program(1.3)
[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3600.16.1"}, {"coremlc-version", "3600.22.1"}})]
{
    func vocoder_l128<ios18>(tensor<fp16, [1, 144, 128]> latent) {
            fp16 _inversed_input_tensor_1_y_0_to_fp16 = const()[name = string("_inversed_input_tensor_1_y_0_to_fp16"), val = fp16(0x1p+2)];
            tensor<fp16, [1, 144, 128]> _inversed_input_tensor_1_cast_fp16 = mul(x = latent, y = _inversed_input_tensor_1_y_0_to_fp16)[name = string("_inversed_input_tensor_1_cast_fp16")];
            tensor<int32, [4]> var_213 = const()[name = string("op_213"), val = tensor<int32, [4]>([1, -1, 6, 128])];
            tensor<fp16, [1, 24, 6, 128]> input_tensor_9_cast_fp16 = reshape(shape = var_213, x = _inversed_input_tensor_1_cast_fp16)[name = string("input_tensor_9_cast_fp16")];
            tensor<int32, [4]> var_219 = const()[name = string("op_219"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_264 = const()[name = string("op_264"), val = tensor<int32, [3]>([1, 24, -1])];
            tensor<fp16, [1, 24, 128, 6]> input_tensor_11_cast_fp16 = transpose(perm = var_219, x = input_tensor_9_cast_fp16)[name = string("transpose_21")];
            tensor<fp16, [1, 24, 768]> first_1_cast_fp16 = reshape(shape = var_264, x = input_tensor_11_cast_fp16)[name = string("first_1_cast_fp16")];
            tensor<fp16, [1, 24, 1]> initializers_onnx_initializer_1_to_fp16 = const()[name = string("initializers_onnx_initializer_1_to_fp16"), val = tensor<fp16, [1, 24, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [1, 24, 768]> first_3_cast_fp16 = mul(x = first_1_cast_fp16, y = initializers_onnx_initializer_1_to_fp16)[name = string("first_3_cast_fp16")];
            tensor<fp16, [1, 24, 1]> initializers_onnx_initializer_2_to_fp16 = const()[name = string("initializers_onnx_initializer_2_to_fp16"), val = tensor<fp16, [1, 24, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192)))];
            tensor<fp16, [1, 24, 768]> input_1_cast_fp16 = add(x = first_3_cast_fp16, y = initializers_onnx_initializer_2_to_fp16)[name = string("input_1_cast_fp16")];
            tensor<int32, [6]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("replicate")];
            fp16 const_7_to_fp16 = const()[name = string("const_7_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 24, 774]> input_3_cast_fp16 = pad(constant_val = const_7_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string input_5_pad_type_0 = const()[name = string("input_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_5_strides_0 = const()[name = string("input_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_5_pad_0 = const()[name = string("input_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_5_dilations_0 = const()[name = string("input_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_5_groups_0 = const()[name = string("input_5_groups_0"), val = int32(1)];
            tensor<fp16, [512, 24, 7]> decoder_embed_net_Conv_weight_to_fp16 = const()[name = string("decoder_embed_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 24, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(320)))];
            tensor<fp16, [512]> decoder_embed_net_Conv_bias_to_fp16 = const()[name = string("decoder_embed_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(172416)))];
            tensor<fp16, [1, 512, 768]> input_5_cast_fp16 = conv(bias = decoder_embed_net_Conv_bias_to_fp16, dilations = input_5_dilations_0, groups = input_5_groups_0, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = input_5_strides_0, weight = decoder_embed_net_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = string("input_5_cast_fp16")];
            tensor<int32, [6]> input_7_pad_0 = const()[name = string("input_7_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_7_mode_0 = const()[name = string("input_7_mode_0"), val = string("replicate")];
            fp16 const_8_to_fp16 = const()[name = string("const_8_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 774]> input_7_cast_fp16 = pad(constant_val = const_8_to_fp16, mode = input_7_mode_0, pad = input_7_pad_0, x = input_5_cast_fp16)[name = string("input_7_cast_fp16")];
            string input_tensor_37_pad_type_0 = const()[name = string("input_tensor_37_pad_type_0"), val = string("valid")];
            int32 input_tensor_37_groups_0 = const()[name = string("input_tensor_37_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_37_strides_0 = const()[name = string("input_tensor_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_37_pad_0 = const()[name = string("input_tensor_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_37_dilations_0 = const()[name = string("input_tensor_37_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_0_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_0_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(173504)))];
            tensor<fp16, [512]> decoder_convnext_0_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_0_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(180736)))];
            tensor<fp16, [1, 512, 768]> input_tensor_37_cast_fp16 = conv(bias = decoder_convnext_0_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_37_dilations_0, groups = input_tensor_37_groups_0, pad = input_tensor_37_pad_0, pad_type = input_tensor_37_pad_type_0, strides = input_tensor_37_strides_0, weight = decoder_convnext_0_dwconv_net_Conv_weight_to_fp16, x = input_7_cast_fp16)[name = string("input_tensor_37_cast_fp16")];
            tensor<int32, [3]> var_307 = const()[name = string("op_307"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_39_axes_0 = const()[name = string("input_tensor_39_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(181824)))];
            tensor<fp16, [512]> decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(182912)))];
            fp16 var_310_to_fp16 = const()[name = string("op_310_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 768, 512]> input_9_cast_fp16 = transpose(perm = var_307, x = input_tensor_37_cast_fp16)[name = string("transpose_20")];
            tensor<fp16, [1, 768, 512]> input_tensor_39_cast_fp16 = layer_norm(axes = input_tensor_39_axes_0, beta = decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_310_to_fp16, gamma = decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16, x = input_9_cast_fp16)[name = string("input_tensor_39_cast_fp16")];
            tensor<int32, [3]> var_319 = const()[name = string("op_319"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_5_pad_type_0 = const()[name = string("first_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_5_strides_0 = const()[name = string("first_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_5_pad_0 = const()[name = string("first_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_5_dilations_0 = const()[name = string("first_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_5_groups_0 = const()[name = string("first_5_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_0_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_0_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(184000)))];
            tensor<fp16, [2048]> decoder_convnext_0_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_0_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2281216)))];
            tensor<fp16, [1, 512, 768]> input_11_cast_fp16 = transpose(perm = var_319, x = input_tensor_39_cast_fp16)[name = string("transpose_19")];
            tensor<fp16, [1, 2048, 768]> first_5_cast_fp16 = conv(bias = decoder_convnext_0_pwconv1_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = decoder_convnext_0_pwconv1_Conv_weight_to_fp16, x = input_11_cast_fp16)[name = string("first_5_cast_fp16")];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 768]> input_13_cast_fp16 = gelu(mode = input_13_mode_0, x = first_5_cast_fp16)[name = string("input_13_cast_fp16")];
            string second_15_pad_type_0 = const()[name = string("second_15_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_15_strides_0 = const()[name = string("second_15_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_15_pad_0 = const()[name = string("second_15_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_15_dilations_0 = const()[name = string("second_15_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_15_groups_0 = const()[name = string("second_15_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_17_weight_0_to_fp16 = const()[name = string("second_17_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2285376)))];
            tensor<fp16, [512]> second_17_bias_0_to_fp16 = const()[name = string("second_17_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4382592)))];
            tensor<fp16, [1, 512, 768]> second_17_cast_fp16 = conv(bias = second_17_bias_0_to_fp16, dilations = second_15_dilations_0, groups = second_15_groups_0, pad = second_15_pad_0, pad_type = second_15_pad_type_0, strides = second_15_strides_0, weight = second_17_weight_0_to_fp16, x = input_13_cast_fp16)[name = string("second_17_cast_fp16")];
            tensor<fp16, [1, 512, 768]> input_15_cast_fp16 = add(x = input_5_cast_fp16, y = second_17_cast_fp16)[name = string("input_15_cast_fp16")];
            tensor<int32, [6]> input_17_pad_0 = const()[name = string("input_17_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 12, 0])];
            string input_17_mode_0 = const()[name = string("input_17_mode_0"), val = string("replicate")];
            fp16 const_9_to_fp16 = const()[name = string("const_9_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 780]> input_17_cast_fp16 = pad(constant_val = const_9_to_fp16, mode = input_17_mode_0, pad = input_17_pad_0, x = input_15_cast_fp16)[name = string("input_17_cast_fp16")];
            string input_tensor_51_pad_type_0 = const()[name = string("input_tensor_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_51_dilations_0 = const()[name = string("input_tensor_51_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 input_tensor_51_groups_0 = const()[name = string("input_tensor_51_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_51_strides_0 = const()[name = string("input_tensor_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_51_pad_0 = const()[name = string("input_tensor_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_1_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_1_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4383680)))];
            tensor<fp16, [512]> decoder_convnext_1_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_1_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4390912)))];
            tensor<fp16, [1, 512, 768]> input_tensor_51_cast_fp16 = conv(bias = decoder_convnext_1_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_51_dilations_0, groups = input_tensor_51_groups_0, pad = input_tensor_51_pad_0, pad_type = input_tensor_51_pad_type_0, strides = input_tensor_51_strides_0, weight = decoder_convnext_1_dwconv_net_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = string("input_tensor_51_cast_fp16")];
            tensor<int32, [3]> var_374 = const()[name = string("op_374"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_53_axes_0 = const()[name = string("input_tensor_53_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4392000)))];
            tensor<fp16, [512]> decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4393088)))];
            fp16 var_377_to_fp16 = const()[name = string("op_377_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 768, 512]> input_19_cast_fp16 = transpose(perm = var_374, x = input_tensor_51_cast_fp16)[name = string("transpose_18")];
            tensor<fp16, [1, 768, 512]> input_tensor_53_cast_fp16 = layer_norm(axes = input_tensor_53_axes_0, beta = decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_377_to_fp16, gamma = decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16, x = input_19_cast_fp16)[name = string("input_tensor_53_cast_fp16")];
            tensor<int32, [3]> var_386 = const()[name = string("op_386"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_13_pad_type_0 = const()[name = string("first_13_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_13_strides_0 = const()[name = string("first_13_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_13_pad_0 = const()[name = string("first_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_13_dilations_0 = const()[name = string("first_13_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_13_groups_0 = const()[name = string("first_13_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_1_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_1_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4394176)))];
            tensor<fp16, [2048]> decoder_convnext_1_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_1_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6491392)))];
            tensor<fp16, [1, 512, 768]> input_21_cast_fp16 = transpose(perm = var_386, x = input_tensor_53_cast_fp16)[name = string("transpose_17")];
            tensor<fp16, [1, 2048, 768]> first_13_cast_fp16 = conv(bias = decoder_convnext_1_pwconv1_Conv_bias_to_fp16, dilations = first_13_dilations_0, groups = first_13_groups_0, pad = first_13_pad_0, pad_type = first_13_pad_type_0, strides = first_13_strides_0, weight = decoder_convnext_1_pwconv1_Conv_weight_to_fp16, x = input_21_cast_fp16)[name = string("first_13_cast_fp16")];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 768]> input_23_cast_fp16 = gelu(mode = input_23_mode_0, x = first_13_cast_fp16)[name = string("input_23_cast_fp16")];
            string second_27_pad_type_0 = const()[name = string("second_27_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_27_strides_0 = const()[name = string("second_27_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_27_pad_0 = const()[name = string("second_27_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_27_dilations_0 = const()[name = string("second_27_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_27_groups_0 = const()[name = string("second_27_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_29_weight_0_to_fp16 = const()[name = string("second_29_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6495552)))];
            tensor<fp16, [512]> second_29_bias_0_to_fp16 = const()[name = string("second_29_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8592768)))];
            tensor<fp16, [1, 512, 768]> second_29_cast_fp16 = conv(bias = second_29_bias_0_to_fp16, dilations = second_27_dilations_0, groups = second_27_groups_0, pad = second_27_pad_0, pad_type = second_27_pad_type_0, strides = second_27_strides_0, weight = second_29_weight_0_to_fp16, x = input_23_cast_fp16)[name = string("second_29_cast_fp16")];
            tensor<fp16, [1, 512, 768]> input_25_cast_fp16 = add(x = input_15_cast_fp16, y = second_29_cast_fp16)[name = string("input_25_cast_fp16")];
            tensor<int32, [6]> input_27_pad_0 = const()[name = string("input_27_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 24, 0])];
            string input_27_mode_0 = const()[name = string("input_27_mode_0"), val = string("replicate")];
            fp16 const_10_to_fp16 = const()[name = string("const_10_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 792]> input_27_cast_fp16 = pad(constant_val = const_10_to_fp16, mode = input_27_mode_0, pad = input_27_pad_0, x = input_25_cast_fp16)[name = string("input_27_cast_fp16")];
            string input_tensor_65_pad_type_0 = const()[name = string("input_tensor_65_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_65_dilations_0 = const()[name = string("input_tensor_65_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 input_tensor_65_groups_0 = const()[name = string("input_tensor_65_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_65_strides_0 = const()[name = string("input_tensor_65_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_65_pad_0 = const()[name = string("input_tensor_65_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_2_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_2_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8593856)))];
            tensor<fp16, [512]> decoder_convnext_2_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_2_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8601088)))];
            tensor<fp16, [1, 512, 768]> input_tensor_65_cast_fp16 = conv(bias = decoder_convnext_2_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_65_dilations_0, groups = input_tensor_65_groups_0, pad = input_tensor_65_pad_0, pad_type = input_tensor_65_pad_type_0, strides = input_tensor_65_strides_0, weight = decoder_convnext_2_dwconv_net_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = string("input_tensor_65_cast_fp16")];
            tensor<int32, [3]> var_441 = const()[name = string("op_441"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_67_axes_0 = const()[name = string("input_tensor_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8602176)))];
            tensor<fp16, [512]> decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8603264)))];
            fp16 var_444_to_fp16 = const()[name = string("op_444_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 768, 512]> input_29_cast_fp16 = transpose(perm = var_441, x = input_tensor_65_cast_fp16)[name = string("transpose_16")];
            tensor<fp16, [1, 768, 512]> input_tensor_67_cast_fp16 = layer_norm(axes = input_tensor_67_axes_0, beta = decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_444_to_fp16, gamma = decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16, x = input_29_cast_fp16)[name = string("input_tensor_67_cast_fp16")];
            tensor<int32, [3]> var_453 = const()[name = string("op_453"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_21_pad_type_0 = const()[name = string("first_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_21_strides_0 = const()[name = string("first_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_21_pad_0 = const()[name = string("first_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_21_dilations_0 = const()[name = string("first_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_21_groups_0 = const()[name = string("first_21_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_2_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_2_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8604352)))];
            tensor<fp16, [2048]> decoder_convnext_2_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_2_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10701568)))];
            tensor<fp16, [1, 512, 768]> input_31_cast_fp16 = transpose(perm = var_453, x = input_tensor_67_cast_fp16)[name = string("transpose_15")];
            tensor<fp16, [1, 2048, 768]> first_21_cast_fp16 = conv(bias = decoder_convnext_2_pwconv1_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = decoder_convnext_2_pwconv1_Conv_weight_to_fp16, x = input_31_cast_fp16)[name = string("first_21_cast_fp16")];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 768]> input_33_cast_fp16 = gelu(mode = input_33_mode_0, x = first_21_cast_fp16)[name = string("input_33_cast_fp16")];
            string second_39_pad_type_0 = const()[name = string("second_39_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_39_strides_0 = const()[name = string("second_39_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_39_pad_0 = const()[name = string("second_39_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_39_dilations_0 = const()[name = string("second_39_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_39_groups_0 = const()[name = string("second_39_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_41_weight_0_to_fp16 = const()[name = string("second_41_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10705728)))];
            tensor<fp16, [512]> second_41_bias_0_to_fp16 = const()[name = string("second_41_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12802944)))];
            tensor<fp16, [1, 512, 768]> second_41_cast_fp16 = conv(bias = second_41_bias_0_to_fp16, dilations = second_39_dilations_0, groups = second_39_groups_0, pad = second_39_pad_0, pad_type = second_39_pad_type_0, strides = second_39_strides_0, weight = second_41_weight_0_to_fp16, x = input_33_cast_fp16)[name = string("second_41_cast_fp16")];
            tensor<fp16, [1, 512, 768]> input_35_cast_fp16 = add(x = input_25_cast_fp16, y = second_41_cast_fp16)[name = string("input_35_cast_fp16")];
            tensor<int32, [6]> input_37_pad_0 = const()[name = string("input_37_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_37_mode_0 = const()[name = string("input_37_mode_0"), val = string("replicate")];
            fp16 const_11_to_fp16 = const()[name = string("const_11_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 774]> input_37_cast_fp16 = pad(constant_val = const_11_to_fp16, mode = input_37_mode_0, pad = input_37_pad_0, x = input_35_cast_fp16)[name = string("input_37_cast_fp16")];
            string input_tensor_79_pad_type_0 = const()[name = string("input_tensor_79_pad_type_0"), val = string("valid")];
            int32 input_tensor_79_groups_0 = const()[name = string("input_tensor_79_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_79_strides_0 = const()[name = string("input_tensor_79_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_79_pad_0 = const()[name = string("input_tensor_79_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_79_dilations_0 = const()[name = string("input_tensor_79_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_3_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_3_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12804032)))];
            tensor<fp16, [512]> decoder_convnext_3_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_3_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12811264)))];
            tensor<fp16, [1, 512, 768]> input_tensor_79_cast_fp16 = conv(bias = decoder_convnext_3_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_79_dilations_0, groups = input_tensor_79_groups_0, pad = input_tensor_79_pad_0, pad_type = input_tensor_79_pad_type_0, strides = input_tensor_79_strides_0, weight = decoder_convnext_3_dwconv_net_Conv_weight_to_fp16, x = input_37_cast_fp16)[name = string("input_tensor_79_cast_fp16")];
            tensor<int32, [3]> var_507 = const()[name = string("op_507"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_81_axes_0 = const()[name = string("input_tensor_81_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12812352)))];
            tensor<fp16, [512]> decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12813440)))];
            fp16 var_510_to_fp16 = const()[name = string("op_510_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 768, 512]> input_39_cast_fp16 = transpose(perm = var_507, x = input_tensor_79_cast_fp16)[name = string("transpose_14")];
            tensor<fp16, [1, 768, 512]> input_tensor_81_cast_fp16 = layer_norm(axes = input_tensor_81_axes_0, beta = decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_510_to_fp16, gamma = decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16, x = input_39_cast_fp16)[name = string("input_tensor_81_cast_fp16")];
            tensor<int32, [3]> var_519 = const()[name = string("op_519"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_29_pad_type_0 = const()[name = string("first_29_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_29_strides_0 = const()[name = string("first_29_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_29_pad_0 = const()[name = string("first_29_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_29_dilations_0 = const()[name = string("first_29_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_29_groups_0 = const()[name = string("first_29_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_3_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_3_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12814528)))];
            tensor<fp16, [2048]> decoder_convnext_3_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_3_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14911744)))];
            tensor<fp16, [1, 512, 768]> input_41_cast_fp16 = transpose(perm = var_519, x = input_tensor_81_cast_fp16)[name = string("transpose_13")];
            tensor<fp16, [1, 2048, 768]> first_29_cast_fp16 = conv(bias = decoder_convnext_3_pwconv1_Conv_bias_to_fp16, dilations = first_29_dilations_0, groups = first_29_groups_0, pad = first_29_pad_0, pad_type = first_29_pad_type_0, strides = first_29_strides_0, weight = decoder_convnext_3_pwconv1_Conv_weight_to_fp16, x = input_41_cast_fp16)[name = string("first_29_cast_fp16")];
            string input_43_mode_0 = const()[name = string("input_43_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 768]> input_43_cast_fp16 = gelu(mode = input_43_mode_0, x = first_29_cast_fp16)[name = string("input_43_cast_fp16")];
            string second_51_pad_type_0 = const()[name = string("second_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_51_strides_0 = const()[name = string("second_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_51_pad_0 = const()[name = string("second_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_51_dilations_0 = const()[name = string("second_51_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_51_groups_0 = const()[name = string("second_51_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_53_weight_0_to_fp16 = const()[name = string("second_53_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14915904)))];
            tensor<fp16, [512]> second_53_bias_0_to_fp16 = const()[name = string("second_53_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17013120)))];
            tensor<fp16, [1, 512, 768]> second_53_cast_fp16 = conv(bias = second_53_bias_0_to_fp16, dilations = second_51_dilations_0, groups = second_51_groups_0, pad = second_51_pad_0, pad_type = second_51_pad_type_0, strides = second_51_strides_0, weight = second_53_weight_0_to_fp16, x = input_43_cast_fp16)[name = string("second_53_cast_fp16")];
            tensor<fp16, [1, 512, 768]> input_45_cast_fp16 = add(x = input_35_cast_fp16, y = second_53_cast_fp16)[name = string("input_45_cast_fp16")];
            tensor<int32, [6]> input_47_pad_0 = const()[name = string("input_47_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 12, 0])];
            string input_47_mode_0 = const()[name = string("input_47_mode_0"), val = string("replicate")];
            fp16 const_12_to_fp16 = const()[name = string("const_12_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 780]> input_47_cast_fp16 = pad(constant_val = const_12_to_fp16, mode = input_47_mode_0, pad = input_47_pad_0, x = input_45_cast_fp16)[name = string("input_47_cast_fp16")];
            string input_tensor_93_pad_type_0 = const()[name = string("input_tensor_93_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_93_dilations_0 = const()[name = string("input_tensor_93_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 input_tensor_93_groups_0 = const()[name = string("input_tensor_93_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_93_strides_0 = const()[name = string("input_tensor_93_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_93_pad_0 = const()[name = string("input_tensor_93_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_4_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_4_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17014208)))];
            tensor<fp16, [512]> decoder_convnext_4_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_4_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17021440)))];
            tensor<fp16, [1, 512, 768]> input_tensor_93_cast_fp16 = conv(bias = decoder_convnext_4_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_93_dilations_0, groups = input_tensor_93_groups_0, pad = input_tensor_93_pad_0, pad_type = input_tensor_93_pad_type_0, strides = input_tensor_93_strides_0, weight = decoder_convnext_4_dwconv_net_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("input_tensor_93_cast_fp16")];
            tensor<int32, [3]> var_574 = const()[name = string("op_574"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_95_axes_0 = const()[name = string("input_tensor_95_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17022528)))];
            tensor<fp16, [512]> decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17023616)))];
            fp16 var_577_to_fp16 = const()[name = string("op_577_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 768, 512]> input_49_cast_fp16 = transpose(perm = var_574, x = input_tensor_93_cast_fp16)[name = string("transpose_12")];
            tensor<fp16, [1, 768, 512]> input_tensor_95_cast_fp16 = layer_norm(axes = input_tensor_95_axes_0, beta = decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_577_to_fp16, gamma = decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16, x = input_49_cast_fp16)[name = string("input_tensor_95_cast_fp16")];
            tensor<int32, [3]> var_586 = const()[name = string("op_586"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_37_pad_type_0 = const()[name = string("first_37_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_37_strides_0 = const()[name = string("first_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_37_pad_0 = const()[name = string("first_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_37_dilations_0 = const()[name = string("first_37_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_37_groups_0 = const()[name = string("first_37_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_4_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_4_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17024704)))];
            tensor<fp16, [2048]> decoder_convnext_4_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_4_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19121920)))];
            tensor<fp16, [1, 512, 768]> input_51_cast_fp16 = transpose(perm = var_586, x = input_tensor_95_cast_fp16)[name = string("transpose_11")];
            tensor<fp16, [1, 2048, 768]> first_37_cast_fp16 = conv(bias = decoder_convnext_4_pwconv1_Conv_bias_to_fp16, dilations = first_37_dilations_0, groups = first_37_groups_0, pad = first_37_pad_0, pad_type = first_37_pad_type_0, strides = first_37_strides_0, weight = decoder_convnext_4_pwconv1_Conv_weight_to_fp16, x = input_51_cast_fp16)[name = string("first_37_cast_fp16")];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 768]> input_53_cast_fp16 = gelu(mode = input_53_mode_0, x = first_37_cast_fp16)[name = string("input_53_cast_fp16")];
            string second_63_pad_type_0 = const()[name = string("second_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_63_strides_0 = const()[name = string("second_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_63_pad_0 = const()[name = string("second_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_63_dilations_0 = const()[name = string("second_63_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_63_groups_0 = const()[name = string("second_63_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_65_weight_0_to_fp16 = const()[name = string("second_65_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19126080)))];
            tensor<fp16, [512]> second_65_bias_0_to_fp16 = const()[name = string("second_65_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21223296)))];
            tensor<fp16, [1, 512, 768]> second_65_cast_fp16 = conv(bias = second_65_bias_0_to_fp16, dilations = second_63_dilations_0, groups = second_63_groups_0, pad = second_63_pad_0, pad_type = second_63_pad_type_0, strides = second_63_strides_0, weight = second_65_weight_0_to_fp16, x = input_53_cast_fp16)[name = string("second_65_cast_fp16")];
            tensor<fp16, [1, 512, 768]> input_55_cast_fp16 = add(x = input_45_cast_fp16, y = second_65_cast_fp16)[name = string("input_55_cast_fp16")];
            tensor<int32, [6]> input_57_pad_0 = const()[name = string("input_57_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 24, 0])];
            string input_57_mode_0 = const()[name = string("input_57_mode_0"), val = string("replicate")];
            fp16 const_13_to_fp16 = const()[name = string("const_13_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 792]> input_57_cast_fp16 = pad(constant_val = const_13_to_fp16, mode = input_57_mode_0, pad = input_57_pad_0, x = input_55_cast_fp16)[name = string("input_57_cast_fp16")];
            string input_tensor_107_pad_type_0 = const()[name = string("input_tensor_107_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_107_dilations_0 = const()[name = string("input_tensor_107_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 input_tensor_107_groups_0 = const()[name = string("input_tensor_107_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_107_strides_0 = const()[name = string("input_tensor_107_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_107_pad_0 = const()[name = string("input_tensor_107_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_5_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_5_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21224384)))];
            tensor<fp16, [512]> decoder_convnext_5_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_5_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21231616)))];
            tensor<fp16, [1, 512, 768]> input_tensor_107_cast_fp16 = conv(bias = decoder_convnext_5_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_107_dilations_0, groups = input_tensor_107_groups_0, pad = input_tensor_107_pad_0, pad_type = input_tensor_107_pad_type_0, strides = input_tensor_107_strides_0, weight = decoder_convnext_5_dwconv_net_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = string("input_tensor_107_cast_fp16")];
            tensor<int32, [3]> var_641 = const()[name = string("op_641"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_109_axes_0 = const()[name = string("input_tensor_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21232704)))];
            tensor<fp16, [512]> decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21233792)))];
            fp16 var_644_to_fp16 = const()[name = string("op_644_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 768, 512]> input_59_cast_fp16 = transpose(perm = var_641, x = input_tensor_107_cast_fp16)[name = string("transpose_10")];
            tensor<fp16, [1, 768, 512]> input_tensor_109_cast_fp16 = layer_norm(axes = input_tensor_109_axes_0, beta = decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_644_to_fp16, gamma = decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16, x = input_59_cast_fp16)[name = string("input_tensor_109_cast_fp16")];
            tensor<int32, [3]> var_653 = const()[name = string("op_653"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_45_pad_type_0 = const()[name = string("first_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_45_strides_0 = const()[name = string("first_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_45_pad_0 = const()[name = string("first_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_45_dilations_0 = const()[name = string("first_45_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_45_groups_0 = const()[name = string("first_45_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_5_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_5_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21234880)))];
            tensor<fp16, [2048]> decoder_convnext_5_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_5_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23332096)))];
            tensor<fp16, [1, 512, 768]> input_61_cast_fp16 = transpose(perm = var_653, x = input_tensor_109_cast_fp16)[name = string("transpose_9")];
            tensor<fp16, [1, 2048, 768]> first_45_cast_fp16 = conv(bias = decoder_convnext_5_pwconv1_Conv_bias_to_fp16, dilations = first_45_dilations_0, groups = first_45_groups_0, pad = first_45_pad_0, pad_type = first_45_pad_type_0, strides = first_45_strides_0, weight = decoder_convnext_5_pwconv1_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("first_45_cast_fp16")];
            string input_63_mode_0 = const()[name = string("input_63_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 768]> input_63_cast_fp16 = gelu(mode = input_63_mode_0, x = first_45_cast_fp16)[name = string("input_63_cast_fp16")];
            string second_75_pad_type_0 = const()[name = string("second_75_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_75_strides_0 = const()[name = string("second_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_75_pad_0 = const()[name = string("second_75_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_75_dilations_0 = const()[name = string("second_75_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_75_groups_0 = const()[name = string("second_75_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_77_weight_0_to_fp16 = const()[name = string("second_77_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23336256)))];
            tensor<fp16, [512]> second_77_bias_0_to_fp16 = const()[name = string("second_77_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25433472)))];
            tensor<fp16, [1, 512, 768]> second_77_cast_fp16 = conv(bias = second_77_bias_0_to_fp16, dilations = second_75_dilations_0, groups = second_75_groups_0, pad = second_75_pad_0, pad_type = second_75_pad_type_0, strides = second_75_strides_0, weight = second_77_weight_0_to_fp16, x = input_63_cast_fp16)[name = string("second_77_cast_fp16")];
            tensor<fp16, [1, 512, 768]> input_65_cast_fp16 = add(x = input_55_cast_fp16, y = second_77_cast_fp16)[name = string("input_65_cast_fp16")];
            tensor<int32, [6]> input_67_pad_0 = const()[name = string("input_67_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_67_mode_0 = const()[name = string("input_67_mode_0"), val = string("replicate")];
            fp16 const_14_to_fp16 = const()[name = string("const_14_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 774]> input_67_cast_fp16 = pad(constant_val = const_14_to_fp16, mode = input_67_mode_0, pad = input_67_pad_0, x = input_65_cast_fp16)[name = string("input_67_cast_fp16")];
            string input_tensor_121_pad_type_0 = const()[name = string("input_tensor_121_pad_type_0"), val = string("valid")];
            int32 input_tensor_121_groups_0 = const()[name = string("input_tensor_121_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_121_strides_0 = const()[name = string("input_tensor_121_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_121_pad_0 = const()[name = string("input_tensor_121_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_121_dilations_0 = const()[name = string("input_tensor_121_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_6_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_6_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25434560)))];
            tensor<fp16, [512]> decoder_convnext_6_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_6_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25441792)))];
            tensor<fp16, [1, 512, 768]> input_tensor_121_cast_fp16 = conv(bias = decoder_convnext_6_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_121_dilations_0, groups = input_tensor_121_groups_0, pad = input_tensor_121_pad_0, pad_type = input_tensor_121_pad_type_0, strides = input_tensor_121_strides_0, weight = decoder_convnext_6_dwconv_net_Conv_weight_to_fp16, x = input_67_cast_fp16)[name = string("input_tensor_121_cast_fp16")];
            tensor<int32, [3]> var_707 = const()[name = string("op_707"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_123_axes_0 = const()[name = string("input_tensor_123_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25442880)))];
            tensor<fp16, [512]> decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25443968)))];
            fp16 var_710_to_fp16 = const()[name = string("op_710_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 768, 512]> input_69_cast_fp16 = transpose(perm = var_707, x = input_tensor_121_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 768, 512]> input_tensor_123_cast_fp16 = layer_norm(axes = input_tensor_123_axes_0, beta = decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_710_to_fp16, gamma = decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16, x = input_69_cast_fp16)[name = string("input_tensor_123_cast_fp16")];
            tensor<int32, [3]> var_719 = const()[name = string("op_719"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_53_pad_type_0 = const()[name = string("first_53_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_53_strides_0 = const()[name = string("first_53_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_53_pad_0 = const()[name = string("first_53_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_53_dilations_0 = const()[name = string("first_53_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_53_groups_0 = const()[name = string("first_53_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_6_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_6_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25445056)))];
            tensor<fp16, [2048]> decoder_convnext_6_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_6_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27542272)))];
            tensor<fp16, [1, 512, 768]> input_71_cast_fp16 = transpose(perm = var_719, x = input_tensor_123_cast_fp16)[name = string("transpose_7")];
            tensor<fp16, [1, 2048, 768]> first_53_cast_fp16 = conv(bias = decoder_convnext_6_pwconv1_Conv_bias_to_fp16, dilations = first_53_dilations_0, groups = first_53_groups_0, pad = first_53_pad_0, pad_type = first_53_pad_type_0, strides = first_53_strides_0, weight = decoder_convnext_6_pwconv1_Conv_weight_to_fp16, x = input_71_cast_fp16)[name = string("first_53_cast_fp16")];
            string input_73_mode_0 = const()[name = string("input_73_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 768]> input_73_cast_fp16 = gelu(mode = input_73_mode_0, x = first_53_cast_fp16)[name = string("input_73_cast_fp16")];
            string second_87_pad_type_0 = const()[name = string("second_87_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_87_strides_0 = const()[name = string("second_87_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_87_pad_0 = const()[name = string("second_87_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_87_dilations_0 = const()[name = string("second_87_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_87_groups_0 = const()[name = string("second_87_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_89_weight_0_to_fp16 = const()[name = string("second_89_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27546432)))];
            tensor<fp16, [512]> second_89_bias_0_to_fp16 = const()[name = string("second_89_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29643648)))];
            tensor<fp16, [1, 512, 768]> second_89_cast_fp16 = conv(bias = second_89_bias_0_to_fp16, dilations = second_87_dilations_0, groups = second_87_groups_0, pad = second_87_pad_0, pad_type = second_87_pad_type_0, strides = second_87_strides_0, weight = second_89_weight_0_to_fp16, x = input_73_cast_fp16)[name = string("second_89_cast_fp16")];
            tensor<fp16, [1, 512, 768]> input_75_cast_fp16 = add(x = input_65_cast_fp16, y = second_89_cast_fp16)[name = string("input_75_cast_fp16")];
            tensor<int32, [6]> input_77_pad_0 = const()[name = string("input_77_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_77_mode_0 = const()[name = string("input_77_mode_0"), val = string("replicate")];
            fp16 const_15_to_fp16 = const()[name = string("const_15_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 774]> input_77_cast_fp16 = pad(constant_val = const_15_to_fp16, mode = input_77_mode_0, pad = input_77_pad_0, x = input_75_cast_fp16)[name = string("input_77_cast_fp16")];
            string input_tensor_135_pad_type_0 = const()[name = string("input_tensor_135_pad_type_0"), val = string("valid")];
            int32 input_tensor_135_groups_0 = const()[name = string("input_tensor_135_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_135_strides_0 = const()[name = string("input_tensor_135_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_135_pad_0 = const()[name = string("input_tensor_135_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_135_dilations_0 = const()[name = string("input_tensor_135_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_7_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_7_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29644736)))];
            tensor<fp16, [512]> decoder_convnext_7_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_7_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29651968)))];
            tensor<fp16, [1, 512, 768]> input_tensor_135_cast_fp16 = conv(bias = decoder_convnext_7_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_135_dilations_0, groups = input_tensor_135_groups_0, pad = input_tensor_135_pad_0, pad_type = input_tensor_135_pad_type_0, strides = input_tensor_135_strides_0, weight = decoder_convnext_7_dwconv_net_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = string("input_tensor_135_cast_fp16")];
            tensor<int32, [3]> var_773 = const()[name = string("op_773"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_137_axes_0 = const()[name = string("input_tensor_137_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29653056)))];
            tensor<fp16, [512]> decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29654144)))];
            fp16 var_776_to_fp16 = const()[name = string("op_776_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 768, 512]> input_79_cast_fp16 = transpose(perm = var_773, x = input_tensor_135_cast_fp16)[name = string("transpose_6")];
            tensor<fp16, [1, 768, 512]> input_tensor_137_cast_fp16 = layer_norm(axes = input_tensor_137_axes_0, beta = decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_776_to_fp16, gamma = decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_tensor_137_cast_fp16")];
            tensor<int32, [3]> var_785 = const()[name = string("op_785"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_61_pad_type_0 = const()[name = string("first_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_61_strides_0 = const()[name = string("first_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_61_pad_0 = const()[name = string("first_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_61_dilations_0 = const()[name = string("first_61_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_61_groups_0 = const()[name = string("first_61_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_7_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_7_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29655232)))];
            tensor<fp16, [2048]> decoder_convnext_7_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_7_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31752448)))];
            tensor<fp16, [1, 512, 768]> input_81_cast_fp16 = transpose(perm = var_785, x = input_tensor_137_cast_fp16)[name = string("transpose_5")];
            tensor<fp16, [1, 2048, 768]> first_61_cast_fp16 = conv(bias = decoder_convnext_7_pwconv1_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = decoder_convnext_7_pwconv1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = string("first_61_cast_fp16")];
            string input_83_mode_0 = const()[name = string("input_83_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 768]> input_83_cast_fp16 = gelu(mode = input_83_mode_0, x = first_61_cast_fp16)[name = string("input_83_cast_fp16")];
            string second_99_pad_type_0 = const()[name = string("second_99_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_99_strides_0 = const()[name = string("second_99_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_99_pad_0 = const()[name = string("second_99_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_99_dilations_0 = const()[name = string("second_99_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_99_groups_0 = const()[name = string("second_99_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_101_weight_0_to_fp16 = const()[name = string("second_101_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31756608)))];
            tensor<fp16, [512]> second_101_bias_0_to_fp16 = const()[name = string("second_101_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33853824)))];
            tensor<fp16, [1, 512, 768]> second_101_cast_fp16 = conv(bias = second_101_bias_0_to_fp16, dilations = second_99_dilations_0, groups = second_99_groups_0, pad = second_99_pad_0, pad_type = second_99_pad_type_0, strides = second_99_strides_0, weight = second_101_weight_0_to_fp16, x = input_83_cast_fp16)[name = string("second_101_cast_fp16")];
            tensor<fp16, [1, 512, 768]> input_85_cast_fp16 = add(x = input_75_cast_fp16, y = second_101_cast_fp16)[name = string("input_85_cast_fp16")];
            tensor<int32, [6]> input_87_pad_0 = const()[name = string("input_87_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_87_mode_0 = const()[name = string("input_87_mode_0"), val = string("replicate")];
            fp16 const_16_to_fp16 = const()[name = string("const_16_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 774]> input_87_cast_fp16 = pad(constant_val = const_16_to_fp16, mode = input_87_mode_0, pad = input_87_pad_0, x = input_85_cast_fp16)[name = string("input_87_cast_fp16")];
            string input_tensor_149_pad_type_0 = const()[name = string("input_tensor_149_pad_type_0"), val = string("valid")];
            int32 input_tensor_149_groups_0 = const()[name = string("input_tensor_149_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_149_strides_0 = const()[name = string("input_tensor_149_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_149_pad_0 = const()[name = string("input_tensor_149_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_149_dilations_0 = const()[name = string("input_tensor_149_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_8_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_8_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33854912)))];
            tensor<fp16, [512]> decoder_convnext_8_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_8_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33862144)))];
            tensor<fp16, [1, 512, 768]> input_tensor_149_cast_fp16 = conv(bias = decoder_convnext_8_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_149_dilations_0, groups = input_tensor_149_groups_0, pad = input_tensor_149_pad_0, pad_type = input_tensor_149_pad_type_0, strides = input_tensor_149_strides_0, weight = decoder_convnext_8_dwconv_net_Conv_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_tensor_149_cast_fp16")];
            tensor<int32, [3]> var_839 = const()[name = string("op_839"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_151_axes_0 = const()[name = string("input_tensor_151_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33863232)))];
            tensor<fp16, [512]> decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33864320)))];
            fp16 var_842_to_fp16 = const()[name = string("op_842_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 768, 512]> input_89_cast_fp16 = transpose(perm = var_839, x = input_tensor_149_cast_fp16)[name = string("transpose_4")];
            tensor<fp16, [1, 768, 512]> input_tensor_151_cast_fp16 = layer_norm(axes = input_tensor_151_axes_0, beta = decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_842_to_fp16, gamma = decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_151_cast_fp16")];
            tensor<int32, [3]> var_851 = const()[name = string("op_851"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_69_pad_type_0 = const()[name = string("first_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_69_strides_0 = const()[name = string("first_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_69_pad_0 = const()[name = string("first_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_69_dilations_0 = const()[name = string("first_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_69_groups_0 = const()[name = string("first_69_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_8_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_8_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33865408)))];
            tensor<fp16, [2048]> decoder_convnext_8_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_8_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35962624)))];
            tensor<fp16, [1, 512, 768]> input_91_cast_fp16 = transpose(perm = var_851, x = input_tensor_151_cast_fp16)[name = string("transpose_3")];
            tensor<fp16, [1, 2048, 768]> first_69_cast_fp16 = conv(bias = decoder_convnext_8_pwconv1_Conv_bias_to_fp16, dilations = first_69_dilations_0, groups = first_69_groups_0, pad = first_69_pad_0, pad_type = first_69_pad_type_0, strides = first_69_strides_0, weight = decoder_convnext_8_pwconv1_Conv_weight_to_fp16, x = input_91_cast_fp16)[name = string("first_69_cast_fp16")];
            string input_93_mode_0 = const()[name = string("input_93_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 768]> input_93_cast_fp16 = gelu(mode = input_93_mode_0, x = first_69_cast_fp16)[name = string("input_93_cast_fp16")];
            string second_111_pad_type_0 = const()[name = string("second_111_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_111_strides_0 = const()[name = string("second_111_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_111_pad_0 = const()[name = string("second_111_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_111_dilations_0 = const()[name = string("second_111_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_111_groups_0 = const()[name = string("second_111_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_113_weight_0_to_fp16 = const()[name = string("second_113_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35966784)))];
            tensor<fp16, [512]> second_113_bias_0_to_fp16 = const()[name = string("second_113_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38064000)))];
            tensor<fp16, [1, 512, 768]> second_113_cast_fp16 = conv(bias = second_113_bias_0_to_fp16, dilations = second_111_dilations_0, groups = second_111_groups_0, pad = second_111_pad_0, pad_type = second_111_pad_type_0, strides = second_111_strides_0, weight = second_113_weight_0_to_fp16, x = input_93_cast_fp16)[name = string("second_113_cast_fp16")];
            tensor<fp16, [1, 512, 768]> input_95_cast_fp16 = add(x = input_85_cast_fp16, y = second_113_cast_fp16)[name = string("input_95_cast_fp16")];
            tensor<int32, [6]> input_97_pad_0 = const()[name = string("input_97_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_97_mode_0 = const()[name = string("input_97_mode_0"), val = string("replicate")];
            fp16 const_17_to_fp16 = const()[name = string("const_17_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 774]> input_97_cast_fp16 = pad(constant_val = const_17_to_fp16, mode = input_97_mode_0, pad = input_97_pad_0, x = input_95_cast_fp16)[name = string("input_97_cast_fp16")];
            string input_tensor_163_pad_type_0 = const()[name = string("input_tensor_163_pad_type_0"), val = string("valid")];
            int32 input_tensor_163_groups_0 = const()[name = string("input_tensor_163_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_163_strides_0 = const()[name = string("input_tensor_163_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_163_pad_0 = const()[name = string("input_tensor_163_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_163_dilations_0 = const()[name = string("input_tensor_163_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_9_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_9_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38065088)))];
            tensor<fp16, [512]> decoder_convnext_9_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_9_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38072320)))];
            tensor<fp16, [1, 512, 768]> input_tensor_163_cast_fp16 = conv(bias = decoder_convnext_9_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_163_dilations_0, groups = input_tensor_163_groups_0, pad = input_tensor_163_pad_0, pad_type = input_tensor_163_pad_type_0, strides = input_tensor_163_strides_0, weight = decoder_convnext_9_dwconv_net_Conv_weight_to_fp16, x = input_97_cast_fp16)[name = string("input_tensor_163_cast_fp16")];
            tensor<int32, [3]> var_905 = const()[name = string("op_905"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_165_axes_0 = const()[name = string("input_tensor_165_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38073408)))];
            tensor<fp16, [512]> decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38074496)))];
            fp16 var_908_to_fp16 = const()[name = string("op_908_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 768, 512]> input_99_cast_fp16 = transpose(perm = var_905, x = input_tensor_163_cast_fp16)[name = string("transpose_2")];
