program(1.3)
[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3510.2.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-torch", "2.11.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0"}})]
{
    func main<ios18>(tensor<fp32, [1, 1, 10240]> audio, tensor<fp32, [1, 1, 6]> cache_0, tensor<fp32, [1, 128, 80]> cache_1, tensor<fp32, [1, 256, 83]> cache_2, tensor<fp32, [1, 512, 86]> cache_3, tensor<fp32, [1, 1024, 86]> cache_4, tensor<fp32, [1, 2048, 2]> cache_5) {
            int32 var_731 = const()[name = string("op_731"), val = int32(-1)];
            bool input_1_interleave_0 = const()[name = string("input_1_interleave_0"), val = bool(false)];
            string cache_0_to_fp16_dtype_0 = const()[name = string("cache_0_to_fp16_dtype_0"), val = string("fp16")];
            string audio_to_fp16_dtype_0 = const()[name = string("audio_to_fp16_dtype_0"), val = string("fp16")];
            tensor<fp16, [1, 1, 10240]> audio_to_fp16 = cast(dtype = audio_to_fp16_dtype_0, x = audio)[name = string("cast_12")];
            tensor<fp16, [1, 1, 6]> cache_0_to_fp16 = cast(dtype = cache_0_to_fp16_dtype_0, x = cache_0)[name = string("cast_13")];
            tensor<fp16, [1, 1, 10246]> input_1_cast_fp16 = concat(axis = var_731, interleave = input_1_interleave_0, values = (cache_0_to_fp16, audio_to_fp16))[name = string("input_1_cast_fp16")];
            string x_3_pad_type_0 = const()[name = string("x_3_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_3_strides_0 = const()[name = string("x_3_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_3_pad_0 = const()[name = string("x_3_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_3_dilations_0 = const()[name = string("x_3_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_3_groups_0 = const()[name = string("x_3_groups_0"), val = int32(1)];
            tensor<fp16, [128, 1, 7]> vae_encoder_block_0_weight_to_fp16 = const()[name = string("vae_encoder_block_0_weight_to_fp16"), val = tensor<fp16, [128, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [128]> vae_encoder_block_0_bias_to_fp16 = const()[name = string("vae_encoder_block_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1920)))];
            tensor<fp16, [1, 128, 10240]> x_3_cast_fp16 = conv(bias = vae_encoder_block_0_bias_to_fp16, dilations = x_3_dilations_0, groups = x_3_groups_0, pad = x_3_pad_0, pad_type = x_3_pad_type_0, strides = x_3_strides_0, weight = vae_encoder_block_0_weight_to_fp16, x = input_1_cast_fp16)[name = string("x_3_cast_fp16")];
            tensor<int32, [3]> var_752_begin_0 = const()[name = string("op_752_begin_0"), val = tensor<int32, [3]>([0, 0, 10240])];
            tensor<int32, [3]> var_752_end_0 = const()[name = string("op_752_end_0"), val = tensor<int32, [3]>([1, 1, 10246])];
            tensor<bool, [3]> var_752_end_mask_0 = const()[name = string("op_752_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 1, 6]> var_752_cast_fp16 = slice_by_index(begin = var_752_begin_0, end = var_752_end_0, end_mask = var_752_end_mask_0, x = input_1_cast_fp16)[name = string("op_752_cast_fp16")];
            string var_752_cast_fp16_to_fp32_dtype_0 = const()[name = string("op_752_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
            tensor<int32, [4]> var_757 = const()[name = string("op_757"), val = tensor<int32, [4]>([6, 18, 54, 2])];
            int32 var_759_axis_0 = const()[name = string("op_759_axis_0"), val = int32(-1)];
            string cache_1_to_fp16_dtype_0 = const()[name = string("cache_1_to_fp16_dtype_0"), val = string("fp16")];
            tensor<fp16, [1, 128, 80]> cache_1_to_fp16 = cast(dtype = cache_1_to_fp16_dtype_0, x = cache_1)[name = string("cast_10")];
            tensor<fp16, [1, 128, 6]> var_759_cast_fp16_0, tensor<fp16, [1, 128, 18]> var_759_cast_fp16_1, tensor<fp16, [1, 128, 54]> var_759_cast_fp16_2, tensor<fp16, [1, 128, 2]> var_759_cast_fp16_3 = split(axis = var_759_axis_0, split_sizes = var_757, x = cache_1_to_fp16)[name = string("op_759_cast_fp16")];
            tensor<fp16, [1, 128, 1]> vae_encoder_block_1_block_0_block_0_alpha_to_fp16 = const()[name = string("vae_encoder_block_1_block_0_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2240)))];
            tensor<fp16, [1, 128, 10240]> var_770_cast_fp16 = mul(x = vae_encoder_block_1_block_0_block_0_alpha_to_fp16, y = x_3_cast_fp16)[name = string("op_770_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> var_771_cast_fp16 = sin(x = var_770_cast_fp16)[name = string("op_771_cast_fp16")];
            fp16 var_764_promoted_to_fp16 = const()[name = string("op_764_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, 10240]> var_772_cast_fp16 = pow(x = var_771_cast_fp16, y = var_764_promoted_to_fp16)[name = string("op_772_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_769_to_fp16 = const()[name = string("op_769_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2560)))];
            tensor<fp16, [1, 128, 10240]> var_773_cast_fp16 = mul(x = var_769_to_fp16, y = var_772_cast_fp16)[name = string("op_773_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> x_5_cast_fp16 = add(x = x_3_cast_fp16, y = var_773_cast_fp16)[name = string("x_5_cast_fp16")];
            int32 var_776 = const()[name = string("op_776"), val = int32(-1)];
            bool input_3_interleave_0 = const()[name = string("input_3_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 128, 10246]> input_3_cast_fp16 = concat(axis = var_776, interleave = input_3_interleave_0, values = (var_759_cast_fp16_0, x_5_cast_fp16))[name = string("input_3_cast_fp16")];
            string x_7_pad_type_0 = const()[name = string("x_7_pad_type_0"), val = string("valid")];
            int32 x_7_groups_0 = const()[name = string("x_7_groups_0"), val = int32(128)];
            tensor<int32, [1]> x_7_strides_0 = const()[name = string("x_7_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_7_pad_0 = const()[name = string("x_7_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_7_dilations_0 = const()[name = string("x_7_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [128, 1, 7]> vae_encoder_block_1_block_0_block_1_weight_to_fp16 = const()[name = string("vae_encoder_block_1_block_0_block_1_weight_to_fp16"), val = tensor<fp16, [128, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2880)))];
            tensor<fp16, [128]> vae_encoder_block_1_block_0_block_1_bias_to_fp16 = const()[name = string("vae_encoder_block_1_block_0_block_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4736)))];
            tensor<fp16, [1, 128, 10240]> x_7_cast_fp16 = conv(bias = vae_encoder_block_1_block_0_block_1_bias_to_fp16, dilations = x_7_dilations_0, groups = x_7_groups_0, pad = x_7_pad_0, pad_type = x_7_pad_type_0, strides = x_7_strides_0, weight = vae_encoder_block_1_block_0_block_1_weight_to_fp16, x = input_3_cast_fp16)[name = string("x_7_cast_fp16")];
            tensor<int32, [3]> var_797_begin_0 = const()[name = string("op_797_begin_0"), val = tensor<int32, [3]>([0, 0, 10240])];
            tensor<int32, [3]> var_797_end_0 = const()[name = string("op_797_end_0"), val = tensor<int32, [3]>([1, 128, 10246])];
            tensor<bool, [3]> var_797_end_mask_0 = const()[name = string("op_797_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 128, 6]> var_797_cast_fp16 = slice_by_index(begin = var_797_begin_0, end = var_797_end_0, end_mask = var_797_end_mask_0, x = input_3_cast_fp16)[name = string("op_797_cast_fp16")];
            tensor<fp16, [1, 128, 1]> vae_encoder_block_1_block_0_block_2_alpha_to_fp16 = const()[name = string("vae_encoder_block_1_block_0_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5056)))];
            tensor<fp16, [1, 128, 10240]> var_804_cast_fp16 = mul(x = vae_encoder_block_1_block_0_block_2_alpha_to_fp16, y = x_7_cast_fp16)[name = string("op_804_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> var_805_cast_fp16 = sin(x = var_804_cast_fp16)[name = string("op_805_cast_fp16")];
            fp16 var_798_promoted_to_fp16 = const()[name = string("op_798_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, 10240]> var_806_cast_fp16 = pow(x = var_805_cast_fp16, y = var_798_promoted_to_fp16)[name = string("op_806_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_803_to_fp16 = const()[name = string("op_803_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5376)))];
            tensor<fp16, [1, 128, 10240]> var_807_cast_fp16 = mul(x = var_803_to_fp16, y = var_806_cast_fp16)[name = string("op_807_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> input_5_cast_fp16 = add(x = x_7_cast_fp16, y = var_807_cast_fp16)[name = string("input_5_cast_fp16")];
            string y_1_pad_type_0 = const()[name = string("y_1_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_1_strides_0 = const()[name = string("y_1_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_1_pad_0 = const()[name = string("y_1_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_1_dilations_0 = const()[name = string("y_1_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_1_groups_0 = const()[name = string("y_1_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1]> vae_encoder_block_1_block_0_block_3_weight_to_fp16 = const()[name = string("vae_encoder_block_1_block_0_block_3_weight_to_fp16"), val = tensor<fp16, [128, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5696)))];
            tensor<fp16, [128]> vae_encoder_block_1_block_0_block_3_bias_to_fp16 = const()[name = string("vae_encoder_block_1_block_0_block_3_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38528)))];
            tensor<fp16, [1, 128, 10240]> y_1_cast_fp16 = conv(bias = vae_encoder_block_1_block_0_block_3_bias_to_fp16, dilations = y_1_dilations_0, groups = y_1_groups_0, pad = y_1_pad_0, pad_type = y_1_pad_type_0, strides = y_1_strides_0, weight = vae_encoder_block_1_block_0_block_3_weight_to_fp16, x = input_5_cast_fp16)[name = string("y_1_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> x_9_cast_fp16 = add(x = x_3_cast_fp16, y = y_1_cast_fp16)[name = string("x_9_cast_fp16")];
            tensor<fp16, [1, 128, 1]> vae_encoder_block_1_block_1_block_0_alpha_to_fp16 = const()[name = string("vae_encoder_block_1_block_1_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38848)))];
