string("op_3672_promoted_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32, 1]> var_3673_cast_fp16 = add(x = var_3670_cast_fp16_0, y = var_3672_promoted_to_fp16)[name = string("op_3673_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3674_cast_fp16 = instance_norm(epsilon = var_14_to_fp16, x = input_375_cast_fp16)[name = string("op_3674_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3675_cast_fp16 = mul(x = var_3673_cast_fp16, y = var_3674_cast_fp16)[name = string("op_3675_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xt_285_cast_fp16 = add(x = var_3675_cast_fp16, y = var_3670_cast_fp16_1)[name = string("xt_285_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_resblocks_11_alpha2_2_to_fp16 = const()[name = string("generator_resblocks_11_alpha2_2_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41376576)))];
            tensor<fp16, [1, 32, ?]> var_3680_cast_fp16 = mul(x = generator_resblocks_11_alpha2_2_to_fp16, y = xt_285_cast_fp16)[name = string("op_3680_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3681_cast_fp16 = sin(x = var_3680_cast_fp16)[name = string("op_3681_cast_fp16")];
            fp16 var_24_promoted_99_to_fp16 = const()[name = string("op_24_promoted_99_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3682_cast_fp16 = pow(x = var_3681_cast_fp16, y = var_24_promoted_99_to_fp16)[name = string("op_3682_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3677_to_fp16 = const()[name = string("op_3677_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41376704)))];
            tensor<fp16, [1, 32, ?]> var_3683_cast_fp16 = mul(x = var_3677_to_fp16, y = var_3682_cast_fp16)[name = string("op_3683_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_377_cast_fp16 = add(x = xt_285_cast_fp16, y = var_3683_cast_fp16)[name = string("input_377_cast_fp16")];
            string xt_pad_type_0 = const()[name = string("xt_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> xt_pad_0 = const()[name = string("xt_pad_0"), val = tensor<int32, [2]>([5, 5])];
            tensor<int32, [1]> xt_strides_0 = const()[name = string("xt_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> xt_dilations_0 = const()[name = string("xt_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 xt_groups_0 = const()[name = string("xt_groups_0"), val = int32(1)];
            tensor<fp16, [32, 32, 11]> generator_resblocks_11_convs2_2_weight_to_fp16 = const()[name = string("generator_resblocks_11_convs2_2_weight_to_fp16"), val = tensor<fp16, [32, 32, 11]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41376832)))];
            tensor<fp16, [32]> generator_resblocks_11_convs2_2_bias_to_fp16 = const()[name = string("generator_resblocks_11_convs2_2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41399424)))];
            tensor<fp16, [1, 32, ?]> xt_cast_fp16 = conv(bias = generator_resblocks_11_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 = generator_resblocks_11_convs2_2_weight_to_fp16, x = input_377_cast_fp16)[name = string("xt_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3692_cast_fp16 = add(x = xt_cast_fp16, y = input_371_cast_fp16)[name = string("op_3692_cast_fp16")];
            tensor<fp16, [1, 32, ?]> xs_cast_fp16 = add(x = xs_21_cast_fp16, y = var_3692_cast_fp16)[name = string("xs_cast_fp16")];
            fp16 _inversed_x_15_y_0_to_fp16 = const()[name = string("_inversed_x_15_y_0_to_fp16"), val = fp16(0x1.554p-2)];
            tensor<fp16, [1, 32, ?]> _inversed_x_15_cast_fp16 = mul(x = xs_cast_fp16, y = _inversed_x_15_y_0_to_fp16)[name = string("_inversed_x_15_cast_fp16")];
            tensor<fp16, [1, 32, 1]> generator_alphas_4_to_fp16 = const()[name = string("generator_alphas_4_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41399552)))];
            tensor<fp16, [1, 32, ?]> var_3699_cast_fp16 = mul(x = generator_alphas_4_to_fp16, y = _inversed_x_15_cast_fp16)[name = string("op_3699_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3700_cast_fp16 = sin(x = var_3699_cast_fp16)[name = string("op_3700_cast_fp16")];
            fp16 var_24_promoted_100_to_fp16 = const()[name = string("op_24_promoted_100_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 32, ?]> var_3701_cast_fp16 = pow(x = var_3700_cast_fp16, y = var_24_promoted_100_to_fp16)[name = string("op_3701_cast_fp16")];
            tensor<fp16, [1, 32, 1]> var_3696_to_fp16 = const()[name = string("op_3696_to_fp16"), val = tensor<fp16, [1, 32, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41399680)))];
            tensor<fp16, [1, 32, ?]> var_3702_cast_fp16 = mul(x = var_3696_to_fp16, y = var_3701_cast_fp16)[name = string("op_3702_cast_fp16")];
            tensor<fp16, [1, 32, ?]> input_cast_fp16 = add(x = _inversed_x_15_cast_fp16, y = var_3702_cast_fp16)[name = string("input_cast_fp16")];
            string x_pad_type_0 = const()[name = string("x_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> x_pad_0 = const()[name = string("x_pad_0"), val = tensor<int32, [2]>([3, 3])];
            tensor<int32, [1]> x_strides_0 = const()[name = string("x_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> x_dilations_0 = const()[name = string("x_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_groups_0 = const()[name = string("x_groups_0"), val = int32(1)];
            tensor<fp16, [1, 32, 7]> generator_conv_post_weight_to_fp16 = const()[name = string("generator_conv_post_weight_to_fp16"), val = tensor<fp16, [1, 32, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41399808)))];
            tensor<fp16, [1]> generator_conv_post_bias_to_fp16 = const()[name = string("generator_conv_post_bias_to_fp16"), val = tensor<fp16, [1]>([0x1.26p-16])];
            tensor<fp16, [1, 1, ?]> x_cast_fp16 = conv(bias = generator_conv_post_bias_to_fp16, dilations = x_dilations_0, groups = x_groups_0, pad = x_pad_0, pad_type = x_pad_type_0, strides = x_strides_0, weight = generator_conv_post_weight_to_fp16, x = input_cast_fp16)[name = string("x_cast_fp16")];
            tensor<fp16, [1, 1, ?]> var_3711 = tanh(x = x_cast_fp16)[name = string("op_3711_cast_fp16")];
        } -> (var_3711);
}