            tensor<fp16, [1, 768, 512]> input_tensor_165_cast_fp16 = layer_norm(axes = input_tensor_165_axes_0, beta = decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_908_to_fp16, gamma = decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16, x = input_99_cast_fp16)[name = string("input_tensor_165_cast_fp16")];
            tensor<int32, [3]> var_917 = const()[name = string("op_917"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_77_pad_type_0 = const()[name = string("first_77_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_77_strides_0 = const()[name = string("first_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_77_pad_0 = const()[name = string("first_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_77_dilations_0 = const()[name = string("first_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_77_groups_0 = const()[name = string("first_77_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_9_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_9_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38075584)))];
            tensor<fp16, [2048]> decoder_convnext_9_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_9_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40172800)))];
            tensor<fp16, [1, 512, 768]> input_101_cast_fp16 = transpose(perm = var_917, x = input_tensor_165_cast_fp16)[name = string("transpose_1")];
            tensor<fp16, [1, 2048, 768]> first_77_cast_fp16 = conv(bias = decoder_convnext_9_pwconv1_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = decoder_convnext_9_pwconv1_Conv_weight_to_fp16, x = input_101_cast_fp16)[name = string("first_77_cast_fp16")];
            string input_103_mode_0 = const()[name = string("input_103_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 768]> input_103_cast_fp16 = gelu(mode = input_103_mode_0, x = first_77_cast_fp16)[name = string("input_103_cast_fp16")];
            string second_123_pad_type_0 = const()[name = string("second_123_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_123_strides_0 = const()[name = string("second_123_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_123_pad_0 = const()[name = string("second_123_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_123_dilations_0 = const()[name = string("second_123_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_123_groups_0 = const()[name = string("second_123_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_weight_0_to_fp16 = const()[name = string("second_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40176960)))];
            tensor<fp16, [512]> second_bias_0_to_fp16 = const()[name = string("second_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42274176)))];
            tensor<fp16, [1, 512, 768]> second_cast_fp16 = conv(bias = second_bias_0_to_fp16, dilations = second_123_dilations_0, groups = second_123_groups_0, pad = second_123_pad_0, pad_type = second_123_pad_type_0, strides = second_123_strides_0, weight = second_weight_0_to_fp16, x = input_103_cast_fp16)[name = string("second_cast_fp16")];
            tensor<fp16, [1, 512, 768]> input_105_cast_fp16 = add(x = input_95_cast_fp16, y = second_cast_fp16)[name = string("input_105_cast_fp16")];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_running_mean_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42275264)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_running_var_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42276352)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_weight_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42277440)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_bias_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42278528)))];
            fp16 var_951_to_fp16 = const()[name = string("op_951_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 512, 768]> input_107_cast_fp16 = batch_norm(beta = decoder_final_norm_BatchNormalization_bias_to_fp16, epsilon = var_951_to_fp16, gamma = decoder_final_norm_BatchNormalization_weight_to_fp16, mean = decoder_final_norm_BatchNormalization_running_mean_to_fp16, variance = decoder_final_norm_BatchNormalization_running_var_to_fp16, x = input_105_cast_fp16)[name = string("input_107_cast_fp16")];
            tensor<int32, [6]> input_109_pad_0 = const()[name = string("input_109_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 0])];
            string input_109_mode_0 = const()[name = string("input_109_mode_0"), val = string("replicate")];
            fp16 const_18_to_fp16 = const()[name = string("const_18_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 770]> input_109_cast_fp16 = pad(constant_val = const_18_to_fp16, mode = input_109_mode_0, pad = input_109_pad_0, x = input_107_cast_fp16)[name = string("input_109_cast_fp16")];
            string input_tensor_177_pad_type_0 = const()[name = string("input_tensor_177_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_177_strides_0 = const()[name = string("input_tensor_177_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_177_pad_0 = const()[name = string("input_tensor_177_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_177_dilations_0 = const()[name = string("input_tensor_177_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_177_groups_0 = const()[name = string("input_tensor_177_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 3]> decoder_head_layer1_net_Conv_weight_to_fp16 = const()[name = string("decoder_head_layer1_net_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42279616)))];
            tensor<fp16, [2048]> decoder_head_layer1_net_Conv_bias_to_fp16 = const()[name = string("decoder_head_layer1_net_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48571136)))];
            tensor<fp16, [1, 2048, 768]> input_tensor_177_cast_fp16 = conv(bias = decoder_head_layer1_net_Conv_bias_to_fp16, dilations = input_tensor_177_dilations_0, groups = input_tensor_177_groups_0, pad = input_tensor_177_pad_0, pad_type = input_tensor_177_pad_type_0, strides = input_tensor_177_strides_0, weight = decoder_head_layer1_net_Conv_weight_to_fp16, x = input_109_cast_fp16)[name = string("input_tensor_177_cast_fp16")];
            fp32 input_alpha_1 = const()[name = string("input_alpha_1"), val = fp32(0x1.9814fap-13)];
            tensor<fp16, [1, 2048, 768]> input_cast_fp16 = leaky_relu(alpha = input_alpha_1, x = input_tensor_177_cast_fp16)[name = string("input_cast_fp16")];
            string input_tensor_179_pad_type_0 = const()[name = string("input_tensor_179_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_179_strides_0 = const()[name = string("input_tensor_179_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_179_pad_0 = const()[name = string("input_tensor_179_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_179_dilations_0 = const()[name = string("input_tensor_179_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_179_groups_0 = const()[name = string("input_tensor_179_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> decoder_head_layer2_Conv_weight_to_fp16 = const()[name = string("decoder_head_layer2_Conv_weight_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48575296)))];
            tensor<fp16, [1, 512, 768]> input_tensor_179_cast_fp16 = conv(dilations = input_tensor_179_dilations_0, groups = input_tensor_179_groups_0, pad = input_tensor_179_pad_0, pad_type = input_tensor_179_pad_type_0, strides = input_tensor_179_strides_0, weight = decoder_head_layer2_Conv_weight_to_fp16, x = input_cast_fp16)[name = string("input_tensor_179_cast_fp16")];
            tensor<int32, [3]> var_994 = const()[name = string("op_994"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [2]> var_1021 = const()[name = string("op_1021"), val = tensor<int32, [2]>([1, -1])];
            tensor<fp16, [1, 768, 512]> input_tensor_181_cast_fp16 = transpose(perm = var_994, x = input_tensor_179_cast_fp16)[name = string("transpose_0")];
            tensor<fp16, [1, 393216]> wav_tts = reshape(shape = var_1021, x = input_tensor_181_cast_fp16)[name = string("op_1022_cast_fp16")];
        } -> (wav_tts);
    func vocoder_l16<ios18>(tensor<fp16, [1, 144, 16]> latent) {
            fp16 _inversed_input_tensor_1_y_0_to_fp16 = const()[name = string("_inversed_input_tensor_1_y_0_to_fp16"), val = fp16(0x1p+2)];
            tensor<fp16, [1, 144, 16]> _inversed_input_tensor_1_cast_fp16 = mul(x = latent, y = _inversed_input_tensor_1_y_0_to_fp16)[name = string("_inversed_input_tensor_1_cast_fp16")];
            tensor<int32, [4]> var_213 = const()[name = string("op_213"), val = tensor<int32, [4]>([1, -1, 6, 16])];
            tensor<fp16, [1, 24, 6, 16]> input_tensor_9_cast_fp16 = reshape(shape = var_213, x = _inversed_input_tensor_1_cast_fp16)[name = string("input_tensor_9_cast_fp16")];
            tensor<int32, [4]> var_219 = const()[name = string("op_219"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_264 = const()[name = string("op_264"), val = tensor<int32, [3]>([1, 24, -1])];
            tensor<fp16, [1, 24, 16, 6]> input_tensor_11_cast_fp16 = transpose(perm = var_219, x = input_tensor_9_cast_fp16)[name = string("transpose_21")];
            tensor<fp16, [1, 24, 96]> first_1_cast_fp16 = reshape(shape = var_264, x = input_tensor_11_cast_fp16)[name = string("first_1_cast_fp16")];
            tensor<fp16, [1, 24, 1]> initializers_onnx_initializer_1_to_fp16 = const()[name = string("initializers_onnx_initializer_1_to_fp16"), val = tensor<fp16, [1, 24, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [1, 24, 96]> first_3_cast_fp16 = mul(x = first_1_cast_fp16, y = initializers_onnx_initializer_1_to_fp16)[name = string("first_3_cast_fp16")];
            tensor<fp16, [1, 24, 1]> initializers_onnx_initializer_2_to_fp16 = const()[name = string("initializers_onnx_initializer_2_to_fp16"), val = tensor<fp16, [1, 24, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192)))];
            tensor<fp16, [1, 24, 96]> input_1_cast_fp16 = add(x = first_3_cast_fp16, y = initializers_onnx_initializer_2_to_fp16)[name = string("input_1_cast_fp16")];
            tensor<int32, [6]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("replicate")];
            fp16 const_7_to_fp16 = const()[name = string("const_7_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 24, 102]> input_3_cast_fp16 = pad(constant_val = const_7_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string input_5_pad_type_0 = const()[name = string("input_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_5_strides_0 = const()[name = string("input_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_5_pad_0 = const()[name = string("input_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_5_dilations_0 = const()[name = string("input_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_5_groups_0 = const()[name = string("input_5_groups_0"), val = int32(1)];
            tensor<fp16, [512, 24, 7]> decoder_embed_net_Conv_weight_to_fp16 = const()[name = string("decoder_embed_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 24, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(320)))];
            tensor<fp16, [512]> decoder_embed_net_Conv_bias_to_fp16 = const()[name = string("decoder_embed_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(172416)))];
            tensor<fp16, [1, 512, 96]> input_5_cast_fp16 = conv(bias = decoder_embed_net_Conv_bias_to_fp16, dilations = input_5_dilations_0, groups = input_5_groups_0, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = input_5_strides_0, weight = decoder_embed_net_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = string("input_5_cast_fp16")];
            tensor<int32, [6]> input_7_pad_0 = const()[name = string("input_7_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_7_mode_0 = const()[name = string("input_7_mode_0"), val = string("replicate")];
            fp16 const_8_to_fp16 = const()[name = string("const_8_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 102]> input_7_cast_fp16 = pad(constant_val = const_8_to_fp16, mode = input_7_mode_0, pad = input_7_pad_0, x = input_5_cast_fp16)[name = string("input_7_cast_fp16")];
            string input_tensor_37_pad_type_0 = const()[name = string("input_tensor_37_pad_type_0"), val = string("valid")];
            int32 input_tensor_37_groups_0 = const()[name = string("input_tensor_37_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_37_strides_0 = const()[name = string("input_tensor_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_37_pad_0 = const()[name = string("input_tensor_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_37_dilations_0 = const()[name = string("input_tensor_37_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_0_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_0_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(173504)))];
            tensor<fp16, [512]> decoder_convnext_0_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_0_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(180736)))];
            tensor<fp16, [1, 512, 96]> input_tensor_37_cast_fp16 = conv(bias = decoder_convnext_0_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_37_dilations_0, groups = input_tensor_37_groups_0, pad = input_tensor_37_pad_0, pad_type = input_tensor_37_pad_type_0, strides = input_tensor_37_strides_0, weight = decoder_convnext_0_dwconv_net_Conv_weight_to_fp16, x = input_7_cast_fp16)[name = string("input_tensor_37_cast_fp16")];
            tensor<int32, [3]> var_307 = const()[name = string("op_307"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_39_axes_0 = const()[name = string("input_tensor_39_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(181824)))];
            tensor<fp16, [512]> decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(182912)))];
            fp16 var_310_to_fp16 = const()[name = string("op_310_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 96, 512]> input_9_cast_fp16 = transpose(perm = var_307, x = input_tensor_37_cast_fp16)[name = string("transpose_20")];
            tensor<fp16, [1, 96, 512]> input_tensor_39_cast_fp16 = layer_norm(axes = input_tensor_39_axes_0, beta = decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_310_to_fp16, gamma = decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16, x = input_9_cast_fp16)[name = string("input_tensor_39_cast_fp16")];
            tensor<int32, [3]> var_319 = const()[name = string("op_319"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_5_pad_type_0 = const()[name = string("first_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_5_strides_0 = const()[name = string("first_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_5_pad_0 = const()[name = string("first_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_5_dilations_0 = const()[name = string("first_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_5_groups_0 = const()[name = string("first_5_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_0_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_0_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(184000)))];
            tensor<fp16, [2048]> decoder_convnext_0_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_0_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2281216)))];
            tensor<fp16, [1, 512, 96]> input_11_cast_fp16 = transpose(perm = var_319, x = input_tensor_39_cast_fp16)[name = string("transpose_19")];
            tensor<fp16, [1, 2048, 96]> first_5_cast_fp16 = conv(bias = decoder_convnext_0_pwconv1_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = decoder_convnext_0_pwconv1_Conv_weight_to_fp16, x = input_11_cast_fp16)[name = string("first_5_cast_fp16")];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 96]> input_13_cast_fp16 = gelu(mode = input_13_mode_0, x = first_5_cast_fp16)[name = string("input_13_cast_fp16")];
            string second_15_pad_type_0 = const()[name = string("second_15_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_15_strides_0 = const()[name = string("second_15_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_15_pad_0 = const()[name = string("second_15_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_15_dilations_0 = const()[name = string("second_15_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_15_groups_0 = const()[name = string("second_15_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_17_weight_0_to_fp16 = const()[name = string("second_17_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2285376)))];
            tensor<fp16, [512]> second_17_bias_0_to_fp16 = const()[name = string("second_17_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4382592)))];
            tensor<fp16, [1, 512, 96]> second_17_cast_fp16 = conv(bias = second_17_bias_0_to_fp16, dilations = second_15_dilations_0, groups = second_15_groups_0, pad = second_15_pad_0, pad_type = second_15_pad_type_0, strides = second_15_strides_0, weight = second_17_weight_0_to_fp16, x = input_13_cast_fp16)[name = string("second_17_cast_fp16")];
            tensor<fp16, [1, 512, 96]> input_15_cast_fp16 = add(x = input_5_cast_fp16, y = second_17_cast_fp16)[name = string("input_15_cast_fp16")];
            tensor<int32, [6]> input_17_pad_0 = const()[name = string("input_17_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 12, 0])];
            string input_17_mode_0 = const()[name = string("input_17_mode_0"), val = string("replicate")];
            fp16 const_9_to_fp16 = const()[name = string("const_9_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 108]> input_17_cast_fp16 = pad(constant_val = const_9_to_fp16, mode = input_17_mode_0, pad = input_17_pad_0, x = input_15_cast_fp16)[name = string("input_17_cast_fp16")];
            string input_tensor_51_pad_type_0 = const()[name = string("input_tensor_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_51_dilations_0 = const()[name = string("input_tensor_51_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 input_tensor_51_groups_0 = const()[name = string("input_tensor_51_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_51_strides_0 = const()[name = string("input_tensor_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_51_pad_0 = const()[name = string("input_tensor_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_1_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_1_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4383680)))];
            tensor<fp16, [512]> decoder_convnext_1_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_1_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4390912)))];
            tensor<fp16, [1, 512, 96]> input_tensor_51_cast_fp16 = conv(bias = decoder_convnext_1_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_51_dilations_0, groups = input_tensor_51_groups_0, pad = input_tensor_51_pad_0, pad_type = input_tensor_51_pad_type_0, strides = input_tensor_51_strides_0, weight = decoder_convnext_1_dwconv_net_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = string("input_tensor_51_cast_fp16")];
            tensor<int32, [3]> var_374 = const()[name = string("op_374"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_53_axes_0 = const()[name = string("input_tensor_53_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4392000)))];
            tensor<fp16, [512]> decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4393088)))];
            fp16 var_377_to_fp16 = const()[name = string("op_377_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 96, 512]> input_19_cast_fp16 = transpose(perm = var_374, x = input_tensor_51_cast_fp16)[name = string("transpose_18")];
            tensor<fp16, [1, 96, 512]> input_tensor_53_cast_fp16 = layer_norm(axes = input_tensor_53_axes_0, beta = decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_377_to_fp16, gamma = decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16, x = input_19_cast_fp16)[name = string("input_tensor_53_cast_fp16")];
            tensor<int32, [3]> var_386 = const()[name = string("op_386"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_13_pad_type_0 = const()[name = string("first_13_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_13_strides_0 = const()[name = string("first_13_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_13_pad_0 = const()[name = string("first_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_13_dilations_0 = const()[name = string("first_13_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_13_groups_0 = const()[name = string("first_13_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_1_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_1_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4394176)))];
            tensor<fp16, [2048]> decoder_convnext_1_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_1_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6491392)))];
            tensor<fp16, [1, 512, 96]> input_21_cast_fp16 = transpose(perm = var_386, x = input_tensor_53_cast_fp16)[name = string("transpose_17")];
            tensor<fp16, [1, 2048, 96]> first_13_cast_fp16 = conv(bias = decoder_convnext_1_pwconv1_Conv_bias_to_fp16, dilations = first_13_dilations_0, groups = first_13_groups_0, pad = first_13_pad_0, pad_type = first_13_pad_type_0, strides = first_13_strides_0, weight = decoder_convnext_1_pwconv1_Conv_weight_to_fp16, x = input_21_cast_fp16)[name = string("first_13_cast_fp16")];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 96]> input_23_cast_fp16 = gelu(mode = input_23_mode_0, x = first_13_cast_fp16)[name = string("input_23_cast_fp16")];
            string second_27_pad_type_0 = const()[name = string("second_27_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_27_strides_0 = const()[name = string("second_27_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_27_pad_0 = const()[name = string("second_27_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_27_dilations_0 = const()[name = string("second_27_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_27_groups_0 = const()[name = string("second_27_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_29_weight_0_to_fp16 = const()[name = string("second_29_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6495552)))];
            tensor<fp16, [512]> second_29_bias_0_to_fp16 = const()[name = string("second_29_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8592768)))];
            tensor<fp16, [1, 512, 96]> second_29_cast_fp16 = conv(bias = second_29_bias_0_to_fp16, dilations = second_27_dilations_0, groups = second_27_groups_0, pad = second_27_pad_0, pad_type = second_27_pad_type_0, strides = second_27_strides_0, weight = second_29_weight_0_to_fp16, x = input_23_cast_fp16)[name = string("second_29_cast_fp16")];
            tensor<fp16, [1, 512, 96]> input_25_cast_fp16 = add(x = input_15_cast_fp16, y = second_29_cast_fp16)[name = string("input_25_cast_fp16")];
            tensor<int32, [6]> input_27_pad_0 = const()[name = string("input_27_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 24, 0])];
            string input_27_mode_0 = const()[name = string("input_27_mode_0"), val = string("replicate")];
            fp16 const_10_to_fp16 = const()[name = string("const_10_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 120]> input_27_cast_fp16 = pad(constant_val = const_10_to_fp16, mode = input_27_mode_0, pad = input_27_pad_0, x = input_25_cast_fp16)[name = string("input_27_cast_fp16")];
            string input_tensor_65_pad_type_0 = const()[name = string("input_tensor_65_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_65_dilations_0 = const()[name = string("input_tensor_65_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 input_tensor_65_groups_0 = const()[name = string("input_tensor_65_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_65_strides_0 = const()[name = string("input_tensor_65_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_65_pad_0 = const()[name = string("input_tensor_65_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_2_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_2_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8593856)))];
            tensor<fp16, [512]> decoder_convnext_2_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_2_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8601088)))];
            tensor<fp16, [1, 512, 96]> input_tensor_65_cast_fp16 = conv(bias = decoder_convnext_2_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_65_dilations_0, groups = input_tensor_65_groups_0, pad = input_tensor_65_pad_0, pad_type = input_tensor_65_pad_type_0, strides = input_tensor_65_strides_0, weight = decoder_convnext_2_dwconv_net_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = string("input_tensor_65_cast_fp16")];
            tensor<int32, [3]> var_441 = const()[name = string("op_441"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_67_axes_0 = const()[name = string("input_tensor_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8602176)))];
            tensor<fp16, [512]> decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8603264)))];
            fp16 var_444_to_fp16 = const()[name = string("op_444_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 96, 512]> input_29_cast_fp16 = transpose(perm = var_441, x = input_tensor_65_cast_fp16)[name = string("transpose_16")];
            tensor<fp16, [1, 96, 512]> input_tensor_67_cast_fp16 = layer_norm(axes = input_tensor_67_axes_0, beta = decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_444_to_fp16, gamma = decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16, x = input_29_cast_fp16)[name = string("input_tensor_67_cast_fp16")];
            tensor<int32, [3]> var_453 = const()[name = string("op_453"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_21_pad_type_0 = const()[name = string("first_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_21_strides_0 = const()[name = string("first_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_21_pad_0 = const()[name = string("first_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_21_dilations_0 = const()[name = string("first_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_21_groups_0 = const()[name = string("first_21_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_2_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_2_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8604352)))];
            tensor<fp16, [2048]> decoder_convnext_2_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_2_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10701568)))];
            tensor<fp16, [1, 512, 96]> input_31_cast_fp16 = transpose(perm = var_453, x = input_tensor_67_cast_fp16)[name = string("transpose_15")];
            tensor<fp16, [1, 2048, 96]> first_21_cast_fp16 = conv(bias = decoder_convnext_2_pwconv1_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = decoder_convnext_2_pwconv1_Conv_weight_to_fp16, x = input_31_cast_fp16)[name = string("first_21_cast_fp16")];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 96]> input_33_cast_fp16 = gelu(mode = input_33_mode_0, x = first_21_cast_fp16)[name = string("input_33_cast_fp16")];
            string second_39_pad_type_0 = const()[name = string("second_39_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_39_strides_0 = const()[name = string("second_39_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_39_pad_0 = const()[name = string("second_39_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_39_dilations_0 = const()[name = string("second_39_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_39_groups_0 = const()[name = string("second_39_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_41_weight_0_to_fp16 = const()[name = string("second_41_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10705728)))];
            tensor<fp16, [512]> second_41_bias_0_to_fp16 = const()[name = string("second_41_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12802944)))];
            tensor<fp16, [1, 512, 96]> second_41_cast_fp16 = conv(bias = second_41_bias_0_to_fp16, dilations = second_39_dilations_0, groups = second_39_groups_0, pad = second_39_pad_0, pad_type = second_39_pad_type_0, strides = second_39_strides_0, weight = second_41_weight_0_to_fp16, x = input_33_cast_fp16)[name = string("second_41_cast_fp16")];
            tensor<fp16, [1, 512, 96]> input_35_cast_fp16 = add(x = input_25_cast_fp16, y = second_41_cast_fp16)[name = string("input_35_cast_fp16")];
            tensor<int32, [6]> input_37_pad_0 = const()[name = string("input_37_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_37_mode_0 = const()[name = string("input_37_mode_0"), val = string("replicate")];
            fp16 const_11_to_fp16 = const()[name = string("const_11_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 102]> input_37_cast_fp16 = pad(constant_val = const_11_to_fp16, mode = input_37_mode_0, pad = input_37_pad_0, x = input_35_cast_fp16)[name = string("input_37_cast_fp16")];
            string input_tensor_79_pad_type_0 = const()[name = string("input_tensor_79_pad_type_0"), val = string("valid")];
            int32 input_tensor_79_groups_0 = const()[name = string("input_tensor_79_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_79_strides_0 = const()[name = string("input_tensor_79_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_79_pad_0 = const()[name = string("input_tensor_79_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_79_dilations_0 = const()[name = string("input_tensor_79_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_3_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_3_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12804032)))];
            tensor<fp16, [512]> decoder_convnext_3_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_3_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12811264)))];
            tensor<fp16, [1, 512, 96]> input_tensor_79_cast_fp16 = conv(bias = decoder_convnext_3_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_79_dilations_0, groups = input_tensor_79_groups_0, pad = input_tensor_79_pad_0, pad_type = input_tensor_79_pad_type_0, strides = input_tensor_79_strides_0, weight = decoder_convnext_3_dwconv_net_Conv_weight_to_fp16, x = input_37_cast_fp16)[name = string("input_tensor_79_cast_fp16")];
            tensor<int32, [3]> var_507 = const()[name = string("op_507"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_81_axes_0 = const()[name = string("input_tensor_81_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12812352)))];
            tensor<fp16, [512]> decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12813440)))];
            fp16 var_510_to_fp16 = const()[name = string("op_510_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 96, 512]> input_39_cast_fp16 = transpose(perm = var_507, x = input_tensor_79_cast_fp16)[name = string("transpose_14")];
            tensor<fp16, [1, 96, 512]> input_tensor_81_cast_fp16 = layer_norm(axes = input_tensor_81_axes_0, beta = decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_510_to_fp16, gamma = decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16, x = input_39_cast_fp16)[name = string("input_tensor_81_cast_fp16")];
            tensor<int32, [3]> var_519 = const()[name = string("op_519"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_29_pad_type_0 = const()[name = string("first_29_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_29_strides_0 = const()[name = string("first_29_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_29_pad_0 = const()[name = string("first_29_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_29_dilations_0 = const()[name = string("first_29_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_29_groups_0 = const()[name = string("first_29_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_3_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_3_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12814528)))];
            tensor<fp16, [2048]> decoder_convnext_3_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_3_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14911744)))];
            tensor<fp16, [1, 512, 96]> input_41_cast_fp16 = transpose(perm = var_519, x = input_tensor_81_cast_fp16)[name = string("transpose_13")];
            tensor<fp16, [1, 2048, 96]> first_29_cast_fp16 = conv(bias = decoder_convnext_3_pwconv1_Conv_bias_to_fp16, dilations = first_29_dilations_0, groups = first_29_groups_0, pad = first_29_pad_0, pad_type = first_29_pad_type_0, strides = first_29_strides_0, weight = decoder_convnext_3_pwconv1_Conv_weight_to_fp16, x = input_41_cast_fp16)[name = string("first_29_cast_fp16")];
            string input_43_mode_0 = const()[name = string("input_43_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 96]> input_43_cast_fp16 = gelu(mode = input_43_mode_0, x = first_29_cast_fp16)[name = string("input_43_cast_fp16")];
            string second_51_pad_type_0 = const()[name = string("second_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_51_strides_0 = const()[name = string("second_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_51_pad_0 = const()[name = string("second_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_51_dilations_0 = const()[name = string("second_51_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_51_groups_0 = const()[name = string("second_51_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_53_weight_0_to_fp16 = const()[name = string("second_53_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14915904)))];
            tensor<fp16, [512]> second_53_bias_0_to_fp16 = const()[name = string("second_53_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17013120)))];
            tensor<fp16, [1, 512, 96]> second_53_cast_fp16 = conv(bias = second_53_bias_0_to_fp16, dilations = second_51_dilations_0, groups = second_51_groups_0, pad = second_51_pad_0, pad_type = second_51_pad_type_0, strides = second_51_strides_0, weight = second_53_weight_0_to_fp16, x = input_43_cast_fp16)[name = string("second_53_cast_fp16")];
            tensor<fp16, [1, 512, 96]> input_45_cast_fp16 = add(x = input_35_cast_fp16, y = second_53_cast_fp16)[name = string("input_45_cast_fp16")];
            tensor<int32, [6]> input_47_pad_0 = const()[name = string("input_47_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 12, 0])];
            string input_47_mode_0 = const()[name = string("input_47_mode_0"), val = string("replicate")];
            fp16 const_12_to_fp16 = const()[name = string("const_12_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 108]> input_47_cast_fp16 = pad(constant_val = const_12_to_fp16, mode = input_47_mode_0, pad = input_47_pad_0, x = input_45_cast_fp16)[name = string("input_47_cast_fp16")];
            string input_tensor_93_pad_type_0 = const()[name = string("input_tensor_93_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_93_dilations_0 = const()[name = string("input_tensor_93_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 input_tensor_93_groups_0 = const()[name = string("input_tensor_93_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_93_strides_0 = const()[name = string("input_tensor_93_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_93_pad_0 = const()[name = string("input_tensor_93_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_4_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_4_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17014208)))];
            tensor<fp16, [512]> decoder_convnext_4_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_4_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17021440)))];
            tensor<fp16, [1, 512, 96]> input_tensor_93_cast_fp16 = conv(bias = decoder_convnext_4_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_93_dilations_0, groups = input_tensor_93_groups_0, pad = input_tensor_93_pad_0, pad_type = input_tensor_93_pad_type_0, strides = input_tensor_93_strides_0, weight = decoder_convnext_4_dwconv_net_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("input_tensor_93_cast_fp16")];
            tensor<int32, [3]> var_574 = const()[name = string("op_574"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_95_axes_0 = const()[name = string("input_tensor_95_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17022528)))];
            tensor<fp16, [512]> decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17023616)))];
            fp16 var_577_to_fp16 = const()[name = string("op_577_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 96, 512]> input_49_cast_fp16 = transpose(perm = var_574, x = input_tensor_93_cast_fp16)[name = string("transpose_12")];
            tensor<fp16, [1, 96, 512]> input_tensor_95_cast_fp16 = layer_norm(axes = input_tensor_95_axes_0, beta = decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_577_to_fp16, gamma = decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16, x = input_49_cast_fp16)[name = string("input_tensor_95_cast_fp16")];
            tensor<int32, [3]> var_586 = const()[name = string("op_586"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_37_pad_type_0 = const()[name = string("first_37_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_37_strides_0 = const()[name = string("first_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_37_pad_0 = const()[name = string("first_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_37_dilations_0 = const()[name = string("first_37_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_37_groups_0 = const()[name = string("first_37_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_4_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_4_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17024704)))];
            tensor<fp16, [2048]> decoder_convnext_4_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_4_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19121920)))];
            tensor<fp16, [1, 512, 96]> input_51_cast_fp16 = transpose(perm = var_586, x = input_tensor_95_cast_fp16)[name = string("transpose_11")];
            tensor<fp16, [1, 2048, 96]> first_37_cast_fp16 = conv(bias = decoder_convnext_4_pwconv1_Conv_bias_to_fp16, dilations = first_37_dilations_0, groups = first_37_groups_0, pad = first_37_pad_0, pad_type = first_37_pad_type_0, strides = first_37_strides_0, weight = decoder_convnext_4_pwconv1_Conv_weight_to_fp16, x = input_51_cast_fp16)[name = string("first_37_cast_fp16")];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 96]> input_53_cast_fp16 = gelu(mode = input_53_mode_0, x = first_37_cast_fp16)[name = string("input_53_cast_fp16")];
            string second_63_pad_type_0 = const()[name = string("second_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_63_strides_0 = const()[name = string("second_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_63_pad_0 = const()[name = string("second_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_63_dilations_0 = const()[name = string("second_63_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_63_groups_0 = const()[name = string("second_63_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_65_weight_0_to_fp16 = const()[name = string("second_65_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19126080)))];
            tensor<fp16, [512]> second_65_bias_0_to_fp16 = const()[name = string("second_65_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21223296)))];
            tensor<fp16, [1, 512, 96]> second_65_cast_fp16 = conv(bias = second_65_bias_0_to_fp16, dilations = second_63_dilations_0, groups = second_63_groups_0, pad = second_63_pad_0, pad_type = second_63_pad_type_0, strides = second_63_strides_0, weight = second_65_weight_0_to_fp16, x = input_53_cast_fp16)[name = string("second_65_cast_fp16")];
            tensor<fp16, [1, 512, 96]> input_55_cast_fp16 = add(x = input_45_cast_fp16, y = second_65_cast_fp16)[name = string("input_55_cast_fp16")];
            tensor<int32, [6]> input_57_pad_0 = const()[name = string("input_57_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 24, 0])];
            string input_57_mode_0 = const()[name = string("input_57_mode_0"), val = string("replicate")];
            fp16 const_13_to_fp16 = const()[name = string("const_13_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 120]> input_57_cast_fp16 = pad(constant_val = const_13_to_fp16, mode = input_57_mode_0, pad = input_57_pad_0, x = input_55_cast_fp16)[name = string("input_57_cast_fp16")];
            string input_tensor_107_pad_type_0 = const()[name = string("input_tensor_107_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_107_dilations_0 = const()[name = string("input_tensor_107_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 input_tensor_107_groups_0 = const()[name = string("input_tensor_107_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_107_strides_0 = const()[name = string("input_tensor_107_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_107_pad_0 = const()[name = string("input_tensor_107_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_5_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_5_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21224384)))];
            tensor<fp16, [512]> decoder_convnext_5_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_5_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21231616)))];
            tensor<fp16, [1, 512, 96]> input_tensor_107_cast_fp16 = conv(bias = decoder_convnext_5_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_107_dilations_0, groups = input_tensor_107_groups_0, pad = input_tensor_107_pad_0, pad_type = input_tensor_107_pad_type_0, strides = input_tensor_107_strides_0, weight = decoder_convnext_5_dwconv_net_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = string("input_tensor_107_cast_fp16")];
            tensor<int32, [3]> var_641 = const()[name = string("op_641"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_109_axes_0 = const()[name = string("input_tensor_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21232704)))];
            tensor<fp16, [512]> decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21233792)))];
            fp16 var_644_to_fp16 = const()[name = string("op_644_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 96, 512]> input_59_cast_fp16 = transpose(perm = var_641, x = input_tensor_107_cast_fp16)[name = string("transpose_10")];
            tensor<fp16, [1, 96, 512]> input_tensor_109_cast_fp16 = layer_norm(axes = input_tensor_109_axes_0, beta = decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_644_to_fp16, gamma = decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16, x = input_59_cast_fp16)[name = string("input_tensor_109_cast_fp16")];
            tensor<int32, [3]> var_653 = const()[name = string("op_653"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_45_pad_type_0 = const()[name = string("first_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_45_strides_0 = const()[name = string("first_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_45_pad_0 = const()[name = string("first_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_45_dilations_0 = const()[name = string("first_45_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_45_groups_0 = const()[name = string("first_45_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_5_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_5_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21234880)))];
            tensor<fp16, [2048]> decoder_convnext_5_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_5_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23332096)))];
            tensor<fp16, [1, 512, 96]> input_61_cast_fp16 = transpose(perm = var_653, x = input_tensor_109_cast_fp16)[name = string("transpose_9")];
            tensor<fp16, [1, 2048, 96]> first_45_cast_fp16 = conv(bias = decoder_convnext_5_pwconv1_Conv_bias_to_fp16, dilations = first_45_dilations_0, groups = first_45_groups_0, pad = first_45_pad_0, pad_type = first_45_pad_type_0, strides = first_45_strides_0, weight = decoder_convnext_5_pwconv1_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("first_45_cast_fp16")];
            string input_63_mode_0 = const()[name = string("input_63_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 96]> input_63_cast_fp16 = gelu(mode = input_63_mode_0, x = first_45_cast_fp16)[name = string("input_63_cast_fp16")];
            string second_75_pad_type_0 = const()[name = string("second_75_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_75_strides_0 = const()[name = string("second_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_75_pad_0 = const()[name = string("second_75_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_75_dilations_0 = const()[name = string("second_75_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_75_groups_0 = const()[name = string("second_75_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_77_weight_0_to_fp16 = const()[name = string("second_77_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23336256)))];
            tensor<fp16, [512]> second_77_bias_0_to_fp16 = const()[name = string("second_77_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25433472)))];
            tensor<fp16, [1, 512, 96]> second_77_cast_fp16 = conv(bias = second_77_bias_0_to_fp16, dilations = second_75_dilations_0, groups = second_75_groups_0, pad = second_75_pad_0, pad_type = second_75_pad_type_0, strides = second_75_strides_0, weight = second_77_weight_0_to_fp16, x = input_63_cast_fp16)[name = string("second_77_cast_fp16")];
            tensor<fp16, [1, 512, 96]> input_65_cast_fp16 = add(x = input_55_cast_fp16, y = second_77_cast_fp16)[name = string("input_65_cast_fp16")];
            tensor<int32, [6]> input_67_pad_0 = const()[name = string("input_67_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_67_mode_0 = const()[name = string("input_67_mode_0"), val = string("replicate")];
            fp16 const_14_to_fp16 = const()[name = string("const_14_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 102]> input_67_cast_fp16 = pad(constant_val = const_14_to_fp16, mode = input_67_mode_0, pad = input_67_pad_0, x = input_65_cast_fp16)[name = string("input_67_cast_fp16")];
            string input_tensor_121_pad_type_0 = const()[name = string("input_tensor_121_pad_type_0"), val = string("valid")];
            int32 input_tensor_121_groups_0 = const()[name = string("input_tensor_121_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_121_strides_0 = const()[name = string("input_tensor_121_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_121_pad_0 = const()[name = string("input_tensor_121_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_121_dilations_0 = const()[name = string("input_tensor_121_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_6_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_6_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25434560)))];
            tensor<fp16, [512]> decoder_convnext_6_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_6_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25441792)))];
            tensor<fp16, [1, 512, 96]> input_tensor_121_cast_fp16 = conv(bias = decoder_convnext_6_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_121_dilations_0, groups = input_tensor_121_groups_0, pad = input_tensor_121_pad_0, pad_type = input_tensor_121_pad_type_0, strides = input_tensor_121_strides_0, weight = decoder_convnext_6_dwconv_net_Conv_weight_to_fp16, x = input_67_cast_fp16)[name = string("input_tensor_121_cast_fp16")];
            tensor<int32, [3]> var_707 = const()[name = string("op_707"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_123_axes_0 = const()[name = string("input_tensor_123_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25442880)))];
            tensor<fp16, [512]> decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25443968)))];
            fp16 var_710_to_fp16 = const()[name = string("op_710_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 96, 512]> input_69_cast_fp16 = transpose(perm = var_707, x = input_tensor_121_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 96, 512]> input_tensor_123_cast_fp16 = layer_norm(axes = input_tensor_123_axes_0, beta = decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_710_to_fp16, gamma = decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16, x = input_69_cast_fp16)[name = string("input_tensor_123_cast_fp16")];
            tensor<int32, [3]> var_719 = const()[name = string("op_719"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_53_pad_type_0 = const()[name = string("first_53_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_53_strides_0 = const()[name = string("first_53_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_53_pad_0 = const()[name = string("first_53_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_53_dilations_0 = const()[name = string("first_53_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_53_groups_0 = const()[name = string("first_53_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_6_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_6_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25445056)))];
            tensor<fp16, [2048]> decoder_convnext_6_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_6_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27542272)))];
            tensor<fp16, [1, 512, 96]> input_71_cast_fp16 = transpose(perm = var_719, x = input_tensor_123_cast_fp16)[name = string("transpose_7")];
            tensor<fp16, [1, 2048, 96]> first_53_cast_fp16 = conv(bias = decoder_convnext_6_pwconv1_Conv_bias_to_fp16, dilations = first_53_dilations_0, groups = first_53_groups_0, pad = first_53_pad_0, pad_type = first_53_pad_type_0, strides = first_53_strides_0, weight = decoder_convnext_6_pwconv1_Conv_weight_to_fp16, x = input_71_cast_fp16)[name = string("first_53_cast_fp16")];
            string input_73_mode_0 = const()[name = string("input_73_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 96]> input_73_cast_fp16 = gelu(mode = input_73_mode_0, x = first_53_cast_fp16)[name = string("input_73_cast_fp16")];
            string second_87_pad_type_0 = const()[name = string("second_87_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_87_strides_0 = const()[name = string("second_87_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_87_pad_0 = const()[name = string("second_87_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_87_dilations_0 = const()[name = string("second_87_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_87_groups_0 = const()[name = string("second_87_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_89_weight_0_to_fp16 = const()[name = string("second_89_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27546432)))];
            tensor<fp16, [512]> second_89_bias_0_to_fp16 = const()[name = string("second_89_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29643648)))];
            tensor<fp16, [1, 512, 96]> second_89_cast_fp16 = conv(bias = second_89_bias_0_to_fp16, dilations = second_87_dilations_0, groups = second_87_groups_0, pad = second_87_pad_0, pad_type = second_87_pad_type_0, strides = second_87_strides_0, weight = second_89_weight_0_to_fp16, x = input_73_cast_fp16)[name = string("second_89_cast_fp16")];
            tensor<fp16, [1, 512, 96]> input_75_cast_fp16 = add(x = input_65_cast_fp16, y = second_89_cast_fp16)[name = string("input_75_cast_fp16")];
            tensor<int32, [6]> input_77_pad_0 = const()[name = string("input_77_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_77_mode_0 = const()[name = string("input_77_mode_0"), val = string("replicate")];
            fp16 const_15_to_fp16 = const()[name = string("const_15_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 102]> input_77_cast_fp16 = pad(constant_val = const_15_to_fp16, mode = input_77_mode_0, pad = input_77_pad_0, x = input_75_cast_fp16)[name = string("input_77_cast_fp16")];
            string input_tensor_135_pad_type_0 = const()[name = string("input_tensor_135_pad_type_0"), val = string("valid")];
            int32 input_tensor_135_groups_0 = const()[name = string("input_tensor_135_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_135_strides_0 = const()[name = string("input_tensor_135_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_135_pad_0 = const()[name = string("input_tensor_135_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_135_dilations_0 = const()[name = string("input_tensor_135_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_7_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_7_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29644736)))];
            tensor<fp16, [512]> decoder_convnext_7_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_7_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29651968)))];
            tensor<fp16, [1, 512, 96]> input_tensor_135_cast_fp16 = conv(bias = decoder_convnext_7_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_135_dilations_0, groups = input_tensor_135_groups_0, pad = input_tensor_135_pad_0, pad_type = input_tensor_135_pad_type_0, strides = input_tensor_135_strides_0, weight = decoder_convnext_7_dwconv_net_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = string("input_tensor_135_cast_fp16")];
            tensor<int32, [3]> var_773 = const()[name = string("op_773"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_137_axes_0 = const()[name = string("input_tensor_137_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29653056)))];
            tensor<fp16, [512]> decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29654144)))];
            fp16 var_776_to_fp16 = const()[name = string("op_776_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 96, 512]> input_79_cast_fp16 = transpose(perm = var_773, x = input_tensor_135_cast_fp16)[name = string("transpose_6")];
            tensor<fp16, [1, 96, 512]> input_tensor_137_cast_fp16 = layer_norm(axes = input_tensor_137_axes_0, beta = decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_776_to_fp16, gamma = decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_tensor_137_cast_fp16")];
            tensor<int32, [3]> var_785 = const()[name = string("op_785"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_61_pad_type_0 = const()[name = string("first_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_61_strides_0 = const()[name = string("first_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_61_pad_0 = const()[name = string("first_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_61_dilations_0 = const()[name = string("first_61_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_61_groups_0 = const()[name = string("first_61_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_7_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_7_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29655232)))];
            tensor<fp16, [2048]> decoder_convnext_7_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_7_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31752448)))];
            tensor<fp16, [1, 512, 96]> input_81_cast_fp16 = transpose(perm = var_785, x = input_tensor_137_cast_fp16)[name = string("transpose_5")];
            tensor<fp16, [1, 2048, 96]> first_61_cast_fp16 = conv(bias = decoder_convnext_7_pwconv1_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = decoder_convnext_7_pwconv1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = string("first_61_cast_fp16")];
            string input_83_mode_0 = const()[name = string("input_83_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 96]> input_83_cast_fp16 = gelu(mode = input_83_mode_0, x = first_61_cast_fp16)[name = string("input_83_cast_fp16")];
            string second_99_pad_type_0 = const()[name = string("second_99_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_99_strides_0 = const()[name = string("second_99_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_99_pad_0 = const()[name = string("second_99_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_99_dilations_0 = const()[name = string("second_99_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_99_groups_0 = const()[name = string("second_99_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_101_weight_0_to_fp16 = const()[name = string("second_101_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31756608)))];
            tensor<fp16, [512]> second_101_bias_0_to_fp16 = const()[name = string("second_101_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33853824)))];
            tensor<fp16, [1, 512, 96]> second_101_cast_fp16 = conv(bias = second_101_bias_0_to_fp16, dilations = second_99_dilations_0, groups = second_99_groups_0, pad = second_99_pad_0, pad_type = second_99_pad_type_0, strides = second_99_strides_0, weight = second_101_weight_0_to_fp16, x = input_83_cast_fp16)[name = string("second_101_cast_fp16")];
            tensor<fp16, [1, 512, 96]> input_85_cast_fp16 = add(x = input_75_cast_fp16, y = second_101_cast_fp16)[name = string("input_85_cast_fp16")];
            tensor<int32, [6]> input_87_pad_0 = const()[name = string("input_87_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_87_mode_0 = const()[name = string("input_87_mode_0"), val = string("replicate")];