            tensor<fp16, [1, 128, 10240]> var_832_cast_fp16 = mul(x = vae_encoder_block_1_block_1_block_0_alpha_to_fp16, y = x_9_cast_fp16)[name = string("op_832_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> var_833_cast_fp16 = sin(x = var_832_cast_fp16)[name = string("op_833_cast_fp16")];
            fp16 var_826_promoted_to_fp16 = const()[name = string("op_826_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, 10240]> var_834_cast_fp16 = pow(x = var_833_cast_fp16, y = var_826_promoted_to_fp16)[name = string("op_834_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_831_to_fp16 = const()[name = string("op_831_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39168)))];
            tensor<fp16, [1, 128, 10240]> var_835_cast_fp16 = mul(x = var_831_to_fp16, y = var_834_cast_fp16)[name = string("op_835_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> x_11_cast_fp16 = add(x = x_9_cast_fp16, y = var_835_cast_fp16)[name = string("x_11_cast_fp16")];
            int32 var_838 = const()[name = string("op_838"), val = int32(-1)];
            bool input_7_interleave_0 = const()[name = string("input_7_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 128, 10258]> input_7_cast_fp16 = concat(axis = var_838, interleave = input_7_interleave_0, values = (var_759_cast_fp16_1, x_11_cast_fp16))[name = string("input_7_cast_fp16")];
            string x_13_pad_type_0 = const()[name = string("x_13_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_13_dilations_0 = const()[name = string("x_13_dilations_0"), val = tensor<int32, [1]>([3])];
            int32 x_13_groups_0 = const()[name = string("x_13_groups_0"), val = int32(128)];
            tensor<int32, [1]> x_13_strides_0 = const()[name = string("x_13_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_13_pad_0 = const()[name = string("x_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [128, 1, 7]> vae_encoder_block_1_block_1_block_1_weight_to_fp16 = const()[name = string("vae_encoder_block_1_block_1_block_1_weight_to_fp16"), val = tensor<fp16, [128, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39488)))];
            tensor<fp16, [128]> vae_encoder_block_1_block_1_block_1_bias_to_fp16 = const()[name = string("vae_encoder_block_1_block_1_block_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41344)))];
            tensor<fp16, [1, 128, 10240]> x_13_cast_fp16 = conv(bias = vae_encoder_block_1_block_1_block_1_bias_to_fp16, dilations = x_13_dilations_0, groups = x_13_groups_0, pad = x_13_pad_0, pad_type = x_13_pad_type_0, strides = x_13_strides_0, weight = vae_encoder_block_1_block_1_block_1_weight_to_fp16, x = input_7_cast_fp16)[name = string("x_13_cast_fp16")];
            tensor<int32, [3]> var_859_begin_0 = const()[name = string("op_859_begin_0"), val = tensor<int32, [3]>([0, 0, 10240])];
            tensor<int32, [3]> var_859_end_0 = const()[name = string("op_859_end_0"), val = tensor<int32, [3]>([1, 128, 10258])];
            tensor<bool, [3]> var_859_end_mask_0 = const()[name = string("op_859_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 128, 18]> var_859_cast_fp16 = slice_by_index(begin = var_859_begin_0, end = var_859_end_0, end_mask = var_859_end_mask_0, x = input_7_cast_fp16)[name = string("op_859_cast_fp16")];
            tensor<fp16, [1, 128, 1]> vae_encoder_block_1_block_1_block_2_alpha_to_fp16 = const()[name = string("vae_encoder_block_1_block_1_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41664)))];
            tensor<fp16, [1, 128, 10240]> var_866_cast_fp16 = mul(x = vae_encoder_block_1_block_1_block_2_alpha_to_fp16, y = x_13_cast_fp16)[name = string("op_866_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> var_867_cast_fp16 = sin(x = var_866_cast_fp16)[name = string("op_867_cast_fp16")];
            fp16 var_860_promoted_to_fp16 = const()[name = string("op_860_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, 10240]> var_868_cast_fp16 = pow(x = var_867_cast_fp16, y = var_860_promoted_to_fp16)[name = string("op_868_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_865_to_fp16 = const()[name = string("op_865_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41984)))];
            tensor<fp16, [1, 128, 10240]> var_869_cast_fp16 = mul(x = var_865_to_fp16, y = var_868_cast_fp16)[name = string("op_869_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> input_9_cast_fp16 = add(x = x_13_cast_fp16, y = var_869_cast_fp16)[name = string("input_9_cast_fp16")];
            string y_3_pad_type_0 = const()[name = string("y_3_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_3_strides_0 = const()[name = string("y_3_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_3_pad_0 = const()[name = string("y_3_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_3_dilations_0 = const()[name = string("y_3_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_3_groups_0 = const()[name = string("y_3_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1]> vae_encoder_block_1_block_1_block_3_weight_to_fp16 = const()[name = string("vae_encoder_block_1_block_1_block_3_weight_to_fp16"), val = tensor<fp16, [128, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42304)))];
            tensor<fp16, [128]> vae_encoder_block_1_block_1_block_3_bias_to_fp16 = const()[name = string("vae_encoder_block_1_block_1_block_3_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(75136)))];
            tensor<fp16, [1, 128, 10240]> y_3_cast_fp16 = conv(bias = vae_encoder_block_1_block_1_block_3_bias_to_fp16, dilations = y_3_dilations_0, groups = y_3_groups_0, pad = y_3_pad_0, pad_type = y_3_pad_type_0, strides = y_3_strides_0, weight = vae_encoder_block_1_block_1_block_3_weight_to_fp16, x = input_9_cast_fp16)[name = string("y_3_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> x_15_cast_fp16 = add(x = x_9_cast_fp16, y = y_3_cast_fp16)[name = string("x_15_cast_fp16")];
            tensor<fp16, [1, 128, 1]> vae_encoder_block_1_block_2_block_0_alpha_to_fp16 = const()[name = string("vae_encoder_block_1_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(75456)))];
            tensor<fp16, [1, 128, 10240]> var_894_cast_fp16 = mul(x = vae_encoder_block_1_block_2_block_0_alpha_to_fp16, y = x_15_cast_fp16)[name = string("op_894_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> var_895_cast_fp16 = sin(x = var_894_cast_fp16)[name = string("op_895_cast_fp16")];
            fp16 var_888_promoted_to_fp16 = const()[name = string("op_888_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, 10240]> var_896_cast_fp16 = pow(x = var_895_cast_fp16, y = var_888_promoted_to_fp16)[name = string("op_896_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_893_to_fp16 = const()[name = string("op_893_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(75776)))];
            tensor<fp16, [1, 128, 10240]> var_897_cast_fp16 = mul(x = var_893_to_fp16, y = var_896_cast_fp16)[name = string("op_897_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> x_17_cast_fp16 = add(x = x_15_cast_fp16, y = var_897_cast_fp16)[name = string("x_17_cast_fp16")];
            int32 var_900 = const()[name = string("op_900"), val = int32(-1)];
            bool input_11_interleave_0 = const()[name = string("input_11_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 128, 10294]> input_11_cast_fp16 = concat(axis = var_900, interleave = input_11_interleave_0, values = (var_759_cast_fp16_2, x_17_cast_fp16))[name = string("input_11_cast_fp16")];
            string x_19_pad_type_0 = const()[name = string("x_19_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_19_dilations_0 = const()[name = string("x_19_dilations_0"), val = tensor<int32, [1]>([9])];
            int32 x_19_groups_0 = const()[name = string("x_19_groups_0"), val = int32(128)];
            tensor<int32, [1]> x_19_strides_0 = const()[name = string("x_19_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_19_pad_0 = const()[name = string("x_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [128, 1, 7]> vae_encoder_block_1_block_2_block_1_weight_to_fp16 = const()[name = string("vae_encoder_block_1_block_2_block_1_weight_to_fp16"), val = tensor<fp16, [128, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(76096)))];
            tensor<fp16, [128]> vae_encoder_block_1_block_2_block_1_bias_to_fp16 = const()[name = string("vae_encoder_block_1_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(77952)))];
            tensor<fp16, [1, 128, 10240]> x_19_cast_fp16 = conv(bias = vae_encoder_block_1_block_2_block_1_bias_to_fp16, dilations = x_19_dilations_0, groups = x_19_groups_0, pad = x_19_pad_0, pad_type = x_19_pad_type_0, strides = x_19_strides_0, weight = vae_encoder_block_1_block_2_block_1_weight_to_fp16, x = input_11_cast_fp16)[name = string("x_19_cast_fp16")];
            tensor<int32, [3]> var_921_begin_0 = const()[name = string("op_921_begin_0"), val = tensor<int32, [3]>([0, 0, 10240])];
            tensor<int32, [3]> var_921_end_0 = const()[name = string("op_921_end_0"), val = tensor<int32, [3]>([1, 128, 10294])];
            tensor<bool, [3]> var_921_end_mask_0 = const()[name = string("op_921_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 128, 54]> var_921_cast_fp16 = slice_by_index(begin = var_921_begin_0, end = var_921_end_0, end_mask = var_921_end_mask_0, x = input_11_cast_fp16)[name = string("op_921_cast_fp16")];
            tensor<fp16, [1, 128, 1]> vae_encoder_block_1_block_2_block_2_alpha_to_fp16 = const()[name = string("vae_encoder_block_1_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78272)))];
            tensor<fp16, [1, 128, 10240]> var_928_cast_fp16 = mul(x = vae_encoder_block_1_block_2_block_2_alpha_to_fp16, y = x_19_cast_fp16)[name = string("op_928_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> var_929_cast_fp16 = sin(x = var_928_cast_fp16)[name = string("op_929_cast_fp16")];
            fp16 var_922_promoted_to_fp16 = const()[name = string("op_922_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, 10240]> var_930_cast_fp16 = pow(x = var_929_cast_fp16, y = var_922_promoted_to_fp16)[name = string("op_930_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_927_to_fp16 = const()[name = string("op_927_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78592)))];
            tensor<fp16, [1, 128, 10240]> var_931_cast_fp16 = mul(x = var_927_to_fp16, y = var_930_cast_fp16)[name = string("op_931_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> input_13_cast_fp16 = add(x = x_19_cast_fp16, y = var_931_cast_fp16)[name = string("input_13_cast_fp16")];