            fp16 const_16_to_fp16 = const()[name = string("const_16_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 102]> input_87_cast_fp16 = pad(constant_val = const_16_to_fp16, mode = input_87_mode_0, pad = input_87_pad_0, x = input_85_cast_fp16)[name = string("input_87_cast_fp16")];
            string input_tensor_149_pad_type_0 = const()[name = string("input_tensor_149_pad_type_0"), val = string("valid")];
            int32 input_tensor_149_groups_0 = const()[name = string("input_tensor_149_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_149_strides_0 = const()[name = string("input_tensor_149_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_149_pad_0 = const()[name = string("input_tensor_149_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_149_dilations_0 = const()[name = string("input_tensor_149_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_8_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_8_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33854912)))];
            tensor<fp16, [512]> decoder_convnext_8_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_8_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33862144)))];
            tensor<fp16, [1, 512, 96]> input_tensor_149_cast_fp16 = conv(bias = decoder_convnext_8_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_149_dilations_0, groups = input_tensor_149_groups_0, pad = input_tensor_149_pad_0, pad_type = input_tensor_149_pad_type_0, strides = input_tensor_149_strides_0, weight = decoder_convnext_8_dwconv_net_Conv_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_tensor_149_cast_fp16")];
            tensor<int32, [3]> var_839 = const()[name = string("op_839"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_151_axes_0 = const()[name = string("input_tensor_151_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33863232)))];
            tensor<fp16, [512]> decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33864320)))];
            fp16 var_842_to_fp16 = const()[name = string("op_842_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 96, 512]> input_89_cast_fp16 = transpose(perm = var_839, x = input_tensor_149_cast_fp16)[name = string("transpose_4")];
            tensor<fp16, [1, 96, 512]> input_tensor_151_cast_fp16 = layer_norm(axes = input_tensor_151_axes_0, beta = decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_842_to_fp16, gamma = decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_151_cast_fp16")];
            tensor<int32, [3]> var_851 = const()[name = string("op_851"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_69_pad_type_0 = const()[name = string("first_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_69_strides_0 = const()[name = string("first_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_69_pad_0 = const()[name = string("first_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_69_dilations_0 = const()[name = string("first_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_69_groups_0 = const()[name = string("first_69_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_8_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_8_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33865408)))];
            tensor<fp16, [2048]> decoder_convnext_8_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_8_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35962624)))];
            tensor<fp16, [1, 512, 96]> input_91_cast_fp16 = transpose(perm = var_851, x = input_tensor_151_cast_fp16)[name = string("transpose_3")];
            tensor<fp16, [1, 2048, 96]> first_69_cast_fp16 = conv(bias = decoder_convnext_8_pwconv1_Conv_bias_to_fp16, dilations = first_69_dilations_0, groups = first_69_groups_0, pad = first_69_pad_0, pad_type = first_69_pad_type_0, strides = first_69_strides_0, weight = decoder_convnext_8_pwconv1_Conv_weight_to_fp16, x = input_91_cast_fp16)[name = string("first_69_cast_fp16")];
            string input_93_mode_0 = const()[name = string("input_93_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 96]> input_93_cast_fp16 = gelu(mode = input_93_mode_0, x = first_69_cast_fp16)[name = string("input_93_cast_fp16")];
            string second_111_pad_type_0 = const()[name = string("second_111_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_111_strides_0 = const()[name = string("second_111_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_111_pad_0 = const()[name = string("second_111_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_111_dilations_0 = const()[name = string("second_111_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_111_groups_0 = const()[name = string("second_111_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_113_weight_0_to_fp16 = const()[name = string("second_113_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35966784)))];
            tensor<fp16, [512]> second_113_bias_0_to_fp16 = const()[name = string("second_113_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38064000)))];
            tensor<fp16, [1, 512, 96]> second_113_cast_fp16 = conv(bias = second_113_bias_0_to_fp16, dilations = second_111_dilations_0, groups = second_111_groups_0, pad = second_111_pad_0, pad_type = second_111_pad_type_0, strides = second_111_strides_0, weight = second_113_weight_0_to_fp16, x = input_93_cast_fp16)[name = string("second_113_cast_fp16")];
            tensor<fp16, [1, 512, 96]> input_95_cast_fp16 = add(x = input_85_cast_fp16, y = second_113_cast_fp16)[name = string("input_95_cast_fp16")];
            tensor<int32, [6]> input_97_pad_0 = const()[name = string("input_97_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_97_mode_0 = const()[name = string("input_97_mode_0"), val = string("replicate")];
            fp16 const_17_to_fp16 = const()[name = string("const_17_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 102]> input_97_cast_fp16 = pad(constant_val = const_17_to_fp16, mode = input_97_mode_0, pad = input_97_pad_0, x = input_95_cast_fp16)[name = string("input_97_cast_fp16")];
            string input_tensor_163_pad_type_0 = const()[name = string("input_tensor_163_pad_type_0"), val = string("valid")];
            int32 input_tensor_163_groups_0 = const()[name = string("input_tensor_163_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_163_strides_0 = const()[name = string("input_tensor_163_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_163_pad_0 = const()[name = string("input_tensor_163_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_163_dilations_0 = const()[name = string("input_tensor_163_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_9_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_9_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38065088)))];
            tensor<fp16, [512]> decoder_convnext_9_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_9_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38072320)))];
            tensor<fp16, [1, 512, 96]> input_tensor_163_cast_fp16 = conv(bias = decoder_convnext_9_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_163_dilations_0, groups = input_tensor_163_groups_0, pad = input_tensor_163_pad_0, pad_type = input_tensor_163_pad_type_0, strides = input_tensor_163_strides_0, weight = decoder_convnext_9_dwconv_net_Conv_weight_to_fp16, x = input_97_cast_fp16)[name = string("input_tensor_163_cast_fp16")];
            tensor<int32, [3]> var_905 = const()[name = string("op_905"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_165_axes_0 = const()[name = string("input_tensor_165_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38073408)))];
            tensor<fp16, [512]> decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38074496)))];
            fp16 var_908_to_fp16 = const()[name = string("op_908_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 96, 512]> input_99_cast_fp16 = transpose(perm = var_905, x = input_tensor_163_cast_fp16)[name = string("transpose_2")];
            tensor<fp16, [1, 96, 512]> input_tensor_165_cast_fp16 = layer_norm(axes = input_tensor_165_axes_0, beta = decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_908_to_fp16, gamma = decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16, x = input_99_cast_fp16)[name = string("input_tensor_165_cast_fp16")];
            tensor<int32, [3]> var_917 = const()[name = string("op_917"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_77_pad_type_0 = const()[name = string("first_77_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_77_strides_0 = const()[name = string("first_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_77_pad_0 = const()[name = string("first_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_77_dilations_0 = const()[name = string("first_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_77_groups_0 = const()[name = string("first_77_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_9_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_9_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38075584)))];
            tensor<fp16, [2048]> decoder_convnext_9_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_9_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40172800)))];
            tensor<fp16, [1, 512, 96]> input_101_cast_fp16 = transpose(perm = var_917, x = input_tensor_165_cast_fp16)[name = string("transpose_1")];
            tensor<fp16, [1, 2048, 96]> first_77_cast_fp16 = conv(bias = decoder_convnext_9_pwconv1_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = decoder_convnext_9_pwconv1_Conv_weight_to_fp16, x = input_101_cast_fp16)[name = string("first_77_cast_fp16")];
            string input_103_mode_0 = const()[name = string("input_103_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 96]> input_103_cast_fp16 = gelu(mode = input_103_mode_0, x = first_77_cast_fp16)[name = string("input_103_cast_fp16")];
            string second_123_pad_type_0 = const()[name = string("second_123_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_123_strides_0 = const()[name = string("second_123_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_123_pad_0 = const()[name = string("second_123_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_123_dilations_0 = const()[name = string("second_123_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_123_groups_0 = const()[name = string("second_123_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_weight_0_to_fp16 = const()[name = string("second_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40176960)))];
            tensor<fp16, [512]> second_bias_0_to_fp16 = const()[name = string("second_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42274176)))];
            tensor<fp16, [1, 512, 96]> second_cast_fp16 = conv(bias = second_bias_0_to_fp16, dilations = second_123_dilations_0, groups = second_123_groups_0, pad = second_123_pad_0, pad_type = second_123_pad_type_0, strides = second_123_strides_0, weight = second_weight_0_to_fp16, x = input_103_cast_fp16)[name = string("second_cast_fp16")];
            tensor<fp16, [1, 512, 96]> input_105_cast_fp16 = add(x = input_95_cast_fp16, y = second_cast_fp16)[name = string("input_105_cast_fp16")];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_running_mean_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42275264)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_running_var_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42276352)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_weight_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42277440)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_bias_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42278528)))];
            fp16 var_951_to_fp16 = const()[name = string("op_951_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 512, 96]> input_107_cast_fp16 = batch_norm(beta = decoder_final_norm_BatchNormalization_bias_to_fp16, epsilon = var_951_to_fp16, gamma = decoder_final_norm_BatchNormalization_weight_to_fp16, mean = decoder_final_norm_BatchNormalization_running_mean_to_fp16, variance = decoder_final_norm_BatchNormalization_running_var_to_fp16, x = input_105_cast_fp16)[name = string("input_107_cast_fp16")];
            tensor<int32, [6]> input_109_pad_0 = const()[name = string("input_109_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 0])];
            string input_109_mode_0 = const()[name = string("input_109_mode_0"), val = string("replicate")];
            fp16 const_18_to_fp16 = const()[name = string("const_18_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 98]> input_109_cast_fp16 = pad(constant_val = const_18_to_fp16, mode = input_109_mode_0, pad = input_109_pad_0, x = input_107_cast_fp16)[name = string("input_109_cast_fp16")];
            string input_tensor_177_pad_type_0 = const()[name = string("input_tensor_177_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_177_strides_0 = const()[name = string("input_tensor_177_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_177_pad_0 = const()[name = string("input_tensor_177_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_177_dilations_0 = const()[name = string("input_tensor_177_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_177_groups_0 = const()[name = string("input_tensor_177_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 3]> decoder_head_layer1_net_Conv_weight_to_fp16 = const()[name = string("decoder_head_layer1_net_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42279616)))];
            tensor<fp16, [2048]> decoder_head_layer1_net_Conv_bias_to_fp16 = const()[name = string("decoder_head_layer1_net_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48571136)))];
            tensor<fp16, [1, 2048, 96]> input_tensor_177_cast_fp16 = conv(bias = decoder_head_layer1_net_Conv_bias_to_fp16, dilations = input_tensor_177_dilations_0, groups = input_tensor_177_groups_0, pad = input_tensor_177_pad_0, pad_type = input_tensor_177_pad_type_0, strides = input_tensor_177_strides_0, weight = decoder_head_layer1_net_Conv_weight_to_fp16, x = input_109_cast_fp16)[name = string("input_tensor_177_cast_fp16")];
            fp32 input_alpha_1 = const()[name = string("input_alpha_1"), val = fp32(0x1.9814fap-13)];
            tensor<fp16, [1, 2048, 96]> input_cast_fp16 = leaky_relu(alpha = input_alpha_1, x = input_tensor_177_cast_fp16)[name = string("input_cast_fp16")];
            string input_tensor_179_pad_type_0 = const()[name = string("input_tensor_179_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_179_strides_0 = const()[name = string("input_tensor_179_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_179_pad_0 = const()[name = string("input_tensor_179_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_179_dilations_0 = const()[name = string("input_tensor_179_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_179_groups_0 = const()[name = string("input_tensor_179_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> decoder_head_layer2_Conv_weight_to_fp16 = const()[name = string("decoder_head_layer2_Conv_weight_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48575296)))];
            tensor<fp16, [1, 512, 96]> input_tensor_179_cast_fp16 = conv(dilations = input_tensor_179_dilations_0, groups = input_tensor_179_groups_0, pad = input_tensor_179_pad_0, pad_type = input_tensor_179_pad_type_0, strides = input_tensor_179_strides_0, weight = decoder_head_layer2_Conv_weight_to_fp16, x = input_cast_fp16)[name = string("input_tensor_179_cast_fp16")];
            tensor<int32, [3]> var_994 = const()[name = string("op_994"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [2]> var_1021 = const()[name = string("op_1021"), val = tensor<int32, [2]>([1, -1])];
            tensor<fp16, [1, 96, 512]> input_tensor_181_cast_fp16 = transpose(perm = var_994, x = input_tensor_179_cast_fp16)[name = string("transpose_0")];
            tensor<fp16, [1, 49152]> wav_tts = reshape(shape = var_1021, x = input_tensor_181_cast_fp16)[name = string("op_1022_cast_fp16")];
        } -> (wav_tts);
    func vocoder_l256<ios18>(tensor<fp16, [1, 144, 256]> latent) {
            fp16 _inversed_input_tensor_1_y_0_to_fp16 = const()[name = string("_inversed_input_tensor_1_y_0_to_fp16"), val = fp16(0x1p+2)];
            tensor<fp16, [1, 144, 256]> _inversed_input_tensor_1_cast_fp16 = mul(x = latent, y = _inversed_input_tensor_1_y_0_to_fp16)[name = string("_inversed_input_tensor_1_cast_fp16")];
            tensor<int32, [4]> var_213 = const()[name = string("op_213"), val = tensor<int32, [4]>([1, -1, 6, 256])];
            tensor<fp16, [1, 24, 6, 256]> input_tensor_9_cast_fp16 = reshape(shape = var_213, x = _inversed_input_tensor_1_cast_fp16)[name = string("input_tensor_9_cast_fp16")];
            tensor<int32, [4]> var_219 = const()[name = string("op_219"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_264 = const()[name = string("op_264"), val = tensor<int32, [3]>([1, 24, -1])];
            tensor<fp16, [1, 24, 256, 6]> input_tensor_11_cast_fp16 = transpose(perm = var_219, x = input_tensor_9_cast_fp16)[name = string("transpose_21")];
            tensor<fp16, [1, 24, 1536]> first_1_cast_fp16 = reshape(shape = var_264, x = input_tensor_11_cast_fp16)[name = string("first_1_cast_fp16")];
            tensor<fp16, [1, 24, 1]> initializers_onnx_initializer_1_to_fp16 = const()[name = string("initializers_onnx_initializer_1_to_fp16"), val = tensor<fp16, [1, 24, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [1, 24, 1536]> first_3_cast_fp16 = mul(x = first_1_cast_fp16, y = initializers_onnx_initializer_1_to_fp16)[name = string("first_3_cast_fp16")];
            tensor<fp16, [1, 24, 1]> initializers_onnx_initializer_2_to_fp16 = const()[name = string("initializers_onnx_initializer_2_to_fp16"), val = tensor<fp16, [1, 24, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192)))];
            tensor<fp16, [1, 24, 1536]> input_1_cast_fp16 = add(x = first_3_cast_fp16, y = initializers_onnx_initializer_2_to_fp16)[name = string("input_1_cast_fp16")];
            tensor<int32, [6]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("replicate")];
            fp16 const_7_to_fp16 = const()[name = string("const_7_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 24, 1542]> input_3_cast_fp16 = pad(constant_val = const_7_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string input_5_pad_type_0 = const()[name = string("input_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_5_strides_0 = const()[name = string("input_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_5_pad_0 = const()[name = string("input_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_5_dilations_0 = const()[name = string("input_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_5_groups_0 = const()[name = string("input_5_groups_0"), val = int32(1)];
            tensor<fp16, [512, 24, 7]> decoder_embed_net_Conv_weight_to_fp16 = const()[name = string("decoder_embed_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 24, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(320)))];
            tensor<fp16, [512]> decoder_embed_net_Conv_bias_to_fp16 = const()[name = string("decoder_embed_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(172416)))];
            tensor<fp16, [1, 512, 1536]> input_5_cast_fp16 = conv(bias = decoder_embed_net_Conv_bias_to_fp16, dilations = input_5_dilations_0, groups = input_5_groups_0, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = input_5_strides_0, weight = decoder_embed_net_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = string("input_5_cast_fp16")];
            tensor<int32, [6]> input_7_pad_0 = const()[name = string("input_7_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_7_mode_0 = const()[name = string("input_7_mode_0"), val = string("replicate")];
            fp16 const_8_to_fp16 = const()[name = string("const_8_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 1542]> input_7_cast_fp16 = pad(constant_val = const_8_to_fp16, mode = input_7_mode_0, pad = input_7_pad_0, x = input_5_cast_fp16)[name = string("input_7_cast_fp16")];
            string input_tensor_37_pad_type_0 = const()[name = string("input_tensor_37_pad_type_0"), val = string("valid")];
            int32 input_tensor_37_groups_0 = const()[name = string("input_tensor_37_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_37_strides_0 = const()[name = string("input_tensor_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_37_pad_0 = const()[name = string("input_tensor_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_37_dilations_0 = const()[name = string("input_tensor_37_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_0_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_0_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(173504)))];
            tensor<fp16, [512]> decoder_convnext_0_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_0_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(180736)))];
            tensor<fp16, [1, 512, 1536]> input_tensor_37_cast_fp16 = conv(bias = decoder_convnext_0_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_37_dilations_0, groups = input_tensor_37_groups_0, pad = input_tensor_37_pad_0, pad_type = input_tensor_37_pad_type_0, strides = input_tensor_37_strides_0, weight = decoder_convnext_0_dwconv_net_Conv_weight_to_fp16, x = input_7_cast_fp16)[name = string("input_tensor_37_cast_fp16")];
            tensor<int32, [3]> var_307 = const()[name = string("op_307"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_39_axes_0 = const()[name = string("input_tensor_39_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(181824)))];
            tensor<fp16, [512]> decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(182912)))];
            fp16 var_310_to_fp16 = const()[name = string("op_310_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 1536, 512]> input_9_cast_fp16 = transpose(perm = var_307, x = input_tensor_37_cast_fp16)[name = string("transpose_20")];
            tensor<fp16, [1, 1536, 512]> input_tensor_39_cast_fp16 = layer_norm(axes = input_tensor_39_axes_0, beta = decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_310_to_fp16, gamma = decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16, x = input_9_cast_fp16)[name = string("input_tensor_39_cast_fp16")];
            tensor<int32, [3]> var_319 = const()[name = string("op_319"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_5_pad_type_0 = const()[name = string("first_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_5_strides_0 = const()[name = string("first_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_5_pad_0 = const()[name = string("first_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_5_dilations_0 = const()[name = string("first_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_5_groups_0 = const()[name = string("first_5_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_0_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_0_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(184000)))];
            tensor<fp16, [2048]> decoder_convnext_0_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_0_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2281216)))];
            tensor<fp16, [1, 512, 1536]> input_11_cast_fp16 = transpose(perm = var_319, x = input_tensor_39_cast_fp16)[name = string("transpose_19")];
            tensor<fp16, [1, 2048, 1536]> first_5_cast_fp16 = conv(bias = decoder_convnext_0_pwconv1_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = decoder_convnext_0_pwconv1_Conv_weight_to_fp16, x = input_11_cast_fp16)[name = string("first_5_cast_fp16")];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 1536]> input_13_cast_fp16 = gelu(mode = input_13_mode_0, x = first_5_cast_fp16)[name = string("input_13_cast_fp16")];
            string second_15_pad_type_0 = const()[name = string("second_15_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_15_strides_0 = const()[name = string("second_15_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_15_pad_0 = const()[name = string("second_15_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_15_dilations_0 = const()[name = string("second_15_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_15_groups_0 = const()[name = string("second_15_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_17_weight_0_to_fp16 = const()[name = string("second_17_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2285376)))];
            tensor<fp16, [512]> second_17_bias_0_to_fp16 = const()[name = string("second_17_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4382592)))];
            tensor<fp16, [1, 512, 1536]> second_17_cast_fp16 = conv(bias = second_17_bias_0_to_fp16, dilations = second_15_dilations_0, groups = second_15_groups_0, pad = second_15_pad_0, pad_type = second_15_pad_type_0, strides = second_15_strides_0, weight = second_17_weight_0_to_fp16, x = input_13_cast_fp16)[name = string("second_17_cast_fp16")];
            tensor<fp16, [1, 512, 1536]> input_15_cast_fp16 = add(x = input_5_cast_fp16, y = second_17_cast_fp16)[name = string("input_15_cast_fp16")];
            tensor<int32, [6]> input_17_pad_0 = const()[name = string("input_17_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 12, 0])];
            string input_17_mode_0 = const()[name = string("input_17_mode_0"), val = string("replicate")];
            fp16 const_9_to_fp16 = const()[name = string("const_9_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 1548]> input_17_cast_fp16 = pad(constant_val = const_9_to_fp16, mode = input_17_mode_0, pad = input_17_pad_0, x = input_15_cast_fp16)[name = string("input_17_cast_fp16")];
            string input_tensor_51_pad_type_0 = const()[name = string("input_tensor_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_51_dilations_0 = const()[name = string("input_tensor_51_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 input_tensor_51_groups_0 = const()[name = string("input_tensor_51_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_51_strides_0 = const()[name = string("input_tensor_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_51_pad_0 = const()[name = string("input_tensor_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_1_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_1_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4383680)))];
            tensor<fp16, [512]> decoder_convnext_1_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_1_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4390912)))];
            tensor<fp16, [1, 512, 1536]> input_tensor_51_cast_fp16 = conv(bias = decoder_convnext_1_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_51_dilations_0, groups = input_tensor_51_groups_0, pad = input_tensor_51_pad_0, pad_type = input_tensor_51_pad_type_0, strides = input_tensor_51_strides_0, weight = decoder_convnext_1_dwconv_net_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = string("input_tensor_51_cast_fp16")];
            tensor<int32, [3]> var_374 = const()[name = string("op_374"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_53_axes_0 = const()[name = string("input_tensor_53_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4392000)))];
            tensor<fp16, [512]> decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4393088)))];
            fp16 var_377_to_fp16 = const()[name = string("op_377_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 1536, 512]> input_19_cast_fp16 = transpose(perm = var_374, x = input_tensor_51_cast_fp16)[name = string("transpose_18")];
            tensor<fp16, [1, 1536, 512]> input_tensor_53_cast_fp16 = layer_norm(axes = input_tensor_53_axes_0, beta = decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_377_to_fp16, gamma = decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16, x = input_19_cast_fp16)[name = string("input_tensor_53_cast_fp16")];
            tensor<int32, [3]> var_386 = const()[name = string("op_386"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_13_pad_type_0 = const()[name = string("first_13_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_13_strides_0 = const()[name = string("first_13_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_13_pad_0 = const()[name = string("first_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_13_dilations_0 = const()[name = string("first_13_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_13_groups_0 = const()[name = string("first_13_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_1_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_1_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4394176)))];
            tensor<fp16, [2048]> decoder_convnext_1_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_1_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6491392)))];
            tensor<fp16, [1, 512, 1536]> input_21_cast_fp16 = transpose(perm = var_386, x = input_tensor_53_cast_fp16)[name = string("transpose_17")];
            tensor<fp16, [1, 2048, 1536]> first_13_cast_fp16 = conv(bias = decoder_convnext_1_pwconv1_Conv_bias_to_fp16, dilations = first_13_dilations_0, groups = first_13_groups_0, pad = first_13_pad_0, pad_type = first_13_pad_type_0, strides = first_13_strides_0, weight = decoder_convnext_1_pwconv1_Conv_weight_to_fp16, x = input_21_cast_fp16)[name = string("first_13_cast_fp16")];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 1536]> input_23_cast_fp16 = gelu(mode = input_23_mode_0, x = first_13_cast_fp16)[name = string("input_23_cast_fp16")];
            string second_27_pad_type_0 = const()[name = string("second_27_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_27_strides_0 = const()[name = string("second_27_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_27_pad_0 = const()[name = string("second_27_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_27_dilations_0 = const()[name = string("second_27_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_27_groups_0 = const()[name = string("second_27_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_29_weight_0_to_fp16 = const()[name = string("second_29_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6495552)))];
            tensor<fp16, [512]> second_29_bias_0_to_fp16 = const()[name = string("second_29_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8592768)))];
            tensor<fp16, [1, 512, 1536]> second_29_cast_fp16 = conv(bias = second_29_bias_0_to_fp16, dilations = second_27_dilations_0, groups = second_27_groups_0, pad = second_27_pad_0, pad_type = second_27_pad_type_0, strides = second_27_strides_0, weight = second_29_weight_0_to_fp16, x = input_23_cast_fp16)[name = string("second_29_cast_fp16")];
            tensor<fp16, [1, 512, 1536]> input_25_cast_fp16 = add(x = input_15_cast_fp16, y = second_29_cast_fp16)[name = string("input_25_cast_fp16")];
            tensor<int32, [6]> input_27_pad_0 = const()[name = string("input_27_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 24, 0])];
            string input_27_mode_0 = const()[name = string("input_27_mode_0"), val = string("replicate")];
            fp16 const_10_to_fp16 = const()[name = string("const_10_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 1560]> input_27_cast_fp16 = pad(constant_val = const_10_to_fp16, mode = input_27_mode_0, pad = input_27_pad_0, x = input_25_cast_fp16)[name = string("input_27_cast_fp16")];
            string input_tensor_65_pad_type_0 = const()[name = string("input_tensor_65_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_65_dilations_0 = const()[name = string("input_tensor_65_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 input_tensor_65_groups_0 = const()[name = string("input_tensor_65_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_65_strides_0 = const()[name = string("input_tensor_65_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_65_pad_0 = const()[name = string("input_tensor_65_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_2_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_2_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8593856)))];
            tensor<fp16, [512]> decoder_convnext_2_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_2_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8601088)))];
            tensor<fp16, [1, 512, 1536]> input_tensor_65_cast_fp16 = conv(bias = decoder_convnext_2_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_65_dilations_0, groups = input_tensor_65_groups_0, pad = input_tensor_65_pad_0, pad_type = input_tensor_65_pad_type_0, strides = input_tensor_65_strides_0, weight = decoder_convnext_2_dwconv_net_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = string("input_tensor_65_cast_fp16")];
            tensor<int32, [3]> var_441 = const()[name = string("op_441"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_67_axes_0 = const()[name = string("input_tensor_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8602176)))];
            tensor<fp16, [512]> decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8603264)))];
            fp16 var_444_to_fp16 = const()[name = string("op_444_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 1536, 512]> input_29_cast_fp16 = transpose(perm = var_441, x = input_tensor_65_cast_fp16)[name = string("transpose_16")];
            tensor<fp16, [1, 1536, 512]> input_tensor_67_cast_fp16 = layer_norm(axes = input_tensor_67_axes_0, beta = decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_444_to_fp16, gamma = decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16, x = input_29_cast_fp16)[name = string("input_tensor_67_cast_fp16")];
            tensor<int32, [3]> var_453 = const()[name = string("op_453"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_21_pad_type_0 = const()[name = string("first_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_21_strides_0 = const()[name = string("first_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_21_pad_0 = const()[name = string("first_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_21_dilations_0 = const()[name = string("first_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_21_groups_0 = const()[name = string("first_21_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_2_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_2_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8604352)))];
            tensor<fp16, [2048]> decoder_convnext_2_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_2_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10701568)))];
            tensor<fp16, [1, 512, 1536]> input_31_cast_fp16 = transpose(perm = var_453, x = input_tensor_67_cast_fp16)[name = string("transpose_15")];
            tensor<fp16, [1, 2048, 1536]> first_21_cast_fp16 = conv(bias = decoder_convnext_2_pwconv1_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = decoder_convnext_2_pwconv1_Conv_weight_to_fp16, x = input_31_cast_fp16)[name = string("first_21_cast_fp16")];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 1536]> input_33_cast_fp16 = gelu(mode = input_33_mode_0, x = first_21_cast_fp16)[name = string("input_33_cast_fp16")];
            string second_39_pad_type_0 = const()[name = string("second_39_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_39_strides_0 = const()[name = string("second_39_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_39_pad_0 = const()[name = string("second_39_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_39_dilations_0 = const()[name = string("second_39_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_39_groups_0 = const()[name = string("second_39_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_41_weight_0_to_fp16 = const()[name = string("second_41_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10705728)))];
            tensor<fp16, [512]> second_41_bias_0_to_fp16 = const()[name = string("second_41_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12802944)))];
            tensor<fp16, [1, 512, 1536]> second_41_cast_fp16 = conv(bias = second_41_bias_0_to_fp16, dilations = second_39_dilations_0, groups = second_39_groups_0, pad = second_39_pad_0, pad_type = second_39_pad_type_0, strides = second_39_strides_0, weight = second_41_weight_0_to_fp16, x = input_33_cast_fp16)[name = string("second_41_cast_fp16")];
            tensor<fp16, [1, 512, 1536]> input_35_cast_fp16 = add(x = input_25_cast_fp16, y = second_41_cast_fp16)[name = string("input_35_cast_fp16")];
            tensor<int32, [6]> input_37_pad_0 = const()[name = string("input_37_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_37_mode_0 = const()[name = string("input_37_mode_0"), val = string("replicate")];
            fp16 const_11_to_fp16 = const()[name = string("const_11_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 1542]> input_37_cast_fp16 = pad(constant_val = const_11_to_fp16, mode = input_37_mode_0, pad = input_37_pad_0, x = input_35_cast_fp16)[name = string("input_37_cast_fp16")];
            string input_tensor_79_pad_type_0 = const()[name = string("input_tensor_79_pad_type_0"), val = string("valid")];
            int32 input_tensor_79_groups_0 = const()[name = string("input_tensor_79_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_79_strides_0 = const()[name = string("input_tensor_79_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_79_pad_0 = const()[name = string("input_tensor_79_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_79_dilations_0 = const()[name = string("input_tensor_79_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_3_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_3_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12804032)))];
            tensor<fp16, [512]> decoder_convnext_3_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_3_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12811264)))];
            tensor<fp16, [1, 512, 1536]> input_tensor_79_cast_fp16 = conv(bias = decoder_convnext_3_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_79_dilations_0, groups = input_tensor_79_groups_0, pad = input_tensor_79_pad_0, pad_type = input_tensor_79_pad_type_0, strides = input_tensor_79_strides_0, weight = decoder_convnext_3_dwconv_net_Conv_weight_to_fp16, x = input_37_cast_fp16)[name = string("input_tensor_79_cast_fp16")];
            tensor<int32, [3]> var_507 = const()[name = string("op_507"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_81_axes_0 = const()[name = string("input_tensor_81_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12812352)))];
            tensor<fp16, [512]> decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12813440)))];
            fp16 var_510_to_fp16 = const()[name = string("op_510_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 1536, 512]> input_39_cast_fp16 = transpose(perm = var_507, x = input_tensor_79_cast_fp16)[name = string("transpose_14")];
            tensor<fp16, [1, 1536, 512]> input_tensor_81_cast_fp16 = layer_norm(axes = input_tensor_81_axes_0, beta = decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_510_to_fp16, gamma = decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16, x = input_39_cast_fp16)[name = string("input_tensor_81_cast_fp16")];
            tensor<int32, [3]> var_519 = const()[name = string("op_519"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_29_pad_type_0 = const()[name = string("first_29_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_29_strides_0 = const()[name = string("first_29_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_29_pad_0 = const()[name = string("first_29_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_29_dilations_0 = const()[name = string("first_29_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_29_groups_0 = const()[name = string("first_29_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_3_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_3_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12814528)))];
            tensor<fp16, [2048]> decoder_convnext_3_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_3_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14911744)))];
            tensor<fp16, [1, 512, 1536]> input_41_cast_fp16 = transpose(perm = var_519, x = input_tensor_81_cast_fp16)[name = string("transpose_13")];
            tensor<fp16, [1, 2048, 1536]> first_29_cast_fp16 = conv(bias = decoder_convnext_3_pwconv1_Conv_bias_to_fp16, dilations = first_29_dilations_0, groups = first_29_groups_0, pad = first_29_pad_0, pad_type = first_29_pad_type_0, strides = first_29_strides_0, weight = decoder_convnext_3_pwconv1_Conv_weight_to_fp16, x = input_41_cast_fp16)[name = string("first_29_cast_fp16")];
            string input_43_mode_0 = const()[name = string("input_43_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 1536]> input_43_cast_fp16 = gelu(mode = input_43_mode_0, x = first_29_cast_fp16)[name = string("input_43_cast_fp16")];
            string second_51_pad_type_0 = const()[name = string("second_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_51_strides_0 = const()[name = string("second_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_51_pad_0 = const()[name = string("second_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_51_dilations_0 = const()[name = string("second_51_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_51_groups_0 = const()[name = string("second_51_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_53_weight_0_to_fp16 = const()[name = string("second_53_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14915904)))];
            tensor<fp16, [512]> second_53_bias_0_to_fp16 = const()[name = string("second_53_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17013120)))];
            tensor<fp16, [1, 512, 1536]> second_53_cast_fp16 = conv(bias = second_53_bias_0_to_fp16, dilations = second_51_dilations_0, groups = second_51_groups_0, pad = second_51_pad_0, pad_type = second_51_pad_type_0, strides = second_51_strides_0, weight = second_53_weight_0_to_fp16, x = input_43_cast_fp16)[name = string("second_53_cast_fp16")];
            tensor<fp16, [1, 512, 1536]> input_45_cast_fp16 = add(x = input_35_cast_fp16, y = second_53_cast_fp16)[name = string("input_45_cast_fp16")];
            tensor<int32, [6]> input_47_pad_0 = const()[name = string("input_47_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 12, 0])];
            string input_47_mode_0 = const()[name = string("input_47_mode_0"), val = string("replicate")];
            fp16 const_12_to_fp16 = const()[name = string("const_12_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 1548]> input_47_cast_fp16 = pad(constant_val = const_12_to_fp16, mode = input_47_mode_0, pad = input_47_pad_0, x = input_45_cast_fp16)[name = string("input_47_cast_fp16")];
            string input_tensor_93_pad_type_0 = const()[name = string("input_tensor_93_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_93_dilations_0 = const()[name = string("input_tensor_93_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 input_tensor_93_groups_0 = const()[name = string("input_tensor_93_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_93_strides_0 = const()[name = string("input_tensor_93_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_93_pad_0 = const()[name = string("input_tensor_93_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_4_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_4_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17014208)))];
            tensor<fp16, [512]> decoder_convnext_4_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_4_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17021440)))];
            tensor<fp16, [1, 512, 1536]> input_tensor_93_cast_fp16 = conv(bias = decoder_convnext_4_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_93_dilations_0, groups = input_tensor_93_groups_0, pad = input_tensor_93_pad_0, pad_type = input_tensor_93_pad_type_0, strides = input_tensor_93_strides_0, weight = decoder_convnext_4_dwconv_net_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("input_tensor_93_cast_fp16")];
            tensor<int32, [3]> var_574 = const()[name = string("op_574"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_95_axes_0 = const()[name = string("input_tensor_95_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17022528)))];
            tensor<fp16, [512]> decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17023616)))];
            fp16 var_577_to_fp16 = const()[name = string("op_577_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 1536, 512]> input_49_cast_fp16 = transpose(perm = var_574, x = input_tensor_93_cast_fp16)[name = string("transpose_12")];
            tensor<fp16, [1, 1536, 512]> input_tensor_95_cast_fp16 = layer_norm(axes = input_tensor_95_axes_0, beta = decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_577_to_fp16, gamma = decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16, x = input_49_cast_fp16)[name = string("input_tensor_95_cast_fp16")];
            tensor<int32, [3]> var_586 = const()[name = string("op_586"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_37_pad_type_0 = const()[name = string("first_37_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_37_strides_0 = const()[name = string("first_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_37_pad_0 = const()[name = string("first_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_37_dilations_0 = const()[name = string("first_37_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_37_groups_0 = const()[name = string("first_37_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_4_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_4_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17024704)))];
            tensor<fp16, [2048]> decoder_convnext_4_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_4_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19121920)))];
            tensor<fp16, [1, 512, 1536]> input_51_cast_fp16 = transpose(perm = var_586, x = input_tensor_95_cast_fp16)[name = string("transpose_11")];
            tensor<fp16, [1, 2048, 1536]> first_37_cast_fp16 = conv(bias = decoder_convnext_4_pwconv1_Conv_bias_to_fp16, dilations = first_37_dilations_0, groups = first_37_groups_0, pad = first_37_pad_0, pad_type = first_37_pad_type_0, strides = first_37_strides_0, weight = decoder_convnext_4_pwconv1_Conv_weight_to_fp16, x = input_51_cast_fp16)[name = string("first_37_cast_fp16")];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 1536]> input_53_cast_fp16 = gelu(mode = input_53_mode_0, x = first_37_cast_fp16)[name = string("input_53_cast_fp16")];
            string second_63_pad_type_0 = const()[name = string("second_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_63_strides_0 = const()[name = string("second_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_63_pad_0 = const()[name = string("second_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_63_dilations_0 = const()[name = string("second_63_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_63_groups_0 = const()[name = string("second_63_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_65_weight_0_to_fp16 = const()[name = string("second_65_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19126080)))];
            tensor<fp16, [512]> second_65_bias_0_to_fp16 = const()[name = string("second_65_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21223296)))];
            tensor<fp16, [1, 512, 1536]> second_65_cast_fp16 = conv(bias = second_65_bias_0_to_fp16, dilations = second_63_dilations_0, groups = second_63_groups_0, pad = second_63_pad_0, pad_type = second_63_pad_type_0, strides = second_63_strides_0, weight = second_65_weight_0_to_fp16, x = input_53_cast_fp16)[name = string("second_65_cast_fp16")];
            tensor<fp16, [1, 512, 1536]> input_55_cast_fp16 = add(x = input_45_cast_fp16, y = second_65_cast_fp16)[name = string("input_55_cast_fp16")];
            tensor<int32, [6]> input_57_pad_0 = const()[name = string("input_57_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 24, 0])];
            string input_57_mode_0 = const()[name = string("input_57_mode_0"), val = string("replicate")];
            fp16 const_13_to_fp16 = const()[name = string("const_13_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 1560]> input_57_cast_fp16 = pad(constant_val = const_13_to_fp16, mode = input_57_mode_0, pad = input_57_pad_0, x = input_55_cast_fp16)[name = string("input_57_cast_fp16")];
            string input_tensor_107_pad_type_0 = const()[name = string("input_tensor_107_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_107_dilations_0 = const()[name = string("input_tensor_107_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 input_tensor_107_groups_0 = const()[name = string("input_tensor_107_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_107_strides_0 = const()[name = string("input_tensor_107_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_107_pad_0 = const()[name = string("input_tensor_107_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_5_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_5_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21224384)))];
            tensor<fp16, [512]> decoder_convnext_5_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_5_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21231616)))];
            tensor<fp16, [1, 512, 1536]> input_tensor_107_cast_fp16 = conv(bias = decoder_convnext_5_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_107_dilations_0, groups = input_tensor_107_groups_0, pad = input_tensor_107_pad_0, pad_type = input_tensor_107_pad_type_0, strides = input_tensor_107_strides_0, weight = decoder_convnext_5_dwconv_net_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = string("input_tensor_107_cast_fp16")];
            tensor<int32, [3]> var_641 = const()[name = string("op_641"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_109_axes_0 = const()[name = string("input_tensor_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21232704)))];
            tensor<fp16, [512]> decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21233792)))];
            fp16 var_644_to_fp16 = const()[name = string("op_644_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 1536, 512]> input_59_cast_fp16 = transpose(perm = var_641, x = input_tensor_107_cast_fp16)[name = string("transpose_10")];
            tensor<fp16, [1, 1536, 512]> input_tensor_109_cast_fp16 = layer_norm(axes = input_tensor_109_axes_0, beta = decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_644_to_fp16, gamma = decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16, x = input_59_cast_fp16)[name = string("input_tensor_109_cast_fp16")];
            tensor<int32, [3]> var_653 = const()[name = string("op_653"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_45_pad_type_0 = const()[name = string("first_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_45_strides_0 = const()[name = string("first_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_45_pad_0 = const()[name = string("first_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_45_dilations_0 = const()[name = string("first_45_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_45_groups_0 = const()[name = string("first_45_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_5_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_5_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21234880)))];
            tensor<fp16, [2048]> decoder_convnext_5_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_5_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23332096)))];
            tensor<fp16, [1, 512, 1536]> input_61_cast_fp16 = transpose(perm = var_653, x = input_tensor_109_cast_fp16)[name = string("transpose_9")];
            tensor<fp16, [1, 2048, 1536]> first_45_cast_fp16 = conv(bias = decoder_convnext_5_pwconv1_Conv_bias_to_fp16, dilations = first_45_dilations_0, groups = first_45_groups_0, pad = first_45_pad_0, pad_type = first_45_pad_type_0, strides = first_45_strides_0, weight = decoder_convnext_5_pwconv1_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("first_45_cast_fp16")];
            string input_63_mode_0 = const()[name = string("input_63_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 1536]> input_63_cast_fp16 = gelu(mode = input_63_mode_0, x = first_45_cast_fp16)[name = string("input_63_cast_fp16")];
            string second_75_pad_type_0 = const()[name = string("second_75_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_75_strides_0 = const()[name = string("second_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_75_pad_0 = const()[name = string("second_75_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_75_dilations_0 = const()[name = string("second_75_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_75_groups_0 = const()[name = string("second_75_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_77_weight_0_to_fp16 = const()[name = string("second_77_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23336256)))];
            tensor<fp16, [512]> second_77_bias_0_to_fp16 = const()[name = string("second_77_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25433472)))];
            tensor<fp16, [1, 512, 1536]> second_77_cast_fp16 = conv(bias = second_77_bias_0_to_fp16, dilations = second_75_dilations_0, groups = second_75_groups_0, pad = second_75_pad_0, pad_type = second_75_pad_type_0, strides = second_75_strides_0, weight = second_77_weight_0_to_fp16, x = input_63_cast_fp16)[name = string("second_77_cast_fp16")];
            tensor<fp16, [1, 512, 1536]> input_65_cast_fp16 = add(x = input_55_cast_fp16, y = second_77_cast_fp16)[name = string("input_65_cast_fp16")];
            tensor<int32, [6]> input_67_pad_0 = const()[name = string("input_67_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_67_mode_0 = const()[name = string("input_67_mode_0"), val = string("replicate")];
            fp16 const_14_to_fp16 = const()[name = string("const_14_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 1542]> input_67_cast_fp16 = pad(constant_val = const_14_to_fp16, mode = input_67_mode_0, pad = input_67_pad_0, x = input_65_cast_fp16)[name = string("input_67_cast_fp16")];
            string input_tensor_121_pad_type_0 = const()[name = string("input_tensor_121_pad_type_0"), val = string("valid")];
            int32 input_tensor_121_groups_0 = const()[name = string("input_tensor_121_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_121_strides_0 = const()[name = string("input_tensor_121_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_121_pad_0 = const()[name = string("input_tensor_121_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_121_dilations_0 = const()[name = string("input_tensor_121_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_6_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_6_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25434560)))];
            tensor<fp16, [512]> decoder_convnext_6_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_6_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25441792)))];
            tensor<fp16, [1, 512, 1536]> input_tensor_121_cast_fp16 = conv(bias = decoder_convnext_6_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_121_dilations_0, groups = input_tensor_121_groups_0, pad = input_tensor_121_pad_0, pad_type = input_tensor_121_pad_type_0, strides = input_tensor_121_strides_0, weight = decoder_convnext_6_dwconv_net_Conv_weight_to_fp16, x = input_67_cast_fp16)[name = string("input_tensor_121_cast_fp16")];
            tensor<int32, [3]> var_707 = const()[name = string("op_707"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_123_axes_0 = const()[name = string("input_tensor_123_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25442880)))];
            tensor<fp16, [512]> decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25443968)))];
            fp16 var_710_to_fp16 = const()[name = string("op_710_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 1536, 512]> input_69_cast_fp16 = transpose(perm = var_707, x = input_tensor_121_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 1536, 512]> input_tensor_123_cast_fp16 = layer_norm(axes = input_tensor_123_axes_0, beta = decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_710_to_fp16, gamma = decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16, x = input_69_cast_fp16)[name = string("input_tensor_123_cast_fp16")];
            tensor<int32, [3]> var_719 = const()[name = string("op_719"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_53_pad_type_0 = const()[name = string("first_53_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_53_strides_0 = const()[name = string("first_53_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_53_pad_0 = const()[name = string("first_53_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_53_dilations_0 = const()[name = string("first_53_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_53_groups_0 = const()[name = string("first_53_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_6_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_6_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25445056)))];