            string y_5_pad_type_0 = const()[name = string("y_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_5_strides_0 = const()[name = string("y_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_5_pad_0 = const()[name = string("y_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_5_dilations_0 = const()[name = string("y_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_5_groups_0 = const()[name = string("y_5_groups_0"), val = int32(1)];
            tensor<fp16, [128, 128, 1]> vae_encoder_block_1_block_2_block_3_weight_to_fp16 = const()[name = string("vae_encoder_block_1_block_2_block_3_weight_to_fp16"), val = tensor<fp16, [128, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78912)))];
            tensor<fp16, [128]> vae_encoder_block_1_block_2_block_3_bias_to_fp16 = const()[name = string("vae_encoder_block_1_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(111744)))];
            tensor<fp16, [1, 128, 10240]> y_5_cast_fp16 = conv(bias = vae_encoder_block_1_block_2_block_3_bias_to_fp16, dilations = y_5_dilations_0, groups = y_5_groups_0, pad = y_5_pad_0, pad_type = y_5_pad_type_0, strides = y_5_strides_0, weight = vae_encoder_block_1_block_2_block_3_weight_to_fp16, x = input_13_cast_fp16)[name = string("y_5_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> x_21_cast_fp16 = add(x = x_15_cast_fp16, y = y_5_cast_fp16)[name = string("x_21_cast_fp16")];
            tensor<fp16, [1, 128, 1]> vae_encoder_block_1_block_3_alpha_to_fp16 = const()[name = string("vae_encoder_block_1_block_3_alpha_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(112064)))];
            tensor<fp16, [1, 128, 10240]> var_956_cast_fp16 = mul(x = vae_encoder_block_1_block_3_alpha_to_fp16, y = x_21_cast_fp16)[name = string("op_956_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> var_957_cast_fp16 = sin(x = var_956_cast_fp16)[name = string("op_957_cast_fp16")];
            fp16 var_950_promoted_to_fp16 = const()[name = string("op_950_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 128, 10240]> var_958_cast_fp16 = pow(x = var_957_cast_fp16, y = var_950_promoted_to_fp16)[name = string("op_958_cast_fp16")];
            tensor<fp16, [1, 128, 1]> var_955_to_fp16 = const()[name = string("op_955_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(112384)))];
            tensor<fp16, [1, 128, 10240]> var_959_cast_fp16 = mul(x = var_955_to_fp16, y = var_958_cast_fp16)[name = string("op_959_cast_fp16")];
            tensor<fp16, [1, 128, 10240]> x_23_cast_fp16 = add(x = x_21_cast_fp16, y = var_959_cast_fp16)[name = string("x_23_cast_fp16")];
            int32 var_962 = const()[name = string("op_962"), val = int32(-1)];
            bool input_15_interleave_0 = const()[name = string("input_15_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 128, 10242]> input_15_cast_fp16 = concat(axis = var_962, interleave = input_15_interleave_0, values = (var_759_cast_fp16_3, x_23_cast_fp16))[name = string("input_15_cast_fp16")];
            string x_25_pad_type_0 = const()[name = string("x_25_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_25_strides_0 = const()[name = string("x_25_strides_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [2]> x_25_pad_0 = const()[name = string("x_25_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_25_dilations_0 = const()[name = string("x_25_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_25_groups_0 = const()[name = string("x_25_groups_0"), val = int32(1)];
            tensor<fp16, [256, 128, 4]> vae_encoder_block_1_block_4_weight_to_fp16 = const()[name = string("vae_encoder_block_1_block_4_weight_to_fp16"), val = tensor<fp16, [256, 128, 4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(112704)))];
            tensor<fp16, [256]> vae_encoder_block_1_block_4_bias_to_fp16 = const()[name = string("vae_encoder_block_1_block_4_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374912)))];
            tensor<fp16, [1, 256, 5120]> x_25_cast_fp16 = conv(bias = vae_encoder_block_1_block_4_bias_to_fp16, dilations = x_25_dilations_0, groups = x_25_groups_0, pad = x_25_pad_0, pad_type = x_25_pad_type_0, strides = x_25_strides_0, weight = vae_encoder_block_1_block_4_weight_to_fp16, x = input_15_cast_fp16)[name = string("x_25_cast_fp16")];
            tensor<int32, [3]> var_983_begin_0 = const()[name = string("op_983_begin_0"), val = tensor<int32, [3]>([0, 0, 10240])];
            tensor<int32, [3]> var_983_end_0 = const()[name = string("op_983_end_0"), val = tensor<int32, [3]>([1, 128, 10242])];
            tensor<bool, [3]> var_983_end_mask_0 = const()[name = string("op_983_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 128, 2]> var_983_cast_fp16 = slice_by_index(begin = var_983_begin_0, end = var_983_end_0, end_mask = var_983_end_mask_0, x = input_15_cast_fp16)[name = string("op_983_cast_fp16")];
            int32 var_985 = const()[name = string("op_985"), val = int32(-1)];
            bool var_986_interleave_0 = const()[name = string("op_986_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 128, 80]> var_986_cast_fp16 = concat(axis = var_985, interleave = var_986_interleave_0, values = (var_797_cast_fp16, var_859_cast_fp16, var_921_cast_fp16, var_983_cast_fp16))[name = string("op_986_cast_fp16")];
            string var_986_cast_fp16_to_fp32_dtype_0 = const()[name = string("op_986_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
            tensor<int32, [4]> var_991 = const()[name = string("op_991"), val = tensor<int32, [4]>([6, 18, 54, 5])];
            int32 var_993_axis_0 = const()[name = string("op_993_axis_0"), val = int32(-1)];
            string cache_2_to_fp16_dtype_0 = const()[name = string("cache_2_to_fp16_dtype_0"), val = string("fp16")];
            tensor<fp16, [1, 256, 83]> cache_2_to_fp16 = cast(dtype = cache_2_to_fp16_dtype_0, x = cache_2)[name = string("cast_8")];
            tensor<fp16, [1, 256, 6]> var_993_cast_fp16_0, tensor<fp16, [1, 256, 18]> var_993_cast_fp16_1, tensor<fp16, [1, 256, 54]> var_993_cast_fp16_2, tensor<fp16, [1, 256, 5]> var_993_cast_fp16_3 = split(axis = var_993_axis_0, split_sizes = var_991, x = cache_2_to_fp16)[name = string("op_993_cast_fp16")];
            tensor<fp16, [1, 256, 1]> vae_encoder_block_2_block_0_block_0_alpha_to_fp16 = const()[name = string("vae_encoder_block_2_block_0_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(375488)))];
            tensor<fp16, [1, 256, 5120]> var_1004_cast_fp16 = mul(x = vae_encoder_block_2_block_0_block_0_alpha_to_fp16, y = x_25_cast_fp16)[name = string("op_1004_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> var_1005_cast_fp16 = sin(x = var_1004_cast_fp16)[name = string("op_1005_cast_fp16")];
            fp16 var_998_promoted_to_fp16 = const()[name = string("op_998_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, 5120]> var_1006_cast_fp16 = pow(x = var_1005_cast_fp16, y = var_998_promoted_to_fp16)[name = string("op_1006_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_1003_to_fp16 = const()[name = string("op_1003_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(376064)))];
            tensor<fp16, [1, 256, 5120]> var_1007_cast_fp16 = mul(x = var_1003_to_fp16, y = var_1006_cast_fp16)[name = string("op_1007_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> x_27_cast_fp16 = add(x = x_25_cast_fp16, y = var_1007_cast_fp16)[name = string("x_27_cast_fp16")];
            int32 var_1010 = const()[name = string("op_1010"), val = int32(-1)];
            bool input_17_interleave_0 = const()[name = string("input_17_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 5126]> input_17_cast_fp16 = concat(axis = var_1010, interleave = input_17_interleave_0, values = (var_993_cast_fp16_0, x_27_cast_fp16))[name = string("input_17_cast_fp16")];
            string x_29_pad_type_0 = const()[name = string("x_29_pad_type_0"), val = string("valid")];
            int32 x_29_groups_0 = const()[name = string("x_29_groups_0"), val = int32(256)];
            tensor<int32, [1]> x_29_strides_0 = const()[name = string("x_29_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_29_pad_0 = const()[name = string("x_29_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_29_dilations_0 = const()[name = string("x_29_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 7]> vae_encoder_block_2_block_0_block_1_weight_to_fp16 = const()[name = string("vae_encoder_block_2_block_0_block_1_weight_to_fp16"), val = tensor<fp16, [256, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(376640)))];
            tensor<fp16, [256]> vae_encoder_block_2_block_0_block_1_bias_to_fp16 = const()[name = string("vae_encoder_block_2_block_0_block_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(380288)))];
            tensor<fp16, [1, 256, 5120]> x_29_cast_fp16 = conv(bias = vae_encoder_block_2_block_0_block_1_bias_to_fp16, dilations = x_29_dilations_0, groups = x_29_groups_0, pad = x_29_pad_0, pad_type = x_29_pad_type_0, strides = x_29_strides_0, weight = vae_encoder_block_2_block_0_block_1_weight_to_fp16, x = input_17_cast_fp16)[name = string("x_29_cast_fp16")];
            tensor<int32, [3]> var_1031_begin_0 = const()[name = string("op_1031_begin_0"), val = tensor<int32, [3]>([0, 0, 5120])];
            tensor<int32, [3]> var_1031_end_0 = const()[name = string("op_1031_end_0"), val = tensor<int32, [3]>([1, 256, 5126])];
            tensor<bool, [3]> var_1031_end_mask_0 = const()[name = string("op_1031_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 256, 6]> var_1031_cast_fp16 = slice_by_index(begin = var_1031_begin_0, end = var_1031_end_0, end_mask = var_1031_end_mask_0, x = input_17_cast_fp16)[name = string("op_1031_cast_fp16")];
            tensor<fp16, [1, 256, 1]> vae_encoder_block_2_block_0_block_2_alpha_to_fp16 = const()[name = string("vae_encoder_block_2_block_0_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(380864)))];
            tensor<fp16, [1, 256, 5120]> var_1038_cast_fp16 = mul(x = vae_encoder_block_2_block_0_block_2_alpha_to_fp16, y = x_29_cast_fp16)[name = string("op_1038_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> var_1039_cast_fp16 = sin(x = var_1038_cast_fp16)[name = string("op_1039_cast_fp16")];
            fp16 var_1032_promoted_to_fp16 = const()[name = string("op_1032_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, 5120]> var_1040_cast_fp16 = pow(x = var_1039_cast_fp16, y = var_1032_promoted_to_fp16)[name = string("op_1040_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_1037_to_fp16 = const()[name = string("op_1037_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(381440)))];
            tensor<fp16, [1, 256, 5120]> var_1041_cast_fp16 = mul(x = var_1037_to_fp16, y = var_1040_cast_fp16)[name = string("op_1041_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> input_19_cast_fp16 = add(x = x_29_cast_fp16, y = var_1041_cast_fp16)[name = string("input_19_cast_fp16")];
            string y_7_pad_type_0 = const()[name = string("y_7_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_7_strides_0 = const()[name = string("y_7_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_7_pad_0 = const()[name = string("y_7_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_7_dilations_0 = const()[name = string("y_7_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_7_groups_0 = const()[name = string("y_7_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> vae_encoder_block_2_block_0_block_3_weight_to_fp16 = const()[name = string("vae_encoder_block_2_block_0_block_3_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(382016)))];
            tensor<fp16, [256]> vae_encoder_block_2_block_0_block_3_bias_to_fp16 = const()[name = string("vae_encoder_block_2_block_0_block_3_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(513152)))];
            tensor<fp16, [1, 256, 5120]> y_7_cast_fp16 = conv(bias = vae_encoder_block_2_block_0_block_3_bias_to_fp16, dilations = y_7_dilations_0, groups = y_7_groups_0, pad = y_7_pad_0, pad_type = y_7_pad_type_0, strides = y_7_strides_0, weight = vae_encoder_block_2_block_0_block_3_weight_to_fp16, x = input_19_cast_fp16)[name = string("y_7_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> x_31_cast_fp16 = add(x = x_25_cast_fp16, y = y_7_cast_fp16)[name = string("x_31_cast_fp16")];
            tensor<fp16, [1, 256, 1]> vae_encoder_block_2_block_1_block_0_alpha_to_fp16 = const()[name = string("vae_encoder_block_2_block_1_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(513728)))];
            tensor<fp16, [1, 256, 5120]> var_1066_cast_fp16 = mul(x = vae_encoder_block_2_block_1_block_0_alpha_to_fp16, y = x_31_cast_fp16)[name = string("op_1066_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> var_1067_cast_fp16 = sin(x = var_1066_cast_fp16)[name = string("op_1067_cast_fp16")];
            fp16 var_1060_promoted_to_fp16 = const()[name = string("op_1060_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, 5120]> var_1068_cast_fp16 = pow(x = var_1067_cast_fp16, y = var_1060_promoted_to_fp16)[name = string("op_1068_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_1065_to_fp16 = const()[name = string("op_1065_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(514304)))];
            tensor<fp16, [1, 256, 5120]> var_1069_cast_fp16 = mul(x = var_1065_to_fp16, y = var_1068_cast_fp16)[name = string("op_1069_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> x_33_cast_fp16 = add(x = x_31_cast_fp16, y = var_1069_cast_fp16)[name = string("x_33_cast_fp16")];
            int32 var_1072 = const()[name = string("op_1072"), val = int32(-1)];
            bool input_21_interleave_0 = const()[name = string("input_21_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 5138]> input_21_cast_fp16 = concat(axis = var_1072, interleave = input_21_interleave_0, values = (var_993_cast_fp16_1, x_33_cast_fp16))[name = string("input_21_cast_fp16")];
            string x_35_pad_type_0 = const()[name = string("x_35_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_35_dilations_0 = const()[name = string("x_35_dilations_0"), val = tensor<int32, [1]>([3])];
            int32 x_35_groups_0 = const()[name = string("x_35_groups_0"), val = int32(256)];
            tensor<int32, [1]> x_35_strides_0 = const()[name = string("x_35_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_35_pad_0 = const()[name = string("x_35_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 7]> vae_encoder_block_2_block_1_block_1_weight_to_fp16 = const()[name = string("vae_encoder_block_2_block_1_block_1_weight_to_fp16"), val = tensor<fp16, [256, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(514880)))];
            tensor<fp16, [256]> vae_encoder_block_2_block_1_block_1_bias_to_fp16 = const()[name = string("vae_encoder_block_2_block_1_block_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(518528)))];
            tensor<fp16, [1, 256, 5120]> x_35_cast_fp16 = conv(bias = vae_encoder_block_2_block_1_block_1_bias_to_fp16, dilations = x_35_dilations_0, groups = x_35_groups_0, pad = x_35_pad_0, pad_type = x_35_pad_type_0, strides = x_35_strides_0, weight = vae_encoder_block_2_block_1_block_1_weight_to_fp16, x = input_21_cast_fp16)[name = string("x_35_cast_fp16")];
            tensor<int32, [3]> var_1093_begin_0 = const()[name = string("op_1093_begin_0"), val = tensor<int32, [3]>([0, 0, 5120])];
            tensor<int32, [3]> var_1093_end_0 = const()[name = string("op_1093_end_0"), val = tensor<int32, [3]>([1, 256, 5138])];
            tensor<bool, [3]> var_1093_end_mask_0 = const()[name = string("op_1093_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 256, 18]> var_1093_cast_fp16 = slice_by_index(begin = var_1093_begin_0, end = var_1093_end_0, end_mask = var_1093_end_mask_0, x = input_21_cast_fp16)[name = string("op_1093_cast_fp16")];
            tensor<fp16, [1, 256, 1]> vae_encoder_block_2_block_1_block_2_alpha_to_fp16 = const()[name = string("vae_encoder_block_2_block_1_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(519104)))];
            tensor<fp16, [1, 256, 5120]> var_1100_cast_fp16 = mul(x = vae_encoder_block_2_block_1_block_2_alpha_to_fp16, y = x_35_cast_fp16)[name = string("op_1100_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> var_1101_cast_fp16 = sin(x = var_1100_cast_fp16)[name = string("op_1101_cast_fp16")];
            fp16 var_1094_promoted_to_fp16 = const()[name = string("op_1094_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, 5120]> var_1102_cast_fp16 = pow(x = var_1101_cast_fp16, y = var_1094_promoted_to_fp16)[name = string("op_1102_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_1099_to_fp16 = const()[name = string("op_1099_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(519680)))];
            tensor<fp16, [1, 256, 5120]> var_1103_cast_fp16 = mul(x = var_1099_to_fp16, y = var_1102_cast_fp16)[name = string("op_1103_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> input_23_cast_fp16 = add(x = x_35_cast_fp16, y = var_1103_cast_fp16)[name = string("input_23_cast_fp16")];
            string y_9_pad_type_0 = const()[name = string("y_9_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_9_strides_0 = const()[name = string("y_9_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_9_pad_0 = const()[name = string("y_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_9_dilations_0 = const()[name = string("y_9_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_9_groups_0 = const()[name = string("y_9_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> vae_encoder_block_2_block_1_block_3_weight_to_fp16 = const()[name = string("vae_encoder_block_2_block_1_block_3_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(520256)))];
            tensor<fp16, [256]> vae_encoder_block_2_block_1_block_3_bias_to_fp16 = const()[name = string("vae_encoder_block_2_block_1_block_3_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(651392)))];
            tensor<fp16, [1, 256, 5120]> y_9_cast_fp16 = conv(bias = vae_encoder_block_2_block_1_block_3_bias_to_fp16, dilations = y_9_dilations_0, groups = y_9_groups_0, pad = y_9_pad_0, pad_type = y_9_pad_type_0, strides = y_9_strides_0, weight = vae_encoder_block_2_block_1_block_3_weight_to_fp16, x = input_23_cast_fp16)[name = string("y_9_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> x_37_cast_fp16 = add(x = x_31_cast_fp16, y = y_9_cast_fp16)[name = string("x_37_cast_fp16")];
            tensor<fp16, [1, 256, 1]> vae_encoder_block_2_block_2_block_0_alpha_to_fp16 = const()[name = string("vae_encoder_block_2_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(651968)))];
            tensor<fp16, [1, 256, 5120]> var_1128_cast_fp16 = mul(x = vae_encoder_block_2_block_2_block_0_alpha_to_fp16, y = x_37_cast_fp16)[name = string("op_1128_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> var_1129_cast_fp16 = sin(x = var_1128_cast_fp16)[name = string("op_1129_cast_fp16")];
            fp16 var_1122_promoted_to_fp16 = const()[name = string("op_1122_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, 5120]> var_1130_cast_fp16 = pow(x = var_1129_cast_fp16, y = var_1122_promoted_to_fp16)[name = string("op_1130_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_1127_to_fp16 = const()[name = string("op_1127_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(652544)))];
            tensor<fp16, [1, 256, 5120]> var_1131_cast_fp16 = mul(x = var_1127_to_fp16, y = var_1130_cast_fp16)[name = string("op_1131_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> x_39_cast_fp16 = add(x = x_37_cast_fp16, y = var_1131_cast_fp16)[name = string("x_39_cast_fp16")];
            int32 var_1134 = const()[name = string("op_1134"), val = int32(-1)];
            bool input_25_interleave_0 = const()[name = string("input_25_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 5174]> input_25_cast_fp16 = concat(axis = var_1134, interleave = input_25_interleave_0, values = (var_993_cast_fp16_2, x_39_cast_fp16))[name = string("input_25_cast_fp16")];
            string x_41_pad_type_0 = const()[name = string("x_41_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_41_dilations_0 = const()[name = string("x_41_dilations_0"), val = tensor<int32, [1]>([9])];
            int32 x_41_groups_0 = const()[name = string("x_41_groups_0"), val = int32(256)];
            tensor<int32, [1]> x_41_strides_0 = const()[name = string("x_41_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_41_pad_0 = const()[name = string("x_41_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 7]> vae_encoder_block_2_block_2_block_1_weight_to_fp16 = const()[name = string("vae_encoder_block_2_block_2_block_1_weight_to_fp16"), val = tensor<fp16, [256, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(653120)))];