            tensor<fp16, [2048]> decoder_convnext_6_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_6_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27542272)))];
            tensor<fp16, [1, 512, 1536]> input_71_cast_fp16 = transpose(perm = var_719, x = input_tensor_123_cast_fp16)[name = string("transpose_7")];
            tensor<fp16, [1, 2048, 1536]> first_53_cast_fp16 = conv(bias = decoder_convnext_6_pwconv1_Conv_bias_to_fp16, dilations = first_53_dilations_0, groups = first_53_groups_0, pad = first_53_pad_0, pad_type = first_53_pad_type_0, strides = first_53_strides_0, weight = decoder_convnext_6_pwconv1_Conv_weight_to_fp16, x = input_71_cast_fp16)[name = string("first_53_cast_fp16")];
            string input_73_mode_0 = const()[name = string("input_73_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 1536]> input_73_cast_fp16 = gelu(mode = input_73_mode_0, x = first_53_cast_fp16)[name = string("input_73_cast_fp16")];
            string second_87_pad_type_0 = const()[name = string("second_87_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_87_strides_0 = const()[name = string("second_87_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_87_pad_0 = const()[name = string("second_87_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_87_dilations_0 = const()[name = string("second_87_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_87_groups_0 = const()[name = string("second_87_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_89_weight_0_to_fp16 = const()[name = string("second_89_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27546432)))];
            tensor<fp16, [512]> second_89_bias_0_to_fp16 = const()[name = string("second_89_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29643648)))];
            tensor<fp16, [1, 512, 1536]> second_89_cast_fp16 = conv(bias = second_89_bias_0_to_fp16, dilations = second_87_dilations_0, groups = second_87_groups_0, pad = second_87_pad_0, pad_type = second_87_pad_type_0, strides = second_87_strides_0, weight = second_89_weight_0_to_fp16, x = input_73_cast_fp16)[name = string("second_89_cast_fp16")];
            tensor<fp16, [1, 512, 1536]> input_75_cast_fp16 = add(x = input_65_cast_fp16, y = second_89_cast_fp16)[name = string("input_75_cast_fp16")];
            tensor<int32, [6]> input_77_pad_0 = const()[name = string("input_77_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_77_mode_0 = const()[name = string("input_77_mode_0"), val = string("replicate")];
            fp16 const_15_to_fp16 = const()[name = string("const_15_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 1542]> input_77_cast_fp16 = pad(constant_val = const_15_to_fp16, mode = input_77_mode_0, pad = input_77_pad_0, x = input_75_cast_fp16)[name = string("input_77_cast_fp16")];
            string input_tensor_135_pad_type_0 = const()[name = string("input_tensor_135_pad_type_0"), val = string("valid")];
            int32 input_tensor_135_groups_0 = const()[name = string("input_tensor_135_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_135_strides_0 = const()[name = string("input_tensor_135_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_135_pad_0 = const()[name = string("input_tensor_135_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_135_dilations_0 = const()[name = string("input_tensor_135_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_7_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_7_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29644736)))];
            tensor<fp16, [512]> decoder_convnext_7_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_7_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29651968)))];
            tensor<fp16, [1, 512, 1536]> input_tensor_135_cast_fp16 = conv(bias = decoder_convnext_7_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_135_dilations_0, groups = input_tensor_135_groups_0, pad = input_tensor_135_pad_0, pad_type = input_tensor_135_pad_type_0, strides = input_tensor_135_strides_0, weight = decoder_convnext_7_dwconv_net_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = string("input_tensor_135_cast_fp16")];
            tensor<int32, [3]> var_773 = const()[name = string("op_773"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_137_axes_0 = const()[name = string("input_tensor_137_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29653056)))];
            tensor<fp16, [512]> decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29654144)))];
            fp16 var_776_to_fp16 = const()[name = string("op_776_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 1536, 512]> input_79_cast_fp16 = transpose(perm = var_773, x = input_tensor_135_cast_fp16)[name = string("transpose_6")];
            tensor<fp16, [1, 1536, 512]> input_tensor_137_cast_fp16 = layer_norm(axes = input_tensor_137_axes_0, beta = decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_776_to_fp16, gamma = decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_tensor_137_cast_fp16")];
            tensor<int32, [3]> var_785 = const()[name = string("op_785"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_61_pad_type_0 = const()[name = string("first_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_61_strides_0 = const()[name = string("first_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_61_pad_0 = const()[name = string("first_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_61_dilations_0 = const()[name = string("first_61_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_61_groups_0 = const()[name = string("first_61_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_7_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_7_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29655232)))];
            tensor<fp16, [2048]> decoder_convnext_7_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_7_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31752448)))];
            tensor<fp16, [1, 512, 1536]> input_81_cast_fp16 = transpose(perm = var_785, x = input_tensor_137_cast_fp16)[name = string("transpose_5")];
            tensor<fp16, [1, 2048, 1536]> first_61_cast_fp16 = conv(bias = decoder_convnext_7_pwconv1_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = decoder_convnext_7_pwconv1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = string("first_61_cast_fp16")];
            string input_83_mode_0 = const()[name = string("input_83_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 1536]> input_83_cast_fp16 = gelu(mode = input_83_mode_0, x = first_61_cast_fp16)[name = string("input_83_cast_fp16")];
            string second_99_pad_type_0 = const()[name = string("second_99_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_99_strides_0 = const()[name = string("second_99_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_99_pad_0 = const()[name = string("second_99_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_99_dilations_0 = const()[name = string("second_99_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_99_groups_0 = const()[name = string("second_99_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_101_weight_0_to_fp16 = const()[name = string("second_101_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31756608)))];
            tensor<fp16, [512]> second_101_bias_0_to_fp16 = const()[name = string("second_101_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33853824)))];
            tensor<fp16, [1, 512, 1536]> second_101_cast_fp16 = conv(bias = second_101_bias_0_to_fp16, dilations = second_99_dilations_0, groups = second_99_groups_0, pad = second_99_pad_0, pad_type = second_99_pad_type_0, strides = second_99_strides_0, weight = second_101_weight_0_to_fp16, x = input_83_cast_fp16)[name = string("second_101_cast_fp16")];
            tensor<fp16, [1, 512, 1536]> input_85_cast_fp16 = add(x = input_75_cast_fp16, y = second_101_cast_fp16)[name = string("input_85_cast_fp16")];
            tensor<int32, [6]> input_87_pad_0 = const()[name = string("input_87_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_87_mode_0 = const()[name = string("input_87_mode_0"), val = string("replicate")];
            fp16 const_16_to_fp16 = const()[name = string("const_16_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 1542]> input_87_cast_fp16 = pad(constant_val = const_16_to_fp16, mode = input_87_mode_0, pad = input_87_pad_0, x = input_85_cast_fp16)[name = string("input_87_cast_fp16")];
            string input_tensor_149_pad_type_0 = const()[name = string("input_tensor_149_pad_type_0"), val = string("valid")];
            int32 input_tensor_149_groups_0 = const()[name = string("input_tensor_149_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_149_strides_0 = const()[name = string("input_tensor_149_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_149_pad_0 = const()[name = string("input_tensor_149_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_149_dilations_0 = const()[name = string("input_tensor_149_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_8_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_8_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33854912)))];
            tensor<fp16, [512]> decoder_convnext_8_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_8_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33862144)))];
            tensor<fp16, [1, 512, 1536]> input_tensor_149_cast_fp16 = conv(bias = decoder_convnext_8_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_149_dilations_0, groups = input_tensor_149_groups_0, pad = input_tensor_149_pad_0, pad_type = input_tensor_149_pad_type_0, strides = input_tensor_149_strides_0, weight = decoder_convnext_8_dwconv_net_Conv_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_tensor_149_cast_fp16")];
            tensor<int32, [3]> var_839 = const()[name = string("op_839"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_151_axes_0 = const()[name = string("input_tensor_151_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33863232)))];
            tensor<fp16, [512]> decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33864320)))];
            fp16 var_842_to_fp16 = const()[name = string("op_842_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 1536, 512]> input_89_cast_fp16 = transpose(perm = var_839, x = input_tensor_149_cast_fp16)[name = string("transpose_4")];
            tensor<fp16, [1, 1536, 512]> input_tensor_151_cast_fp16 = layer_norm(axes = input_tensor_151_axes_0, beta = decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_842_to_fp16, gamma = decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_151_cast_fp16")];
            tensor<int32, [3]> var_851 = const()[name = string("op_851"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_69_pad_type_0 = const()[name = string("first_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_69_strides_0 = const()[name = string("first_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_69_pad_0 = const()[name = string("first_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_69_dilations_0 = const()[name = string("first_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_69_groups_0 = const()[name = string("first_69_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_8_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_8_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33865408)))];
            tensor<fp16, [2048]> decoder_convnext_8_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_8_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35962624)))];
            tensor<fp16, [1, 512, 1536]> input_91_cast_fp16 = transpose(perm = var_851, x = input_tensor_151_cast_fp16)[name = string("transpose_3")];
            tensor<fp16, [1, 2048, 1536]> first_69_cast_fp16 = conv(bias = decoder_convnext_8_pwconv1_Conv_bias_to_fp16, dilations = first_69_dilations_0, groups = first_69_groups_0, pad = first_69_pad_0, pad_type = first_69_pad_type_0, strides = first_69_strides_0, weight = decoder_convnext_8_pwconv1_Conv_weight_to_fp16, x = input_91_cast_fp16)[name = string("first_69_cast_fp16")];
            string input_93_mode_0 = const()[name = string("input_93_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 1536]> input_93_cast_fp16 = gelu(mode = input_93_mode_0, x = first_69_cast_fp16)[name = string("input_93_cast_fp16")];
            string second_111_pad_type_0 = const()[name = string("second_111_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_111_strides_0 = const()[name = string("second_111_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_111_pad_0 = const()[name = string("second_111_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_111_dilations_0 = const()[name = string("second_111_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_111_groups_0 = const()[name = string("second_111_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_113_weight_0_to_fp16 = const()[name = string("second_113_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35966784)))];
            tensor<fp16, [512]> second_113_bias_0_to_fp16 = const()[name = string("second_113_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38064000)))];
            tensor<fp16, [1, 512, 1536]> second_113_cast_fp16 = conv(bias = second_113_bias_0_to_fp16, dilations = second_111_dilations_0, groups = second_111_groups_0, pad = second_111_pad_0, pad_type = second_111_pad_type_0, strides = second_111_strides_0, weight = second_113_weight_0_to_fp16, x = input_93_cast_fp16)[name = string("second_113_cast_fp16")];
            tensor<fp16, [1, 512, 1536]> input_95_cast_fp16 = add(x = input_85_cast_fp16, y = second_113_cast_fp16)[name = string("input_95_cast_fp16")];
            tensor<int32, [6]> input_97_pad_0 = const()[name = string("input_97_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_97_mode_0 = const()[name = string("input_97_mode_0"), val = string("replicate")];
            fp16 const_17_to_fp16 = const()[name = string("const_17_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 1542]> input_97_cast_fp16 = pad(constant_val = const_17_to_fp16, mode = input_97_mode_0, pad = input_97_pad_0, x = input_95_cast_fp16)[name = string("input_97_cast_fp16")];
            string input_tensor_163_pad_type_0 = const()[name = string("input_tensor_163_pad_type_0"), val = string("valid")];
            int32 input_tensor_163_groups_0 = const()[name = string("input_tensor_163_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_163_strides_0 = const()[name = string("input_tensor_163_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_163_pad_0 = const()[name = string("input_tensor_163_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_163_dilations_0 = const()[name = string("input_tensor_163_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_9_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_9_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38065088)))];
            tensor<fp16, [512]> decoder_convnext_9_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_9_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38072320)))];
            tensor<fp16, [1, 512, 1536]> input_tensor_163_cast_fp16 = conv(bias = decoder_convnext_9_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_163_dilations_0, groups = input_tensor_163_groups_0, pad = input_tensor_163_pad_0, pad_type = input_tensor_163_pad_type_0, strides = input_tensor_163_strides_0, weight = decoder_convnext_9_dwconv_net_Conv_weight_to_fp16, x = input_97_cast_fp16)[name = string("input_tensor_163_cast_fp16")];
            tensor<int32, [3]> var_905 = const()[name = string("op_905"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_165_axes_0 = const()[name = string("input_tensor_165_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38073408)))];
            tensor<fp16, [512]> decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38074496)))];
            fp16 var_908_to_fp16 = const()[name = string("op_908_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 1536, 512]> input_99_cast_fp16 = transpose(perm = var_905, x = input_tensor_163_cast_fp16)[name = string("transpose_2")];
            tensor<fp16, [1, 1536, 512]> input_tensor_165_cast_fp16 = layer_norm(axes = input_tensor_165_axes_0, beta = decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_908_to_fp16, gamma = decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16, x = input_99_cast_fp16)[name = string("input_tensor_165_cast_fp16")];
            tensor<int32, [3]> var_917 = const()[name = string("op_917"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_77_pad_type_0 = const()[name = string("first_77_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_77_strides_0 = const()[name = string("first_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_77_pad_0 = const()[name = string("first_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_77_dilations_0 = const()[name = string("first_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_77_groups_0 = const()[name = string("first_77_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_9_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_9_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38075584)))];
            tensor<fp16, [2048]> decoder_convnext_9_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_9_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40172800)))];
            tensor<fp16, [1, 512, 1536]> input_101_cast_fp16 = transpose(perm = var_917, x = input_tensor_165_cast_fp16)[name = string("transpose_1")];
            tensor<fp16, [1, 2048, 1536]> first_77_cast_fp16 = conv(bias = decoder_convnext_9_pwconv1_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = decoder_convnext_9_pwconv1_Conv_weight_to_fp16, x = input_101_cast_fp16)[name = string("first_77_cast_fp16")];
            string input_103_mode_0 = const()[name = string("input_103_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 1536]> input_103_cast_fp16 = gelu(mode = input_103_mode_0, x = first_77_cast_fp16)[name = string("input_103_cast_fp16")];
            string second_123_pad_type_0 = const()[name = string("second_123_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_123_strides_0 = const()[name = string("second_123_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_123_pad_0 = const()[name = string("second_123_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_123_dilations_0 = const()[name = string("second_123_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_123_groups_0 = const()[name = string("second_123_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_weight_0_to_fp16 = const()[name = string("second_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40176960)))];
            tensor<fp16, [512]> second_bias_0_to_fp16 = const()[name = string("second_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42274176)))];
            tensor<fp16, [1, 512, 1536]> second_cast_fp16 = conv(bias = second_bias_0_to_fp16, dilations = second_123_dilations_0, groups = second_123_groups_0, pad = second_123_pad_0, pad_type = second_123_pad_type_0, strides = second_123_strides_0, weight = second_weight_0_to_fp16, x = input_103_cast_fp16)[name = string("second_cast_fp16")];
            tensor<fp16, [1, 512, 1536]> input_105_cast_fp16 = add(x = input_95_cast_fp16, y = second_cast_fp16)[name = string("input_105_cast_fp16")];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_running_mean_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42275264)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_running_var_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42276352)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_weight_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42277440)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_bias_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42278528)))];
            fp16 var_951_to_fp16 = const()[name = string("op_951_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 512, 1536]> input_107_cast_fp16 = batch_norm(beta = decoder_final_norm_BatchNormalization_bias_to_fp16, epsilon = var_951_to_fp16, gamma = decoder_final_norm_BatchNormalization_weight_to_fp16, mean = decoder_final_norm_BatchNormalization_running_mean_to_fp16, variance = decoder_final_norm_BatchNormalization_running_var_to_fp16, x = input_105_cast_fp16)[name = string("input_107_cast_fp16")];
            tensor<int32, [6]> input_109_pad_0 = const()[name = string("input_109_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 0])];
            string input_109_mode_0 = const()[name = string("input_109_mode_0"), val = string("replicate")];
            fp16 const_18_to_fp16 = const()[name = string("const_18_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 1538]> input_109_cast_fp16 = pad(constant_val = const_18_to_fp16, mode = input_109_mode_0, pad = input_109_pad_0, x = input_107_cast_fp16)[name = string("input_109_cast_fp16")];
            string input_tensor_177_pad_type_0 = const()[name = string("input_tensor_177_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_177_strides_0 = const()[name = string("input_tensor_177_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_177_pad_0 = const()[name = string("input_tensor_177_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_177_dilations_0 = const()[name = string("input_tensor_177_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_177_groups_0 = const()[name = string("input_tensor_177_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 3]> decoder_head_layer1_net_Conv_weight_to_fp16 = const()[name = string("decoder_head_layer1_net_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42279616)))];
            tensor<fp16, [2048]> decoder_head_layer1_net_Conv_bias_to_fp16 = const()[name = string("decoder_head_layer1_net_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48571136)))];
            tensor<fp16, [1, 2048, 1536]> input_tensor_177_cast_fp16 = conv(bias = decoder_head_layer1_net_Conv_bias_to_fp16, dilations = input_tensor_177_dilations_0, groups = input_tensor_177_groups_0, pad = input_tensor_177_pad_0, pad_type = input_tensor_177_pad_type_0, strides = input_tensor_177_strides_0, weight = decoder_head_layer1_net_Conv_weight_to_fp16, x = input_109_cast_fp16)[name = string("input_tensor_177_cast_fp16")];
            fp32 input_alpha_1 = const()[name = string("input_alpha_1"), val = fp32(0x1.9814fap-13)];
            tensor<fp16, [1, 2048, 1536]> input_cast_fp16 = leaky_relu(alpha = input_alpha_1, x = input_tensor_177_cast_fp16)[name = string("input_cast_fp16")];
            string input_tensor_179_pad_type_0 = const()[name = string("input_tensor_179_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_179_strides_0 = const()[name = string("input_tensor_179_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_179_pad_0 = const()[name = string("input_tensor_179_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_179_dilations_0 = const()[name = string("input_tensor_179_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_179_groups_0 = const()[name = string("input_tensor_179_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> decoder_head_layer2_Conv_weight_to_fp16 = const()[name = string("decoder_head_layer2_Conv_weight_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48575296)))];
            tensor<fp16, [1, 512, 1536]> input_tensor_179_cast_fp16 = conv(dilations = input_tensor_179_dilations_0, groups = input_tensor_179_groups_0, pad = input_tensor_179_pad_0, pad_type = input_tensor_179_pad_type_0, strides = input_tensor_179_strides_0, weight = decoder_head_layer2_Conv_weight_to_fp16, x = input_cast_fp16)[name = string("input_tensor_179_cast_fp16")];
            tensor<int32, [3]> var_994 = const()[name = string("op_994"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [2]> var_1021 = const()[name = string("op_1021"), val = tensor<int32, [2]>([1, -1])];
            tensor<fp16, [1, 1536, 512]> input_tensor_181_cast_fp16 = transpose(perm = var_994, x = input_tensor_179_cast_fp16)[name = string("transpose_0")];
            tensor<fp16, [1, 786432]> wav_tts = reshape(shape = var_1021, x = input_tensor_181_cast_fp16)[name = string("op_1022_cast_fp16")];
        } -> (wav_tts);
    func vocoder_l32<ios18>(tensor<fp16, [1, 144, 32]> latent) {
            fp16 _inversed_input_tensor_1_y_0_to_fp16 = const()[name = string("_inversed_input_tensor_1_y_0_to_fp16"), val = fp16(0x1p+2)];
            tensor<fp16, [1, 144, 32]> _inversed_input_tensor_1_cast_fp16 = mul(x = latent, y = _inversed_input_tensor_1_y_0_to_fp16)[name = string("_inversed_input_tensor_1_cast_fp16")];
            tensor<int32, [4]> var_213 = const()[name = string("op_213"), val = tensor<int32, [4]>([1, -1, 6, 32])];
            tensor<fp16, [1, 24, 6, 32]> input_tensor_9_cast_fp16 = reshape(shape = var_213, x = _inversed_input_tensor_1_cast_fp16)[name = string("input_tensor_9_cast_fp16")];
            tensor<int32, [4]> var_219 = const()[name = string("op_219"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_264 = const()[name = string("op_264"), val = tensor<int32, [3]>([1, 24, -1])];
            tensor<fp16, [1, 24, 32, 6]> input_tensor_11_cast_fp16 = transpose(perm = var_219, x = input_tensor_9_cast_fp16)[name = string("transpose_21")];
            tensor<fp16, [1, 24, 192]> first_1_cast_fp16 = reshape(shape = var_264, x = input_tensor_11_cast_fp16)[name = string("first_1_cast_fp16")];
            tensor<fp16, [1, 24, 1]> initializers_onnx_initializer_1_to_fp16 = const()[name = string("initializers_onnx_initializer_1_to_fp16"), val = tensor<fp16, [1, 24, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [1, 24, 192]> first_3_cast_fp16 = mul(x = first_1_cast_fp16, y = initializers_onnx_initializer_1_to_fp16)[name = string("first_3_cast_fp16")];
            tensor<fp16, [1, 24, 1]> initializers_onnx_initializer_2_to_fp16 = const()[name = string("initializers_onnx_initializer_2_to_fp16"), val = tensor<fp16, [1, 24, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192)))];
            tensor<fp16, [1, 24, 192]> input_1_cast_fp16 = add(x = first_3_cast_fp16, y = initializers_onnx_initializer_2_to_fp16)[name = string("input_1_cast_fp16")];
            tensor<int32, [6]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("replicate")];
            fp16 const_7_to_fp16 = const()[name = string("const_7_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 24, 198]> input_3_cast_fp16 = pad(constant_val = const_7_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string input_5_pad_type_0 = const()[name = string("input_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_5_strides_0 = const()[name = string("input_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_5_pad_0 = const()[name = string("input_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_5_dilations_0 = const()[name = string("input_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_5_groups_0 = const()[name = string("input_5_groups_0"), val = int32(1)];
            tensor<fp16, [512, 24, 7]> decoder_embed_net_Conv_weight_to_fp16 = const()[name = string("decoder_embed_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 24, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(320)))];
            tensor<fp16, [512]> decoder_embed_net_Conv_bias_to_fp16 = const()[name = string("decoder_embed_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(172416)))];
            tensor<fp16, [1, 512, 192]> input_5_cast_fp16 = conv(bias = decoder_embed_net_Conv_bias_to_fp16, dilations = input_5_dilations_0, groups = input_5_groups_0, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = input_5_strides_0, weight = decoder_embed_net_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = string("input_5_cast_fp16")];
            tensor<int32, [6]> input_7_pad_0 = const()[name = string("input_7_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_7_mode_0 = const()[name = string("input_7_mode_0"), val = string("replicate")];
            fp16 const_8_to_fp16 = const()[name = string("const_8_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 198]> input_7_cast_fp16 = pad(constant_val = const_8_to_fp16, mode = input_7_mode_0, pad = input_7_pad_0, x = input_5_cast_fp16)[name = string("input_7_cast_fp16")];
            string input_tensor_37_pad_type_0 = const()[name = string("input_tensor_37_pad_type_0"), val = string("valid")];
            int32 input_tensor_37_groups_0 = const()[name = string("input_tensor_37_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_37_strides_0 = const()[name = string("input_tensor_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_37_pad_0 = const()[name = string("input_tensor_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_37_dilations_0 = const()[name = string("input_tensor_37_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_0_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_0_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(173504)))];
            tensor<fp16, [512]> decoder_convnext_0_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_0_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(180736)))];
            tensor<fp16, [1, 512, 192]> input_tensor_37_cast_fp16 = conv(bias = decoder_convnext_0_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_37_dilations_0, groups = input_tensor_37_groups_0, pad = input_tensor_37_pad_0, pad_type = input_tensor_37_pad_type_0, strides = input_tensor_37_strides_0, weight = decoder_convnext_0_dwconv_net_Conv_weight_to_fp16, x = input_7_cast_fp16)[name = string("input_tensor_37_cast_fp16")];
            tensor<int32, [3]> var_307 = const()[name = string("op_307"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_39_axes_0 = const()[name = string("input_tensor_39_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(181824)))];
            tensor<fp16, [512]> decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(182912)))];
            fp16 var_310_to_fp16 = const()[name = string("op_310_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 512]> input_9_cast_fp16 = transpose(perm = var_307, x = input_tensor_37_cast_fp16)[name = string("transpose_20")];
            tensor<fp16, [1, 192, 512]> input_tensor_39_cast_fp16 = layer_norm(axes = input_tensor_39_axes_0, beta = decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_310_to_fp16, gamma = decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16, x = input_9_cast_fp16)[name = string("input_tensor_39_cast_fp16")];
            tensor<int32, [3]> var_319 = const()[name = string("op_319"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_5_pad_type_0 = const()[name = string("first_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_5_strides_0 = const()[name = string("first_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_5_pad_0 = const()[name = string("first_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_5_dilations_0 = const()[name = string("first_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_5_groups_0 = const()[name = string("first_5_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_0_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_0_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(184000)))];
            tensor<fp16, [2048]> decoder_convnext_0_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_0_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2281216)))];
            tensor<fp16, [1, 512, 192]> input_11_cast_fp16 = transpose(perm = var_319, x = input_tensor_39_cast_fp16)[name = string("transpose_19")];
            tensor<fp16, [1, 2048, 192]> first_5_cast_fp16 = conv(bias = decoder_convnext_0_pwconv1_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = decoder_convnext_0_pwconv1_Conv_weight_to_fp16, x = input_11_cast_fp16)[name = string("first_5_cast_fp16")];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 192]> input_13_cast_fp16 = gelu(mode = input_13_mode_0, x = first_5_cast_fp16)[name = string("input_13_cast_fp16")];
            string second_15_pad_type_0 = const()[name = string("second_15_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_15_strides_0 = const()[name = string("second_15_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_15_pad_0 = const()[name = string("second_15_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_15_dilations_0 = const()[name = string("second_15_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_15_groups_0 = const()[name = string("second_15_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_17_weight_0_to_fp16 = const()[name = string("second_17_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2285376)))];
            tensor<fp16, [512]> second_17_bias_0_to_fp16 = const()[name = string("second_17_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4382592)))];
            tensor<fp16, [1, 512, 192]> second_17_cast_fp16 = conv(bias = second_17_bias_0_to_fp16, dilations = second_15_dilations_0, groups = second_15_groups_0, pad = second_15_pad_0, pad_type = second_15_pad_type_0, strides = second_15_strides_0, weight = second_17_weight_0_to_fp16, x = input_13_cast_fp16)[name = string("second_17_cast_fp16")];
            tensor<fp16, [1, 512, 192]> input_15_cast_fp16 = add(x = input_5_cast_fp16, y = second_17_cast_fp16)[name = string("input_15_cast_fp16")];
            tensor<int32, [6]> input_17_pad_0 = const()[name = string("input_17_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 12, 0])];
            string input_17_mode_0 = const()[name = string("input_17_mode_0"), val = string("replicate")];
            fp16 const_9_to_fp16 = const()[name = string("const_9_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 204]> input_17_cast_fp16 = pad(constant_val = const_9_to_fp16, mode = input_17_mode_0, pad = input_17_pad_0, x = input_15_cast_fp16)[name = string("input_17_cast_fp16")];
            string input_tensor_51_pad_type_0 = const()[name = string("input_tensor_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_51_dilations_0 = const()[name = string("input_tensor_51_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 input_tensor_51_groups_0 = const()[name = string("input_tensor_51_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_51_strides_0 = const()[name = string("input_tensor_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_51_pad_0 = const()[name = string("input_tensor_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_1_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_1_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4383680)))];
            tensor<fp16, [512]> decoder_convnext_1_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_1_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4390912)))];
            tensor<fp16, [1, 512, 192]> input_tensor_51_cast_fp16 = conv(bias = decoder_convnext_1_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_51_dilations_0, groups = input_tensor_51_groups_0, pad = input_tensor_51_pad_0, pad_type = input_tensor_51_pad_type_0, strides = input_tensor_51_strides_0, weight = decoder_convnext_1_dwconv_net_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = string("input_tensor_51_cast_fp16")];
            tensor<int32, [3]> var_374 = const()[name = string("op_374"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_53_axes_0 = const()[name = string("input_tensor_53_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4392000)))];
            tensor<fp16, [512]> decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4393088)))];
            fp16 var_377_to_fp16 = const()[name = string("op_377_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 512]> input_19_cast_fp16 = transpose(perm = var_374, x = input_tensor_51_cast_fp16)[name = string("transpose_18")];
            tensor<fp16, [1, 192, 512]> input_tensor_53_cast_fp16 = layer_norm(axes = input_tensor_53_axes_0, beta = decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_377_to_fp16, gamma = decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16, x = input_19_cast_fp16)[name = string("input_tensor_53_cast_fp16")];
            tensor<int32, [3]> var_386 = const()[name = string("op_386"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_13_pad_type_0 = const()[name = string("first_13_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_13_strides_0 = const()[name = string("first_13_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_13_pad_0 = const()[name = string("first_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_13_dilations_0 = const()[name = string("first_13_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_13_groups_0 = const()[name = string("first_13_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_1_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_1_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4394176)))];
            tensor<fp16, [2048]> decoder_convnext_1_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_1_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6491392)))];
            tensor<fp16, [1, 512, 192]> input_21_cast_fp16 = transpose(perm = var_386, x = input_tensor_53_cast_fp16)[name = string("transpose_17")];
            tensor<fp16, [1, 2048, 192]> first_13_cast_fp16 = conv(bias = decoder_convnext_1_pwconv1_Conv_bias_to_fp16, dilations = first_13_dilations_0, groups = first_13_groups_0, pad = first_13_pad_0, pad_type = first_13_pad_type_0, strides = first_13_strides_0, weight = decoder_convnext_1_pwconv1_Conv_weight_to_fp16, x = input_21_cast_fp16)[name = string("first_13_cast_fp16")];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 192]> input_23_cast_fp16 = gelu(mode = input_23_mode_0, x = first_13_cast_fp16)[name = string("input_23_cast_fp16")];
            string second_27_pad_type_0 = const()[name = string("second_27_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_27_strides_0 = const()[name = string("second_27_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_27_pad_0 = const()[name = string("second_27_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_27_dilations_0 = const()[name = string("second_27_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_27_groups_0 = const()[name = string("second_27_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_29_weight_0_to_fp16 = const()[name = string("second_29_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6495552)))];
            tensor<fp16, [512]> second_29_bias_0_to_fp16 = const()[name = string("second_29_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8592768)))];
            tensor<fp16, [1, 512, 192]> second_29_cast_fp16 = conv(bias = second_29_bias_0_to_fp16, dilations = second_27_dilations_0, groups = second_27_groups_0, pad = second_27_pad_0, pad_type = second_27_pad_type_0, strides = second_27_strides_0, weight = second_29_weight_0_to_fp16, x = input_23_cast_fp16)[name = string("second_29_cast_fp16")];
            tensor<fp16, [1, 512, 192]> input_25_cast_fp16 = add(x = input_15_cast_fp16, y = second_29_cast_fp16)[name = string("input_25_cast_fp16")];
            tensor<int32, [6]> input_27_pad_0 = const()[name = string("input_27_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 24, 0])];
            string input_27_mode_0 = const()[name = string("input_27_mode_0"), val = string("replicate")];
            fp16 const_10_to_fp16 = const()[name = string("const_10_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 216]> input_27_cast_fp16 = pad(constant_val = const_10_to_fp16, mode = input_27_mode_0, pad = input_27_pad_0, x = input_25_cast_fp16)[name = string("input_27_cast_fp16")];
            string input_tensor_65_pad_type_0 = const()[name = string("input_tensor_65_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_65_dilations_0 = const()[name = string("input_tensor_65_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 input_tensor_65_groups_0 = const()[name = string("input_tensor_65_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_65_strides_0 = const()[name = string("input_tensor_65_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_65_pad_0 = const()[name = string("input_tensor_65_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_2_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_2_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8593856)))];
            tensor<fp16, [512]> decoder_convnext_2_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_2_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8601088)))];
            tensor<fp16, [1, 512, 192]> input_tensor_65_cast_fp16 = conv(bias = decoder_convnext_2_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_65_dilations_0, groups = input_tensor_65_groups_0, pad = input_tensor_65_pad_0, pad_type = input_tensor_65_pad_type_0, strides = input_tensor_65_strides_0, weight = decoder_convnext_2_dwconv_net_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = string("input_tensor_65_cast_fp16")];
            tensor<int32, [3]> var_441 = const()[name = string("op_441"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_67_axes_0 = const()[name = string("input_tensor_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8602176)))];
            tensor<fp16, [512]> decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8603264)))];
            fp16 var_444_to_fp16 = const()[name = string("op_444_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 512]> input_29_cast_fp16 = transpose(perm = var_441, x = input_tensor_65_cast_fp16)[name = string("transpose_16")];
            tensor<fp16, [1, 192, 512]> input_tensor_67_cast_fp16 = layer_norm(axes = input_tensor_67_axes_0, beta = decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_444_to_fp16, gamma = decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16, x = input_29_cast_fp16)[name = string("input_tensor_67_cast_fp16")];
            tensor<int32, [3]> var_453 = const()[name = string("op_453"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_21_pad_type_0 = const()[name = string("first_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_21_strides_0 = const()[name = string("first_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_21_pad_0 = const()[name = string("first_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_21_dilations_0 = const()[name = string("first_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_21_groups_0 = const()[name = string("first_21_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_2_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_2_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8604352)))];
            tensor<fp16, [2048]> decoder_convnext_2_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_2_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10701568)))];
            tensor<fp16, [1, 512, 192]> input_31_cast_fp16 = transpose(perm = var_453, x = input_tensor_67_cast_fp16)[name = string("transpose_15")];
            tensor<fp16, [1, 2048, 192]> first_21_cast_fp16 = conv(bias = decoder_convnext_2_pwconv1_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = decoder_convnext_2_pwconv1_Conv_weight_to_fp16, x = input_31_cast_fp16)[name = string("first_21_cast_fp16")];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 192]> input_33_cast_fp16 = gelu(mode = input_33_mode_0, x = first_21_cast_fp16)[name = string("input_33_cast_fp16")];
            string second_39_pad_type_0 = const()[name = string("second_39_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_39_strides_0 = const()[name = string("second_39_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_39_pad_0 = const()[name = string("second_39_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_39_dilations_0 = const()[name = string("second_39_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_39_groups_0 = const()[name = string("second_39_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_41_weight_0_to_fp16 = const()[name = string("second_41_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10705728)))];
            tensor<fp16, [512]> second_41_bias_0_to_fp16 = const()[name = string("second_41_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12802944)))];
            tensor<fp16, [1, 512, 192]> second_41_cast_fp16 = conv(bias = second_41_bias_0_to_fp16, dilations = second_39_dilations_0, groups = second_39_groups_0, pad = second_39_pad_0, pad_type = second_39_pad_type_0, strides = second_39_strides_0, weight = second_41_weight_0_to_fp16, x = input_33_cast_fp16)[name = string("second_41_cast_fp16")];
            tensor<fp16, [1, 512, 192]> input_35_cast_fp16 = add(x = input_25_cast_fp16, y = second_41_cast_fp16)[name = string("input_35_cast_fp16")];
            tensor<int32, [6]> input_37_pad_0 = const()[name = string("input_37_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_37_mode_0 = const()[name = string("input_37_mode_0"), val = string("replicate")];
            fp16 const_11_to_fp16 = const()[name = string("const_11_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 198]> input_37_cast_fp16 = pad(constant_val = const_11_to_fp16, mode = input_37_mode_0, pad = input_37_pad_0, x = input_35_cast_fp16)[name = string("input_37_cast_fp16")];
            string input_tensor_79_pad_type_0 = const()[name = string("input_tensor_79_pad_type_0"), val = string("valid")];
            int32 input_tensor_79_groups_0 = const()[name = string("input_tensor_79_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_79_strides_0 = const()[name = string("input_tensor_79_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_79_pad_0 = const()[name = string("input_tensor_79_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_79_dilations_0 = const()[name = string("input_tensor_79_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_3_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_3_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12804032)))];
            tensor<fp16, [512]> decoder_convnext_3_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_3_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12811264)))];
            tensor<fp16, [1, 512, 192]> input_tensor_79_cast_fp16 = conv(bias = decoder_convnext_3_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_79_dilations_0, groups = input_tensor_79_groups_0, pad = input_tensor_79_pad_0, pad_type = input_tensor_79_pad_type_0, strides = input_tensor_79_strides_0, weight = decoder_convnext_3_dwconv_net_Conv_weight_to_fp16, x = input_37_cast_fp16)[name = string("input_tensor_79_cast_fp16")];
            tensor<int32, [3]> var_507 = const()[name = string("op_507"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_81_axes_0 = const()[name = string("input_tensor_81_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12812352)))];
            tensor<fp16, [512]> decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12813440)))];
            fp16 var_510_to_fp16 = const()[name = string("op_510_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 512]> input_39_cast_fp16 = transpose(perm = var_507, x = input_tensor_79_cast_fp16)[name = string("transpose_14")];
            tensor<fp16, [1, 192, 512]> input_tensor_81_cast_fp16 = layer_norm(axes = input_tensor_81_axes_0, beta = decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_510_to_fp16, gamma = decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16, x = input_39_cast_fp16)[name = string("input_tensor_81_cast_fp16")];
            tensor<int32, [3]> var_519 = const()[name = string("op_519"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_29_pad_type_0 = const()[name = string("first_29_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_29_strides_0 = const()[name = string("first_29_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_29_pad_0 = const()[name = string("first_29_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_29_dilations_0 = const()[name = string("first_29_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_29_groups_0 = const()[name = string("first_29_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_3_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_3_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12814528)))];
            tensor<fp16, [2048]> decoder_convnext_3_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_3_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14911744)))];
            tensor<fp16, [1, 512, 192]> input_41_cast_fp16 = transpose(perm = var_519, x = input_tensor_81_cast_fp16)[name = string("transpose_13")];
            tensor<fp16, [1, 2048, 192]> first_29_cast_fp16 = conv(bias = decoder_convnext_3_pwconv1_Conv_bias_to_fp16, dilations = first_29_dilations_0, groups = first_29_groups_0, pad = first_29_pad_0, pad_type = first_29_pad_type_0, strides = first_29_strides_0, weight = decoder_convnext_3_pwconv1_Conv_weight_to_fp16, x = input_41_cast_fp16)[name = string("first_29_cast_fp16")];
            string input_43_mode_0 = const()[name = string("input_43_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 192]> input_43_cast_fp16 = gelu(mode = input_43_mode_0, x = first_29_cast_fp16)[name = string("input_43_cast_fp16")];
            string second_51_pad_type_0 = const()[name = string("second_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_51_strides_0 = const()[name = string("second_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_51_pad_0 = const()[name = string("second_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_51_dilations_0 = const()[name = string("second_51_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_51_groups_0 = const()[name = string("second_51_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_53_weight_0_to_fp16 = const()[name = string("second_53_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14915904)))];
            tensor<fp16, [512]> second_53_bias_0_to_fp16 = const()[name = string("second_53_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17013120)))];
            tensor<fp16, [1, 512, 192]> second_53_cast_fp16 = conv(bias = second_53_bias_0_to_fp16, dilations = second_51_dilations_0, groups = second_51_groups_0, pad = second_51_pad_0, pad_type = second_51_pad_type_0, strides = second_51_strides_0, weight = second_53_weight_0_to_fp16, x = input_43_cast_fp16)[name = string("second_53_cast_fp16")];
            tensor<fp16, [1, 512, 192]> input_45_cast_fp16 = add(x = input_35_cast_fp16, y = second_53_cast_fp16)[name = string("input_45_cast_fp16")];
            tensor<int32, [6]> input_47_pad_0 = const()[name = string("input_47_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 12, 0])];
            string input_47_mode_0 = const()[name = string("input_47_mode_0"), val = string("replicate")];
            fp16 const_12_to_fp16 = const()[name = string("const_12_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 204]> input_47_cast_fp16 = pad(constant_val = const_12_to_fp16, mode = input_47_mode_0, pad = input_47_pad_0, x = input_45_cast_fp16)[name = string("input_47_cast_fp16")];
            string input_tensor_93_pad_type_0 = const()[name = string("input_tensor_93_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_93_dilations_0 = const()[name = string("input_tensor_93_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 input_tensor_93_groups_0 = const()[name = string("input_tensor_93_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_93_strides_0 = const()[name = string("input_tensor_93_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_93_pad_0 = const()[name = string("input_tensor_93_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_4_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_4_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17014208)))];
            tensor<fp16, [512]> decoder_convnext_4_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_4_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17021440)))];
            tensor<fp16, [1, 512, 192]> input_tensor_93_cast_fp16 = conv(bias = decoder_convnext_4_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_93_dilations_0, groups = input_tensor_93_groups_0, pad = input_tensor_93_pad_0, pad_type = input_tensor_93_pad_type_0, strides = input_tensor_93_strides_0, weight = decoder_convnext_4_dwconv_net_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("input_tensor_93_cast_fp16")];
            tensor<int32, [3]> var_574 = const()[name = string("op_574"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_95_axes_0 = const()[name = string("input_tensor_95_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17022528)))];
            tensor<fp16, [512]> decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17023616)))];
            fp16 var_577_to_fp16 = const()[name = string("op_577_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 512]> input_49_cast_fp16 = transpose(perm = var_574, x = input_tensor_93_cast_fp16)[name = string("transpose_12")];
            tensor<fp16, [1, 192, 512]> input_tensor_95_cast_fp16 = layer_norm(axes = input_tensor_95_axes_0, beta = decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_577_to_fp16, gamma = decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16, x = input_49_cast_fp16)[name = string("input_tensor_95_cast_fp16")];
            tensor<int32, [3]> var_586 = const()[name = string("op_586"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_37_pad_type_0 = const()[name = string("first_37_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_37_strides_0 = const()[name = string("first_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_37_pad_0 = const()[name = string("first_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_37_dilations_0 = const()[name = string("first_37_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_37_groups_0 = const()[name = string("first_37_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_4_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_4_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17024704)))];
            tensor<fp16, [2048]> decoder_convnext_4_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_4_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19121920)))];
            tensor<fp16, [1, 512, 192]> input_51_cast_fp16 = transpose(perm = var_586, x = input_tensor_95_cast_fp16)[name = string("transpose_11")];
            tensor<fp16, [1, 2048, 192]> first_37_cast_fp16 = conv(bias = decoder_convnext_4_pwconv1_Conv_bias_to_fp16, dilations = first_37_dilations_0, groups = first_37_groups_0, pad = first_37_pad_0, pad_type = first_37_pad_type_0, strides = first_37_strides_0, weight = decoder_convnext_4_pwconv1_Conv_weight_to_fp16, x = input_51_cast_fp16)[name = string("first_37_cast_fp16")];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 192]> input_53_cast_fp16 = gelu(mode = input_53_mode_0, x = first_37_cast_fp16)[name = string("input_53_cast_fp16")];
            string second_63_pad_type_0 = const()[name = string("second_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_63_strides_0 = const()[name = string("second_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_63_pad_0 = const()[name = string("second_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_63_dilations_0 = const()[name = string("second_63_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_63_groups_0 = const()[name = string("second_63_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_65_weight_0_to_fp16 = const()[name = string("second_65_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19126080)))];
            tensor<fp16, [512]> second_65_bias_0_to_fp16 = const()[name = string("second_65_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21223296)))];
            tensor<fp16, [1, 512, 192]> second_65_cast_fp16 = conv(bias = second_65_bias_0_to_fp16, dilations = second_63_dilations_0, groups = second_63_groups_0, pad = second_63_pad_0, pad_type = second_63_pad_type_0, strides = second_63_strides_0, weight = second_65_weight_0_to_fp16, x = input_53_cast_fp16)[name = string("second_65_cast_fp16")];
            tensor<fp16, [1, 512, 192]> input_55_cast_fp16 = add(x = input_45_cast_fp16, y = second_65_cast_fp16)[name = string("input_55_cast_fp16")];
            tensor<int32, [6]> input_57_pad_0 = const()[name = string("input_57_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 24, 0])];
            string input_57_mode_0 = const()[name = string("input_57_mode_0"), val = string("replicate")];
            fp16 const_13_to_fp16 = const()[name = string("const_13_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 216]> input_57_cast_fp16 = pad(constant_val = const_13_to_fp16, mode = input_57_mode_0, pad = input_57_pad_0, x = input_55_cast_fp16)[name = string("input_57_cast_fp16")];
            string input_tensor_107_pad_type_0 = const()[name = string("input_tensor_107_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_107_dilations_0 = const()[name = string("input_tensor_107_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 input_tensor_107_groups_0 = const()[name = string("input_tensor_107_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_107_strides_0 = const()[name = string("input_tensor_107_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_107_pad_0 = const()[name = string("input_tensor_107_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_5_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_5_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21224384)))];