            tensor<fp16, [256]> vae_encoder_block_2_block_2_block_1_bias_to_fp16 = const()[name = string("vae_encoder_block_2_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(656768)))];
            tensor<fp16, [1, 256, 5120]> x_41_cast_fp16 = conv(bias = vae_encoder_block_2_block_2_block_1_bias_to_fp16, dilations = x_41_dilations_0, groups = x_41_groups_0, pad = x_41_pad_0, pad_type = x_41_pad_type_0, strides = x_41_strides_0, weight = vae_encoder_block_2_block_2_block_1_weight_to_fp16, x = input_25_cast_fp16)[name = string("x_41_cast_fp16")];
            tensor<int32, [3]> var_1155_begin_0 = const()[name = string("op_1155_begin_0"), val = tensor<int32, [3]>([0, 0, 5120])];
            tensor<int32, [3]> var_1155_end_0 = const()[name = string("op_1155_end_0"), val = tensor<int32, [3]>([1, 256, 5174])];
            tensor<bool, [3]> var_1155_end_mask_0 = const()[name = string("op_1155_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 256, 54]> var_1155_cast_fp16 = slice_by_index(begin = var_1155_begin_0, end = var_1155_end_0, end_mask = var_1155_end_mask_0, x = input_25_cast_fp16)[name = string("op_1155_cast_fp16")];
            tensor<fp16, [1, 256, 1]> vae_encoder_block_2_block_2_block_2_alpha_to_fp16 = const()[name = string("vae_encoder_block_2_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(657344)))];
            tensor<fp16, [1, 256, 5120]> var_1162_cast_fp16 = mul(x = vae_encoder_block_2_block_2_block_2_alpha_to_fp16, y = x_41_cast_fp16)[name = string("op_1162_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> var_1163_cast_fp16 = sin(x = var_1162_cast_fp16)[name = string("op_1163_cast_fp16")];
            fp16 var_1156_promoted_to_fp16 = const()[name = string("op_1156_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, 5120]> var_1164_cast_fp16 = pow(x = var_1163_cast_fp16, y = var_1156_promoted_to_fp16)[name = string("op_1164_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_1161_to_fp16 = const()[name = string("op_1161_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(657920)))];
            tensor<fp16, [1, 256, 5120]> var_1165_cast_fp16 = mul(x = var_1161_to_fp16, y = var_1164_cast_fp16)[name = string("op_1165_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> input_27_cast_fp16 = add(x = x_41_cast_fp16, y = var_1165_cast_fp16)[name = string("input_27_cast_fp16")];
            string y_11_pad_type_0 = const()[name = string("y_11_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_11_strides_0 = const()[name = string("y_11_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_11_pad_0 = const()[name = string("y_11_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_11_dilations_0 = const()[name = string("y_11_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_11_groups_0 = const()[name = string("y_11_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> vae_encoder_block_2_block_2_block_3_weight_to_fp16 = const()[name = string("vae_encoder_block_2_block_2_block_3_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(658496)))];
            tensor<fp16, [256]> vae_encoder_block_2_block_2_block_3_bias_to_fp16 = const()[name = string("vae_encoder_block_2_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(789632)))];
            tensor<fp16, [1, 256, 5120]> y_11_cast_fp16 = conv(bias = vae_encoder_block_2_block_2_block_3_bias_to_fp16, dilations = y_11_dilations_0, groups = y_11_groups_0, pad = y_11_pad_0, pad_type = y_11_pad_type_0, strides = y_11_strides_0, weight = vae_encoder_block_2_block_2_block_3_weight_to_fp16, x = input_27_cast_fp16)[name = string("y_11_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> x_43_cast_fp16 = add(x = x_37_cast_fp16, y = y_11_cast_fp16)[name = string("x_43_cast_fp16")];
            tensor<fp16, [1, 256, 1]> vae_encoder_block_2_block_3_alpha_to_fp16 = const()[name = string("vae_encoder_block_2_block_3_alpha_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(790208)))];
            tensor<fp16, [1, 256, 5120]> var_1190_cast_fp16 = mul(x = vae_encoder_block_2_block_3_alpha_to_fp16, y = x_43_cast_fp16)[name = string("op_1190_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> var_1191_cast_fp16 = sin(x = var_1190_cast_fp16)[name = string("op_1191_cast_fp16")];
            fp16 var_1184_promoted_to_fp16 = const()[name = string("op_1184_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 256, 5120]> var_1192_cast_fp16 = pow(x = var_1191_cast_fp16, y = var_1184_promoted_to_fp16)[name = string("op_1192_cast_fp16")];
            tensor<fp16, [1, 256, 1]> var_1189_to_fp16 = const()[name = string("op_1189_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(790784)))];
            tensor<fp16, [1, 256, 5120]> var_1193_cast_fp16 = mul(x = var_1189_to_fp16, y = var_1192_cast_fp16)[name = string("op_1193_cast_fp16")];
            tensor<fp16, [1, 256, 5120]> x_45_cast_fp16 = add(x = x_43_cast_fp16, y = var_1193_cast_fp16)[name = string("x_45_cast_fp16")];
            int32 var_1196 = const()[name = string("op_1196"), val = int32(-1)];
            bool input_29_interleave_0 = const()[name = string("input_29_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 5125]> input_29_cast_fp16 = concat(axis = var_1196, interleave = input_29_interleave_0, values = (var_993_cast_fp16_3, x_45_cast_fp16))[name = string("input_29_cast_fp16")];
            string x_47_pad_type_0 = const()[name = string("x_47_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_47_strides_0 = const()[name = string("x_47_strides_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [2]> x_47_pad_0 = const()[name = string("x_47_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_47_dilations_0 = const()[name = string("x_47_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_47_groups_0 = const()[name = string("x_47_groups_0"), val = int32(1)];
            tensor<fp16, [512, 256, 10]> vae_encoder_block_2_block_4_weight_to_fp16 = const()[name = string("vae_encoder_block_2_block_4_weight_to_fp16"), val = tensor<fp16, [512, 256, 10]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(791360)))];
            tensor<fp16, [512]> vae_encoder_block_2_block_4_bias_to_fp16 = const()[name = string("vae_encoder_block_2_block_4_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3412864)))];
            tensor<fp16, [1, 512, 1024]> x_47_cast_fp16 = conv(bias = vae_encoder_block_2_block_4_bias_to_fp16, dilations = x_47_dilations_0, groups = x_47_groups_0, pad = x_47_pad_0, pad_type = x_47_pad_type_0, strides = x_47_strides_0, weight = vae_encoder_block_2_block_4_weight_to_fp16, x = input_29_cast_fp16)[name = string("x_47_cast_fp16")];
            tensor<int32, [3]> var_1217_begin_0 = const()[name = string("op_1217_begin_0"), val = tensor<int32, [3]>([0, 0, 5120])];
            tensor<int32, [3]> var_1217_end_0 = const()[name = string("op_1217_end_0"), val = tensor<int32, [3]>([1, 256, 5125])];
            tensor<bool, [3]> var_1217_end_mask_0 = const()[name = string("op_1217_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 256, 5]> var_1217_cast_fp16 = slice_by_index(begin = var_1217_begin_0, end = var_1217_end_0, end_mask = var_1217_end_mask_0, x = input_29_cast_fp16)[name = string("op_1217_cast_fp16")];
            int32 var_1219 = const()[name = string("op_1219"), val = int32(-1)];
            bool var_1220_interleave_0 = const()[name = string("op_1220_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 83]> var_1220_cast_fp16 = concat(axis = var_1219, interleave = var_1220_interleave_0, values = (var_1031_cast_fp16, var_1093_cast_fp16, var_1155_cast_fp16, var_1217_cast_fp16))[name = string("op_1220_cast_fp16")];
            string var_1220_cast_fp16_to_fp32_dtype_0 = const()[name = string("op_1220_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
            tensor<int32, [4]> var_1225 = const()[name = string("op_1225"), val = tensor<int32, [4]>([6, 18, 54, 8])];
            int32 var_1227_axis_0 = const()[name = string("op_1227_axis_0"), val = int32(-1)];
            string cache_3_to_fp16_dtype_0 = const()[name = string("cache_3_to_fp16_dtype_0"), val = string("fp16")];
            tensor<fp16, [1, 512, 86]> cache_3_to_fp16 = cast(dtype = cache_3_to_fp16_dtype_0, x = cache_3)[name = string("cast_6")];
            tensor<fp16, [1, 512, 6]> var_1227_cast_fp16_0, tensor<fp16, [1, 512, 18]> var_1227_cast_fp16_1, tensor<fp16, [1, 512, 54]> var_1227_cast_fp16_2, tensor<fp16, [1, 512, 8]> var_1227_cast_fp16_3 = split(axis = var_1227_axis_0, split_sizes = var_1225, x = cache_3_to_fp16)[name = string("op_1227_cast_fp16")];
            tensor<fp16, [1, 512, 1]> vae_encoder_block_3_block_0_block_0_alpha_to_fp16 = const()[name = string("vae_encoder_block_3_block_0_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3413952)))];
            tensor<fp16, [1, 512, 1024]> var_1238_cast_fp16 = mul(x = vae_encoder_block_3_block_0_block_0_alpha_to_fp16, y = x_47_cast_fp16)[name = string("op_1238_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> var_1239_cast_fp16 = sin(x = var_1238_cast_fp16)[name = string("op_1239_cast_fp16")];
            fp16 var_1232_promoted_to_fp16 = const()[name = string("op_1232_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 512, 1024]> var_1240_cast_fp16 = pow(x = var_1239_cast_fp16, y = var_1232_promoted_to_fp16)[name = string("op_1240_cast_fp16")];
            tensor<fp16, [1, 512, 1]> var_1237_to_fp16 = const()[name = string("op_1237_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3415040)))];
            tensor<fp16, [1, 512, 1024]> var_1241_cast_fp16 = mul(x = var_1237_to_fp16, y = var_1240_cast_fp16)[name = string("op_1241_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> x_49_cast_fp16 = add(x = x_47_cast_fp16, y = var_1241_cast_fp16)[name = string("x_49_cast_fp16")];
            int32 var_1244 = const()[name = string("op_1244"), val = int32(-1)];
            bool input_31_interleave_0 = const()[name = string("input_31_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 1030]> input_31_cast_fp16 = concat(axis = var_1244, interleave = input_31_interleave_0, values = (var_1227_cast_fp16_0, x_49_cast_fp16))[name = string("input_31_cast_fp16")];
            string x_51_pad_type_0 = const()[name = string("x_51_pad_type_0"), val = string("valid")];
            int32 x_51_groups_0 = const()[name = string("x_51_groups_0"), val = int32(512)];
            tensor<int32, [1]> x_51_strides_0 = const()[name = string("x_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_51_pad_0 = const()[name = string("x_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_51_dilations_0 = const()[name = string("x_51_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 7]> vae_encoder_block_3_block_0_block_1_weight_to_fp16 = const()[name = string("vae_encoder_block_3_block_0_block_1_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3416128)))];
            tensor<fp16, [512]> vae_encoder_block_3_block_0_block_1_bias_to_fp16 = const()[name = string("vae_encoder_block_3_block_0_block_1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3423360)))];
            tensor<fp16, [1, 512, 1024]> x_51_cast_fp16 = conv(bias = vae_encoder_block_3_block_0_block_1_bias_to_fp16, dilations = x_51_dilations_0, groups = x_51_groups_0, pad = x_51_pad_0, pad_type = x_51_pad_type_0, strides = x_51_strides_0, weight = vae_encoder_block_3_block_0_block_1_weight_to_fp16, x = input_31_cast_fp16)[name = string("x_51_cast_fp16")];
            tensor<int32, [3]> var_1265_begin_0 = const()[name = string("op_1265_begin_0"), val = tensor<int32, [3]>([0, 0, 1024])];
            tensor<int32, [3]> var_1265_end_0 = const()[name = string("op_1265_end_0"), val = tensor<int32, [3]>([1, 512, 1030])];
            tensor<bool, [3]> var_1265_end_mask_0 = const()[name = string("op_1265_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 512, 6]> var_1265_cast_fp16 = slice_by_index(begin = var_1265_begin_0, end = var_1265_end_0, end_mask = var_1265_end_mask_0, x = input_31_cast_fp16)[name = string("op_1265_cast_fp16")];
            tensor<fp16, [1, 512, 1]> vae_encoder_block_3_block_0_block_2_alpha_to_fp16 = const()[name = string("vae_encoder_block_3_block_0_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3424448)))];
            tensor<fp16, [1, 512, 1024]> var_1272_cast_fp16 = mul(x = vae_encoder_block_3_block_0_block_2_alpha_to_fp16, y = x_51_cast_fp16)[name = string("op_1272_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> var_1273_cast_fp16 = sin(x = var_1272_cast_fp16)[name = string("op_1273_cast_fp16")];
            fp16 var_1266_promoted_to_fp16 = const()[name = string("op_1266_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 512, 1024]> var_1274_cast_fp16 = pow(x = var_1273_cast_fp16, y = var_1266_promoted_to_fp16)[name = string("op_1274_cast_fp16")];
            tensor<fp16, [1, 512, 1]> var_1271_to_fp16 = const()[name = string("op_1271_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3425536)))];
            tensor<fp16, [1, 512, 1024]> var_1275_cast_fp16 = mul(x = var_1271_to_fp16, y = var_1274_cast_fp16)[name = string("op_1275_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> input_33_cast_fp16 = add(x = x_51_cast_fp16, y = var_1275_cast_fp16)[name = string("input_33_cast_fp16")];
            string y_13_pad_type_0 = const()[name = string("y_13_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_13_strides_0 = const()[name = string("y_13_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_13_pad_0 = const()[name = string("y_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_13_dilations_0 = const()[name = string("y_13_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_13_groups_0 = const()[name = string("y_13_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1]> vae_encoder_block_3_block_0_block_3_weight_to_fp16 = const()[name = string("vae_encoder_block_3_block_0_block_3_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3426624)))];
            tensor<fp16, [512]> vae_encoder_block_3_block_0_block_3_bias_to_fp16 = const()[name = string("vae_encoder_block_3_block_0_block_3_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3950976)))];
            tensor<fp16, [1, 512, 1024]> y_13_cast_fp16 = conv(bias = vae_encoder_block_3_block_0_block_3_bias_to_fp16, dilations = y_13_dilations_0, groups = y_13_groups_0, pad = y_13_pad_0, pad_type = y_13_pad_type_0, strides = y_13_strides_0, weight = vae_encoder_block_3_block_0_block_3_weight_to_fp16, x = input_33_cast_fp16)[name = string("y_13_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> x_53_cast_fp16 = add(x = x_47_cast_fp16, y = y_13_cast_fp16)[name = string("x_53_cast_fp16")];
            tensor<fp16, [1, 512, 1]> vae_encoder_block_3_block_1_block_0_alpha_to_fp16 = const()[name = string("vae_encoder_block_3_block_1_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3952064)))];
            tensor<fp16, [1, 512, 1024]> var_1300_cast_fp16 = mul(x = vae_encoder_block_3_block_1_block_0_alpha_to_fp16, y = x_53_cast_fp16)[name = string("op_1300_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> var_1301_cast_fp16 = sin(x = var_1300_cast_fp16)[name = string("op_1301_cast_fp16")];
            fp16 var_1294_promoted_to_fp16 = const()[name = string("op_1294_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 512, 1024]> var_1302_cast_fp16 = pow(x = var_1301_cast_fp16, y = var_1294_promoted_to_fp16)[name = string("op_1302_cast_fp16")];
            tensor<fp16, [1, 512, 1]> var_1299_to_fp16 = const()[name = string("op_1299_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3953152)))];
            tensor<fp16, [1, 512, 1024]> var_1303_cast_fp16 = mul(x = var_1299_to_fp16, y = var_1302_cast_fp16)[name = string("op_1303_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> x_55_cast_fp16 = add(x = x_53_cast_fp16, y = var_1303_cast_fp16)[name = string("x_55_cast_fp16")];
            int32 var_1306 = const()[name = string("op_1306"), val = int32(-1)];
            bool input_35_interleave_0 = const()[name = string("input_35_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 1042]> input_35_cast_fp16 = concat(axis = var_1306, interleave = input_35_interleave_0, values = (var_1227_cast_fp16_1, x_55_cast_fp16))[name = string("input_35_cast_fp16")];
            string x_57_pad_type_0 = const()[name = string("x_57_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_57_dilations_0 = const()[name = string("x_57_dilations_0"), val = tensor<int32, [1]>([3])];
            int32 x_57_groups_0 = const()[name = string("x_57_groups_0"), val = int32(512)];
            tensor<int32, [1]> x_57_strides_0 = const()[name = string("x_57_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_57_pad_0 = const()[name = string("x_57_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> vae_encoder_block_3_block_1_block_1_weight_to_fp16 = const()[name = string("vae_encoder_block_3_block_1_block_1_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3954240)))];
            tensor<fp16, [512]> vae_encoder_block_3_block_1_block_1_bias_to_fp16 = const()[name = string("vae_encoder_block_3_block_1_block_1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3961472)))];
            tensor<fp16, [1, 512, 1024]> x_57_cast_fp16 = conv(bias = vae_encoder_block_3_block_1_block_1_bias_to_fp16, dilations = x_57_dilations_0, groups = x_57_groups_0, pad = x_57_pad_0, pad_type = x_57_pad_type_0, strides = x_57_strides_0, weight = vae_encoder_block_3_block_1_block_1_weight_to_fp16, x = input_35_cast_fp16)[name = string("x_57_cast_fp16")];
            tensor<int32, [3]> var_1327_begin_0 = const()[name = string("op_1327_begin_0"), val = tensor<int32, [3]>([0, 0, 1024])];
            tensor<int32, [3]> var_1327_end_0 = const()[name = string("op_1327_end_0"), val = tensor<int32, [3]>([1, 512, 1042])];
            tensor<bool, [3]> var_1327_end_mask_0 = const()[name = string("op_1327_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 512, 18]> var_1327_cast_fp16 = slice_by_index(begin = var_1327_begin_0, end = var_1327_end_0, end_mask = var_1327_end_mask_0, x = input_35_cast_fp16)[name = string("op_1327_cast_fp16")];
            tensor<fp16, [1, 512, 1]> vae_encoder_block_3_block_1_block_2_alpha_to_fp16 = const()[name = string("vae_encoder_block_3_block_1_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3962560)))];
            tensor<fp16, [1, 512, 1024]> var_1334_cast_fp16 = mul(x = vae_encoder_block_3_block_1_block_2_alpha_to_fp16, y = x_57_cast_fp16)[name = string("op_1334_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> var_1335_cast_fp16 = sin(x = var_1334_cast_fp16)[name = string("op_1335_cast_fp16")];
            fp16 var_1328_promoted_to_fp16 = const()[name = string("op_1328_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 512, 1024]> var_1336_cast_fp16 = pow(x = var_1335_cast_fp16, y = var_1328_promoted_to_fp16)[name = string("op_1336_cast_fp16")];
            tensor<fp16, [1, 512, 1]> var_1333_to_fp16 = const()[name = string("op_1333_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3963648)))];
            tensor<fp16, [1, 512, 1024]> var_1337_cast_fp16 = mul(x = var_1333_to_fp16, y = var_1336_cast_fp16)[name = string("op_1337_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> input_37_cast_fp16 = add(x = x_57_cast_fp16, y = var_1337_cast_fp16)[name = string("input_37_cast_fp16")];
            string y_15_pad_type_0 = const()[name = string("y_15_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_15_strides_0 = const()[name = string("y_15_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_15_pad_0 = const()[name = string("y_15_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_15_dilations_0 = const()[name = string("y_15_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_15_groups_0 = const()[name = string("y_15_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1]> vae_encoder_block_3_block_1_block_3_weight_to_fp16 = const()[name = string("vae_encoder_block_3_block_1_block_3_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3964736)))];
            tensor<fp16, [512]> vae_encoder_block_3_block_1_block_3_bias_to_fp16 = const()[name = string("vae_encoder_block_3_block_1_block_3_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4489088)))];