            tensor<fp16, [512]> decoder_convnext_5_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_5_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21231616)))];
            tensor<fp16, [1, 512, 192]> input_tensor_107_cast_fp16 = conv(bias = decoder_convnext_5_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_107_dilations_0, groups = input_tensor_107_groups_0, pad = input_tensor_107_pad_0, pad_type = input_tensor_107_pad_type_0, strides = input_tensor_107_strides_0, weight = decoder_convnext_5_dwconv_net_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = string("input_tensor_107_cast_fp16")];
            tensor<int32, [3]> var_641 = const()[name = string("op_641"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_109_axes_0 = const()[name = string("input_tensor_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21232704)))];
            tensor<fp16, [512]> decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21233792)))];
            fp16 var_644_to_fp16 = const()[name = string("op_644_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 512]> input_59_cast_fp16 = transpose(perm = var_641, x = input_tensor_107_cast_fp16)[name = string("transpose_10")];
            tensor<fp16, [1, 192, 512]> input_tensor_109_cast_fp16 = layer_norm(axes = input_tensor_109_axes_0, beta = decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_644_to_fp16, gamma = decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16, x = input_59_cast_fp16)[name = string("input_tensor_109_cast_fp16")];
            tensor<int32, [3]> var_653 = const()[name = string("op_653"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_45_pad_type_0 = const()[name = string("first_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_45_strides_0 = const()[name = string("first_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_45_pad_0 = const()[name = string("first_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_45_dilations_0 = const()[name = string("first_45_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_45_groups_0 = const()[name = string("first_45_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_5_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_5_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21234880)))];
            tensor<fp16, [2048]> decoder_convnext_5_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_5_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23332096)))];
            tensor<fp16, [1, 512, 192]> input_61_cast_fp16 = transpose(perm = var_653, x = input_tensor_109_cast_fp16)[name = string("transpose_9")];
            tensor<fp16, [1, 2048, 192]> first_45_cast_fp16 = conv(bias = decoder_convnext_5_pwconv1_Conv_bias_to_fp16, dilations = first_45_dilations_0, groups = first_45_groups_0, pad = first_45_pad_0, pad_type = first_45_pad_type_0, strides = first_45_strides_0, weight = decoder_convnext_5_pwconv1_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("first_45_cast_fp16")];
            string input_63_mode_0 = const()[name = string("input_63_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 192]> input_63_cast_fp16 = gelu(mode = input_63_mode_0, x = first_45_cast_fp16)[name = string("input_63_cast_fp16")];
            string second_75_pad_type_0 = const()[name = string("second_75_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_75_strides_0 = const()[name = string("second_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_75_pad_0 = const()[name = string("second_75_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_75_dilations_0 = const()[name = string("second_75_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_75_groups_0 = const()[name = string("second_75_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_77_weight_0_to_fp16 = const()[name = string("second_77_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23336256)))];
            tensor<fp16, [512]> second_77_bias_0_to_fp16 = const()[name = string("second_77_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25433472)))];
            tensor<fp16, [1, 512, 192]> second_77_cast_fp16 = conv(bias = second_77_bias_0_to_fp16, dilations = second_75_dilations_0, groups = second_75_groups_0, pad = second_75_pad_0, pad_type = second_75_pad_type_0, strides = second_75_strides_0, weight = second_77_weight_0_to_fp16, x = input_63_cast_fp16)[name = string("second_77_cast_fp16")];
            tensor<fp16, [1, 512, 192]> input_65_cast_fp16 = add(x = input_55_cast_fp16, y = second_77_cast_fp16)[name = string("input_65_cast_fp16")];
            tensor<int32, [6]> input_67_pad_0 = const()[name = string("input_67_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_67_mode_0 = const()[name = string("input_67_mode_0"), val = string("replicate")];
            fp16 const_14_to_fp16 = const()[name = string("const_14_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 198]> input_67_cast_fp16 = pad(constant_val = const_14_to_fp16, mode = input_67_mode_0, pad = input_67_pad_0, x = input_65_cast_fp16)[name = string("input_67_cast_fp16")];
            string input_tensor_121_pad_type_0 = const()[name = string("input_tensor_121_pad_type_0"), val = string("valid")];
            int32 input_tensor_121_groups_0 = const()[name = string("input_tensor_121_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_121_strides_0 = const()[name = string("input_tensor_121_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_121_pad_0 = const()[name = string("input_tensor_121_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_121_dilations_0 = const()[name = string("input_tensor_121_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_6_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_6_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25434560)))];
            tensor<fp16, [512]> decoder_convnext_6_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_6_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25441792)))];
            tensor<fp16, [1, 512, 192]> input_tensor_121_cast_fp16 = conv(bias = decoder_convnext_6_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_121_dilations_0, groups = input_tensor_121_groups_0, pad = input_tensor_121_pad_0, pad_type = input_tensor_121_pad_type_0, strides = input_tensor_121_strides_0, weight = decoder_convnext_6_dwconv_net_Conv_weight_to_fp16, x = input_67_cast_fp16)[name = string("input_tensor_121_cast_fp16")];
            tensor<int32, [3]> var_707 = const()[name = string("op_707"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_123_axes_0 = const()[name = string("input_tensor_123_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25442880)))];
            tensor<fp16, [512]> decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25443968)))];
            fp16 var_710_to_fp16 = const()[name = string("op_710_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 512]> input_69_cast_fp16 = transpose(perm = var_707, x = input_tensor_121_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 192, 512]> input_tensor_123_cast_fp16 = layer_norm(axes = input_tensor_123_axes_0, beta = decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_710_to_fp16, gamma = decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16, x = input_69_cast_fp16)[name = string("input_tensor_123_cast_fp16")];
            tensor<int32, [3]> var_719 = const()[name = string("op_719"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_53_pad_type_0 = const()[name = string("first_53_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_53_strides_0 = const()[name = string("first_53_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_53_pad_0 = const()[name = string("first_53_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_53_dilations_0 = const()[name = string("first_53_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_53_groups_0 = const()[name = string("first_53_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_6_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_6_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25445056)))];
            tensor<fp16, [2048]> decoder_convnext_6_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_6_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27542272)))];
            tensor<fp16, [1, 512, 192]> input_71_cast_fp16 = transpose(perm = var_719, x = input_tensor_123_cast_fp16)[name = string("transpose_7")];
            tensor<fp16, [1, 2048, 192]> first_53_cast_fp16 = conv(bias = decoder_convnext_6_pwconv1_Conv_bias_to_fp16, dilations = first_53_dilations_0, groups = first_53_groups_0, pad = first_53_pad_0, pad_type = first_53_pad_type_0, strides = first_53_strides_0, weight = decoder_convnext_6_pwconv1_Conv_weight_to_fp16, x = input_71_cast_fp16)[name = string("first_53_cast_fp16")];
            string input_73_mode_0 = const()[name = string("input_73_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 192]> input_73_cast_fp16 = gelu(mode = input_73_mode_0, x = first_53_cast_fp16)[name = string("input_73_cast_fp16")];
            string second_87_pad_type_0 = const()[name = string("second_87_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_87_strides_0 = const()[name = string("second_87_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_87_pad_0 = const()[name = string("second_87_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_87_dilations_0 = const()[name = string("second_87_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_87_groups_0 = const()[name = string("second_87_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_89_weight_0_to_fp16 = const()[name = string("second_89_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27546432)))];
            tensor<fp16, [512]> second_89_bias_0_to_fp16 = const()[name = string("second_89_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29643648)))];
            tensor<fp16, [1, 512, 192]> second_89_cast_fp16 = conv(bias = second_89_bias_0_to_fp16, dilations = second_87_dilations_0, groups = second_87_groups_0, pad = second_87_pad_0, pad_type = second_87_pad_type_0, strides = second_87_strides_0, weight = second_89_weight_0_to_fp16, x = input_73_cast_fp16)[name = string("second_89_cast_fp16")];
            tensor<fp16, [1, 512, 192]> input_75_cast_fp16 = add(x = input_65_cast_fp16, y = second_89_cast_fp16)[name = string("input_75_cast_fp16")];
            tensor<int32, [6]> input_77_pad_0 = const()[name = string("input_77_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_77_mode_0 = const()[name = string("input_77_mode_0"), val = string("replicate")];
            fp16 const_15_to_fp16 = const()[name = string("const_15_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 198]> input_77_cast_fp16 = pad(constant_val = const_15_to_fp16, mode = input_77_mode_0, pad = input_77_pad_0, x = input_75_cast_fp16)[name = string("input_77_cast_fp16")];
            string input_tensor_135_pad_type_0 = const()[name = string("input_tensor_135_pad_type_0"), val = string("valid")];
            int32 input_tensor_135_groups_0 = const()[name = string("input_tensor_135_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_135_strides_0 = const()[name = string("input_tensor_135_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_135_pad_0 = const()[name = string("input_tensor_135_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_135_dilations_0 = const()[name = string("input_tensor_135_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_7_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_7_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29644736)))];
            tensor<fp16, [512]> decoder_convnext_7_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_7_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29651968)))];
            tensor<fp16, [1, 512, 192]> input_tensor_135_cast_fp16 = conv(bias = decoder_convnext_7_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_135_dilations_0, groups = input_tensor_135_groups_0, pad = input_tensor_135_pad_0, pad_type = input_tensor_135_pad_type_0, strides = input_tensor_135_strides_0, weight = decoder_convnext_7_dwconv_net_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = string("input_tensor_135_cast_fp16")];
            tensor<int32, [3]> var_773 = const()[name = string("op_773"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_137_axes_0 = const()[name = string("input_tensor_137_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29653056)))];
            tensor<fp16, [512]> decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29654144)))];
            fp16 var_776_to_fp16 = const()[name = string("op_776_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 512]> input_79_cast_fp16 = transpose(perm = var_773, x = input_tensor_135_cast_fp16)[name = string("transpose_6")];
            tensor<fp16, [1, 192, 512]> input_tensor_137_cast_fp16 = layer_norm(axes = input_tensor_137_axes_0, beta = decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_776_to_fp16, gamma = decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_tensor_137_cast_fp16")];
            tensor<int32, [3]> var_785 = const()[name = string("op_785"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_61_pad_type_0 = const()[name = string("first_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_61_strides_0 = const()[name = string("first_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_61_pad_0 = const()[name = string("first_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_61_dilations_0 = const()[name = string("first_61_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_61_groups_0 = const()[name = string("first_61_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_7_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_7_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29655232)))];
            tensor<fp16, [2048]> decoder_convnext_7_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_7_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31752448)))];
            tensor<fp16, [1, 512, 192]> input_81_cast_fp16 = transpose(perm = var_785, x = input_tensor_137_cast_fp16)[name = string("transpose_5")];
            tensor<fp16, [1, 2048, 192]> first_61_cast_fp16 = conv(bias = decoder_convnext_7_pwconv1_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = decoder_convnext_7_pwconv1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = string("first_61_cast_fp16")];
            string input_83_mode_0 = const()[name = string("input_83_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 192]> input_83_cast_fp16 = gelu(mode = input_83_mode_0, x = first_61_cast_fp16)[name = string("input_83_cast_fp16")];
            string second_99_pad_type_0 = const()[name = string("second_99_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_99_strides_0 = const()[name = string("second_99_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_99_pad_0 = const()[name = string("second_99_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_99_dilations_0 = const()[name = string("second_99_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_99_groups_0 = const()[name = string("second_99_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_101_weight_0_to_fp16 = const()[name = string("second_101_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31756608)))];
            tensor<fp16, [512]> second_101_bias_0_to_fp16 = const()[name = string("second_101_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33853824)))];
            tensor<fp16, [1, 512, 192]> second_101_cast_fp16 = conv(bias = second_101_bias_0_to_fp16, dilations = second_99_dilations_0, groups = second_99_groups_0, pad = second_99_pad_0, pad_type = second_99_pad_type_0, strides = second_99_strides_0, weight = second_101_weight_0_to_fp16, x = input_83_cast_fp16)[name = string("second_101_cast_fp16")];
            tensor<fp16, [1, 512, 192]> input_85_cast_fp16 = add(x = input_75_cast_fp16, y = second_101_cast_fp16)[name = string("input_85_cast_fp16")];
            tensor<int32, [6]> input_87_pad_0 = const()[name = string("input_87_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_87_mode_0 = const()[name = string("input_87_mode_0"), val = string("replicate")];
            fp16 const_16_to_fp16 = const()[name = string("const_16_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 198]> input_87_cast_fp16 = pad(constant_val = const_16_to_fp16, mode = input_87_mode_0, pad = input_87_pad_0, x = input_85_cast_fp16)[name = string("input_87_cast_fp16")];
            string input_tensor_149_pad_type_0 = const()[name = string("input_tensor_149_pad_type_0"), val = string("valid")];
            int32 input_tensor_149_groups_0 = const()[name = string("input_tensor_149_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_149_strides_0 = const()[name = string("input_tensor_149_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_149_pad_0 = const()[name = string("input_tensor_149_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_149_dilations_0 = const()[name = string("input_tensor_149_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_8_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_8_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33854912)))];
            tensor<fp16, [512]> decoder_convnext_8_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_8_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33862144)))];
            tensor<fp16, [1, 512, 192]> input_tensor_149_cast_fp16 = conv(bias = decoder_convnext_8_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_149_dilations_0, groups = input_tensor_149_groups_0, pad = input_tensor_149_pad_0, pad_type = input_tensor_149_pad_type_0, strides = input_tensor_149_strides_0, weight = decoder_convnext_8_dwconv_net_Conv_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_tensor_149_cast_fp16")];
            tensor<int32, [3]> var_839 = const()[name = string("op_839"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_151_axes_0 = const()[name = string("input_tensor_151_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33863232)))];
            tensor<fp16, [512]> decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33864320)))];
            fp16 var_842_to_fp16 = const()[name = string("op_842_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 512]> input_89_cast_fp16 = transpose(perm = var_839, x = input_tensor_149_cast_fp16)[name = string("transpose_4")];
            tensor<fp16, [1, 192, 512]> input_tensor_151_cast_fp16 = layer_norm(axes = input_tensor_151_axes_0, beta = decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_842_to_fp16, gamma = decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_151_cast_fp16")];
            tensor<int32, [3]> var_851 = const()[name = string("op_851"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_69_pad_type_0 = const()[name = string("first_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_69_strides_0 = const()[name = string("first_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_69_pad_0 = const()[name = string("first_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_69_dilations_0 = const()[name = string("first_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_69_groups_0 = const()[name = string("first_69_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_8_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_8_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33865408)))];
            tensor<fp16, [2048]> decoder_convnext_8_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_8_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35962624)))];
            tensor<fp16, [1, 512, 192]> input_91_cast_fp16 = transpose(perm = var_851, x = input_tensor_151_cast_fp16)[name = string("transpose_3")];
            tensor<fp16, [1, 2048, 192]> first_69_cast_fp16 = conv(bias = decoder_convnext_8_pwconv1_Conv_bias_to_fp16, dilations = first_69_dilations_0, groups = first_69_groups_0, pad = first_69_pad_0, pad_type = first_69_pad_type_0, strides = first_69_strides_0, weight = decoder_convnext_8_pwconv1_Conv_weight_to_fp16, x = input_91_cast_fp16)[name = string("first_69_cast_fp16")];
            string input_93_mode_0 = const()[name = string("input_93_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 192]> input_93_cast_fp16 = gelu(mode = input_93_mode_0, x = first_69_cast_fp16)[name = string("input_93_cast_fp16")];
            string second_111_pad_type_0 = const()[name = string("second_111_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_111_strides_0 = const()[name = string("second_111_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_111_pad_0 = const()[name = string("second_111_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_111_dilations_0 = const()[name = string("second_111_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_111_groups_0 = const()[name = string("second_111_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_113_weight_0_to_fp16 = const()[name = string("second_113_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35966784)))];
            tensor<fp16, [512]> second_113_bias_0_to_fp16 = const()[name = string("second_113_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38064000)))];
            tensor<fp16, [1, 512, 192]> second_113_cast_fp16 = conv(bias = second_113_bias_0_to_fp16, dilations = second_111_dilations_0, groups = second_111_groups_0, pad = second_111_pad_0, pad_type = second_111_pad_type_0, strides = second_111_strides_0, weight = second_113_weight_0_to_fp16, x = input_93_cast_fp16)[name = string("second_113_cast_fp16")];
            tensor<fp16, [1, 512, 192]> input_95_cast_fp16 = add(x = input_85_cast_fp16, y = second_113_cast_fp16)[name = string("input_95_cast_fp16")];
            tensor<int32, [6]> input_97_pad_0 = const()[name = string("input_97_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_97_mode_0 = const()[name = string("input_97_mode_0"), val = string("replicate")];
            fp16 const_17_to_fp16 = const()[name = string("const_17_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 198]> input_97_cast_fp16 = pad(constant_val = const_17_to_fp16, mode = input_97_mode_0, pad = input_97_pad_0, x = input_95_cast_fp16)[name = string("input_97_cast_fp16")];
            string input_tensor_163_pad_type_0 = const()[name = string("input_tensor_163_pad_type_0"), val = string("valid")];
            int32 input_tensor_163_groups_0 = const()[name = string("input_tensor_163_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_163_strides_0 = const()[name = string("input_tensor_163_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_163_pad_0 = const()[name = string("input_tensor_163_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_163_dilations_0 = const()[name = string("input_tensor_163_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_9_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_9_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38065088)))];
            tensor<fp16, [512]> decoder_convnext_9_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_9_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38072320)))];
            tensor<fp16, [1, 512, 192]> input_tensor_163_cast_fp16 = conv(bias = decoder_convnext_9_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_163_dilations_0, groups = input_tensor_163_groups_0, pad = input_tensor_163_pad_0, pad_type = input_tensor_163_pad_type_0, strides = input_tensor_163_strides_0, weight = decoder_convnext_9_dwconv_net_Conv_weight_to_fp16, x = input_97_cast_fp16)[name = string("input_tensor_163_cast_fp16")];
            tensor<int32, [3]> var_905 = const()[name = string("op_905"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_165_axes_0 = const()[name = string("input_tensor_165_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38073408)))];
            tensor<fp16, [512]> decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38074496)))];
            fp16 var_908_to_fp16 = const()[name = string("op_908_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 512]> input_99_cast_fp16 = transpose(perm = var_905, x = input_tensor_163_cast_fp16)[name = string("transpose_2")];
            tensor<fp16, [1, 192, 512]> input_tensor_165_cast_fp16 = layer_norm(axes = input_tensor_165_axes_0, beta = decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_908_to_fp16, gamma = decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16, x = input_99_cast_fp16)[name = string("input_tensor_165_cast_fp16")];
            tensor<int32, [3]> var_917 = const()[name = string("op_917"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_77_pad_type_0 = const()[name = string("first_77_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_77_strides_0 = const()[name = string("first_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_77_pad_0 = const()[name = string("first_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_77_dilations_0 = const()[name = string("first_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_77_groups_0 = const()[name = string("first_77_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_9_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_9_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38075584)))];
            tensor<fp16, [2048]> decoder_convnext_9_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_9_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40172800)))];
            tensor<fp16, [1, 512, 192]> input_101_cast_fp16 = transpose(perm = var_917, x = input_tensor_165_cast_fp16)[name = string("transpose_1")];
            tensor<fp16, [1, 2048, 192]> first_77_cast_fp16 = conv(bias = decoder_convnext_9_pwconv1_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = decoder_convnext_9_pwconv1_Conv_weight_to_fp16, x = input_101_cast_fp16)[name = string("first_77_cast_fp16")];
            string input_103_mode_0 = const()[name = string("input_103_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 192]> input_103_cast_fp16 = gelu(mode = input_103_mode_0, x = first_77_cast_fp16)[name = string("input_103_cast_fp16")];
            string second_123_pad_type_0 = const()[name = string("second_123_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_123_strides_0 = const()[name = string("second_123_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_123_pad_0 = const()[name = string("second_123_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_123_dilations_0 = const()[name = string("second_123_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_123_groups_0 = const()[name = string("second_123_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_weight_0_to_fp16 = const()[name = string("second_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40176960)))];
            tensor<fp16, [512]> second_bias_0_to_fp16 = const()[name = string("second_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42274176)))];
            tensor<fp16, [1, 512, 192]> second_cast_fp16 = conv(bias = second_bias_0_to_fp16, dilations = second_123_dilations_0, groups = second_123_groups_0, pad = second_123_pad_0, pad_type = second_123_pad_type_0, strides = second_123_strides_0, weight = second_weight_0_to_fp16, x = input_103_cast_fp16)[name = string("second_cast_fp16")];
            tensor<fp16, [1, 512, 192]> input_105_cast_fp16 = add(x = input_95_cast_fp16, y = second_cast_fp16)[name = string("input_105_cast_fp16")];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_running_mean_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42275264)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_running_var_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42276352)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_weight_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42277440)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_bias_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42278528)))];
            fp16 var_951_to_fp16 = const()[name = string("op_951_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 512, 192]> input_107_cast_fp16 = batch_norm(beta = decoder_final_norm_BatchNormalization_bias_to_fp16, epsilon = var_951_to_fp16, gamma = decoder_final_norm_BatchNormalization_weight_to_fp16, mean = decoder_final_norm_BatchNormalization_running_mean_to_fp16, variance = decoder_final_norm_BatchNormalization_running_var_to_fp16, x = input_105_cast_fp16)[name = string("input_107_cast_fp16")];
            tensor<int32, [6]> input_109_pad_0 = const()[name = string("input_109_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 0])];
            string input_109_mode_0 = const()[name = string("input_109_mode_0"), val = string("replicate")];
            fp16 const_18_to_fp16 = const()[name = string("const_18_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 194]> input_109_cast_fp16 = pad(constant_val = const_18_to_fp16, mode = input_109_mode_0, pad = input_109_pad_0, x = input_107_cast_fp16)[name = string("input_109_cast_fp16")];
            string input_tensor_177_pad_type_0 = const()[name = string("input_tensor_177_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_177_strides_0 = const()[name = string("input_tensor_177_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_177_pad_0 = const()[name = string("input_tensor_177_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_177_dilations_0 = const()[name = string("input_tensor_177_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_177_groups_0 = const()[name = string("input_tensor_177_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 3]> decoder_head_layer1_net_Conv_weight_to_fp16 = const()[name = string("decoder_head_layer1_net_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42279616)))];
            tensor<fp16, [2048]> decoder_head_layer1_net_Conv_bias_to_fp16 = const()[name = string("decoder_head_layer1_net_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48571136)))];
            tensor<fp16, [1, 2048, 192]> input_tensor_177_cast_fp16 = conv(bias = decoder_head_layer1_net_Conv_bias_to_fp16, dilations = input_tensor_177_dilations_0, groups = input_tensor_177_groups_0, pad = input_tensor_177_pad_0, pad_type = input_tensor_177_pad_type_0, strides = input_tensor_177_strides_0, weight = decoder_head_layer1_net_Conv_weight_to_fp16, x = input_109_cast_fp16)[name = string("input_tensor_177_cast_fp16")];
            fp32 input_alpha_1 = const()[name = string("input_alpha_1"), val = fp32(0x1.9814fap-13)];
            tensor<fp16, [1, 2048, 192]> input_cast_fp16 = leaky_relu(alpha = input_alpha_1, x = input_tensor_177_cast_fp16)[name = string("input_cast_fp16")];
            string input_tensor_179_pad_type_0 = const()[name = string("input_tensor_179_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_179_strides_0 = const()[name = string("input_tensor_179_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_179_pad_0 = const()[name = string("input_tensor_179_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_179_dilations_0 = const()[name = string("input_tensor_179_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_179_groups_0 = const()[name = string("input_tensor_179_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> decoder_head_layer2_Conv_weight_to_fp16 = const()[name = string("decoder_head_layer2_Conv_weight_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48575296)))];
            tensor<fp16, [1, 512, 192]> input_tensor_179_cast_fp16 = conv(dilations = input_tensor_179_dilations_0, groups = input_tensor_179_groups_0, pad = input_tensor_179_pad_0, pad_type = input_tensor_179_pad_type_0, strides = input_tensor_179_strides_0, weight = decoder_head_layer2_Conv_weight_to_fp16, x = input_cast_fp16)[name = string("input_tensor_179_cast_fp16")];
            tensor<int32, [3]> var_994 = const()[name = string("op_994"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [2]> var_1021 = const()[name = string("op_1021"), val = tensor<int32, [2]>([1, -1])];
            tensor<fp16, [1, 192, 512]> input_tensor_181_cast_fp16 = transpose(perm = var_994, x = input_tensor_179_cast_fp16)[name = string("transpose_0")];
            tensor<fp16, [1, 98304]> wav_tts = reshape(shape = var_1021, x = input_tensor_181_cast_fp16)[name = string("op_1022_cast_fp16")];
        } -> (wav_tts);
    func vocoder_l384<ios18>(tensor<fp16, [1, 144, 384]> latent) {
            fp16 _inversed_input_tensor_1_y_0_to_fp16 = const()[name = string("_inversed_input_tensor_1_y_0_to_fp16"), val = fp16(0x1p+2)];
            tensor<fp16, [1, 144, 384]> _inversed_input_tensor_1_cast_fp16 = mul(x = latent, y = _inversed_input_tensor_1_y_0_to_fp16)[name = string("_inversed_input_tensor_1_cast_fp16")];
            tensor<int32, [4]> var_213 = const()[name = string("op_213"), val = tensor<int32, [4]>([1, -1, 6, 384])];
            tensor<fp16, [1, 24, 6, 384]> input_tensor_9_cast_fp16 = reshape(shape = var_213, x = _inversed_input_tensor_1_cast_fp16)[name = string("input_tensor_9_cast_fp16")];
            tensor<int32, [4]> var_219 = const()[name = string("op_219"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_264 = const()[name = string("op_264"), val = tensor<int32, [3]>([1, 24, -1])];
            tensor<fp16, [1, 24, 384, 6]> input_tensor_11_cast_fp16 = transpose(perm = var_219, x = input_tensor_9_cast_fp16)[name = string("transpose_21")];
            tensor<fp16, [1, 24, 2304]> first_1_cast_fp16 = reshape(shape = var_264, x = input_tensor_11_cast_fp16)[name = string("first_1_cast_fp16")];
            tensor<fp16, [1, 24, 1]> initializers_onnx_initializer_1_to_fp16 = const()[name = string("initializers_onnx_initializer_1_to_fp16"), val = tensor<fp16, [1, 24, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [1, 24, 2304]> first_3_cast_fp16 = mul(x = first_1_cast_fp16, y = initializers_onnx_initializer_1_to_fp16)[name = string("first_3_cast_fp16")];
            tensor<fp16, [1, 24, 1]> initializers_onnx_initializer_2_to_fp16 = const()[name = string("initializers_onnx_initializer_2_to_fp16"), val = tensor<fp16, [1, 24, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192)))];
            tensor<fp16, [1, 24, 2304]> input_1_cast_fp16 = add(x = first_3_cast_fp16, y = initializers_onnx_initializer_2_to_fp16)[name = string("input_1_cast_fp16")];
            tensor<int32, [6]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("replicate")];
            fp16 const_7_to_fp16 = const()[name = string("const_7_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 24, 2310]> input_3_cast_fp16 = pad(constant_val = const_7_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string input_5_pad_type_0 = const()[name = string("input_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_5_strides_0 = const()[name = string("input_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_5_pad_0 = const()[name = string("input_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_5_dilations_0 = const()[name = string("input_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_5_groups_0 = const()[name = string("input_5_groups_0"), val = int32(1)];
            tensor<fp16, [512, 24, 7]> decoder_embed_net_Conv_weight_to_fp16 = const()[name = string("decoder_embed_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 24, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(320)))];
            tensor<fp16, [512]> decoder_embed_net_Conv_bias_to_fp16 = const()[name = string("decoder_embed_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(172416)))];
            tensor<fp16, [1, 512, 2304]> input_5_cast_fp16 = conv(bias = decoder_embed_net_Conv_bias_to_fp16, dilations = input_5_dilations_0, groups = input_5_groups_0, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = input_5_strides_0, weight = decoder_embed_net_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = string("input_5_cast_fp16")];
            tensor<int32, [6]> input_7_pad_0 = const()[name = string("input_7_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_7_mode_0 = const()[name = string("input_7_mode_0"), val = string("replicate")];
            fp16 const_8_to_fp16 = const()[name = string("const_8_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 2310]> input_7_cast_fp16 = pad(constant_val = const_8_to_fp16, mode = input_7_mode_0, pad = input_7_pad_0, x = input_5_cast_fp16)[name = string("input_7_cast_fp16")];
            string input_tensor_37_pad_type_0 = const()[name = string("input_tensor_37_pad_type_0"), val = string("valid")];
            int32 input_tensor_37_groups_0 = const()[name = string("input_tensor_37_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_37_strides_0 = const()[name = string("input_tensor_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_37_pad_0 = const()[name = string("input_tensor_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_37_dilations_0 = const()[name = string("input_tensor_37_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_0_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_0_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(173504)))];
            tensor<fp16, [512]> decoder_convnext_0_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_0_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(180736)))];
            tensor<fp16, [1, 512, 2304]> input_tensor_37_cast_fp16 = conv(bias = decoder_convnext_0_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_37_dilations_0, groups = input_tensor_37_groups_0, pad = input_tensor_37_pad_0, pad_type = input_tensor_37_pad_type_0, strides = input_tensor_37_strides_0, weight = decoder_convnext_0_dwconv_net_Conv_weight_to_fp16, x = input_7_cast_fp16)[name = string("input_tensor_37_cast_fp16")];
            tensor<int32, [3]> var_307 = const()[name = string("op_307"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_39_axes_0 = const()[name = string("input_tensor_39_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(181824)))];
            tensor<fp16, [512]> decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(182912)))];
            fp16 var_310_to_fp16 = const()[name = string("op_310_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 2304, 512]> input_9_cast_fp16 = transpose(perm = var_307, x = input_tensor_37_cast_fp16)[name = string("transpose_20")];
            tensor<fp16, [1, 2304, 512]> input_tensor_39_cast_fp16 = layer_norm(axes = input_tensor_39_axes_0, beta = decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_310_to_fp16, gamma = decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16, x = input_9_cast_fp16)[name = string("input_tensor_39_cast_fp16")];
            tensor<int32, [3]> var_319 = const()[name = string("op_319"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_5_pad_type_0 = const()[name = string("first_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_5_strides_0 = const()[name = string("first_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_5_pad_0 = const()[name = string("first_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_5_dilations_0 = const()[name = string("first_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_5_groups_0 = const()[name = string("first_5_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_0_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_0_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(184000)))];
            tensor<fp16, [2048]> decoder_convnext_0_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_0_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2281216)))];
            tensor<fp16, [1, 512, 2304]> input_11_cast_fp16 = transpose(perm = var_319, x = input_tensor_39_cast_fp16)[name = string("transpose_19")];
            tensor<fp16, [1, 2048, 2304]> first_5_cast_fp16 = conv(bias = decoder_convnext_0_pwconv1_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = decoder_convnext_0_pwconv1_Conv_weight_to_fp16, x = input_11_cast_fp16)[name = string("first_5_cast_fp16")];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 2304]> input_13_cast_fp16 = gelu(mode = input_13_mode_0, x = first_5_cast_fp16)[name = string("input_13_cast_fp16")];
            string second_15_pad_type_0 = const()[name = string("second_15_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_15_strides_0 = const()[name = string("second_15_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_15_pad_0 = const()[name = string("second_15_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_15_dilations_0 = const()[name = string("second_15_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_15_groups_0 = const()[name = string("second_15_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_17_weight_0_to_fp16 = const()[name = string("second_17_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2285376)))];
            tensor<fp16, [512]> second_17_bias_0_to_fp16 = const()[name = string("second_17_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4382592)))];
            tensor<fp16, [1, 512, 2304]> second_17_cast_fp16 = conv(bias = second_17_bias_0_to_fp16, dilations = second_15_dilations_0, groups = second_15_groups_0, pad = second_15_pad_0, pad_type = second_15_pad_type_0, strides = second_15_strides_0, weight = second_17_weight_0_to_fp16, x = input_13_cast_fp16)[name = string("second_17_cast_fp16")];
            tensor<fp16, [1, 512, 2304]> input_15_cast_fp16 = add(x = input_5_cast_fp16, y = second_17_cast_fp16)[name = string("input_15_cast_fp16")];
            tensor<int32, [6]> input_17_pad_0 = const()[name = string("input_17_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 12, 0])];
            string input_17_mode_0 = const()[name = string("input_17_mode_0"), val = string("replicate")];
            fp16 const_9_to_fp16 = const()[name = string("const_9_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 2316]> input_17_cast_fp16 = pad(constant_val = const_9_to_fp16, mode = input_17_mode_0, pad = input_17_pad_0, x = input_15_cast_fp16)[name = string("input_17_cast_fp16")];
            string input_tensor_51_pad_type_0 = const()[name = string("input_tensor_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_51_dilations_0 = const()[name = string("input_tensor_51_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 input_tensor_51_groups_0 = const()[name = string("input_tensor_51_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_51_strides_0 = const()[name = string("input_tensor_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_51_pad_0 = const()[name = string("input_tensor_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_1_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_1_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4383680)))];
            tensor<fp16, [512]> decoder_convnext_1_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_1_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4390912)))];
            tensor<fp16, [1, 512, 2304]> input_tensor_51_cast_fp16 = conv(bias = decoder_convnext_1_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_51_dilations_0, groups = input_tensor_51_groups_0, pad = input_tensor_51_pad_0, pad_type = input_tensor_51_pad_type_0, strides = input_tensor_51_strides_0, weight = decoder_convnext_1_dwconv_net_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = string("input_tensor_51_cast_fp16")];
            tensor<int32, [3]> var_374 = const()[name = string("op_374"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_53_axes_0 = const()[name = string("input_tensor_53_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4392000)))];
            tensor<fp16, [512]> decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4393088)))];
            fp16 var_377_to_fp16 = const()[name = string("op_377_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 2304, 512]> input_19_cast_fp16 = transpose(perm = var_374, x = input_tensor_51_cast_fp16)[name = string("transpose_18")];
            tensor<fp16, [1, 2304, 512]> input_tensor_53_cast_fp16 = layer_norm(axes = input_tensor_53_axes_0, beta = decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_377_to_fp16, gamma = decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16, x = input_19_cast_fp16)[name = string("input_tensor_53_cast_fp16")];
            tensor<int32, [3]> var_386 = const()[name = string("op_386"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_13_pad_type_0 = const()[name = string("first_13_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_13_strides_0 = const()[name = string("first_13_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_13_pad_0 = const()[name = string("first_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_13_dilations_0 = const()[name = string("first_13_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_13_groups_0 = const()[name = string("first_13_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_1_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_1_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4394176)))];
            tensor<fp16, [2048]> decoder_convnext_1_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_1_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6491392)))];
            tensor<fp16, [1, 512, 2304]> input_21_cast_fp16 = transpose(perm = var_386, x = input_tensor_53_cast_fp16)[name = string("transpose_17")];
            tensor<fp16, [1, 2048, 2304]> first_13_cast_fp16 = conv(bias = decoder_convnext_1_pwconv1_Conv_bias_to_fp16, dilations = first_13_dilations_0, groups = first_13_groups_0, pad = first_13_pad_0, pad_type = first_13_pad_type_0, strides = first_13_strides_0, weight = decoder_convnext_1_pwconv1_Conv_weight_to_fp16, x = input_21_cast_fp16)[name = string("first_13_cast_fp16")];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 2304]> input_23_cast_fp16 = gelu(mode = input_23_mode_0, x = first_13_cast_fp16)[name = string("input_23_cast_fp16")];
            string second_27_pad_type_0 = const()[name = string("second_27_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_27_strides_0 = const()[name = string("second_27_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_27_pad_0 = const()[name = string("second_27_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_27_dilations_0 = const()[name = string("second_27_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_27_groups_0 = const()[name = string("second_27_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_29_weight_0_to_fp16 = const()[name = string("second_29_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6495552)))];
            tensor<fp16, [512]> second_29_bias_0_to_fp16 = const()[name = string("second_29_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8592768)))];
            tensor<fp16, [1, 512, 2304]> second_29_cast_fp16 = conv(bias = second_29_bias_0_to_fp16, dilations = second_27_dilations_0, groups = second_27_groups_0, pad = second_27_pad_0, pad_type = second_27_pad_type_0, strides = second_27_strides_0, weight = second_29_weight_0_to_fp16, x = input_23_cast_fp16)[name = string("second_29_cast_fp16")];
            tensor<fp16, [1, 512, 2304]> input_25_cast_fp16 = add(x = input_15_cast_fp16, y = second_29_cast_fp16)[name = string("input_25_cast_fp16")];
            tensor<int32, [6]> input_27_pad_0 = const()[name = string("input_27_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 24, 0])];
            string input_27_mode_0 = const()[name = string("input_27_mode_0"), val = string("replicate")];
            fp16 const_10_to_fp16 = const()[name = string("const_10_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 2328]> input_27_cast_fp16 = pad(constant_val = const_10_to_fp16, mode = input_27_mode_0, pad = input_27_pad_0, x = input_25_cast_fp16)[name = string("input_27_cast_fp16")];
            string input_tensor_65_pad_type_0 = const()[name = string("input_tensor_65_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_65_dilations_0 = const()[name = string("input_tensor_65_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 input_tensor_65_groups_0 = const()[name = string("input_tensor_65_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_65_strides_0 = const()[name = string("input_tensor_65_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_65_pad_0 = const()[name = string("input_tensor_65_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_2_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_2_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8593856)))];
            tensor<fp16, [512]> decoder_convnext_2_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_2_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8601088)))];
            tensor<fp16, [1, 512, 2304]> input_tensor_65_cast_fp16 = conv(bias = decoder_convnext_2_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_65_dilations_0, groups = input_tensor_65_groups_0, pad = input_tensor_65_pad_0, pad_type = input_tensor_65_pad_type_0, strides = input_tensor_65_strides_0, weight = decoder_convnext_2_dwconv_net_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = string("input_tensor_65_cast_fp16")];
            tensor<int32, [3]> var_441 = const()[name = string("op_441"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_67_axes_0 = const()[name = string("input_tensor_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8602176)))];
            tensor<fp16, [512]> decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8603264)))];
            fp16 var_444_to_fp16 = const()[name = string("op_444_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 2304, 512]> input_29_cast_fp16 = transpose(perm = var_441, x = input_tensor_65_cast_fp16)[name = string("transpose_16")];
            tensor<fp16, [1, 2304, 512]> input_tensor_67_cast_fp16 = layer_norm(axes = input_tensor_67_axes_0, beta = decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_444_to_fp16, gamma = decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16, x = input_29_cast_fp16)[name = string("input_tensor_67_cast_fp16")];
            tensor<int32, [3]> var_453 = const()[name = string("op_453"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_21_pad_type_0 = const()[name = string("first_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_21_strides_0 = const()[name = string("first_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_21_pad_0 = const()[name = string("first_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_21_dilations_0 = const()[name = string("first_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_21_groups_0 = const()[name = string("first_21_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_2_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_2_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8604352)))];
            tensor<fp16, [2048]> decoder_convnext_2_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_2_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10701568)))];
            tensor<fp16, [1, 512, 2304]> input_31_cast_fp16 = transpose(perm = var_453, x = input_tensor_67_cast_fp16)[name = string("transpose_15")];
            tensor<fp16, [1, 2048, 2304]> first_21_cast_fp16 = conv(bias = decoder_convnext_2_pwconv1_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = decoder_convnext_2_pwconv1_Conv_weight_to_fp16, x = input_31_cast_fp16)[name = string("first_21_cast_fp16")];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 2304]> input_33_cast_fp16 = gelu(mode = input_33_mode_0, x = first_21_cast_fp16)[name = string("input_33_cast_fp16")];
            string second_39_pad_type_0 = const()[name = string("second_39_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_39_strides_0 = const()[name = string("second_39_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_39_pad_0 = const()[name = string("second_39_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_39_dilations_0 = const()[name = string("second_39_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_39_groups_0 = const()[name = string("second_39_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_41_weight_0_to_fp16 = const()[name = string("second_41_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10705728)))];
            tensor<fp16, [512]> second_41_bias_0_to_fp16 = const()[name = string("second_41_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12802944)))];
            tensor<fp16, [1, 512, 2304]> second_41_cast_fp16 = conv(bias = second_41_bias_0_to_fp16, dilations = second_39_dilations_0, groups = second_39_groups_0, pad = second_39_pad_0, pad_type = second_39_pad_type_0, strides = second_39_strides_0, weight = second_41_weight_0_to_fp16, x = input_33_cast_fp16)[name = string("second_41_cast_fp16")];
            tensor<fp16, [1, 512, 2304]> input_35_cast_fp16 = add(x = input_25_cast_fp16, y = second_41_cast_fp16)[name = string("input_35_cast_fp16")];
            tensor<int32, [6]> input_37_pad_0 = const()[name = string("input_37_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_37_mode_0 = const()[name = string("input_37_mode_0"), val = string("replicate")];
            fp16 const_11_to_fp16 = const()[name = string("const_11_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 2310]> input_37_cast_fp16 = pad(constant_val = const_11_to_fp16, mode = input_37_mode_0, pad = input_37_pad_0, x = input_35_cast_fp16)[name = string("input_37_cast_fp16")];
            string input_tensor_79_pad_type_0 = const()[name = string("input_tensor_79_pad_type_0"), val = string("valid")];
            int32 input_tensor_79_groups_0 = const()[name = string("input_tensor_79_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_79_strides_0 = const()[name = string("input_tensor_79_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_79_pad_0 = const()[name = string("input_tensor_79_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_79_dilations_0 = const()[name = string("input_tensor_79_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_3_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_3_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12804032)))];
            tensor<fp16, [512]> decoder_convnext_3_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_3_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12811264)))];
            tensor<fp16, [1, 512, 2304]> input_tensor_79_cast_fp16 = conv(bias = decoder_convnext_3_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_79_dilations_0, groups = input_tensor_79_groups_0, pad = input_tensor_79_pad_0, pad_type = input_tensor_79_pad_type_0, strides = input_tensor_79_strides_0, weight = decoder_convnext_3_dwconv_net_Conv_weight_to_fp16, x = input_37_cast_fp16)[name = string("input_tensor_79_cast_fp16")];
            tensor<int32, [3]> var_507 = const()[name = string("op_507"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_81_axes_0 = const()[name = string("input_tensor_81_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12812352)))];
            tensor<fp16, [512]> decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12813440)))];
            fp16 var_510_to_fp16 = const()[name = string("op_510_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 2304, 512]> input_39_cast_fp16 = transpose(perm = var_507, x = input_tensor_79_cast_fp16)[name = string("transpose_14")];
            tensor<fp16, [1, 2304, 512]> input_tensor_81_cast_fp16 = layer_norm(axes = input_tensor_81_axes_0, beta = decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_510_to_fp16, gamma = decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16, x = input_39_cast_fp16)[name = string("input_tensor_81_cast_fp16")];
            tensor<int32, [3]> var_519 = const()[name = string("op_519"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_29_pad_type_0 = const()[name = string("first_29_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_29_strides_0 = const()[name = string("first_29_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_29_pad_0 = const()[name = string("first_29_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_29_dilations_0 = const()[name = string("first_29_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_29_groups_0 = const()[name = string("first_29_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_3_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_3_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12814528)))];
            tensor<fp16, [2048]> decoder_convnext_3_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_3_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14911744)))];
            tensor<fp16, [1, 512, 2304]> input_41_cast_fp16 = transpose(perm = var_519, x = input_tensor_81_cast_fp16)[name = string("transpose_13")];
            tensor<fp16, [1, 2048, 2304]> first_29_cast_fp16 = conv(bias = decoder_convnext_3_pwconv1_Conv_bias_to_fp16, dilations = first_29_dilations_0, groups = first_29_groups_0, pad = first_29_pad_0, pad_type = first_29_pad_type_0, strides = first_29_strides_0, weight = decoder_convnext_3_pwconv1_Conv_weight_to_fp16, x = input_41_cast_fp16)[name = string("first_29_cast_fp16")];
            string input_43_mode_0 = const()[name = string("input_43_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 2304]> input_43_cast_fp16 = gelu(mode = input_43_mode_0, x = first_29_cast_fp16)[name = string("input_43_cast_fp16")];