            tensor<fp16, [1, 512, 1024]> y_15_cast_fp16 = conv(bias = vae_encoder_block_3_block_1_block_3_bias_to_fp16, dilations = y_15_dilations_0, groups = y_15_groups_0, pad = y_15_pad_0, pad_type = y_15_pad_type_0, strides = y_15_strides_0, weight = vae_encoder_block_3_block_1_block_3_weight_to_fp16, x = input_37_cast_fp16)[name = string("y_15_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> x_59_cast_fp16 = add(x = x_53_cast_fp16, y = y_15_cast_fp16)[name = string("x_59_cast_fp16")];
            tensor<fp16, [1, 512, 1]> vae_encoder_block_3_block_2_block_0_alpha_to_fp16 = const()[name = string("vae_encoder_block_3_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4490176)))];
            tensor<fp16, [1, 512, 1024]> var_1362_cast_fp16 = mul(x = vae_encoder_block_3_block_2_block_0_alpha_to_fp16, y = x_59_cast_fp16)[name = string("op_1362_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> var_1363_cast_fp16 = sin(x = var_1362_cast_fp16)[name = string("op_1363_cast_fp16")];
            fp16 var_1356_promoted_to_fp16 = const()[name = string("op_1356_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 512, 1024]> var_1364_cast_fp16 = pow(x = var_1363_cast_fp16, y = var_1356_promoted_to_fp16)[name = string("op_1364_cast_fp16")];
            tensor<fp16, [1, 512, 1]> var_1361_to_fp16 = const()[name = string("op_1361_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4491264)))];
            tensor<fp16, [1, 512, 1024]> var_1365_cast_fp16 = mul(x = var_1361_to_fp16, y = var_1364_cast_fp16)[name = string("op_1365_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> x_61_cast_fp16 = add(x = x_59_cast_fp16, y = var_1365_cast_fp16)[name = string("x_61_cast_fp16")];
            int32 var_1368 = const()[name = string("op_1368"), val = int32(-1)];
            bool input_39_interleave_0 = const()[name = string("input_39_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 1078]> input_39_cast_fp16 = concat(axis = var_1368, interleave = input_39_interleave_0, values = (var_1227_cast_fp16_2, x_61_cast_fp16))[name = string("input_39_cast_fp16")];
            string x_63_pad_type_0 = const()[name = string("x_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_63_dilations_0 = const()[name = string("x_63_dilations_0"), val = tensor<int32, [1]>([9])];
            int32 x_63_groups_0 = const()[name = string("x_63_groups_0"), val = int32(512)];
            tensor<int32, [1]> x_63_strides_0 = const()[name = string("x_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_63_pad_0 = const()[name = string("x_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [512, 1, 7]> vae_encoder_block_3_block_2_block_1_weight_to_fp16 = const()[name = string("vae_encoder_block_3_block_2_block_1_weight_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4492352)))];
            tensor<fp16, [512]> vae_encoder_block_3_block_2_block_1_bias_to_fp16 = const()[name = string("vae_encoder_block_3_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4499584)))];
            tensor<fp16, [1, 512, 1024]> x_63_cast_fp16 = conv(bias = vae_encoder_block_3_block_2_block_1_bias_to_fp16, dilations = x_63_dilations_0, groups = x_63_groups_0, pad = x_63_pad_0, pad_type = x_63_pad_type_0, strides = x_63_strides_0, weight = vae_encoder_block_3_block_2_block_1_weight_to_fp16, x = input_39_cast_fp16)[name = string("x_63_cast_fp16")];
            tensor<int32, [3]> var_1389_begin_0 = const()[name = string("op_1389_begin_0"), val = tensor<int32, [3]>([0, 0, 1024])];
            tensor<int32, [3]> var_1389_end_0 = const()[name = string("op_1389_end_0"), val = tensor<int32, [3]>([1, 512, 1078])];
            tensor<bool, [3]> var_1389_end_mask_0 = const()[name = string("op_1389_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 512, 54]> var_1389_cast_fp16 = slice_by_index(begin = var_1389_begin_0, end = var_1389_end_0, end_mask = var_1389_end_mask_0, x = input_39_cast_fp16)[name = string("op_1389_cast_fp16")];
            tensor<fp16, [1, 512, 1]> vae_encoder_block_3_block_2_block_2_alpha_to_fp16 = const()[name = string("vae_encoder_block_3_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4500672)))];
            tensor<fp16, [1, 512, 1024]> var_1396_cast_fp16 = mul(x = vae_encoder_block_3_block_2_block_2_alpha_to_fp16, y = x_63_cast_fp16)[name = string("op_1396_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> var_1397_cast_fp16 = sin(x = var_1396_cast_fp16)[name = string("op_1397_cast_fp16")];
            fp16 var_1390_promoted_to_fp16 = const()[name = string("op_1390_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 512, 1024]> var_1398_cast_fp16 = pow(x = var_1397_cast_fp16, y = var_1390_promoted_to_fp16)[name = string("op_1398_cast_fp16")];
            tensor<fp16, [1, 512, 1]> var_1395_to_fp16 = const()[name = string("op_1395_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4501760)))];
            tensor<fp16, [1, 512, 1024]> var_1399_cast_fp16 = mul(x = var_1395_to_fp16, y = var_1398_cast_fp16)[name = string("op_1399_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> input_41_cast_fp16 = add(x = x_63_cast_fp16, y = var_1399_cast_fp16)[name = string("input_41_cast_fp16")];
            string y_17_pad_type_0 = const()[name = string("y_17_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_17_strides_0 = const()[name = string("y_17_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_17_pad_0 = const()[name = string("y_17_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_17_dilations_0 = const()[name = string("y_17_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_17_groups_0 = const()[name = string("y_17_groups_0"), val = int32(1)];
            tensor<fp16, [512, 512, 1]> vae_encoder_block_3_block_2_block_3_weight_to_fp16 = const()[name = string("vae_encoder_block_3_block_2_block_3_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4502848)))];
            tensor<fp16, [512]> vae_encoder_block_3_block_2_block_3_bias_to_fp16 = const()[name = string("vae_encoder_block_3_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5027200)))];
            tensor<fp16, [1, 512, 1024]> y_17_cast_fp16 = conv(bias = vae_encoder_block_3_block_2_block_3_bias_to_fp16, dilations = y_17_dilations_0, groups = y_17_groups_0, pad = y_17_pad_0, pad_type = y_17_pad_type_0, strides = y_17_strides_0, weight = vae_encoder_block_3_block_2_block_3_weight_to_fp16, x = input_41_cast_fp16)[name = string("y_17_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> x_65_cast_fp16 = add(x = x_59_cast_fp16, y = y_17_cast_fp16)[name = string("x_65_cast_fp16")];
            tensor<fp16, [1, 512, 1]> vae_encoder_block_3_block_3_alpha_to_fp16 = const()[name = string("vae_encoder_block_3_block_3_alpha_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5028288)))];
            tensor<fp16, [1, 512, 1024]> var_1424_cast_fp16 = mul(x = vae_encoder_block_3_block_3_alpha_to_fp16, y = x_65_cast_fp16)[name = string("op_1424_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> var_1425_cast_fp16 = sin(x = var_1424_cast_fp16)[name = string("op_1425_cast_fp16")];
            fp16 var_1418_promoted_to_fp16 = const()[name = string("op_1418_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 512, 1024]> var_1426_cast_fp16 = pow(x = var_1425_cast_fp16, y = var_1418_promoted_to_fp16)[name = string("op_1426_cast_fp16")];
            tensor<fp16, [1, 512, 1]> var_1423_to_fp16 = const()[name = string("op_1423_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5029376)))];
            tensor<fp16, [1, 512, 1024]> var_1427_cast_fp16 = mul(x = var_1423_to_fp16, y = var_1426_cast_fp16)[name = string("op_1427_cast_fp16")];
            tensor<fp16, [1, 512, 1024]> x_67_cast_fp16 = add(x = x_65_cast_fp16, y = var_1427_cast_fp16)[name = string("x_67_cast_fp16")];
            int32 var_1430 = const()[name = string("op_1430"), val = int32(-1)];
            bool input_43_interleave_0 = const()[name = string("input_43_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 1032]> input_43_cast_fp16 = concat(axis = var_1430, interleave = input_43_interleave_0, values = (var_1227_cast_fp16_3, x_67_cast_fp16))[name = string("input_43_cast_fp16")];
            string x_69_pad_type_0 = const()[name = string("x_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_69_strides_0 = const()[name = string("x_69_strides_0"), val = tensor<int32, [1]>([8])];
            tensor<int32, [2]> x_69_pad_0 = const()[name = string("x_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_69_dilations_0 = const()[name = string("x_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_69_groups_0 = const()[name = string("x_69_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 512, 16]> vae_encoder_block_3_block_4_weight_to_fp16 = const()[name = string("vae_encoder_block_3_block_4_weight_to_fp16"), val = tensor<fp16, [1024, 512, 16]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5030464)))];
            tensor<fp16, [1024]> vae_encoder_block_3_block_4_bias_to_fp16 = const()[name = string("vae_encoder_block_3_block_4_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21807744)))];
            tensor<fp16, [1, 1024, 128]> x_69_cast_fp16 = conv(bias = vae_encoder_block_3_block_4_bias_to_fp16, dilations = x_69_dilations_0, groups = x_69_groups_0, pad = x_69_pad_0, pad_type = x_69_pad_type_0, strides = x_69_strides_0, weight = vae_encoder_block_3_block_4_weight_to_fp16, x = input_43_cast_fp16)[name = string("x_69_cast_fp16")];
            tensor<int32, [3]> var_1451_begin_0 = const()[name = string("op_1451_begin_0"), val = tensor<int32, [3]>([0, 0, 1024])];
            tensor<int32, [3]> var_1451_end_0 = const()[name = string("op_1451_end_0"), val = tensor<int32, [3]>([1, 512, 1032])];
            tensor<bool, [3]> var_1451_end_mask_0 = const()[name = string("op_1451_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 512, 8]> var_1451_cast_fp16 = slice_by_index(begin = var_1451_begin_0, end = var_1451_end_0, end_mask = var_1451_end_mask_0, x = input_43_cast_fp16)[name = string("op_1451_cast_fp16")];
            int32 var_1453 = const()[name = string("op_1453"), val = int32(-1)];
            bool var_1454_interleave_0 = const()[name = string("op_1454_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 512, 86]> var_1454_cast_fp16 = concat(axis = var_1453, interleave = var_1454_interleave_0, values = (var_1265_cast_fp16, var_1327_cast_fp16, var_1389_cast_fp16, var_1451_cast_fp16))[name = string("op_1454_cast_fp16")];
            string var_1454_cast_fp16_to_fp32_dtype_0 = const()[name = string("op_1454_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