            string second_51_pad_type_0 = const()[name = string("second_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_51_strides_0 = const()[name = string("second_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_51_pad_0 = const()[name = string("second_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_51_dilations_0 = const()[name = string("second_51_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_51_groups_0 = const()[name = string("second_51_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_53_weight_0_to_fp16 = const()[name = string("second_53_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14915904)))];
            tensor<fp16, [512]> second_53_bias_0_to_fp16 = const()[name = string("second_53_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17013120)))];
            tensor<fp16, [1, 512, 2304]> second_53_cast_fp16 = conv(bias = second_53_bias_0_to_fp16, dilations = second_51_dilations_0, groups = second_51_groups_0, pad = second_51_pad_0, pad_type = second_51_pad_type_0, strides = second_51_strides_0, weight = second_53_weight_0_to_fp16, x = input_43_cast_fp16)[name = string("second_53_cast_fp16")];
            tensor<fp16, [1, 512, 2304]> input_45_cast_fp16 = add(x = input_35_cast_fp16, y = second_53_cast_fp16)[name = string("input_45_cast_fp16")];
            tensor<int32, [6]> input_47_pad_0 = const()[name = string("input_47_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 12, 0])];
            string input_47_mode_0 = const()[name = string("input_47_mode_0"), val = string("replicate")];
            fp16 const_12_to_fp16 = const()[name = string("const_12_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 2316]> input_47_cast_fp16 = pad(constant_val = const_12_to_fp16, mode = input_47_mode_0, pad = input_47_pad_0, x = input_45_cast_fp16)[name = string("input_47_cast_fp16")];
            string input_tensor_93_pad_type_0 = const()[name = string("input_tensor_93_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_93_dilations_0 = const()[name = string("input_tensor_93_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 input_tensor_93_groups_0 = const()[name = string("input_tensor_93_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_93_strides_0 = const()[name = string("input_tensor_93_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_93_pad_0 = const()[name = string("input_tensor_93_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_4_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_4_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17014208)))];
            tensor<fp16, [512]> decoder_convnext_4_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_4_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17021440)))];
            tensor<fp16, [1, 512, 2304]> input_tensor_93_cast_fp16 = conv(bias = decoder_convnext_4_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_93_dilations_0, groups = input_tensor_93_groups_0, pad = input_tensor_93_pad_0, pad_type = input_tensor_93_pad_type_0, strides = input_tensor_93_strides_0, weight = decoder_convnext_4_dwconv_net_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("input_tensor_93_cast_fp16")];
            tensor<int32, [3]> var_574 = const()[name = string("op_574"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_95_axes_0 = const()[name = string("input_tensor_95_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17022528)))];
            tensor<fp16, [512]> decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17023616)))];
            fp16 var_577_to_fp16 = const()[name = string("op_577_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 2304, 512]> input_49_cast_fp16 = transpose(perm = var_574, x = input_tensor_93_cast_fp16)[name = string("transpose_12")];
            tensor<fp16, [1, 2304, 512]> input_tensor_95_cast_fp16 = layer_norm(axes = input_tensor_95_axes_0, beta = decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_577_to_fp16, gamma = decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16, x = input_49_cast_fp16)[name = string("input_tensor_95_cast_fp16")];
            tensor<int32, [3]> var_586 = const()[name = string("op_586"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_37_pad_type_0 = const()[name = string("first_37_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_37_strides_0 = const()[name = string("first_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_37_pad_0 = const()[name = string("first_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_37_dilations_0 = const()[name = string("first_37_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_37_groups_0 = const()[name = string("first_37_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_4_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_4_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17024704)))];
            tensor<fp16, [2048]> decoder_convnext_4_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_4_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19121920)))];
            tensor<fp16, [1, 512, 2304]> input_51_cast_fp16 = transpose(perm = var_586, x = input_tensor_95_cast_fp16)[name = string("transpose_11")];
            tensor<fp16, [1, 2048, 2304]> first_37_cast_fp16 = conv(bias = decoder_convnext_4_pwconv1_Conv_bias_to_fp16, dilations = first_37_dilations_0, groups = first_37_groups_0, pad = first_37_pad_0, pad_type = first_37_pad_type_0, strides = first_37_strides_0, weight = decoder_convnext_4_pwconv1_Conv_weight_to_fp16, x = input_51_cast_fp16)[name = string("first_37_cast_fp16")];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 2304]> input_53_cast_fp16 = gelu(mode = input_53_mode_0, x = first_37_cast_fp16)[name = string("input_53_cast_fp16")];
            string second_63_pad_type_0 = const()[name = string("second_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_63_strides_0 = const()[name = string("second_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_63_pad_0 = const()[name = string("second_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_63_dilations_0 = const()[name = string("second_63_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_63_groups_0 = const()[name = string("second_63_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_65_weight_0_to_fp16 = const()[name = string("second_65_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19126080)))];
            tensor<fp16, [512]> second_65_bias_0_to_fp16 = const()[name = string("second_65_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21223296)))];
            tensor<fp16, [1, 512, 2304]> second_65_cast_fp16 = conv(bias = second_65_bias_0_to_fp16, dilations = second_63_dilations_0, groups = second_63_groups_0, pad = second_63_pad_0, pad_type = second_63_pad_type_0, strides = second_63_strides_0, weight = second_65_weight_0_to_fp16, x = input_53_cast_fp16)[name = string("second_65_cast_fp16")];
            tensor<fp16, [1, 512, 2304]> input_55_cast_fp16 = add(x = input_45_cast_fp16, y = second_65_cast_fp16)[name = string("input_55_cast_fp16")];
            tensor<int32, [6]> input_57_pad_0 = const()[name = string("input_57_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 24, 0])];
            string input_57_mode_0 = const()[name = string("input_57_mode_0"), val = string("replicate")];
            fp16 const_13_to_fp16 = const()[name = string("const_13_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 2328]> input_57_cast_fp16 = pad(constant_val = const_13_to_fp16, mode = input_57_mode_0, pad = input_57_pad_0, x = input_55_cast_fp16)[name = string("input_57_cast_fp16")];
            string input_tensor_107_pad_type_0 = const()[name = string("input_tensor_107_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_107_dilations_0 = const()[name = string("input_tensor_107_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 input_tensor_107_groups_0 = const()[name = string("input_tensor_107_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_107_strides_0 = const()[name = string("input_tensor_107_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_107_pad_0 = const()[name = string("input_tensor_107_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_5_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_5_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21224384)))];
            tensor<fp16, [512]> decoder_convnext_5_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_5_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21231616)))];
            tensor<fp16, [1, 512, 2304]> input_tensor_107_cast_fp16 = conv(bias = decoder_convnext_5_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_107_dilations_0, groups = input_tensor_107_groups_0, pad = input_tensor_107_pad_0, pad_type = input_tensor_107_pad_type_0, strides = input_tensor_107_strides_0, weight = decoder_convnext_5_dwconv_net_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = string("input_tensor_107_cast_fp16")];
            tensor<int32, [3]> var_641 = const()[name = string("op_641"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_109_axes_0 = const()[name = string("input_tensor_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21232704)))];
            tensor<fp16, [512]> decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21233792)))];
            fp16 var_644_to_fp16 = const()[name = string("op_644_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 2304, 512]> input_59_cast_fp16 = transpose(perm = var_641, x = input_tensor_107_cast_fp16)[name = string("transpose_10")];
            tensor<fp16, [1, 2304, 512]> input_tensor_109_cast_fp16 = layer_norm(axes = input_tensor_109_axes_0, beta = decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_644_to_fp16, gamma = decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16, x = input_59_cast_fp16)[name = string("input_tensor_109_cast_fp16")];
            tensor<int32, [3]> var_653 = const()[name = string("op_653"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_45_pad_type_0 = const()[name = string("first_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_45_strides_0 = const()[name = string("first_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_45_pad_0 = const()[name = string("first_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_45_dilations_0 = const()[name = string("first_45_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_45_groups_0 = const()[name = string("first_45_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_5_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_5_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21234880)))];
            tensor<fp16, [2048]> decoder_convnext_5_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_5_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23332096)))];
            tensor<fp16, [1, 512, 2304]> input_61_cast_fp16 = transpose(perm = var_653, x = input_tensor_109_cast_fp16)[name = string("transpose_9")];
            tensor<fp16, [1, 2048, 2304]> first_45_cast_fp16 = conv(bias = decoder_convnext_5_pwconv1_Conv_bias_to_fp16, dilations = first_45_dilations_0, groups = first_45_groups_0, pad = first_45_pad_0, pad_type = first_45_pad_type_0, strides = first_45_strides_0, weight = decoder_convnext_5_pwconv1_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("first_45_cast_fp16")];
            string input_63_mode_0 = const()[name = string("input_63_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 2304]> input_63_cast_fp16 = gelu(mode = input_63_mode_0, x = first_45_cast_fp16)[name = string("input_63_cast_fp16")];
            string second_75_pad_type_0 = const()[name = string("second_75_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_75_strides_0 = const()[name = string("second_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_75_pad_0 = const()[name = string("second_75_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_75_dilations_0 = const()[name = string("second_75_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_75_groups_0 = const()[name = string("second_75_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_77_weight_0_to_fp16 = const()[name = string("second_77_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23336256)))];
            tensor<fp16, [512]> second_77_bias_0_to_fp16 = const()[name = string("second_77_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25433472)))];
            tensor<fp16, [1, 512, 2304]> second_77_cast_fp16 = conv(bias = second_77_bias_0_to_fp16, dilations = second_75_dilations_0, groups = second_75_groups_0, pad = second_75_pad_0, pad_type = second_75_pad_type_0, strides = second_75_strides_0, weight = second_77_weight_0_to_fp16, x = input_63_cast_fp16)[name = string("second_77_cast_fp16")];
            tensor<fp16, [1, 512, 2304]> input_65_cast_fp16 = add(x = input_55_cast_fp16, y = second_77_cast_fp16)[name = string("input_65_cast_fp16")];
            tensor<int32, [6]> input_67_pad_0 = const()[name = string("input_67_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_67_mode_0 = const()[name = string("input_67_mode_0"), val = string("replicate")];
            fp16 const_14_to_fp16 = const()[name = string("const_14_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 2310]> input_67_cast_fp16 = pad(constant_val = const_14_to_fp16, mode = input_67_mode_0, pad = input_67_pad_0, x = input_65_cast_fp16)[name = string("input_67_cast_fp16")];
            string input_tensor_121_pad_type_0 = const()[name = string("input_tensor_121_pad_type_0"), val = string("valid")];
            int32 input_tensor_121_groups_0 = const()[name = string("input_tensor_121_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_121_strides_0 = const()[name = string("input_tensor_121_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_121_pad_0 = const()[name = string("input_tensor_121_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_121_dilations_0 = const()[name = string("input_tensor_121_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_6_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_6_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25434560)))];
            tensor<fp16, [512]> decoder_convnext_6_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_6_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25441792)))];
            tensor<fp16, [1, 512, 2304]> input_tensor_121_cast_fp16 = conv(bias = decoder_convnext_6_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_121_dilations_0, groups = input_tensor_121_groups_0, pad = input_tensor_121_pad_0, pad_type = input_tensor_121_pad_type_0, strides = input_tensor_121_strides_0, weight = decoder_convnext_6_dwconv_net_Conv_weight_to_fp16, x = input_67_cast_fp16)[name = string("input_tensor_121_cast_fp16")];
            tensor<int32, [3]> var_707 = const()[name = string("op_707"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_123_axes_0 = const()[name = string("input_tensor_123_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25442880)))];
            tensor<fp16, [512]> decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25443968)))];
            fp16 var_710_to_fp16 = const()[name = string("op_710_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 2304, 512]> input_69_cast_fp16 = transpose(perm = var_707, x = input_tensor_121_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 2304, 512]> input_tensor_123_cast_fp16 = layer_norm(axes = input_tensor_123_axes_0, beta = decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_710_to_fp16, gamma = decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16, x = input_69_cast_fp16)[name = string("input_tensor_123_cast_fp16")];
            tensor<int32, [3]> var_719 = const()[name = string("op_719"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_53_pad_type_0 = const()[name = string("first_53_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_53_strides_0 = const()[name = string("first_53_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_53_pad_0 = const()[name = string("first_53_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_53_dilations_0 = const()[name = string("first_53_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_53_groups_0 = const()[name = string("first_53_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_6_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_6_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25445056)))];
            tensor<fp16, [2048]> decoder_convnext_6_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_6_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27542272)))];
            tensor<fp16, [1, 512, 2304]> input_71_cast_fp16 = transpose(perm = var_719, x = input_tensor_123_cast_fp16)[name = string("transpose_7")];
            tensor<fp16, [1, 2048, 2304]> first_53_cast_fp16 = conv(bias = decoder_convnext_6_pwconv1_Conv_bias_to_fp16, dilations = first_53_dilations_0, groups = first_53_groups_0, pad = first_53_pad_0, pad_type = first_53_pad_type_0, strides = first_53_strides_0, weight = decoder_convnext_6_pwconv1_Conv_weight_to_fp16, x = input_71_cast_fp16)[name = string("first_53_cast_fp16")];
            string input_73_mode_0 = const()[name = string("input_73_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 2304]> input_73_cast_fp16 = gelu(mode = input_73_mode_0, x = first_53_cast_fp16)[name = string("input_73_cast_fp16")];
            string second_87_pad_type_0 = const()[name = string("second_87_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_87_strides_0 = const()[name = string("second_87_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_87_pad_0 = const()[name = string("second_87_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_87_dilations_0 = const()[name = string("second_87_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_87_groups_0 = const()[name = string("second_87_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_89_weight_0_to_fp16 = const()[name = string("second_89_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27546432)))];
            tensor<fp16, [512]> second_89_bias_0_to_fp16 = const()[name = string("second_89_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29643648)))];
            tensor<fp16, [1, 512, 2304]> second_89_cast_fp16 = conv(bias = second_89_bias_0_to_fp16, dilations = second_87_dilations_0, groups = second_87_groups_0, pad = second_87_pad_0, pad_type = second_87_pad_type_0, strides = second_87_strides_0, weight = second_89_weight_0_to_fp16, x = input_73_cast_fp16)[name = string("second_89_cast_fp16")];
            tensor<fp16, [1, 512, 2304]> input_75_cast_fp16 = add(x = input_65_cast_fp16, y = second_89_cast_fp16)[name = string("input_75_cast_fp16")];
            tensor<int32, [6]> input_77_pad_0 = const()[name = string("input_77_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_77_mode_0 = const()[name = string("input_77_mode_0"), val = string("replicate")];
            fp16 const_15_to_fp16 = const()[name = string("const_15_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 2310]> input_77_cast_fp16 = pad(constant_val = const_15_to_fp16, mode = input_77_mode_0, pad = input_77_pad_0, x = input_75_cast_fp16)[name = string("input_77_cast_fp16")];
            string input_tensor_135_pad_type_0 = const()[name = string("input_tensor_135_pad_type_0"), val = string("valid")];
            int32 input_tensor_135_groups_0 = const()[name = string("input_tensor_135_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_135_strides_0 = const()[name = string("input_tensor_135_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_135_pad_0 = const()[name = string("input_tensor_135_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_135_dilations_0 = const()[name = string("input_tensor_135_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_7_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_7_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29644736)))];
            tensor<fp16, [512]> decoder_convnext_7_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_7_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29651968)))];
            tensor<fp16, [1, 512, 2304]> input_tensor_135_cast_fp16 = conv(bias = decoder_convnext_7_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_135_dilations_0, groups = input_tensor_135_groups_0, pad = input_tensor_135_pad_0, pad_type = input_tensor_135_pad_type_0, strides = input_tensor_135_strides_0, weight = decoder_convnext_7_dwconv_net_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = string("input_tensor_135_cast_fp16")];
            tensor<int32, [3]> var_773 = const()[name = string("op_773"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_137_axes_0 = const()[name = string("input_tensor_137_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29653056)))];
            tensor<fp16, [512]> decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29654144)))];
            fp16 var_776_to_fp16 = const()[name = string("op_776_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 2304, 512]> input_79_cast_fp16 = transpose(perm = var_773, x = input_tensor_135_cast_fp16)[name = string("transpose_6")];
            tensor<fp16, [1, 2304, 512]> input_tensor_137_cast_fp16 = layer_norm(axes = input_tensor_137_axes_0, beta = decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_776_to_fp16, gamma = decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_tensor_137_cast_fp16")];
            tensor<int32, [3]> var_785 = const()[name = string("op_785"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_61_pad_type_0 = const()[name = string("first_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_61_strides_0 = const()[name = string("first_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_61_pad_0 = const()[name = string("first_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_61_dilations_0 = const()[name = string("first_61_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_61_groups_0 = const()[name = string("first_61_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_7_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_7_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29655232)))];
            tensor<fp16, [2048]> decoder_convnext_7_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_7_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31752448)))];
            tensor<fp16, [1, 512, 2304]> input_81_cast_fp16 = transpose(perm = var_785, x = input_tensor_137_cast_fp16)[name = string("transpose_5")];
            tensor<fp16, [1, 2048, 2304]> first_61_cast_fp16 = conv(bias = decoder_convnext_7_pwconv1_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = decoder_convnext_7_pwconv1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = string("first_61_cast_fp16")];
            string input_83_mode_0 = const()[name = string("input_83_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 2304]> input_83_cast_fp16 = gelu(mode = input_83_mode_0, x = first_61_cast_fp16)[name = string("input_83_cast_fp16")];
            string second_99_pad_type_0 = const()[name = string("second_99_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_99_strides_0 = const()[name = string("second_99_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_99_pad_0 = const()[name = string("second_99_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_99_dilations_0 = const()[name = string("second_99_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_99_groups_0 = const()[name = string("second_99_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_101_weight_0_to_fp16 = const()[name = string("second_101_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31756608)))];
            tensor<fp16, [512]> second_101_bias_0_to_fp16 = const()[name = string("second_101_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33853824)))];
            tensor<fp16, [1, 512, 2304]> second_101_cast_fp16 = conv(bias = second_101_bias_0_to_fp16, dilations = second_99_dilations_0, groups = second_99_groups_0, pad = second_99_pad_0, pad_type = second_99_pad_type_0, strides = second_99_strides_0, weight = second_101_weight_0_to_fp16, x = input_83_cast_fp16)[name = string("second_101_cast_fp16")];
            tensor<fp16, [1, 512, 2304]> input_85_cast_fp16 = add(x = input_75_cast_fp16, y = second_101_cast_fp16)[name = string("input_85_cast_fp16")];
            tensor<int32, [6]> input_87_pad_0 = const()[name = string("input_87_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_87_mode_0 = const()[name = string("input_87_mode_0"), val = string("replicate")];
            fp16 const_16_to_fp16 = const()[name = string("const_16_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 2310]> input_87_cast_fp16 = pad(constant_val = const_16_to_fp16, mode = input_87_mode_0, pad = input_87_pad_0, x = input_85_cast_fp16)[name = string("input_87_cast_fp16")];
            string input_tensor_149_pad_type_0 = const()[name = string("input_tensor_149_pad_type_0"), val = string("valid")];
            int32 input_tensor_149_groups_0 = const()[name = string("input_tensor_149_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_149_strides_0 = const()[name = string("input_tensor_149_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_149_pad_0 = const()[name = string("input_tensor_149_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_149_dilations_0 = const()[name = string("input_tensor_149_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_8_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_8_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33854912)))];
            tensor<fp16, [512]> decoder_convnext_8_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_8_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33862144)))];
            tensor<fp16, [1, 512, 2304]> input_tensor_149_cast_fp16 = conv(bias = decoder_convnext_8_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_149_dilations_0, groups = input_tensor_149_groups_0, pad = input_tensor_149_pad_0, pad_type = input_tensor_149_pad_type_0, strides = input_tensor_149_strides_0, weight = decoder_convnext_8_dwconv_net_Conv_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_tensor_149_cast_fp16")];
            tensor<int32, [3]> var_839 = const()[name = string("op_839"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_151_axes_0 = const()[name = string("input_tensor_151_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33863232)))];
            tensor<fp16, [512]> decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33864320)))];
            fp16 var_842_to_fp16 = const()[name = string("op_842_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 2304, 512]> input_89_cast_fp16 = transpose(perm = var_839, x = input_tensor_149_cast_fp16)[name = string("transpose_4")];
            tensor<fp16, [1, 2304, 512]> input_tensor_151_cast_fp16 = layer_norm(axes = input_tensor_151_axes_0, beta = decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_842_to_fp16, gamma = decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_151_cast_fp16")];
            tensor<int32, [3]> var_851 = const()[name = string("op_851"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_69_pad_type_0 = const()[name = string("first_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_69_strides_0 = const()[name = string("first_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_69_pad_0 = const()[name = string("first_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_69_dilations_0 = const()[name = string("first_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_69_groups_0 = const()[name = string("first_69_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_8_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_8_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33865408)))];
            tensor<fp16, [2048]> decoder_convnext_8_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_8_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35962624)))];
            tensor<fp16, [1, 512, 2304]> input_91_cast_fp16 = transpose(perm = var_851, x = input_tensor_151_cast_fp16)[name = string("transpose_3")];
            tensor<fp16, [1, 2048, 2304]> first_69_cast_fp16 = conv(bias = decoder_convnext_8_pwconv1_Conv_bias_to_fp16, dilations = first_69_dilations_0, groups = first_69_groups_0, pad = first_69_pad_0, pad_type = first_69_pad_type_0, strides = first_69_strides_0, weight = decoder_convnext_8_pwconv1_Conv_weight_to_fp16, x = input_91_cast_fp16)[name = string("first_69_cast_fp16")];
            string input_93_mode_0 = const()[name = string("input_93_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 2304]> input_93_cast_fp16 = gelu(mode = input_93_mode_0, x = first_69_cast_fp16)[name = string("input_93_cast_fp16")];
            string second_111_pad_type_0 = const()[name = string("second_111_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_111_strides_0 = const()[name = string("second_111_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_111_pad_0 = const()[name = string("second_111_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_111_dilations_0 = const()[name = string("second_111_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_111_groups_0 = const()[name = string("second_111_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_113_weight_0_to_fp16 = const()[name = string("second_113_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35966784)))];
            tensor<fp16, [512]> second_113_bias_0_to_fp16 = const()[name = string("second_113_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38064000)))];
            tensor<fp16, [1, 512, 2304]> second_113_cast_fp16 = conv(bias = second_113_bias_0_to_fp16, dilations = second_111_dilations_0, groups = second_111_groups_0, pad = second_111_pad_0, pad_type = second_111_pad_type_0, strides = second_111_strides_0, weight = second_113_weight_0_to_fp16, x = input_93_cast_fp16)[name = string("second_113_cast_fp16")];
            tensor<fp16, [1, 512, 2304]> input_95_cast_fp16 = add(x = input_85_cast_fp16, y = second_113_cast_fp16)[name = string("input_95_cast_fp16")];
            tensor<int32, [6]> input_97_pad_0 = const()[name = string("input_97_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_97_mode_0 = const()[name = string("input_97_mode_0"), val = string("replicate")];
            fp16 const_17_to_fp16 = const()[name = string("const_17_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 2310]> input_97_cast_fp16 = pad(constant_val = const_17_to_fp16, mode = input_97_mode_0, pad = input_97_pad_0, x = input_95_cast_fp16)[name = string("input_97_cast_fp16")];
            string input_tensor_163_pad_type_0 = const()[name = string("input_tensor_163_pad_type_0"), val = string("valid")];
            int32 input_tensor_163_groups_0 = const()[name = string("input_tensor_163_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_163_strides_0 = const()[name = string("input_tensor_163_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_163_pad_0 = const()[name = string("input_tensor_163_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_163_dilations_0 = const()[name = string("input_tensor_163_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_9_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_9_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38065088)))];
            tensor<fp16, [512]> decoder_convnext_9_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_9_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38072320)))];
            tensor<fp16, [1, 512, 2304]> input_tensor_163_cast_fp16 = conv(bias = decoder_convnext_9_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_163_dilations_0, groups = input_tensor_163_groups_0, pad = input_tensor_163_pad_0, pad_type = input_tensor_163_pad_type_0, strides = input_tensor_163_strides_0, weight = decoder_convnext_9_dwconv_net_Conv_weight_to_fp16, x = input_97_cast_fp16)[name = string("input_tensor_163_cast_fp16")];
            tensor<int32, [3]> var_905 = const()[name = string("op_905"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_165_axes_0 = const()[name = string("input_tensor_165_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38073408)))];
            tensor<fp16, [512]> decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38074496)))];
            fp16 var_908_to_fp16 = const()[name = string("op_908_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 2304, 512]> input_99_cast_fp16 = transpose(perm = var_905, x = input_tensor_163_cast_fp16)[name = string("transpose_2")];
            tensor<fp16, [1, 2304, 512]> input_tensor_165_cast_fp16 = layer_norm(axes = input_tensor_165_axes_0, beta = decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_908_to_fp16, gamma = decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16, x = input_99_cast_fp16)[name = string("input_tensor_165_cast_fp16")];
            tensor<int32, [3]> var_917 = const()[name = string("op_917"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_77_pad_type_0 = const()[name = string("first_77_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_77_strides_0 = const()[name = string("first_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_77_pad_0 = const()[name = string("first_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_77_dilations_0 = const()[name = string("first_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_77_groups_0 = const()[name = string("first_77_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_9_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_9_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38075584)))];
            tensor<fp16, [2048]> decoder_convnext_9_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_9_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40172800)))];
            tensor<fp16, [1, 512, 2304]> input_101_cast_fp16 = transpose(perm = var_917, x = input_tensor_165_cast_fp16)[name = string("transpose_1")];
            tensor<fp16, [1, 2048, 2304]> first_77_cast_fp16 = conv(bias = decoder_convnext_9_pwconv1_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = decoder_convnext_9_pwconv1_Conv_weight_to_fp16, x = input_101_cast_fp16)[name = string("first_77_cast_fp16")];
            string input_103_mode_0 = const()[name = string("input_103_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 2304]> input_103_cast_fp16 = gelu(mode = input_103_mode_0, x = first_77_cast_fp16)[name = string("input_103_cast_fp16")];
            string second_123_pad_type_0 = const()[name = string("second_123_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_123_strides_0 = const()[name = string("second_123_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_123_pad_0 = const()[name = string("second_123_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_123_dilations_0 = const()[name = string("second_123_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_123_groups_0 = const()[name = string("second_123_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_weight_0_to_fp16 = const()[name = string("second_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40176960)))];
            tensor<fp16, [512]> second_bias_0_to_fp16 = const()[name = string("second_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42274176)))];
            tensor<fp16, [1, 512, 2304]> second_cast_fp16 = conv(bias = second_bias_0_to_fp16, dilations = second_123_dilations_0, groups = second_123_groups_0, pad = second_123_pad_0, pad_type = second_123_pad_type_0, strides = second_123_strides_0, weight = second_weight_0_to_fp16, x = input_103_cast_fp16)[name = string("second_cast_fp16")];
            tensor<fp16, [1, 512, 2304]> input_105_cast_fp16 = add(x = input_95_cast_fp16, y = second_cast_fp16)[name = string("input_105_cast_fp16")];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_running_mean_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42275264)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_running_var_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42276352)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_weight_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42277440)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_bias_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42278528)))];
            fp16 var_951_to_fp16 = const()[name = string("op_951_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 512, 2304]> input_107_cast_fp16 = batch_norm(beta = decoder_final_norm_BatchNormalization_bias_to_fp16, epsilon = var_951_to_fp16, gamma = decoder_final_norm_BatchNormalization_weight_to_fp16, mean = decoder_final_norm_BatchNormalization_running_mean_to_fp16, variance = decoder_final_norm_BatchNormalization_running_var_to_fp16, x = input_105_cast_fp16)[name = string("input_107_cast_fp16")];
            tensor<int32, [6]> input_109_pad_0 = const()[name = string("input_109_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 0])];
            string input_109_mode_0 = const()[name = string("input_109_mode_0"), val = string("replicate")];
            fp16 const_18_to_fp16 = const()[name = string("const_18_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 2306]> input_109_cast_fp16 = pad(constant_val = const_18_to_fp16, mode = input_109_mode_0, pad = input_109_pad_0, x = input_107_cast_fp16)[name = string("input_109_cast_fp16")];
            string input_tensor_177_pad_type_0 = const()[name = string("input_tensor_177_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_177_strides_0 = const()[name = string("input_tensor_177_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_177_pad_0 = const()[name = string("input_tensor_177_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_177_dilations_0 = const()[name = string("input_tensor_177_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_177_groups_0 = const()[name = string("input_tensor_177_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 3]> decoder_head_layer1_net_Conv_weight_to_fp16 = const()[name = string("decoder_head_layer1_net_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42279616)))];
            tensor<fp16, [2048]> decoder_head_layer1_net_Conv_bias_to_fp16 = const()[name = string("decoder_head_layer1_net_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48571136)))];
            tensor<fp16, [1, 2048, 2304]> input_tensor_177_cast_fp16 = conv(bias = decoder_head_layer1_net_Conv_bias_to_fp16, dilations = input_tensor_177_dilations_0, groups = input_tensor_177_groups_0, pad = input_tensor_177_pad_0, pad_type = input_tensor_177_pad_type_0, strides = input_tensor_177_strides_0, weight = decoder_head_layer1_net_Conv_weight_to_fp16, x = input_109_cast_fp16)[name = string("input_tensor_177_cast_fp16")];
            fp32 input_alpha_1 = const()[name = string("input_alpha_1"), val = fp32(0x1.9814fap-13)];
            tensor<fp16, [1, 2048, 2304]> input_cast_fp16 = leaky_relu(alpha = input_alpha_1, x = input_tensor_177_cast_fp16)[name = string("input_cast_fp16")];
            string input_tensor_179_pad_type_0 = const()[name = string("input_tensor_179_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_179_strides_0 = const()[name = string("input_tensor_179_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_179_pad_0 = const()[name = string("input_tensor_179_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_179_dilations_0 = const()[name = string("input_tensor_179_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_179_groups_0 = const()[name = string("input_tensor_179_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> decoder_head_layer2_Conv_weight_to_fp16 = const()[name = string("decoder_head_layer2_Conv_weight_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48575296)))];
            tensor<fp16, [1, 512, 2304]> input_tensor_179_cast_fp16 = conv(dilations = input_tensor_179_dilations_0, groups = input_tensor_179_groups_0, pad = input_tensor_179_pad_0, pad_type = input_tensor_179_pad_type_0, strides = input_tensor_179_strides_0, weight = decoder_head_layer2_Conv_weight_to_fp16, x = input_cast_fp16)[name = string("input_tensor_179_cast_fp16")];
            tensor<int32, [3]> var_994 = const()[name = string("op_994"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [2]> var_1021 = const()[name = string("op_1021"), val = tensor<int32, [2]>([1, -1])];
            tensor<fp16, [1, 2304, 512]> input_tensor_181_cast_fp16 = transpose(perm = var_994, x = input_tensor_179_cast_fp16)[name = string("transpose_0")];
            tensor<fp16, [1, 1179648]> wav_tts = reshape(shape = var_1021, x = input_tensor_181_cast_fp16)[name = string("op_1022_cast_fp16")];
        } -> (wav_tts);
    func vocoder_l512<ios18>(tensor<fp16, [1, 144, 512]> latent) {
            fp16 _inversed_input_tensor_1_y_0_to_fp16 = const()[name = string("_inversed_input_tensor_1_y_0_to_fp16"), val = fp16(0x1p+2)];
            tensor<fp16, [1, 144, 512]> _inversed_input_tensor_1_cast_fp16 = mul(x = latent, y = _inversed_input_tensor_1_y_0_to_fp16)[name = string("_inversed_input_tensor_1_cast_fp16")];
            tensor<int32, [4]> var_213 = const()[name = string("op_213"), val = tensor<int32, [4]>([1, -1, 6, 512])];
            tensor<fp16, [1, 24, 6, 512]> input_tensor_9_cast_fp16 = reshape(shape = var_213, x = _inversed_input_tensor_1_cast_fp16)[name = string("input_tensor_9_cast_fp16")];
            tensor<int32, [4]> var_219 = const()[name = string("op_219"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_264 = const()[name = string("op_264"), val = tensor<int32, [3]>([1, 24, -1])];
            tensor<fp16, [1, 24, 512, 6]> input_tensor_11_cast_fp16 = transpose(perm = var_219, x = input_tensor_9_cast_fp16)[name = string("transpose_21")];
            tensor<fp16, [1, 24, 3072]> first_1_cast_fp16 = reshape(shape = var_264, x = input_tensor_11_cast_fp16)[name = string("first_1_cast_fp16")];
            tensor<fp16, [1, 24, 1]> initializers_onnx_initializer_1_to_fp16 = const()[name = string("initializers_onnx_initializer_1_to_fp16"), val = tensor<fp16, [1, 24, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [1, 24, 3072]> first_3_cast_fp16 = mul(x = first_1_cast_fp16, y = initializers_onnx_initializer_1_to_fp16)[name = string("first_3_cast_fp16")];
            tensor<fp16, [1, 24, 1]> initializers_onnx_initializer_2_to_fp16 = const()[name = string("initializers_onnx_initializer_2_to_fp16"), val = tensor<fp16, [1, 24, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192)))];
            tensor<fp16, [1, 24, 3072]> input_1_cast_fp16 = add(x = first_3_cast_fp16, y = initializers_onnx_initializer_2_to_fp16)[name = string("input_1_cast_fp16")];
            tensor<int32, [6]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("replicate")];
            fp16 const_7_to_fp16 = const()[name = string("const_7_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 24, 3078]> input_3_cast_fp16 = pad(constant_val = const_7_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string input_5_pad_type_0 = const()[name = string("input_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_5_strides_0 = const()[name = string("input_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_5_pad_0 = const()[name = string("input_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_5_dilations_0 = const()[name = string("input_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_5_groups_0 = const()[name = string("input_5_groups_0"), val = int32(1)];
            tensor<fp16, [512, 24, 7]> decoder_embed_net_Conv_weight_to_fp16 = const()[name = string("decoder_embed_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 24, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(320)))];
            tensor<fp16, [512]> decoder_embed_net_Conv_bias_to_fp16 = const()[name = string("decoder_embed_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(172416)))];
            tensor<fp16, [1, 512, 3072]> input_5_cast_fp16 = conv(bias = decoder_embed_net_Conv_bias_to_fp16, dilations = input_5_dilations_0, groups = input_5_groups_0, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = input_5_strides_0, weight = decoder_embed_net_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = string("input_5_cast_fp16")];
            tensor<int32, [6]> input_7_pad_0 = const()[name = string("input_7_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_7_mode_0 = const()[name = string("input_7_mode_0"), val = string("replicate")];
            fp16 const_8_to_fp16 = const()[name = string("const_8_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 3078]> input_7_cast_fp16 = pad(constant_val = const_8_to_fp16, mode = input_7_mode_0, pad = input_7_pad_0, x = input_5_cast_fp16)[name = string("input_7_cast_fp16")];
            string input_tensor_37_pad_type_0 = const()[name = string("input_tensor_37_pad_type_0"), val = string("valid")];
            int32 input_tensor_37_groups_0 = const()[name = string("input_tensor_37_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_37_strides_0 = const()[name = string("input_tensor_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_37_pad_0 = const()[name = string("input_tensor_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_37_dilations_0 = const()[name = string("input_tensor_37_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_0_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_0_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(173504)))];
            tensor<fp16, [512]> decoder_convnext_0_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_0_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(180736)))];
            tensor<fp16, [1, 512, 3072]> input_tensor_37_cast_fp16 = conv(bias = decoder_convnext_0_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_37_dilations_0, groups = input_tensor_37_groups_0, pad = input_tensor_37_pad_0, pad_type = input_tensor_37_pad_type_0, strides = input_tensor_37_strides_0, weight = decoder_convnext_0_dwconv_net_Conv_weight_to_fp16, x = input_7_cast_fp16)[name = string("input_tensor_37_cast_fp16")];
            tensor<int32, [3]> var_307 = const()[name = string("op_307"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_39_axes_0 = const()[name = string("input_tensor_39_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(181824)))];
            tensor<fp16, [512]> decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(182912)))];
            fp16 var_310_to_fp16 = const()[name = string("op_310_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 3072, 512]> input_9_cast_fp16 = transpose(perm = var_307, x = input_tensor_37_cast_fp16)[name = string("transpose_20")];
            tensor<fp16, [1, 3072, 512]> input_tensor_39_cast_fp16 = layer_norm(axes = input_tensor_39_axes_0, beta = decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_310_to_fp16, gamma = decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16, x = input_9_cast_fp16)[name = string("input_tensor_39_cast_fp16")];
            tensor<int32, [3]> var_319 = const()[name = string("op_319"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_5_pad_type_0 = const()[name = string("first_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_5_strides_0 = const()[name = string("first_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_5_pad_0 = const()[name = string("first_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_5_dilations_0 = const()[name = string("first_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_5_groups_0 = const()[name = string("first_5_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_0_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_0_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(184000)))];
            tensor<fp16, [2048]> decoder_convnext_0_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_0_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2281216)))];
            tensor<fp16, [1, 512, 3072]> input_11_cast_fp16 = transpose(perm = var_319, x = input_tensor_39_cast_fp16)[name = string("transpose_19")];
            tensor<fp16, [1, 2048, 3072]> first_5_cast_fp16 = conv(bias = decoder_convnext_0_pwconv1_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = decoder_convnext_0_pwconv1_Conv_weight_to_fp16, x = input_11_cast_fp16)[name = string("first_5_cast_fp16")];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 3072]> input_13_cast_fp16 = gelu(mode = input_13_mode_0, x = first_5_cast_fp16)[name = string("input_13_cast_fp16")];
            string second_15_pad_type_0 = const()[name = string("second_15_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_15_strides_0 = const()[name = string("second_15_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_15_pad_0 = const()[name = string("second_15_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_15_dilations_0 = const()[name = string("second_15_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_15_groups_0 = const()[name = string("second_15_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_17_weight_0_to_fp16 = const()[name = string("second_17_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2285376)))];
            tensor<fp16, [512]> second_17_bias_0_to_fp16 = const()[name = string("second_17_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4382592)))];
            tensor<fp16, [1, 512, 3072]> second_17_cast_fp16 = conv(bias = second_17_bias_0_to_fp16, dilations = second_15_dilations_0, groups = second_15_groups_0, pad = second_15_pad_0, pad_type = second_15_pad_type_0, strides = second_15_strides_0, weight = second_17_weight_0_to_fp16, x = input_13_cast_fp16)[name = string("second_17_cast_fp16")];
            tensor<fp16, [1, 512, 3072]> input_15_cast_fp16 = add(x = input_5_cast_fp16, y = second_17_cast_fp16)[name = string("input_15_cast_fp16")];
            tensor<int32, [6]> input_17_pad_0 = const()[name = string("input_17_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 12, 0])];
            string input_17_mode_0 = const()[name = string("input_17_mode_0"), val = string("replicate")];
            fp16 const_9_to_fp16 = const()[name = string("const_9_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 3084]> input_17_cast_fp16 = pad(constant_val = const_9_to_fp16, mode = input_17_mode_0, pad = input_17_pad_0, x = input_15_cast_fp16)[name = string("input_17_cast_fp16")];
            string input_tensor_51_pad_type_0 = const()[name = string("input_tensor_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_51_dilations_0 = const()[name = string("input_tensor_51_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 input_tensor_51_groups_0 = const()[name = string("input_tensor_51_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_51_strides_0 = const()[name = string("input_tensor_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_51_pad_0 = const()[name = string("input_tensor_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_1_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_1_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4383680)))];
            tensor<fp16, [512]> decoder_convnext_1_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_1_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4390912)))];
            tensor<fp16, [1, 512, 3072]> input_tensor_51_cast_fp16 = conv(bias = decoder_convnext_1_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_51_dilations_0, groups = input_tensor_51_groups_0, pad = input_tensor_51_pad_0, pad_type = input_tensor_51_pad_type_0, strides = input_tensor_51_strides_0, weight = decoder_convnext_1_dwconv_net_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = string("input_tensor_51_cast_fp16")];
            tensor<int32, [3]> var_374 = const()[name = string("op_374"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_53_axes_0 = const()[name = string("input_tensor_53_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4392000)))];
            tensor<fp16, [512]> decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4393088)))];
            fp16 var_377_to_fp16 = const()[name = string("op_377_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 3072, 512]> input_19_cast_fp16 = transpose(perm = var_374, x = input_tensor_51_cast_fp16)[name = string("transpose_18")];
            tensor<fp16, [1, 3072, 512]> input_tensor_53_cast_fp16 = layer_norm(axes = input_tensor_53_axes_0, beta = decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_377_to_fp16, gamma = decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16, x = input_19_cast_fp16)[name = string("input_tensor_53_cast_fp16")];
            tensor<int32, [3]> var_386 = const()[name = string("op_386"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_13_pad_type_0 = const()[name = string("first_13_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_13_strides_0 = const()[name = string("first_13_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_13_pad_0 = const()[name = string("first_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_13_dilations_0 = const()[name = string("first_13_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_13_groups_0 = const()[name = string("first_13_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_1_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_1_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4394176)))];
            tensor<fp16, [2048]> decoder_convnext_1_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_1_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6491392)))];
            tensor<fp16, [1, 512, 3072]> input_21_cast_fp16 = transpose(perm = var_386, x = input_tensor_53_cast_fp16)[name = string("transpose_17")];
            tensor<fp16, [1, 2048, 3072]> first_13_cast_fp16 = conv(bias = decoder_convnext_1_pwconv1_Conv_bias_to_fp16, dilations = first_13_dilations_0, groups = first_13_groups_0, pad = first_13_pad_0, pad_type = first_13_pad_type_0, strides = first_13_strides_0, weight = decoder_convnext_1_pwconv1_Conv_weight_to_fp16, x = input_21_cast_fp16)[name = string("first_13_cast_fp16")];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 3072]> input_23_cast_fp16 = gelu(mode = input_23_mode_0, x = first_13_cast_fp16)[name = string("input_23_cast_fp16")];
            string second_27_pad_type_0 = const()[name = string("second_27_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_27_strides_0 = const()[name = string("second_27_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_27_pad_0 = const()[name = string("second_27_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_27_dilations_0 = const()[name = string("second_27_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_27_groups_0 = const()[name = string("second_27_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_29_weight_0_to_fp16 = const()[name = string("second_29_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6495552)))];
            tensor<fp16, [512]> second_29_bias_0_to_fp16 = const()[name = string("second_29_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8592768)))];
            tensor<fp16, [1, 512, 3072]> second_29_cast_fp16 = conv(bias = second_29_bias_0_to_fp16, dilations = second_27_dilations_0, groups = second_27_groups_0, pad = second_27_pad_0, pad_type = second_27_pad_type_0, strides = second_27_strides_0, weight = second_29_weight_0_to_fp16, x = input_23_cast_fp16)[name = string("second_29_cast_fp16")];
            tensor<fp16, [1, 512, 3072]> input_25_cast_fp16 = add(x = input_15_cast_fp16, y = second_29_cast_fp16)[name = string("input_25_cast_fp16")];
            tensor<int32, [6]> input_27_pad_0 = const()[name = string("input_27_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 24, 0])];
            string input_27_mode_0 = const()[name = string("input_27_mode_0"), val = string("replicate")];
            fp16 const_10_to_fp16 = const()[name = string("const_10_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 3096]> input_27_cast_fp16 = pad(constant_val = const_10_to_fp16, mode = input_27_mode_0, pad = input_27_pad_0, x = input_25_cast_fp16)[name = string("input_27_cast_fp16")];
            string input_tensor_65_pad_type_0 = const()[name = string("input_tensor_65_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_65_dilations_0 = const()[name = string("input_tensor_65_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 input_tensor_65_groups_0 = const()[name = string("input_tensor_65_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_65_strides_0 = const()[name = string("input_tensor_65_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_65_pad_0 = const()[name = string("input_tensor_65_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_2_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_2_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8593856)))];
            tensor<fp16, [512]> decoder_convnext_2_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_2_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8601088)))];
            tensor<fp16, [1, 512, 3072]> input_tensor_65_cast_fp16 = conv(bias = decoder_convnext_2_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_65_dilations_0, groups = input_tensor_65_groups_0, pad = input_tensor_65_pad_0, pad_type = input_tensor_65_pad_type_0, strides = input_tensor_65_strides_0, weight = decoder_convnext_2_dwconv_net_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = string("input_tensor_65_cast_fp16")];
            tensor<int32, [3]> var_441 = const()[name = string("op_441"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_67_axes_0 = const()[name = string("input_tensor_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8602176)))];
            tensor<fp16, [512]> decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8603264)))];
            fp16 var_444_to_fp16 = const()[name = string("op_444_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 3072, 512]> input_29_cast_fp16 = transpose(perm = var_441, x = input_tensor_65_cast_fp16)[name = string("transpose_16")];
            tensor<fp16, [1, 3072, 512]> input_tensor_67_cast_fp16 = layer_norm(axes = input_tensor_67_axes_0, beta = decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_444_to_fp16, gamma = decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16, x = input_29_cast_fp16)[name = string("input_tensor_67_cast_fp16")];
            tensor<int32, [3]> var_453 = const()[name = string("op_453"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_21_pad_type_0 = const()[name = string("first_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_21_strides_0 = const()[name = string("first_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_21_pad_0 = const()[name = string("first_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_21_dilations_0 = const()[name = string("first_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_21_groups_0 = const()[name = string("first_21_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_2_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_2_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8604352)))];
            tensor<fp16, [2048]> decoder_convnext_2_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_2_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10701568)))];
            tensor<fp16, [1, 512, 3072]> input_31_cast_fp16 = transpose(perm = var_453, x = input_tensor_67_cast_fp16)[name = string("transpose_15")];
            tensor<fp16, [1, 2048, 3072]> first_21_cast_fp16 = conv(bias = decoder_convnext_2_pwconv1_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = decoder_convnext_2_pwconv1_Conv_weight_to_fp16, x = input_31_cast_fp16)[name = string("first_21_cast_fp16")];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 3072]> input_33_cast_fp16 = gelu(mode = input_33_mode_0, x = first_21_cast_fp16)[name = string("input_33_cast_fp16")];
            string second_39_pad_type_0 = const()[name = string("second_39_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_39_strides_0 = const()[name = string("second_39_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_39_pad_0 = const()[name = string("second_39_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_39_dilations_0 = const()[name = string("second_39_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_39_groups_0 = const()[name = string("second_39_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_41_weight_0_to_fp16 = const()[name = string("second_41_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10705728)))];
            tensor<fp16, [512]> second_41_bias_0_to_fp16 = const()[name = string("second_41_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12802944)))];
            tensor<fp16, [1, 512, 3072]> second_41_cast_fp16 = conv(bias = second_41_bias_0_to_fp16, dilations = second_39_dilations_0, groups = second_39_groups_0, pad = second_39_pad_0, pad_type = second_39_pad_type_0, strides = second_39_strides_0, weight = second_41_weight_0_to_fp16, x = input_33_cast_fp16)[name = string("second_41_cast_fp16")];
            tensor<fp16, [1, 512, 3072]> input_35_cast_fp16 = add(x = input_25_cast_fp16, y = second_41_cast_fp16)[name = string("input_35_cast_fp16")];
            tensor<int32, [6]> input_37_pad_0 = const()[name = string("input_37_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_37_mode_0 = const()[name = string("input_37_mode_0"), val = string("replicate")];
            fp16 const_11_to_fp16 = const()[name = string("const_11_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 3078]> input_37_cast_fp16 = pad(constant_val = const_11_to_fp16, mode = input_37_mode_0, pad = input_37_pad_0, x = input_35_cast_fp16)[name = string("input_37_cast_fp16")];
            string input_tensor_79_pad_type_0 = const()[name = string("input_tensor_79_pad_type_0"), val = string("valid")];
            int32 input_tensor_79_groups_0 = const()[name = string("input_tensor_79_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_79_strides_0 = const()[name = string("input_tensor_79_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_79_pad_0 = const()[name = string("input_tensor_79_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_79_dilations_0 = const()[name = string("input_tensor_79_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_3_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_3_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12804032)))];
            tensor<fp16, [512]> decoder_convnext_3_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_3_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12811264)))];
            tensor<fp16, [1, 512, 3072]> input_tensor_79_cast_fp16 = conv(bias = decoder_convnext_3_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_79_dilations_0, groups = input_tensor_79_groups_0, pad = input_tensor_79_pad_0, pad_type = input_tensor_79_pad_type_0, strides = input_tensor_79_strides_0, weight = decoder_convnext_3_dwconv_net_Conv_weight_to_fp16, x = input_37_cast_fp16)[name = string("input_tensor_79_cast_fp16")];
            tensor<int32, [3]> var_507 = const()[name = string("op_507"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_81_axes_0 = const()[name = string("input_tensor_81_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12812352)))];
            tensor<fp16, [512]> decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12813440)))];
            fp16 var_510_to_fp16 = const()[name = string("op_510_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 3072, 512]> input_39_cast_fp16 = transpose(perm = var_507, x = input_tensor_79_cast_fp16)[name = string("transpose_14")];
            tensor<fp16, [1, 3072, 512]> input_tensor_81_cast_fp16 = layer_norm(axes = input_tensor_81_axes_0, beta = decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_510_to_fp16, gamma = decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16, x = input_39_cast_fp16)[name = string("input_tensor_81_cast_fp16")];
            tensor<int32, [3]> var_519 = const()[name = string("op_519"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_29_pad_type_0 = const()[name = string("first_29_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_29_strides_0 = const()[name = string("first_29_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_29_pad_0 = const()[name = string("first_29_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_29_dilations_0 = const()[name = string("first_29_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_29_groups_0 = const()[name = string("first_29_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_3_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_3_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12814528)))];
            tensor<fp16, [2048]> decoder_convnext_3_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_3_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14911744)))];
            tensor<fp16, [1, 512, 3072]> input_41_cast_fp16 = transpose(perm = var_519, x = input_tensor_81_cast_fp16)[name = string("transpose_13")];
            tensor<fp16, [1, 2048, 3072]> first_29_cast_fp16 = conv(bias = decoder_convnext_3_pwconv1_Conv_bias_to_fp16, dilations = first_29_dilations_0, groups = first_29_groups_0, pad = first_29_pad_0, pad_type = first_29_pad_type_0, strides = first_29_strides_0, weight = decoder_convnext_3_pwconv1_Conv_weight_to_fp16, x = input_41_cast_fp16)[name = string("first_29_cast_fp16")];
            string input_43_mode_0 = const()[name = string("input_43_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 3072]> input_43_cast_fp16 = gelu(mode = input_43_mode_0, x = first_29_cast_fp16)[name = string("input_43_cast_fp16")];
            string second_51_pad_type_0 = const()[name = string("second_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_51_strides_0 = const()[name = string("second_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_51_pad_0 = const()[name = string("second_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_51_dilations_0 = const()[name = string("second_51_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_51_groups_0 = const()[name = string("second_51_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_53_weight_0_to_fp16 = const()[name = string("second_53_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14915904)))];
            tensor<fp16, [512]> second_53_bias_0_to_fp16 = const()[name = string("second_53_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17013120)))];
            tensor<fp16, [1, 512, 3072]> second_53_cast_fp16 = conv(bias = second_53_bias_0_to_fp16, dilations = second_51_dilations_0, groups = second_51_groups_0, pad = second_51_pad_0, pad_type = second_51_pad_type_0, strides = second_51_strides_0, weight = second_53_weight_0_to_fp16, x = input_43_cast_fp16)[name = string("second_53_cast_fp16")];
            tensor<fp16, [1, 512, 3072]> input_45_cast_fp16 = add(x = input_35_cast_fp16, y = second_53_cast_fp16)[name = string("input_45_cast_fp16")];
            tensor<int32, [6]> input_47_pad_0 = const()[name = string("input_47_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 12, 0])];
            string input_47_mode_0 = const()[name = string("input_47_mode_0"), val = string("replicate")];
            fp16 const_12_to_fp16 = const()[name = string("const_12_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 3084]> input_47_cast_fp16 = pad(constant_val = const_12_to_fp16, mode = input_47_mode_0, pad = input_47_pad_0, x = input_45_cast_fp16)[name = string("input_47_cast_fp16")];
            string input_tensor_93_pad_type_0 = const()[name = string("input_tensor_93_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_93_dilations_0 = const()[name = string("input_tensor_93_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 input_tensor_93_groups_0 = const()[name = string("input_tensor_93_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_93_strides_0 = const()[name = string("input_tensor_93_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_93_pad_0 = const()[name = string("input_tensor_93_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_4_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_4_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17014208)))];
            tensor<fp16, [512]> decoder_convnext_4_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_4_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17021440)))];
            tensor<fp16, [1, 512, 3072]> input_tensor_93_cast_fp16 = conv(bias = decoder_convnext_4_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_93_dilations_0, groups = input_tensor_93_groups_0, pad = input_tensor_93_pad_0, pad_type = input_tensor_93_pad_type_0, strides = input_tensor_93_strides_0, weight = decoder_convnext_4_dwconv_net_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("input_tensor_93_cast_fp16")];
            tensor<int32, [3]> var_574 = const()[name = string("op_574"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_95_axes_0 = const()[name = string("input_tensor_95_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17022528)))];
            tensor<fp16, [512]> decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17023616)))];
            fp16 var_577_to_fp16 = const()[name = string("op_577_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 3072, 512]> input_49_cast_fp16 = transpose(perm = var_574, x = input_tensor_93_cast_fp16)[name = string("transpose_12")];
            tensor<fp16, [1, 3072, 512]> input_tensor_95_cast_fp16 = layer_norm(axes = input_tensor_95_axes_0, beta = decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_577_to_fp16, gamma = decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16, x = input_49_cast_fp16)[name = string("input_tensor_95_cast_fp16")];
            tensor<int32, [3]> var_586 = const()[name = string("op_586"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_37_pad_type_0 = const()[name = string("first_37_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_37_strides_0 = const()[name = string("first_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_37_pad_0 = const()[name = string("first_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_37_dilations_0 = const()[name = string("first_37_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_37_groups_0 = const()[name = string("first_37_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_4_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_4_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17024704)))];
            tensor<fp16, [2048]> decoder_convnext_4_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_4_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19121920)))];
            tensor<fp16, [1, 512, 3072]> input_51_cast_fp16 = transpose(perm = var_586, x = input_tensor_95_cast_fp16)[name = string("transpose_11")];
            tensor<fp16, [1, 2048, 3072]> first_37_cast_fp16 = conv(bias = decoder_convnext_4_pwconv1_Conv_bias_to_fp16, dilations = first_37_dilations_0, groups = first_37_groups_0, pad = first_37_pad_0, pad_type = first_37_pad_type_0, strides = first_37_strides_0, weight = decoder_convnext_4_pwconv1_Conv_weight_to_fp16, x = input_51_cast_fp16)[name = string("first_37_cast_fp16")];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 3072]> input_53_cast_fp16 = gelu(mode = input_53_mode_0, x = first_37_cast_fp16)[name = string("input_53_cast_fp16")];
            string second_63_pad_type_0 = const()[name = string("second_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_63_strides_0 = const()[name = string("second_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_63_pad_0 = const()[name = string("second_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_63_dilations_0 = const()[name = string("second_63_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_63_groups_0 = const()[name = string("second_63_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_65_weight_0_to_fp16 = const()[name = string("second_65_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19126080)))];
            tensor<fp16, [512]> second_65_bias_0_to_fp16 = const()[name = string("second_65_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21223296)))];
            tensor<fp16, [1, 512, 3072]> second_65_cast_fp16 = conv(bias = second_65_bias_0_to_fp16, dilations = second_63_dilations_0, groups = second_63_groups_0, pad = second_63_pad_0, pad_type = second_63_pad_type_0, strides = second_63_strides_0, weight = second_65_weight_0_to_fp16, x = input_53_cast_fp16)[name = string("second_65_cast_fp16")];
            tensor<fp16, [1, 512, 3072]> input_55_cast_fp16 = add(x = input_45_cast_fp16, y = second_65_cast_fp16)[name = string("input_55_cast_fp16")];
            tensor<int32, [6]> input_57_pad_0 = const()[name = string("input_57_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 24, 0])];
            string input_57_mode_0 = const()[name = string("input_57_mode_0"), val = string("replicate")];
            fp16 const_13_to_fp16 = const()[name = string("const_13_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 3096]> input_57_cast_fp16 = pad(constant_val = const_13_to_fp16, mode = input_57_mode_0, pad = input_57_pad_0, x = input_55_cast_fp16)[name = string("input_57_cast_fp16")];
            string input_tensor_107_pad_type_0 = const()[name = string("input_tensor_107_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_107_dilations_0 = const()[name = string("input_tensor_107_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 input_tensor_107_groups_0 = const()[name = string("input_tensor_107_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_107_strides_0 = const()[name = string("input_tensor_107_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_107_pad_0 = const()[name = string("input_tensor_107_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_5_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_5_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21224384)))];
            tensor<fp16, [512]> decoder_convnext_5_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_5_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21231616)))];
            tensor<fp16, [1, 512, 3072]> input_tensor_107_cast_fp16 = conv(bias = decoder_convnext_5_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_107_dilations_0, groups = input_tensor_107_groups_0, pad = input_tensor_107_pad_0, pad_type = input_tensor_107_pad_type_0, strides = input_tensor_107_strides_0, weight = decoder_convnext_5_dwconv_net_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = string("input_tensor_107_cast_fp16")];
            tensor<int32, [3]> var_641 = const()[name = string("op_641"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_109_axes_0 = const()[name = string("input_tensor_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21232704)))];
            tensor<fp16, [512]> decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21233792)))];
            fp16 var_644_to_fp16 = const()[name = string("op_644_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 3072, 512]> input_59_cast_fp16 = transpose(perm = var_641, x = input_tensor_107_cast_fp16)[name = string("transpose_10")];
            tensor<fp16, [1, 3072, 512]> input_tensor_109_cast_fp16 = layer_norm(axes = input_tensor_109_axes_0, beta = decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_644_to_fp16, gamma = decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16, x = input_59_cast_fp16)[name = string("input_tensor_109_cast_fp16")];
            tensor<int32, [3]> var_653 = const()[name = string("op_653"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_45_pad_type_0 = const()[name = string("first_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_45_strides_0 = const()[name = string("first_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_45_pad_0 = const()[name = string("first_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_45_dilations_0 = const()[name = string("first_45_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_45_groups_0 = const()[name = string("first_45_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_5_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_5_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21234880)))];
            tensor<fp16, [2048]> decoder_convnext_5_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_5_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23332096)))];
            tensor<fp16, [1, 512, 3072]> input_61_cast_fp16 = transpose(perm = var_653, x = input_tensor_109_cast_fp16)[name = string("transpose_9")];
            tensor<fp16, [1, 2048, 3072]> first_45_cast_fp16 = conv(bias = decoder_convnext_5_pwconv1_Conv_bias_to_fp16, dilations = first_45_dilations_0, groups = first_45_groups_0, pad = first_45_pad_0, pad_type = first_45_pad_type_0, strides = first_45_strides_0, weight = decoder_convnext_5_pwconv1_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("first_45_cast_fp16")];
            string input_63_mode_0 = const()[name = string("input_63_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 3072]> input_63_cast_fp16 = gelu(mode = input_63_mode_0, x = first_45_cast_fp16)[name = string("input_63_cast_fp16")];
            string second_75_pad_type_0 = const()[name = string("second_75_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_75_strides_0 = const()[name = string("second_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_75_pad_0 = const()[name = string("second_75_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_75_dilations_0 = const()[name = string("second_75_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_75_groups_0 = const()[name = string("second_75_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_77_weight_0_to_fp16 = const()[name = string("second_77_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23336256)))];
            tensor<fp16, [512]> second_77_bias_0_to_fp16 = const()[name = string("second_77_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25433472)))];
            tensor<fp16, [1, 512, 3072]> second_77_cast_fp16 = conv(bias = second_77_bias_0_to_fp16, dilations = second_75_dilations_0, groups = second_75_groups_0, pad = second_75_pad_0, pad_type = second_75_pad_type_0, strides = second_75_strides_0, weight = second_77_weight_0_to_fp16, x = input_63_cast_fp16)[name = string("second_77_cast_fp16")];
            tensor<fp16, [1, 512, 3072]> input_65_cast_fp16 = add(x = input_55_cast_fp16, y = second_77_cast_fp16)[name = string("input_65_cast_fp16")];
            tensor<int32, [6]> input_67_pad_0 = const()[name = string("input_67_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_67_mode_0 = const()[name = string("input_67_mode_0"), val = string("replicate")];
            fp16 const_14_to_fp16 = const()[name = string("const_14_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 3078]> input_67_cast_fp16 = pad(constant_val = const_14_to_fp16, mode = input_67_mode_0, pad = input_67_pad_0, x = input_65_cast_fp16)[name = string("input_67_cast_fp16")];
            string input_tensor_121_pad_type_0 = const()[name = string("input_tensor_121_pad_type_0"), val = string("valid")];
            int32 input_tensor_121_groups_0 = const()[name = string("input_tensor_121_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_121_strides_0 = const()[name = string("input_tensor_121_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_121_pad_0 = const()[name = string("input_tensor_121_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_121_dilations_0 = const()[name = string("input_tensor_121_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_6_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_6_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25434560)))];
            tensor<fp16, [512]> decoder_convnext_6_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_6_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25441792)))];
            tensor<fp16, [1, 512, 3072]> input_tensor_121_cast_fp16 = conv(bias = decoder_convnext_6_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_121_dilations_0, groups = input_tensor_121_groups_0, pad = input_tensor_121_pad_0, pad_type = input_tensor_121_pad_type_0, strides = input_tensor_121_strides_0, weight = decoder_convnext_6_dwconv_net_Conv_weight_to_fp16, x = input_67_cast_fp16)[name = string("input_tensor_121_cast_fp16")];
            tensor<int32, [3]> var_707 = const()[name = string("op_707"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_123_axes_0 = const()[name = string("input_tensor_123_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25442880)))];
            tensor<fp16, [512]> decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25443968)))];
            fp16 var_710_to_fp16 = const()[name = string("op_710_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 3072, 512]> input_69_cast_fp16 = transpose(perm = var_707, x = input_tensor_121_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 3072, 512]> input_tensor_123_cast_fp16 = layer_norm(axes = input_tensor_123_axes_0, beta = decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_710_to_fp16, gamma = decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16, x = input_69_cast_fp16)[name = string("input_tensor_123_cast_fp16")];
            tensor<int32, [3]> var_719 = const()[name = string("op_719"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_53_pad_type_0 = const()[name = string("first_53_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_53_strides_0 = const()[name = string("first_53_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_53_pad_0 = const()[name = string("first_53_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_53_dilations_0 = const()[name = string("first_53_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_53_groups_0 = const()[name = string("first_53_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_6_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_6_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25445056)))];
            tensor<fp16, [2048]> decoder_convnext_6_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_6_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27542272)))];
            tensor<fp16, [1, 512, 3072]> input_71_cast_fp16 = transpose(perm = var_719, x = input_tensor_123_cast_fp16)[name = string("transpose_7")];
            tensor<fp16, [1, 2048, 3072]> first_53_cast_fp16 = conv(bias = decoder_convnext_6_pwconv1_Conv_bias_to_fp16, dilations = first_53_dilations_0, groups = first_53_groups_0, pad = first_53_pad_0, pad_type = first_53_pad_type_0, strides = first_53_strides_0, weight = decoder_convnext_6_pwconv1_Conv_weight_to_fp16, x = input_71_cast_fp16)[name = string("first_53_cast_fp16")];
            string input_73_mode_0 = const()[name = string("input_73_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 3072]> input_73_cast_fp16 = gelu(mode = input_73_mode_0, x = first_53_cast_fp16)[name = string("input_73_cast_fp16")];
            string second_87_pad_type_0 = const()[name = string("second_87_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_87_strides_0 = const()[name = string("second_87_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_87_pad_0 = const()[name = string("second_87_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_87_dilations_0 = const()[name = string("second_87_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_87_groups_0 = const()[name = string("second_87_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_89_weight_0_to_fp16 = const()[name = string("second_89_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27546432)))];
            tensor<fp16, [512]> second_89_bias_0_to_fp16 = const()[name = string("second_89_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29643648)))];
            tensor<fp16, [1, 512, 3072]> second_89_cast_fp16 = conv(bias = second_89_bias_0_to_fp16, dilations = second_87_dilations_0, groups = second_87_groups_0, pad = second_87_pad_0, pad_type = second_87_pad_type_0, strides = second_87_strides_0, weight = second_89_weight_0_to_fp16, x = input_73_cast_fp16)[name = string("second_89_cast_fp16")];
            tensor<fp16, [1, 512, 3072]> input_75_cast_fp16 = add(x = input_65_cast_fp16, y = second_89_cast_fp16)[name = string("input_75_cast_fp16")];
            tensor<int32, [6]> input_77_pad_0 = const()[name = string("input_77_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_77_mode_0 = const()[name = string("input_77_mode_0"), val = string("replicate")];
            fp16 const_15_to_fp16 = const()[name = string("const_15_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 3078]> input_77_cast_fp16 = pad(constant_val = const_15_to_fp16, mode = input_77_mode_0, pad = input_77_pad_0, x = input_75_cast_fp16)[name = string("input_77_cast_fp16")];
            string input_tensor_135_pad_type_0 = const()[name = string("input_tensor_135_pad_type_0"), val = string("valid")];
            int32 input_tensor_135_groups_0 = const()[name = string("input_tensor_135_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_135_strides_0 = const()[name = string("input_tensor_135_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_135_pad_0 = const()[name = string("input_tensor_135_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_135_dilations_0 = const()[name = string("input_tensor_135_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_7_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_7_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29644736)))];
            tensor<fp16, [512]> decoder_convnext_7_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_7_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29651968)))];
            tensor<fp16, [1, 512, 3072]> input_tensor_135_cast_fp16 = conv(bias = decoder_convnext_7_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_135_dilations_0, groups = input_tensor_135_groups_0, pad = input_tensor_135_pad_0, pad_type = input_tensor_135_pad_type_0, strides = input_tensor_135_strides_0, weight = decoder_convnext_7_dwconv_net_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = string("input_tensor_135_cast_fp16")];
            tensor<int32, [3]> var_773 = const()[name = string("op_773"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_137_axes_0 = const()[name = string("input_tensor_137_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29653056)))];
            tensor<fp16, [512]> decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29654144)))];
            fp16 var_776_to_fp16 = const()[name = string("op_776_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 3072, 512]> input_79_cast_fp16 = transpose(perm = var_773, x = input_tensor_135_cast_fp16)[name = string("transpose_6")];
            tensor<fp16, [1, 3072, 512]> input_tensor_137_cast_fp16 = layer_norm(axes = input_tensor_137_axes_0, beta = decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_776_to_fp16, gamma = decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_tensor_137_cast_fp16")];
            tensor<int32, [3]> var_785 = const()[name = string("op_785"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_61_pad_type_0 = const()[name = string("first_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_61_strides_0 = const()[name = string("first_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_61_pad_0 = const()[name = string("first_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_61_dilations_0 = const()[name = string("first_61_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_61_groups_0 = const()[name = string("first_61_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_7_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_7_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29655232)))];
            tensor<fp16, [2048]> decoder_convnext_7_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_7_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31752448)))];
            tensor<fp16, [1, 512, 3072]> input_81_cast_fp16 = transpose(perm = var_785, x = input_tensor_137_cast_fp16)[name = string("transpose_5")];
            tensor<fp16, [1, 2048, 3072]> first_61_cast_fp16 = conv(bias = decoder_convnext_7_pwconv1_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = decoder_convnext_7_pwconv1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = string("first_61_cast_fp16")];
            string input_83_mode_0 = const()[name = string("input_83_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 3072]> input_83_cast_fp16 = gelu(mode = input_83_mode_0, x = first_61_cast_fp16)[name = string("input_83_cast_fp16")];
            string second_99_pad_type_0 = const()[name = string("second_99_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_99_strides_0 = const()[name = string("second_99_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_99_pad_0 = const()[name = string("second_99_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_99_dilations_0 = const()[name = string("second_99_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_99_groups_0 = const()[name = string("second_99_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_101_weight_0_to_fp16 = const()[name = string("second_101_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31756608)))];
            tensor<fp16, [512]> second_101_bias_0_to_fp16 = const()[name = string("second_101_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33853824)))];
            tensor<fp16, [1, 512, 3072]> second_101_cast_fp16 = conv(bias = second_101_bias_0_to_fp16, dilations = second_99_dilations_0, groups = second_99_groups_0, pad = second_99_pad_0, pad_type = second_99_pad_type_0, strides = second_99_strides_0, weight = second_101_weight_0_to_fp16, x = input_83_cast_fp16)[name = string("second_101_cast_fp16")];
            tensor<fp16, [1, 512, 3072]> input_85_cast_fp16 = add(x = input_75_cast_fp16, y = second_101_cast_fp16)[name = string("input_85_cast_fp16")];
            tensor<int32, [6]> input_87_pad_0 = const()[name = string("input_87_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_87_mode_0 = const()[name = string("input_87_mode_0"), val = string("replicate")];
            fp16 const_16_to_fp16 = const()[name = string("const_16_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 3078]> input_87_cast_fp16 = pad(constant_val = const_16_to_fp16, mode = input_87_mode_0, pad = input_87_pad_0, x = input_85_cast_fp16)[name = string("input_87_cast_fp16")];
            string input_tensor_149_pad_type_0 = const()[name = string("input_tensor_149_pad_type_0"), val = string("valid")];
            int32 input_tensor_149_groups_0 = const()[name = string("input_tensor_149_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_149_strides_0 = const()[name = string("input_tensor_149_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_149_pad_0 = const()[name = string("input_tensor_149_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_149_dilations_0 = const()[name = string("input_tensor_149_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_8_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_8_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33854912)))];
            tensor<fp16, [512]> decoder_convnext_8_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_8_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33862144)))];
            tensor<fp16, [1, 512, 3072]> input_tensor_149_cast_fp16 = conv(bias = decoder_convnext_8_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_149_dilations_0, groups = input_tensor_149_groups_0, pad = input_tensor_149_pad_0, pad_type = input_tensor_149_pad_type_0, strides = input_tensor_149_strides_0, weight = decoder_convnext_8_dwconv_net_Conv_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_tensor_149_cast_fp16")];
            tensor<int32, [3]> var_839 = const()[name = string("op_839"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_151_axes_0 = const()[name = string("input_tensor_151_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33863232)))];
            tensor<fp16, [512]> decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33864320)))];
            fp16 var_842_to_fp16 = const()[name = string("op_842_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 3072, 512]> input_89_cast_fp16 = transpose(perm = var_839, x = input_tensor_149_cast_fp16)[name = string("transpose_4")];
            tensor<fp16, [1, 3072, 512]> input_tensor_151_cast_fp16 = layer_norm(axes = input_tensor_151_axes_0, beta = decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_842_to_fp16, gamma = decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_151_cast_fp16")];
            tensor<int32, [3]> var_851 = const()[name = string("op_851"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_69_pad_type_0 = const()[name = string("first_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_69_strides_0 = const()[name = string("first_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_69_pad_0 = const()[name = string("first_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_69_dilations_0 = const()[name = string("first_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_69_groups_0 = const()[name = string("first_69_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_8_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_8_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33865408)))];
            tensor<fp16, [2048]> decoder_convnext_8_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_8_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35962624)))];
            tensor<fp16, [1, 512, 3072]> input_91_cast_fp16 = transpose(perm = var_851, x = input_tensor_151_cast_fp16)[name = string("transpose_3")];
            tensor<fp16, [1, 2048, 3072]> first_69_cast_fp16 = conv(bias = decoder_convnext_8_pwconv1_Conv_bias_to_fp16, dilations = first_69_dilations_0, groups = first_69_groups_0, pad = first_69_pad_0, pad_type = first_69_pad_type_0, strides = first_69_strides_0, weight = decoder_convnext_8_pwconv1_Conv_weight_to_fp16, x = input_91_cast_fp16)[name = string("first_69_cast_fp16")];
            string input_93_mode_0 = const()[name = string("input_93_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 3072]> input_93_cast_fp16 = gelu(mode = input_93_mode_0, x = first_69_cast_fp16)[name = string("input_93_cast_fp16")];
            string second_111_pad_type_0 = const()[name = string("second_111_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_111_strides_0 = const()[name = string("second_111_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_111_pad_0 = const()[name = string("second_111_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_111_dilations_0 = const()[name = string("second_111_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_111_groups_0 = const()[name = string("second_111_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_113_weight_0_to_fp16 = const()[name = string("second_113_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35966784)))];
            tensor<fp16, [512]> second_113_bias_0_to_fp16 = const()[name = string("second_113_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38064000)))];
            tensor<fp16, [1, 512, 3072]> second_113_cast_fp16 = conv(bias = second_113_bias_0_to_fp16, dilations = second_111_dilations_0, groups = second_111_groups_0, pad = second_111_pad_0, pad_type = second_111_pad_type_0, strides = second_111_strides_0, weight = second_113_weight_0_to_fp16, x = input_93_cast_fp16)[name = string("second_113_cast_fp16")];
            tensor<fp16, [1, 512, 3072]> input_95_cast_fp16 = add(x = input_85_cast_fp16, y = second_113_cast_fp16)[name = string("input_95_cast_fp16")];
            tensor<int32, [6]> input_97_pad_0 = const()[name = string("input_97_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_97_mode_0 = const()[name = string("input_97_mode_0"), val = string("replicate")];
            fp16 const_17_to_fp16 = const()[name = string("const_17_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 3078]> input_97_cast_fp16 = pad(constant_val = const_17_to_fp16, mode = input_97_mode_0, pad = input_97_pad_0, x = input_95_cast_fp16)[name = string("input_97_cast_fp16")];
            string input_tensor_163_pad_type_0 = const()[name = string("input_tensor_163_pad_type_0"), val = string("valid")];
            int32 input_tensor_163_groups_0 = const()[name = string("input_tensor_163_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_163_strides_0 = const()[name = string("input_tensor_163_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_163_pad_0 = const()[name = string("input_tensor_163_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_163_dilations_0 = const()[name = string("input_tensor_163_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_9_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_9_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38065088)))];
            tensor<fp16, [512]> decoder_convnext_9_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_9_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38072320)))];
            tensor<fp16, [1, 512, 3072]> input_tensor_163_cast_fp16 = conv(bias = decoder_convnext_9_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_163_dilations_0, groups = input_tensor_163_groups_0, pad = input_tensor_163_pad_0, pad_type = input_tensor_163_pad_type_0, strides = input_tensor_163_strides_0, weight = decoder_convnext_9_dwconv_net_Conv_weight_to_fp16, x = input_97_cast_fp16)[name = string("input_tensor_163_cast_fp16")];
            tensor<int32, [3]> var_905 = const()[name = string("op_905"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_165_axes_0 = const()[name = string("input_tensor_165_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38073408)))];
            tensor<fp16, [512]> decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38074496)))];
            fp16 var_908_to_fp16 = const()[name = string("op_908_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 3072, 512]> input_99_cast_fp16 = transpose(perm = var_905, x = input_tensor_163_cast_fp16)[name = string("transpose_2")];
            tensor<fp16, [1, 3072, 512]> input_tensor_165_cast_fp16 = layer_norm(axes = input_tensor_165_axes_0, beta = decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_908_to_fp16, gamma = decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16, x = input_99_cast_fp16)[name = string("input_tensor_165_cast_fp16")];
            tensor<int32, [3]> var_917 = const()[name = string("op_917"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_77_pad_type_0 = const()[name = string("first_77_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_77_strides_0 = const()[name = string("first_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_77_pad_0 = const()[name = string("first_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_77_dilations_0 = const()[name = string("first_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_77_groups_0 = const()[name = string("first_77_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_9_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_9_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38075584)))];
            tensor<fp16, [2048]> decoder_convnext_9_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_9_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40172800)))];
            tensor<fp16, [1, 512, 3072]> input_101_cast_fp16 = transpose(perm = var_917, x = input_tensor_165_cast_fp16)[name = string("transpose_1")];
            tensor<fp16, [1, 2048, 3072]> first_77_cast_fp16 = conv(bias = decoder_convnext_9_pwconv1_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = decoder_convnext_9_pwconv1_Conv_weight_to_fp16, x = input_101_cast_fp16)[name = string("first_77_cast_fp16")];
            string input_103_mode_0 = const()[name = string("input_103_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 3072]> input_103_cast_fp16 = gelu(mode = input_103_mode_0, x = first_77_cast_fp16)[name = string("input_103_cast_fp16")];
            string second_123_pad_type_0 = const()[name = string("second_123_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_123_strides_0 = const()[name = string("second_123_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_123_pad_0 = const()[name = string("second_123_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_123_dilations_0 = const()[name = string("second_123_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_123_groups_0 = const()[name = string("second_123_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_weight_0_to_fp16 = const()[name = string("second_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40176960)))];
            tensor<fp16, [512]> second_bias_0_to_fp16 = const()[name = string("second_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42274176)))];
            tensor<fp16, [1, 512, 3072]> second_cast_fp16 = conv(bias = second_bias_0_to_fp16, dilations = second_123_dilations_0, groups = second_123_groups_0, pad = second_123_pad_0, pad_type = second_123_pad_type_0, strides = second_123_strides_0, weight = second_weight_0_to_fp16, x = input_103_cast_fp16)[name = string("second_cast_fp16")];
            tensor<fp16, [1, 512, 3072]> input_105_cast_fp16 = add(x = input_95_cast_fp16, y = second_cast_fp16)[name = string("input_105_cast_fp16")];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_running_mean_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42275264)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_running_var_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42276352)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_weight_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42277440)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_bias_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42278528)))];
            fp16 var_951_to_fp16 = const()[name = string("op_951_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 512, 3072]> input_107_cast_fp16 = batch_norm(beta = decoder_final_norm_BatchNormalization_bias_to_fp16, epsilon = var_951_to_fp16, gamma = decoder_final_norm_BatchNormalization_weight_to_fp16, mean = decoder_final_norm_BatchNormalization_running_mean_to_fp16, variance = decoder_final_norm_BatchNormalization_running_var_to_fp16, x = input_105_cast_fp16)[name = string("input_107_cast_fp16")];
            tensor<int32, [6]> input_109_pad_0 = const()[name = string("input_109_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 0])];
            string input_109_mode_0 = const()[name = string("input_109_mode_0"), val = string("replicate")];
            fp16 const_18_to_fp16 = const()[name = string("const_18_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 3074]> input_109_cast_fp16 = pad(constant_val = const_18_to_fp16, mode = input_109_mode_0, pad = input_109_pad_0, x = input_107_cast_fp16)[name = string("input_109_cast_fp16")];
            string input_tensor_177_pad_type_0 = const()[name = string("input_tensor_177_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_177_strides_0 = const()[name = string("input_tensor_177_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_177_pad_0 = const()[name = string("input_tensor_177_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_177_dilations_0 = const()[name = string("input_tensor_177_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_177_groups_0 = const()[name = string("input_tensor_177_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 3]> decoder_head_layer1_net_Conv_weight_to_fp16 = const()[name = string("decoder_head_layer1_net_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42279616)))];
            tensor<fp16, [2048]> decoder_head_layer1_net_Conv_bias_to_fp16 = const()[name = string("decoder_head_layer1_net_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48571136)))];
            tensor<fp16, [1, 2048, 3072]> input_tensor_177_cast_fp16 = conv(bias = decoder_head_layer1_net_Conv_bias_to_fp16, dilations = input_tensor_177_dilations_0, groups = input_tensor_177_groups_0, pad = input_tensor_177_pad_0, pad_type = input_tensor_177_pad_type_0, strides = input_tensor_177_strides_0, weight = decoder_head_layer1_net_Conv_weight_to_fp16, x = input_109_cast_fp16)[name = string("input_tensor_177_cast_fp16")];
            fp32 input_alpha_1 = const()[name = string("input_alpha_1"), val = fp32(0x1.9814fap-13)];
            tensor<fp16, [1, 2048, 3072]> input_cast_fp16 = leaky_relu(alpha = input_alpha_1, x = input_tensor_177_cast_fp16)[name = string("input_cast_fp16")];
            string input_tensor_179_pad_type_0 = const()[name = string("input_tensor_179_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_179_strides_0 = const()[name = string("input_tensor_179_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_179_pad_0 = const()[name = string("input_tensor_179_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_179_dilations_0 = const()[name = string("input_tensor_179_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_179_groups_0 = const()[name = string("input_tensor_179_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> decoder_head_layer2_Conv_weight_to_fp16 = const()[name = string("decoder_head_layer2_Conv_weight_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48575296)))];
            tensor<fp16, [1, 512, 3072]> input_tensor_179_cast_fp16 = conv(dilations = input_tensor_179_dilations_0, groups = input_tensor_179_groups_0, pad = input_tensor_179_pad_0, pad_type = input_tensor_179_pad_type_0, strides = input_tensor_179_strides_0, weight = decoder_head_layer2_Conv_weight_to_fp16, x = input_cast_fp16)[name = string("input_tensor_179_cast_fp16")];
            tensor<int32, [3]> var_994 = const()[name = string("op_994"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [2]> var_1021 = const()[name = string("op_1021"), val = tensor<int32, [2]>([1, -1])];
            tensor<fp16, [1, 3072, 512]> input_tensor_181_cast_fp16 = transpose(perm = var_994, x = input_tensor_179_cast_fp16)[name = string("transpose_0")];
            tensor<fp16, [1, 1572864]> wav_tts = reshape(shape = var_1021, x = input_tensor_181_cast_fp16)[name = string("op_1022_cast_fp16")];
        } -> (wav_tts);
    func vocoder_l64<ios18>(tensor<fp16, [1, 144, 64]> latent) {
            fp16 _inversed_input_tensor_1_y_0_to_fp16 = const()[name = string("_inversed_input_tensor_1_y_0_to_fp16"), val = fp16(0x1p+2)];
            tensor<fp16, [1, 144, 64]> _inversed_input_tensor_1_cast_fp16 = mul(x = latent, y = _inversed_input_tensor_1_y_0_to_fp16)[name = string("_inversed_input_tensor_1_cast_fp16")];
            tensor<int32, [4]> var_213 = const()[name = string("op_213"), val = tensor<int32, [4]>([1, -1, 6, 64])];
            tensor<fp16, [1, 24, 6, 64]> input_tensor_9_cast_fp16 = reshape(shape = var_213, x = _inversed_input_tensor_1_cast_fp16)[name = string("input_tensor_9_cast_fp16")];
            tensor<int32, [4]> var_219 = const()[name = string("op_219"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_264 = const()[name = string("op_264"), val = tensor<int32, [3]>([1, 24, -1])];
            tensor<fp16, [1, 24, 64, 6]> input_tensor_11_cast_fp16 = transpose(perm = var_219, x = input_tensor_9_cast_fp16)[name = string("transpose_21")];
            tensor<fp16, [1, 24, 384]> first_1_cast_fp16 = reshape(shape = var_264, x = input_tensor_11_cast_fp16)[name = string("first_1_cast_fp16")];
            tensor<fp16, [1, 24, 1]> initializers_onnx_initializer_1_to_fp16 = const()[name = string("initializers_onnx_initializer_1_to_fp16"), val = tensor<fp16, [1, 24, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [1, 24, 384]> first_3_cast_fp16 = mul(x = first_1_cast_fp16, y = initializers_onnx_initializer_1_to_fp16)[name = string("first_3_cast_fp16")];
            tensor<fp16, [1, 24, 1]> initializers_onnx_initializer_2_to_fp16 = const()[name = string("initializers_onnx_initializer_2_to_fp16"), val = tensor<fp16, [1, 24, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192)))];
            tensor<fp16, [1, 24, 384]> input_1_cast_fp16 = add(x = first_3_cast_fp16, y = initializers_onnx_initializer_2_to_fp16)[name = string("input_1_cast_fp16")];
            tensor<int32, [6]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("replicate")];
            fp16 const_7_to_fp16 = const()[name = string("const_7_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 24, 390]> input_3_cast_fp16 = pad(constant_val = const_7_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string input_5_pad_type_0 = const()[name = string("input_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_5_strides_0 = const()[name = string("input_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_5_pad_0 = const()[name = string("input_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_5_dilations_0 = const()[name = string("input_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_5_groups_0 = const()[name = string("input_5_groups_0"), val = int32(1)];
            tensor<fp16, [512, 24, 7]> decoder_embed_net_Conv_weight_to_fp16 = const()[name = string("decoder_embed_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 24, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(320)))];
            tensor<fp16, [512]> decoder_embed_net_Conv_bias_to_fp16 = const()[name = string("decoder_embed_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(172416)))];
            tensor<fp16, [1, 512, 384]> input_5_cast_fp16 = conv(bias = decoder_embed_net_Conv_bias_to_fp16, dilations = input_5_dilations_0, groups = input_5_groups_0, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = input_5_strides_0, weight = decoder_embed_net_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = string("input_5_cast_fp16")];
            tensor<int32, [6]> input_7_pad_0 = const()[name = string("input_7_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_7_mode_0 = const()[name = string("input_7_mode_0"), val = string("replicate")];
            fp16 const_8_to_fp16 = const()[name = string("const_8_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 390]> input_7_cast_fp16 = pad(constant_val = const_8_to_fp16, mode = input_7_mode_0, pad = input_7_pad_0, x = input_5_cast_fp16)[name = string("input_7_cast_fp16")];
            string input_tensor_37_pad_type_0 = const()[name = string("input_tensor_37_pad_type_0"), val = string("valid")];
            int32 input_tensor_37_groups_0 = const()[name = string("input_tensor_37_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_37_strides_0 = const()[name = string("input_tensor_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_37_pad_0 = const()[name = string("input_tensor_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_37_dilations_0 = const()[name = string("input_tensor_37_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_0_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_0_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(173504)))];
            tensor<fp16, [512]> decoder_convnext_0_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_0_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(180736)))];
            tensor<fp16, [1, 512, 384]> input_tensor_37_cast_fp16 = conv(bias = decoder_convnext_0_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_37_dilations_0, groups = input_tensor_37_groups_0, pad = input_tensor_37_pad_0, pad_type = input_tensor_37_pad_type_0, strides = input_tensor_37_strides_0, weight = decoder_convnext_0_dwconv_net_Conv_weight_to_fp16, x = input_7_cast_fp16)[name = string("input_tensor_37_cast_fp16")];
            tensor<int32, [3]> var_307 = const()[name = string("op_307"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_39_axes_0 = const()[name = string("input_tensor_39_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(181824)))];
            tensor<fp16, [512]> decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(182912)))];
            fp16 var_310_to_fp16 = const()[name = string("op_310_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 384, 512]> input_9_cast_fp16 = transpose(perm = var_307, x = input_tensor_37_cast_fp16)[name = string("transpose_20")];
            tensor<fp16, [1, 384, 512]> input_tensor_39_cast_fp16 = layer_norm(axes = input_tensor_39_axes_0, beta = decoder_convnext_0_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_310_to_fp16, gamma = decoder_convnext_0_norm_norm_LayerNormalization_weight_to_fp16, x = input_9_cast_fp16)[name = string("input_tensor_39_cast_fp16")];
            tensor<int32, [3]> var_319 = const()[name = string("op_319"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_5_pad_type_0 = const()[name = string("first_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_5_strides_0 = const()[name = string("first_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_5_pad_0 = const()[name = string("first_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_5_dilations_0 = const()[name = string("first_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_5_groups_0 = const()[name = string("first_5_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_0_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_0_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(184000)))];
            tensor<fp16, [2048]> decoder_convnext_0_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_0_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2281216)))];
            tensor<fp16, [1, 512, 384]> input_11_cast_fp16 = transpose(perm = var_319, x = input_tensor_39_cast_fp16)[name = string("transpose_19")];
            tensor<fp16, [1, 2048, 384]> first_5_cast_fp16 = conv(bias = decoder_convnext_0_pwconv1_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = decoder_convnext_0_pwconv1_Conv_weight_to_fp16, x = input_11_cast_fp16)[name = string("first_5_cast_fp16")];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 384]> input_13_cast_fp16 = gelu(mode = input_13_mode_0, x = first_5_cast_fp16)[name = string("input_13_cast_fp16")];
            string second_15_pad_type_0 = const()[name = string("second_15_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_15_strides_0 = const()[name = string("second_15_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_15_pad_0 = const()[name = string("second_15_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_15_dilations_0 = const()[name = string("second_15_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_15_groups_0 = const()[name = string("second_15_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_17_weight_0_to_fp16 = const()[name = string("second_17_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2285376)))];
            tensor<fp16, [512]> second_17_bias_0_to_fp16 = const()[name = string("second_17_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4382592)))];
            tensor<fp16, [1, 512, 384]> second_17_cast_fp16 = conv(bias = second_17_bias_0_to_fp16, dilations = second_15_dilations_0, groups = second_15_groups_0, pad = second_15_pad_0, pad_type = second_15_pad_type_0, strides = second_15_strides_0, weight = second_17_weight_0_to_fp16, x = input_13_cast_fp16)[name = string("second_17_cast_fp16")];
            tensor<fp16, [1, 512, 384]> input_15_cast_fp16 = add(x = input_5_cast_fp16, y = second_17_cast_fp16)[name = string("input_15_cast_fp16")];
            tensor<int32, [6]> input_17_pad_0 = const()[name = string("input_17_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 12, 0])];
            string input_17_mode_0 = const()[name = string("input_17_mode_0"), val = string("replicate")];
            fp16 const_9_to_fp16 = const()[name = string("const_9_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 396]> input_17_cast_fp16 = pad(constant_val = const_9_to_fp16, mode = input_17_mode_0, pad = input_17_pad_0, x = input_15_cast_fp16)[name = string("input_17_cast_fp16")];
            string input_tensor_51_pad_type_0 = const()[name = string("input_tensor_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_51_dilations_0 = const()[name = string("input_tensor_51_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 input_tensor_51_groups_0 = const()[name = string("input_tensor_51_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_51_strides_0 = const()[name = string("input_tensor_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_51_pad_0 = const()[name = string("input_tensor_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_1_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_1_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4383680)))];
            tensor<fp16, [512]> decoder_convnext_1_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_1_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4390912)))];
            tensor<fp16, [1, 512, 384]> input_tensor_51_cast_fp16 = conv(bias = decoder_convnext_1_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_51_dilations_0, groups = input_tensor_51_groups_0, pad = input_tensor_51_pad_0, pad_type = input_tensor_51_pad_type_0, strides = input_tensor_51_strides_0, weight = decoder_convnext_1_dwconv_net_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = string("input_tensor_51_cast_fp16")];
            tensor<int32, [3]> var_374 = const()[name = string("op_374"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_53_axes_0 = const()[name = string("input_tensor_53_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4392000)))];
            tensor<fp16, [512]> decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4393088)))];
            fp16 var_377_to_fp16 = const()[name = string("op_377_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 384, 512]> input_19_cast_fp16 = transpose(perm = var_374, x = input_tensor_51_cast_fp16)[name = string("transpose_18")];
            tensor<fp16, [1, 384, 512]> input_tensor_53_cast_fp16 = layer_norm(axes = input_tensor_53_axes_0, beta = decoder_convnext_1_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_377_to_fp16, gamma = decoder_convnext_1_norm_norm_LayerNormalization_weight_to_fp16, x = input_19_cast_fp16)[name = string("input_tensor_53_cast_fp16")];
            tensor<int32, [3]> var_386 = const()[name = string("op_386"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_13_pad_type_0 = const()[name = string("first_13_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_13_strides_0 = const()[name = string("first_13_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_13_pad_0 = const()[name = string("first_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_13_dilations_0 = const()[name = string("first_13_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_13_groups_0 = const()[name = string("first_13_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_1_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_1_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4394176)))];
            tensor<fp16, [2048]> decoder_convnext_1_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_1_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6491392)))];
            tensor<fp16, [1, 512, 384]> input_21_cast_fp16 = transpose(perm = var_386, x = input_tensor_53_cast_fp16)[name = string("transpose_17")];
            tensor<fp16, [1, 2048, 384]> first_13_cast_fp16 = conv(bias = decoder_convnext_1_pwconv1_Conv_bias_to_fp16, dilations = first_13_dilations_0, groups = first_13_groups_0, pad = first_13_pad_0, pad_type = first_13_pad_type_0, strides = first_13_strides_0, weight = decoder_convnext_1_pwconv1_Conv_weight_to_fp16, x = input_21_cast_fp16)[name = string("first_13_cast_fp16")];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 384]> input_23_cast_fp16 = gelu(mode = input_23_mode_0, x = first_13_cast_fp16)[name = string("input_23_cast_fp16")];
            string second_27_pad_type_0 = const()[name = string("second_27_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_27_strides_0 = const()[name = string("second_27_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_27_pad_0 = const()[name = string("second_27_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_27_dilations_0 = const()[name = string("second_27_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_27_groups_0 = const()[name = string("second_27_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_29_weight_0_to_fp16 = const()[name = string("second_29_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6495552)))];
            tensor<fp16, [512]> second_29_bias_0_to_fp16 = const()[name = string("second_29_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8592768)))];
            tensor<fp16, [1, 512, 384]> second_29_cast_fp16 = conv(bias = second_29_bias_0_to_fp16, dilations = second_27_dilations_0, groups = second_27_groups_0, pad = second_27_pad_0, pad_type = second_27_pad_type_0, strides = second_27_strides_0, weight = second_29_weight_0_to_fp16, x = input_23_cast_fp16)[name = string("second_29_cast_fp16")];
            tensor<fp16, [1, 512, 384]> input_25_cast_fp16 = add(x = input_15_cast_fp16, y = second_29_cast_fp16)[name = string("input_25_cast_fp16")];
            tensor<int32, [6]> input_27_pad_0 = const()[name = string("input_27_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 24, 0])];
            string input_27_mode_0 = const()[name = string("input_27_mode_0"), val = string("replicate")];
            fp16 const_10_to_fp16 = const()[name = string("const_10_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 408]> input_27_cast_fp16 = pad(constant_val = const_10_to_fp16, mode = input_27_mode_0, pad = input_27_pad_0, x = input_25_cast_fp16)[name = string("input_27_cast_fp16")];
            string input_tensor_65_pad_type_0 = const()[name = string("input_tensor_65_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_65_dilations_0 = const()[name = string("input_tensor_65_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 input_tensor_65_groups_0 = const()[name = string("input_tensor_65_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_65_strides_0 = const()[name = string("input_tensor_65_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_65_pad_0 = const()[name = string("input_tensor_65_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_2_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_2_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8593856)))];
            tensor<fp16, [512]> decoder_convnext_2_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_2_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8601088)))];
            tensor<fp16, [1, 512, 384]> input_tensor_65_cast_fp16 = conv(bias = decoder_convnext_2_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_65_dilations_0, groups = input_tensor_65_groups_0, pad = input_tensor_65_pad_0, pad_type = input_tensor_65_pad_type_0, strides = input_tensor_65_strides_0, weight = decoder_convnext_2_dwconv_net_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = string("input_tensor_65_cast_fp16")];
            tensor<int32, [3]> var_441 = const()[name = string("op_441"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_67_axes_0 = const()[name = string("input_tensor_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8602176)))];
            tensor<fp16, [512]> decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8603264)))];
            fp16 var_444_to_fp16 = const()[name = string("op_444_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 384, 512]> input_29_cast_fp16 = transpose(perm = var_441, x = input_tensor_65_cast_fp16)[name = string("transpose_16")];
            tensor<fp16, [1, 384, 512]> input_tensor_67_cast_fp16 = layer_norm(axes = input_tensor_67_axes_0, beta = decoder_convnext_2_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_444_to_fp16, gamma = decoder_convnext_2_norm_norm_LayerNormalization_weight_to_fp16, x = input_29_cast_fp16)[name = string("input_tensor_67_cast_fp16")];
            tensor<int32, [3]> var_453 = const()[name = string("op_453"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_21_pad_type_0 = const()[name = string("first_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_21_strides_0 = const()[name = string("first_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_21_pad_0 = const()[name = string("first_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_21_dilations_0 = const()[name = string("first_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_21_groups_0 = const()[name = string("first_21_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_2_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_2_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8604352)))];
            tensor<fp16, [2048]> decoder_convnext_2_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_2_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10701568)))];
            tensor<fp16, [1, 512, 384]> input_31_cast_fp16 = transpose(perm = var_453, x = input_tensor_67_cast_fp16)[name = string("transpose_15")];
            tensor<fp16, [1, 2048, 384]> first_21_cast_fp16 = conv(bias = decoder_convnext_2_pwconv1_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = decoder_convnext_2_pwconv1_Conv_weight_to_fp16, x = input_31_cast_fp16)[name = string("first_21_cast_fp16")];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 384]> input_33_cast_fp16 = gelu(mode = input_33_mode_0, x = first_21_cast_fp16)[name = string("input_33_cast_fp16")];
            string second_39_pad_type_0 = const()[name = string("second_39_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_39_strides_0 = const()[name = string("second_39_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_39_pad_0 = const()[name = string("second_39_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_39_dilations_0 = const()[name = string("second_39_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_39_groups_0 = const()[name = string("second_39_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_41_weight_0_to_fp16 = const()[name = string("second_41_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10705728)))];
            tensor<fp16, [512]> second_41_bias_0_to_fp16 = const()[name = string("second_41_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12802944)))];
            tensor<fp16, [1, 512, 384]> second_41_cast_fp16 = conv(bias = second_41_bias_0_to_fp16, dilations = second_39_dilations_0, groups = second_39_groups_0, pad = second_39_pad_0, pad_type = second_39_pad_type_0, strides = second_39_strides_0, weight = second_41_weight_0_to_fp16, x = input_33_cast_fp16)[name = string("second_41_cast_fp16")];
            tensor<fp16, [1, 512, 384]> input_35_cast_fp16 = add(x = input_25_cast_fp16, y = second_41_cast_fp16)[name = string("input_35_cast_fp16")];
            tensor<int32, [6]> input_37_pad_0 = const()[name = string("input_37_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_37_mode_0 = const()[name = string("input_37_mode_0"), val = string("replicate")];
            fp16 const_11_to_fp16 = const()[name = string("const_11_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 390]> input_37_cast_fp16 = pad(constant_val = const_11_to_fp16, mode = input_37_mode_0, pad = input_37_pad_0, x = input_35_cast_fp16)[name = string("input_37_cast_fp16")];
            string input_tensor_79_pad_type_0 = const()[name = string("input_tensor_79_pad_type_0"), val = string("valid")];
            int32 input_tensor_79_groups_0 = const()[name = string("input_tensor_79_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_79_strides_0 = const()[name = string("input_tensor_79_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_79_pad_0 = const()[name = string("input_tensor_79_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_79_dilations_0 = const()[name = string("input_tensor_79_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_3_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_3_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12804032)))];
            tensor<fp16, [512]> decoder_convnext_3_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_3_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12811264)))];
            tensor<fp16, [1, 512, 384]> input_tensor_79_cast_fp16 = conv(bias = decoder_convnext_3_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_79_dilations_0, groups = input_tensor_79_groups_0, pad = input_tensor_79_pad_0, pad_type = input_tensor_79_pad_type_0, strides = input_tensor_79_strides_0, weight = decoder_convnext_3_dwconv_net_Conv_weight_to_fp16, x = input_37_cast_fp16)[name = string("input_tensor_79_cast_fp16")];
            tensor<int32, [3]> var_507 = const()[name = string("op_507"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_81_axes_0 = const()[name = string("input_tensor_81_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12812352)))];
            tensor<fp16, [512]> decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12813440)))];
            fp16 var_510_to_fp16 = const()[name = string("op_510_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 384, 512]> input_39_cast_fp16 = transpose(perm = var_507, x = input_tensor_79_cast_fp16)[name = string("transpose_14")];
            tensor<fp16, [1, 384, 512]> input_tensor_81_cast_fp16 = layer_norm(axes = input_tensor_81_axes_0, beta = decoder_convnext_3_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_510_to_fp16, gamma = decoder_convnext_3_norm_norm_LayerNormalization_weight_to_fp16, x = input_39_cast_fp16)[name = string("input_tensor_81_cast_fp16")];
            tensor<int32, [3]> var_519 = const()[name = string("op_519"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_29_pad_type_0 = const()[name = string("first_29_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_29_strides_0 = const()[name = string("first_29_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_29_pad_0 = const()[name = string("first_29_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_29_dilations_0 = const()[name = string("first_29_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_29_groups_0 = const()[name = string("first_29_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_3_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_3_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12814528)))];
            tensor<fp16, [2048]> decoder_convnext_3_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_3_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14911744)))];
            tensor<fp16, [1, 512, 384]> input_41_cast_fp16 = transpose(perm = var_519, x = input_tensor_81_cast_fp16)[name = string("transpose_13")];
            tensor<fp16, [1, 2048, 384]> first_29_cast_fp16 = conv(bias = decoder_convnext_3_pwconv1_Conv_bias_to_fp16, dilations = first_29_dilations_0, groups = first_29_groups_0, pad = first_29_pad_0, pad_type = first_29_pad_type_0, strides = first_29_strides_0, weight = decoder_convnext_3_pwconv1_Conv_weight_to_fp16, x = input_41_cast_fp16)[name = string("first_29_cast_fp16")];
            string input_43_mode_0 = const()[name = string("input_43_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 384]> input_43_cast_fp16 = gelu(mode = input_43_mode_0, x = first_29_cast_fp16)[name = string("input_43_cast_fp16")];
            string second_51_pad_type_0 = const()[name = string("second_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_51_strides_0 = const()[name = string("second_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_51_pad_0 = const()[name = string("second_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_51_dilations_0 = const()[name = string("second_51_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_51_groups_0 = const()[name = string("second_51_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_53_weight_0_to_fp16 = const()[name = string("second_53_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14915904)))];
            tensor<fp16, [512]> second_53_bias_0_to_fp16 = const()[name = string("second_53_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17013120)))];
            tensor<fp16, [1, 512, 384]> second_53_cast_fp16 = conv(bias = second_53_bias_0_to_fp16, dilations = second_51_dilations_0, groups = second_51_groups_0, pad = second_51_pad_0, pad_type = second_51_pad_type_0, strides = second_51_strides_0, weight = second_53_weight_0_to_fp16, x = input_43_cast_fp16)[name = string("second_53_cast_fp16")];
            tensor<fp16, [1, 512, 384]> input_45_cast_fp16 = add(x = input_35_cast_fp16, y = second_53_cast_fp16)[name = string("input_45_cast_fp16")];
            tensor<int32, [6]> input_47_pad_0 = const()[name = string("input_47_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 12, 0])];
            string input_47_mode_0 = const()[name = string("input_47_mode_0"), val = string("replicate")];
            fp16 const_12_to_fp16 = const()[name = string("const_12_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 396]> input_47_cast_fp16 = pad(constant_val = const_12_to_fp16, mode = input_47_mode_0, pad = input_47_pad_0, x = input_45_cast_fp16)[name = string("input_47_cast_fp16")];
            string input_tensor_93_pad_type_0 = const()[name = string("input_tensor_93_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_93_dilations_0 = const()[name = string("input_tensor_93_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 input_tensor_93_groups_0 = const()[name = string("input_tensor_93_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_93_strides_0 = const()[name = string("input_tensor_93_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_93_pad_0 = const()[name = string("input_tensor_93_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_4_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_4_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17014208)))];
            tensor<fp16, [512]> decoder_convnext_4_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_4_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17021440)))];
            tensor<fp16, [1, 512, 384]> input_tensor_93_cast_fp16 = conv(bias = decoder_convnext_4_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_93_dilations_0, groups = input_tensor_93_groups_0, pad = input_tensor_93_pad_0, pad_type = input_tensor_93_pad_type_0, strides = input_tensor_93_strides_0, weight = decoder_convnext_4_dwconv_net_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("input_tensor_93_cast_fp16")];
            tensor<int32, [3]> var_574 = const()[name = string("op_574"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_95_axes_0 = const()[name = string("input_tensor_95_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17022528)))];
            tensor<fp16, [512]> decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17023616)))];
            fp16 var_577_to_fp16 = const()[name = string("op_577_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 384, 512]> input_49_cast_fp16 = transpose(perm = var_574, x = input_tensor_93_cast_fp16)[name = string("transpose_12")];
            tensor<fp16, [1, 384, 512]> input_tensor_95_cast_fp16 = layer_norm(axes = input_tensor_95_axes_0, beta = decoder_convnext_4_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_577_to_fp16, gamma = decoder_convnext_4_norm_norm_LayerNormalization_weight_to_fp16, x = input_49_cast_fp16)[name = string("input_tensor_95_cast_fp16")];
            tensor<int32, [3]> var_586 = const()[name = string("op_586"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_37_pad_type_0 = const()[name = string("first_37_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_37_strides_0 = const()[name = string("first_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_37_pad_0 = const()[name = string("first_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_37_dilations_0 = const()[name = string("first_37_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_37_groups_0 = const()[name = string("first_37_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_4_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_4_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17024704)))];
            tensor<fp16, [2048]> decoder_convnext_4_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_4_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19121920)))];
            tensor<fp16, [1, 512, 384]> input_51_cast_fp16 = transpose(perm = var_586, x = input_tensor_95_cast_fp16)[name = string("transpose_11")];
            tensor<fp16, [1, 2048, 384]> first_37_cast_fp16 = conv(bias = decoder_convnext_4_pwconv1_Conv_bias_to_fp16, dilations = first_37_dilations_0, groups = first_37_groups_0, pad = first_37_pad_0, pad_type = first_37_pad_type_0, strides = first_37_strides_0, weight = decoder_convnext_4_pwconv1_Conv_weight_to_fp16, x = input_51_cast_fp16)[name = string("first_37_cast_fp16")];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 384]> input_53_cast_fp16 = gelu(mode = input_53_mode_0, x = first_37_cast_fp16)[name = string("input_53_cast_fp16")];
            string second_63_pad_type_0 = const()[name = string("second_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_63_strides_0 = const()[name = string("second_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_63_pad_0 = const()[name = string("second_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_63_dilations_0 = const()[name = string("second_63_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_63_groups_0 = const()[name = string("second_63_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_65_weight_0_to_fp16 = const()[name = string("second_65_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19126080)))];
            tensor<fp16, [512]> second_65_bias_0_to_fp16 = const()[name = string("second_65_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21223296)))];
            tensor<fp16, [1, 512, 384]> second_65_cast_fp16 = conv(bias = second_65_bias_0_to_fp16, dilations = second_63_dilations_0, groups = second_63_groups_0, pad = second_63_pad_0, pad_type = second_63_pad_type_0, strides = second_63_strides_0, weight = second_65_weight_0_to_fp16, x = input_53_cast_fp16)[name = string("second_65_cast_fp16")];
            tensor<fp16, [1, 512, 384]> input_55_cast_fp16 = add(x = input_45_cast_fp16, y = second_65_cast_fp16)[name = string("input_55_cast_fp16")];
            tensor<int32, [6]> input_57_pad_0 = const()[name = string("input_57_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 24, 0])];
            string input_57_mode_0 = const()[name = string("input_57_mode_0"), val = string("replicate")];
            fp16 const_13_to_fp16 = const()[name = string("const_13_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 408]> input_57_cast_fp16 = pad(constant_val = const_13_to_fp16, mode = input_57_mode_0, pad = input_57_pad_0, x = input_55_cast_fp16)[name = string("input_57_cast_fp16")];
            string input_tensor_107_pad_type_0 = const()[name = string("input_tensor_107_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_107_dilations_0 = const()[name = string("input_tensor_107_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 input_tensor_107_groups_0 = const()[name = string("input_tensor_107_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_107_strides_0 = const()[name = string("input_tensor_107_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_107_pad_0 = const()[name = string("input_tensor_107_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_5_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_5_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21224384)))];
            tensor<fp16, [512]> decoder_convnext_5_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_5_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21231616)))];
            tensor<fp16, [1, 512, 384]> input_tensor_107_cast_fp16 = conv(bias = decoder_convnext_5_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_107_dilations_0, groups = input_tensor_107_groups_0, pad = input_tensor_107_pad_0, pad_type = input_tensor_107_pad_type_0, strides = input_tensor_107_strides_0, weight = decoder_convnext_5_dwconv_net_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = string("input_tensor_107_cast_fp16")];
            tensor<int32, [3]> var_641 = const()[name = string("op_641"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_109_axes_0 = const()[name = string("input_tensor_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21232704)))];
            tensor<fp16, [512]> decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21233792)))];
            fp16 var_644_to_fp16 = const()[name = string("op_644_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 384, 512]> input_59_cast_fp16 = transpose(perm = var_641, x = input_tensor_107_cast_fp16)[name = string("transpose_10")];
            tensor<fp16, [1, 384, 512]> input_tensor_109_cast_fp16 = layer_norm(axes = input_tensor_109_axes_0, beta = decoder_convnext_5_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_644_to_fp16, gamma = decoder_convnext_5_norm_norm_LayerNormalization_weight_to_fp16, x = input_59_cast_fp16)[name = string("input_tensor_109_cast_fp16")];
            tensor<int32, [3]> var_653 = const()[name = string("op_653"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_45_pad_type_0 = const()[name = string("first_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_45_strides_0 = const()[name = string("first_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_45_pad_0 = const()[name = string("first_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_45_dilations_0 = const()[name = string("first_45_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_45_groups_0 = const()[name = string("first_45_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_5_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_5_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21234880)))];
            tensor<fp16, [2048]> decoder_convnext_5_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_5_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23332096)))];
            tensor<fp16, [1, 512, 384]> input_61_cast_fp16 = transpose(perm = var_653, x = input_tensor_109_cast_fp16)[name = string("transpose_9")];
            tensor<fp16, [1, 2048, 384]> first_45_cast_fp16 = conv(bias = decoder_convnext_5_pwconv1_Conv_bias_to_fp16, dilations = first_45_dilations_0, groups = first_45_groups_0, pad = first_45_pad_0, pad_type = first_45_pad_type_0, strides = first_45_strides_0, weight = decoder_convnext_5_pwconv1_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("first_45_cast_fp16")];
            string input_63_mode_0 = const()[name = string("input_63_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 384]> input_63_cast_fp16 = gelu(mode = input_63_mode_0, x = first_45_cast_fp16)[name = string("input_63_cast_fp16")];
            string second_75_pad_type_0 = const()[name = string("second_75_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_75_strides_0 = const()[name = string("second_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_75_pad_0 = const()[name = string("second_75_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_75_dilations_0 = const()[name = string("second_75_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_75_groups_0 = const()[name = string("second_75_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_77_weight_0_to_fp16 = const()[name = string("second_77_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23336256)))];
            tensor<fp16, [512]> second_77_bias_0_to_fp16 = const()[name = string("second_77_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25433472)))];
            tensor<fp16, [1, 512, 384]> second_77_cast_fp16 = conv(bias = second_77_bias_0_to_fp16, dilations = second_75_dilations_0, groups = second_75_groups_0, pad = second_75_pad_0, pad_type = second_75_pad_type_0, strides = second_75_strides_0, weight = second_77_weight_0_to_fp16, x = input_63_cast_fp16)[name = string("second_77_cast_fp16")];
            tensor<fp16, [1, 512, 384]> input_65_cast_fp16 = add(x = input_55_cast_fp16, y = second_77_cast_fp16)[name = string("input_65_cast_fp16")];
            tensor<int32, [6]> input_67_pad_0 = const()[name = string("input_67_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_67_mode_0 = const()[name = string("input_67_mode_0"), val = string("replicate")];
            fp16 const_14_to_fp16 = const()[name = string("const_14_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 390]> input_67_cast_fp16 = pad(constant_val = const_14_to_fp16, mode = input_67_mode_0, pad = input_67_pad_0, x = input_65_cast_fp16)[name = string("input_67_cast_fp16")];
            string input_tensor_121_pad_type_0 = const()[name = string("input_tensor_121_pad_type_0"), val = string("valid")];
            int32 input_tensor_121_groups_0 = const()[name = string("input_tensor_121_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_121_strides_0 = const()[name = string("input_tensor_121_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_121_pad_0 = const()[name = string("input_tensor_121_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_121_dilations_0 = const()[name = string("input_tensor_121_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_6_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_6_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25434560)))];
            tensor<fp16, [512]> decoder_convnext_6_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_6_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25441792)))];
            tensor<fp16, [1, 512, 384]> input_tensor_121_cast_fp16 = conv(bias = decoder_convnext_6_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_121_dilations_0, groups = input_tensor_121_groups_0, pad = input_tensor_121_pad_0, pad_type = input_tensor_121_pad_type_0, strides = input_tensor_121_strides_0, weight = decoder_convnext_6_dwconv_net_Conv_weight_to_fp16, x = input_67_cast_fp16)[name = string("input_tensor_121_cast_fp16")];
            tensor<int32, [3]> var_707 = const()[name = string("op_707"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_123_axes_0 = const()[name = string("input_tensor_123_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25442880)))];
            tensor<fp16, [512]> decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25443968)))];
            fp16 var_710_to_fp16 = const()[name = string("op_710_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 384, 512]> input_69_cast_fp16 = transpose(perm = var_707, x = input_tensor_121_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 384, 512]> input_tensor_123_cast_fp16 = layer_norm(axes = input_tensor_123_axes_0, beta = decoder_convnext_6_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_710_to_fp16, gamma = decoder_convnext_6_norm_norm_LayerNormalization_weight_to_fp16, x = input_69_cast_fp16)[name = string("input_tensor_123_cast_fp16")];
            tensor<int32, [3]> var_719 = const()[name = string("op_719"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_53_pad_type_0 = const()[name = string("first_53_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_53_strides_0 = const()[name = string("first_53_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_53_pad_0 = const()[name = string("first_53_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_53_dilations_0 = const()[name = string("first_53_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_53_groups_0 = const()[name = string("first_53_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_6_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_6_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25445056)))];
            tensor<fp16, [2048]> decoder_convnext_6_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_6_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27542272)))];
            tensor<fp16, [1, 512, 384]> input_71_cast_fp16 = transpose(perm = var_719, x = input_tensor_123_cast_fp16)[name = string("transpose_7")];
            tensor<fp16, [1, 2048, 384]> first_53_cast_fp16 = conv(bias = decoder_convnext_6_pwconv1_Conv_bias_to_fp16, dilations = first_53_dilations_0, groups = first_53_groups_0, pad = first_53_pad_0, pad_type = first_53_pad_type_0, strides = first_53_strides_0, weight = decoder_convnext_6_pwconv1_Conv_weight_to_fp16, x = input_71_cast_fp16)[name = string("first_53_cast_fp16")];
            string input_73_mode_0 = const()[name = string("input_73_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 384]> input_73_cast_fp16 = gelu(mode = input_73_mode_0, x = first_53_cast_fp16)[name = string("input_73_cast_fp16")];
            string second_87_pad_type_0 = const()[name = string("second_87_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_87_strides_0 = const()[name = string("second_87_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_87_pad_0 = const()[name = string("second_87_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_87_dilations_0 = const()[name = string("second_87_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_87_groups_0 = const()[name = string("second_87_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_89_weight_0_to_fp16 = const()[name = string("second_89_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(27546432)))];
            tensor<fp16, [512]> second_89_bias_0_to_fp16 = const()[name = string("second_89_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29643648)))];
            tensor<fp16, [1, 512, 384]> second_89_cast_fp16 = conv(bias = second_89_bias_0_to_fp16, dilations = second_87_dilations_0, groups = second_87_groups_0, pad = second_87_pad_0, pad_type = second_87_pad_type_0, strides = second_87_strides_0, weight = second_89_weight_0_to_fp16, x = input_73_cast_fp16)[name = string("second_89_cast_fp16")];
            tensor<fp16, [1, 512, 384]> input_75_cast_fp16 = add(x = input_65_cast_fp16, y = second_89_cast_fp16)[name = string("input_75_cast_fp16")];
            tensor<int32, [6]> input_77_pad_0 = const()[name = string("input_77_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_77_mode_0 = const()[name = string("input_77_mode_0"), val = string("replicate")];
            fp16 const_15_to_fp16 = const()[name = string("const_15_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 390]> input_77_cast_fp16 = pad(constant_val = const_15_to_fp16, mode = input_77_mode_0, pad = input_77_pad_0, x = input_75_cast_fp16)[name = string("input_77_cast_fp16")];
            string input_tensor_135_pad_type_0 = const()[name = string("input_tensor_135_pad_type_0"), val = string("valid")];
            int32 input_tensor_135_groups_0 = const()[name = string("input_tensor_135_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_135_strides_0 = const()[name = string("input_tensor_135_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_135_pad_0 = const()[name = string("input_tensor_135_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_135_dilations_0 = const()[name = string("input_tensor_135_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_7_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_7_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29644736)))];
            tensor<fp16, [512]> decoder_convnext_7_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_7_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29651968)))];
            tensor<fp16, [1, 512, 384]> input_tensor_135_cast_fp16 = conv(bias = decoder_convnext_7_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_135_dilations_0, groups = input_tensor_135_groups_0, pad = input_tensor_135_pad_0, pad_type = input_tensor_135_pad_type_0, strides = input_tensor_135_strides_0, weight = decoder_convnext_7_dwconv_net_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = string("input_tensor_135_cast_fp16")];
            tensor<int32, [3]> var_773 = const()[name = string("op_773"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_137_axes_0 = const()[name = string("input_tensor_137_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29653056)))];
            tensor<fp16, [512]> decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29654144)))];
            fp16 var_776_to_fp16 = const()[name = string("op_776_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 384, 512]> input_79_cast_fp16 = transpose(perm = var_773, x = input_tensor_135_cast_fp16)[name = string("transpose_6")];
            tensor<fp16, [1, 384, 512]> input_tensor_137_cast_fp16 = layer_norm(axes = input_tensor_137_axes_0, beta = decoder_convnext_7_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_776_to_fp16, gamma = decoder_convnext_7_norm_norm_LayerNormalization_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_tensor_137_cast_fp16")];
            tensor<int32, [3]> var_785 = const()[name = string("op_785"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_61_pad_type_0 = const()[name = string("first_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_61_strides_0 = const()[name = string("first_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_61_pad_0 = const()[name = string("first_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_61_dilations_0 = const()[name = string("first_61_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_61_groups_0 = const()[name = string("first_61_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_7_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_7_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29655232)))];
            tensor<fp16, [2048]> decoder_convnext_7_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_7_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31752448)))];
            tensor<fp16, [1, 512, 384]> input_81_cast_fp16 = transpose(perm = var_785, x = input_tensor_137_cast_fp16)[name = string("transpose_5")];
            tensor<fp16, [1, 2048, 384]> first_61_cast_fp16 = conv(bias = decoder_convnext_7_pwconv1_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = decoder_convnext_7_pwconv1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = string("first_61_cast_fp16")];
            string input_83_mode_0 = const()[name = string("input_83_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 384]> input_83_cast_fp16 = gelu(mode = input_83_mode_0, x = first_61_cast_fp16)[name = string("input_83_cast_fp16")];
            string second_99_pad_type_0 = const()[name = string("second_99_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_99_strides_0 = const()[name = string("second_99_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_99_pad_0 = const()[name = string("second_99_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_99_dilations_0 = const()[name = string("second_99_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_99_groups_0 = const()[name = string("second_99_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_101_weight_0_to_fp16 = const()[name = string("second_101_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31756608)))];
            tensor<fp16, [512]> second_101_bias_0_to_fp16 = const()[name = string("second_101_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33853824)))];
            tensor<fp16, [1, 512, 384]> second_101_cast_fp16 = conv(bias = second_101_bias_0_to_fp16, dilations = second_99_dilations_0, groups = second_99_groups_0, pad = second_99_pad_0, pad_type = second_99_pad_type_0, strides = second_99_strides_0, weight = second_101_weight_0_to_fp16, x = input_83_cast_fp16)[name = string("second_101_cast_fp16")];
            tensor<fp16, [1, 512, 384]> input_85_cast_fp16 = add(x = input_75_cast_fp16, y = second_101_cast_fp16)[name = string("input_85_cast_fp16")];
            tensor<int32, [6]> input_87_pad_0 = const()[name = string("input_87_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_87_mode_0 = const()[name = string("input_87_mode_0"), val = string("replicate")];
            fp16 const_16_to_fp16 = const()[name = string("const_16_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 390]> input_87_cast_fp16 = pad(constant_val = const_16_to_fp16, mode = input_87_mode_0, pad = input_87_pad_0, x = input_85_cast_fp16)[name = string("input_87_cast_fp16")];
            string input_tensor_149_pad_type_0 = const()[name = string("input_tensor_149_pad_type_0"), val = string("valid")];
            int32 input_tensor_149_groups_0 = const()[name = string("input_tensor_149_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_149_strides_0 = const()[name = string("input_tensor_149_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_149_pad_0 = const()[name = string("input_tensor_149_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_149_dilations_0 = const()[name = string("input_tensor_149_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_8_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_8_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33854912)))];
            tensor<fp16, [512]> decoder_convnext_8_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_8_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33862144)))];
            tensor<fp16, [1, 512, 384]> input_tensor_149_cast_fp16 = conv(bias = decoder_convnext_8_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_149_dilations_0, groups = input_tensor_149_groups_0, pad = input_tensor_149_pad_0, pad_type = input_tensor_149_pad_type_0, strides = input_tensor_149_strides_0, weight = decoder_convnext_8_dwconv_net_Conv_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_tensor_149_cast_fp16")];
            tensor<int32, [3]> var_839 = const()[name = string("op_839"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_151_axes_0 = const()[name = string("input_tensor_151_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33863232)))];
            tensor<fp16, [512]> decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33864320)))];
            fp16 var_842_to_fp16 = const()[name = string("op_842_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 384, 512]> input_89_cast_fp16 = transpose(perm = var_839, x = input_tensor_149_cast_fp16)[name = string("transpose_4")];
            tensor<fp16, [1, 384, 512]> input_tensor_151_cast_fp16 = layer_norm(axes = input_tensor_151_axes_0, beta = decoder_convnext_8_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_842_to_fp16, gamma = decoder_convnext_8_norm_norm_LayerNormalization_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_151_cast_fp16")];
            tensor<int32, [3]> var_851 = const()[name = string("op_851"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_69_pad_type_0 = const()[name = string("first_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_69_strides_0 = const()[name = string("first_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_69_pad_0 = const()[name = string("first_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_69_dilations_0 = const()[name = string("first_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_69_groups_0 = const()[name = string("first_69_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_8_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_8_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33865408)))];
            tensor<fp16, [2048]> decoder_convnext_8_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_8_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35962624)))];
            tensor<fp16, [1, 512, 384]> input_91_cast_fp16 = transpose(perm = var_851, x = input_tensor_151_cast_fp16)[name = string("transpose_3")];
            tensor<fp16, [1, 2048, 384]> first_69_cast_fp16 = conv(bias = decoder_convnext_8_pwconv1_Conv_bias_to_fp16, dilations = first_69_dilations_0, groups = first_69_groups_0, pad = first_69_pad_0, pad_type = first_69_pad_type_0, strides = first_69_strides_0, weight = decoder_convnext_8_pwconv1_Conv_weight_to_fp16, x = input_91_cast_fp16)[name = string("first_69_cast_fp16")];
            string input_93_mode_0 = const()[name = string("input_93_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 384]> input_93_cast_fp16 = gelu(mode = input_93_mode_0, x = first_69_cast_fp16)[name = string("input_93_cast_fp16")];
            string second_111_pad_type_0 = const()[name = string("second_111_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_111_strides_0 = const()[name = string("second_111_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_111_pad_0 = const()[name = string("second_111_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_111_dilations_0 = const()[name = string("second_111_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_111_groups_0 = const()[name = string("second_111_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_113_weight_0_to_fp16 = const()[name = string("second_113_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35966784)))];
            tensor<fp16, [512]> second_113_bias_0_to_fp16 = const()[name = string("second_113_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38064000)))];
            tensor<fp16, [1, 512, 384]> second_113_cast_fp16 = conv(bias = second_113_bias_0_to_fp16, dilations = second_111_dilations_0, groups = second_111_groups_0, pad = second_111_pad_0, pad_type = second_111_pad_type_0, strides = second_111_strides_0, weight = second_113_weight_0_to_fp16, x = input_93_cast_fp16)[name = string("second_113_cast_fp16")];
            tensor<fp16, [1, 512, 384]> input_95_cast_fp16 = add(x = input_85_cast_fp16, y = second_113_cast_fp16)[name = string("input_95_cast_fp16")];
            tensor<int32, [6]> input_97_pad_0 = const()[name = string("input_97_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_97_mode_0 = const()[name = string("input_97_mode_0"), val = string("replicate")];
            fp16 const_17_to_fp16 = const()[name = string("const_17_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 390]> input_97_cast_fp16 = pad(constant_val = const_17_to_fp16, mode = input_97_mode_0, pad = input_97_pad_0, x = input_95_cast_fp16)[name = string("input_97_cast_fp16")];
            string input_tensor_163_pad_type_0 = const()[name = string("input_tensor_163_pad_type_0"), val = string("valid")];
            int32 input_tensor_163_groups_0 = const()[name = string("input_tensor_163_groups_0"), val = int32(512)];
            tensor<int32, [1]> input_tensor_163_strides_0 = const()[name = string("input_tensor_163_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_163_pad_0 = const()[name = string("input_tensor_163_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_163_dilations_0 = const()[name = string("input_tensor_163_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> decoder_convnext_9_dwconv_net_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_9_dwconv_net_Conv_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38065088)))];
            tensor<fp16, [512]> decoder_convnext_9_dwconv_net_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_9_dwconv_net_Conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38072320)))];
            tensor<fp16, [1, 512, 384]> input_tensor_163_cast_fp16 = conv(bias = decoder_convnext_9_dwconv_net_Conv_bias_to_fp16, dilations = input_tensor_163_dilations_0, groups = input_tensor_163_groups_0, pad = input_tensor_163_pad_0, pad_type = input_tensor_163_pad_type_0, strides = input_tensor_163_strides_0, weight = decoder_convnext_9_dwconv_net_Conv_weight_to_fp16, x = input_97_cast_fp16)[name = string("input_tensor_163_cast_fp16")];
            tensor<int32, [3]> var_905 = const()[name = string("op_905"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_165_axes_0 = const()[name = string("input_tensor_165_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38073408)))];
            tensor<fp16, [512]> decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38074496)))];
            fp16 var_908_to_fp16 = const()[name = string("op_908_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 384, 512]> input_99_cast_fp16 = transpose(perm = var_905, x = input_tensor_163_cast_fp16)[name = string("transpose_2")];
            tensor<fp16, [1, 384, 512]> input_tensor_165_cast_fp16 = layer_norm(axes = input_tensor_165_axes_0, beta = decoder_convnext_9_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_908_to_fp16, gamma = decoder_convnext_9_norm_norm_LayerNormalization_weight_to_fp16, x = input_99_cast_fp16)[name = string("input_tensor_165_cast_fp16")];
            tensor<int32, [3]> var_917 = const()[name = string("op_917"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_77_pad_type_0 = const()[name = string("first_77_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_77_strides_0 = const()[name = string("first_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_77_pad_0 = const()[name = string("first_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_77_dilations_0 = const()[name = string("first_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_77_groups_0 = const()[name = string("first_77_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 1]> decoder_convnext_9_pwconv1_Conv_weight_to_fp16 = const()[name = string("decoder_convnext_9_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38075584)))];
            tensor<fp16, [2048]> decoder_convnext_9_pwconv1_Conv_bias_to_fp16 = const()[name = string("decoder_convnext_9_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40172800)))];
            tensor<fp16, [1, 512, 384]> input_101_cast_fp16 = transpose(perm = var_917, x = input_tensor_165_cast_fp16)[name = string("transpose_1")];
            tensor<fp16, [1, 2048, 384]> first_77_cast_fp16 = conv(bias = decoder_convnext_9_pwconv1_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = decoder_convnext_9_pwconv1_Conv_weight_to_fp16, x = input_101_cast_fp16)[name = string("first_77_cast_fp16")];
            string input_103_mode_0 = const()[name = string("input_103_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2048, 384]> input_103_cast_fp16 = gelu(mode = input_103_mode_0, x = first_77_cast_fp16)[name = string("input_103_cast_fp16")];
            string second_123_pad_type_0 = const()[name = string("second_123_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_123_strides_0 = const()[name = string("second_123_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_123_pad_0 = const()[name = string("second_123_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_123_dilations_0 = const()[name = string("second_123_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_123_groups_0 = const()[name = string("second_123_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> second_weight_0_to_fp16 = const()[name = string("second_weight_0_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40176960)))];
            tensor<fp16, [512]> second_bias_0_to_fp16 = const()[name = string("second_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42274176)))];
            tensor<fp16, [1, 512, 384]> second_cast_fp16 = conv(bias = second_bias_0_to_fp16, dilations = second_123_dilations_0, groups = second_123_groups_0, pad = second_123_pad_0, pad_type = second_123_pad_type_0, strides = second_123_strides_0, weight = second_weight_0_to_fp16, x = input_103_cast_fp16)[name = string("second_cast_fp16")];
            tensor<fp16, [1, 512, 384]> input_105_cast_fp16 = add(x = input_95_cast_fp16, y = second_cast_fp16)[name = string("input_105_cast_fp16")];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_running_mean_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_running_mean_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42275264)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_running_var_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_running_var_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42276352)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_weight_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42277440)))];
            tensor<fp16, [512]> decoder_final_norm_BatchNormalization_bias_to_fp16 = const()[name = string("decoder_final_norm_BatchNormalization_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42278528)))];
            fp16 var_951_to_fp16 = const()[name = string("op_951_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 512, 384]> input_107_cast_fp16 = batch_norm(beta = decoder_final_norm_BatchNormalization_bias_to_fp16, epsilon = var_951_to_fp16, gamma = decoder_final_norm_BatchNormalization_weight_to_fp16, mean = decoder_final_norm_BatchNormalization_running_mean_to_fp16, variance = decoder_final_norm_BatchNormalization_running_var_to_fp16, x = input_105_cast_fp16)[name = string("input_107_cast_fp16")];
            tensor<int32, [6]> input_109_pad_0 = const()[name = string("input_109_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 0])];
            string input_109_mode_0 = const()[name = string("input_109_mode_0"), val = string("replicate")];
            fp16 const_18_to_fp16 = const()[name = string("const_18_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 512, 386]> input_109_cast_fp16 = pad(constant_val = const_18_to_fp16, mode = input_109_mode_0, pad = input_109_pad_0, x = input_107_cast_fp16)[name = string("input_109_cast_fp16")];
            string input_tensor_177_pad_type_0 = const()[name = string("input_tensor_177_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_177_strides_0 = const()[name = string("input_tensor_177_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_177_pad_0 = const()[name = string("input_tensor_177_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_177_dilations_0 = const()[name = string("input_tensor_177_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_177_groups_0 = const()[name = string("input_tensor_177_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 512, 3]> decoder_head_layer1_net_Conv_weight_to_fp16 = const()[name = string("decoder_head_layer1_net_Conv_weight_to_fp16"), val = tensor<fp16, [2048, 512, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42279616)))];
            tensor<fp16, [2048]> decoder_head_layer1_net_Conv_bias_to_fp16 = const()[name = string("decoder_head_layer1_net_Conv_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48571136)))];
            tensor<fp16, [1, 2048, 384]> input_tensor_177_cast_fp16 = conv(bias = decoder_head_layer1_net_Conv_bias_to_fp16, dilations = input_tensor_177_dilations_0, groups = input_tensor_177_groups_0, pad = input_tensor_177_pad_0, pad_type = input_tensor_177_pad_type_0, strides = input_tensor_177_strides_0, weight = decoder_head_layer1_net_Conv_weight_to_fp16, x = input_109_cast_fp16)[name = string("input_tensor_177_cast_fp16")];
            fp32 input_alpha_1 = const()[name = string("input_alpha_1"), val = fp32(0x1.9814fap-13)];
            tensor<fp16, [1, 2048, 384]> input_cast_fp16 = leaky_relu(alpha = input_alpha_1, x = input_tensor_177_cast_fp16)[name = string("input_cast_fp16")];
            string input_tensor_179_pad_type_0 = const()[name = string("input_tensor_179_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_179_strides_0 = const()[name = string("input_tensor_179_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_179_pad_0 = const()[name = string("input_tensor_179_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_179_dilations_0 = const()[name = string("input_tensor_179_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_179_groups_0 = const()[name = string("input_tensor_179_groups_0"), val = int32(1)];
            tensor<fp16, [512, 2048, 1]> decoder_head_layer2_Conv_weight_to_fp16 = const()[name = string("decoder_head_layer2_Conv_weight_to_fp16"), val = tensor<fp16, [512, 2048, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48575296)))];
            tensor<fp16, [1, 512, 384]> input_tensor_179_cast_fp16 = conv(dilations = input_tensor_179_dilations_0, groups = input_tensor_179_groups_0, pad = input_tensor_179_pad_0, pad_type = input_tensor_179_pad_type_0, strides = input_tensor_179_strides_0, weight = decoder_head_layer2_Conv_weight_to_fp16, x = input_cast_fp16)[name = string("input_tensor_179_cast_fp16")];
            tensor<int32, [3]> var_994 = const()[name = string("op_994"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [2]> var_1021 = const()[name = string("op_1021"), val = tensor<int32, [2]>([1, -1])];
            tensor<fp16, [1, 384, 512]> input_tensor_181_cast_fp16 = transpose(perm = var_994, x = input_tensor_179_cast_fp16)[name = string("transpose_0")];
            tensor<fp16, [1, 196608]> wav_tts = reshape(shape = var_1021, x = input_tensor_181_cast_fp16)[name = string("op_1022_cast_fp16")];
        } -> (wav_tts);
}