            tensor<int32, [4]> var_1459 = const()[name = string("op_1459"), val = tensor<int32, [4]>([6, 18, 54, 8])];
            int32 var_1461_axis_0 = const()[name = string("op_1461_axis_0"), val = int32(-1)];
            string cache_4_to_fp16_dtype_0 = const()[name = string("cache_4_to_fp16_dtype_0"), val = string("fp16")];
            tensor<fp16, [1, 1024, 86]> cache_4_to_fp16 = cast(dtype = cache_4_to_fp16_dtype_0, x = cache_4)[name = string("cast_4")];
            tensor<fp16, [1, 1024, 6]> var_1461_cast_fp16_0, tensor<fp16, [1, 1024, 18]> var_1461_cast_fp16_1, tensor<fp16, [1, 1024, 54]> var_1461_cast_fp16_2, tensor<fp16, [1, 1024, 8]> var_1461_cast_fp16_3 = split(axis = var_1461_axis_0, split_sizes = var_1459, x = cache_4_to_fp16)[name = string("op_1461_cast_fp16")];
            tensor<fp16, [1, 1024, 1]> vae_encoder_block_4_block_0_block_0_alpha_to_fp16 = const()[name = string("vae_encoder_block_4_block_0_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21809856)))];
            tensor<fp16, [1, 1024, 128]> var_1472_cast_fp16 = mul(x = vae_encoder_block_4_block_0_block_0_alpha_to_fp16, y = x_69_cast_fp16)[name = string("op_1472_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> var_1473_cast_fp16 = sin(x = var_1472_cast_fp16)[name = string("op_1473_cast_fp16")];
            fp16 var_1466_promoted_to_fp16 = const()[name = string("op_1466_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 1024, 128]> var_1474_cast_fp16 = pow(x = var_1473_cast_fp16, y = var_1466_promoted_to_fp16)[name = string("op_1474_cast_fp16")];
            tensor<fp16, [1, 1024, 1]> var_1471_to_fp16 = const()[name = string("op_1471_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21811968)))];
            tensor<fp16, [1, 1024, 128]> var_1475_cast_fp16 = mul(x = var_1471_to_fp16, y = var_1474_cast_fp16)[name = string("op_1475_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> x_71_cast_fp16 = add(x = x_69_cast_fp16, y = var_1475_cast_fp16)[name = string("x_71_cast_fp16")];
            int32 var_1478 = const()[name = string("op_1478"), val = int32(-1)];
            bool input_45_interleave_0 = const()[name = string("input_45_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1024, 134]> input_45_cast_fp16 = concat(axis = var_1478, interleave = input_45_interleave_0, values = (var_1461_cast_fp16_0, x_71_cast_fp16))[name = string("input_45_cast_fp16")];
            string x_73_pad_type_0 = const()[name = string("x_73_pad_type_0"), val = string("valid")];
            int32 x_73_groups_0 = const()[name = string("x_73_groups_0"), val = int32(1024)];
            tensor<int32, [1]> x_73_strides_0 = const()[name = string("x_73_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_73_pad_0 = const()[name = string("x_73_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_73_dilations_0 = const()[name = string("x_73_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 7]> vae_encoder_block_4_block_0_block_1_weight_to_fp16 = const()[name = string("vae_encoder_block_4_block_0_block_1_weight_to_fp16"), val = tensor<fp16, [1024, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21814080)))];
            tensor<fp16, [1024]> vae_encoder_block_4_block_0_block_1_bias_to_fp16 = const()[name = string("vae_encoder_block_4_block_0_block_1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21828480)))];
            tensor<fp16, [1, 1024, 128]> x_73_cast_fp16 = conv(bias = vae_encoder_block_4_block_0_block_1_bias_to_fp16, dilations = x_73_dilations_0, groups = x_73_groups_0, pad = x_73_pad_0, pad_type = x_73_pad_type_0, strides = x_73_strides_0, weight = vae_encoder_block_4_block_0_block_1_weight_to_fp16, x = input_45_cast_fp16)[name = string("x_73_cast_fp16")];
            tensor<int32, [3]> var_1499_begin_0 = const()[name = string("op_1499_begin_0"), val = tensor<int32, [3]>([0, 0, 128])];
            tensor<int32, [3]> var_1499_end_0 = const()[name = string("op_1499_end_0"), val = tensor<int32, [3]>([1, 1024, 134])];
            tensor<bool, [3]> var_1499_end_mask_0 = const()[name = string("op_1499_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 1024, 6]> var_1499_cast_fp16 = slice_by_index(begin = var_1499_begin_0, end = var_1499_end_0, end_mask = var_1499_end_mask_0, x = input_45_cast_fp16)[name = string("op_1499_cast_fp16")];
            tensor<fp16, [1, 1024, 1]> vae_encoder_block_4_block_0_block_2_alpha_to_fp16 = const()[name = string("vae_encoder_block_4_block_0_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21830592)))];
            tensor<fp16, [1, 1024, 128]> var_1506_cast_fp16 = mul(x = vae_encoder_block_4_block_0_block_2_alpha_to_fp16, y = x_73_cast_fp16)[name = string("op_1506_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> var_1507_cast_fp16 = sin(x = var_1506_cast_fp16)[name = string("op_1507_cast_fp16")];
            fp16 var_1500_promoted_to_fp16 = const()[name = string("op_1500_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 1024, 128]> var_1508_cast_fp16 = pow(x = var_1507_cast_fp16, y = var_1500_promoted_to_fp16)[name = string("op_1508_cast_fp16")];
            tensor<fp16, [1, 1024, 1]> var_1505_to_fp16 = const()[name = string("op_1505_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21832704)))];
            tensor<fp16, [1, 1024, 128]> var_1509_cast_fp16 = mul(x = var_1505_to_fp16, y = var_1508_cast_fp16)[name = string("op_1509_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> input_47_cast_fp16 = add(x = x_73_cast_fp16, y = var_1509_cast_fp16)[name = string("input_47_cast_fp16")];
            string y_19_pad_type_0 = const()[name = string("y_19_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_19_strides_0 = const()[name = string("y_19_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_19_pad_0 = const()[name = string("y_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_19_dilations_0 = const()[name = string("y_19_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_19_groups_0 = const()[name = string("y_19_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> vae_encoder_block_4_block_0_block_3_weight_to_fp16 = const()[name = string("vae_encoder_block_4_block_0_block_3_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21834816)))];
            tensor<fp16, [1024]> vae_encoder_block_4_block_0_block_3_bias_to_fp16 = const()[name = string("vae_encoder_block_4_block_0_block_3_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23932032)))];
            tensor<fp16, [1, 1024, 128]> y_19_cast_fp16 = conv(bias = vae_encoder_block_4_block_0_block_3_bias_to_fp16, dilations = y_19_dilations_0, groups = y_19_groups_0, pad = y_19_pad_0, pad_type = y_19_pad_type_0, strides = y_19_strides_0, weight = vae_encoder_block_4_block_0_block_3_weight_to_fp16, x = input_47_cast_fp16)[name = string("y_19_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> x_75_cast_fp16 = add(x = x_69_cast_fp16, y = y_19_cast_fp16)[name = string("x_75_cast_fp16")];
            tensor<fp16, [1, 1024, 1]> vae_encoder_block_4_block_1_block_0_alpha_to_fp16 = const()[name = string("vae_encoder_block_4_block_1_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23934144)))];
            tensor<fp16, [1, 1024, 128]> var_1534_cast_fp16 = mul(x = vae_encoder_block_4_block_1_block_0_alpha_to_fp16, y = x_75_cast_fp16)[name = string("op_1534_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> var_1535_cast_fp16 = sin(x = var_1534_cast_fp16)[name = string("op_1535_cast_fp16")];
            fp16 var_1528_promoted_to_fp16 = const()[name = string("op_1528_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 1024, 128]> var_1536_cast_fp16 = pow(x = var_1535_cast_fp16, y = var_1528_promoted_to_fp16)[name = string("op_1536_cast_fp16")];
            tensor<fp16, [1, 1024, 1]> var_1533_to_fp16 = const()[name = string("op_1533_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23936256)))];
            tensor<fp16, [1, 1024, 128]> var_1537_cast_fp16 = mul(x = var_1533_to_fp16, y = var_1536_cast_fp16)[name = string("op_1537_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> x_77_cast_fp16 = add(x = x_75_cast_fp16, y = var_1537_cast_fp16)[name = string("x_77_cast_fp16")];
            int32 var_1540 = const()[name = string("op_1540"), val = int32(-1)];
            bool input_49_interleave_0 = const()[name = string("input_49_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1024, 146]> input_49_cast_fp16 = concat(axis = var_1540, interleave = input_49_interleave_0, values = (var_1461_cast_fp16_1, x_77_cast_fp16))[name = string("input_49_cast_fp16")];
            string x_79_pad_type_0 = const()[name = string("x_79_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_79_dilations_0 = const()[name = string("x_79_dilations_0"), val = tensor<int32, [1]>([3])];
            int32 x_79_groups_0 = const()[name = string("x_79_groups_0"), val = int32(1024)];
            tensor<int32, [1]> x_79_strides_0 = const()[name = string("x_79_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_79_pad_0 = const()[name = string("x_79_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [1024, 1, 7]> vae_encoder_block_4_block_1_block_1_weight_to_fp16 = const()[name = string("vae_encoder_block_4_block_1_block_1_weight_to_fp16"), val = tensor<fp16, [1024, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23938368)))];
            tensor<fp16, [1024]> vae_encoder_block_4_block_1_block_1_bias_to_fp16 = const()[name = string("vae_encoder_block_4_block_1_block_1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23952768)))];
            tensor<fp16, [1, 1024, 128]> x_79_cast_fp16 = conv(bias = vae_encoder_block_4_block_1_block_1_bias_to_fp16, dilations = x_79_dilations_0, groups = x_79_groups_0, pad = x_79_pad_0, pad_type = x_79_pad_type_0, strides = x_79_strides_0, weight = vae_encoder_block_4_block_1_block_1_weight_to_fp16, x = input_49_cast_fp16)[name = string("x_79_cast_fp16")];
            tensor<int32, [3]> var_1561_begin_0 = const()[name = string("op_1561_begin_0"), val = tensor<int32, [3]>([0, 0, 128])];
            tensor<int32, [3]> var_1561_end_0 = const()[name = string("op_1561_end_0"), val = tensor<int32, [3]>([1, 1024, 146])];
            tensor<bool, [3]> var_1561_end_mask_0 = const()[name = string("op_1561_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 1024, 18]> var_1561_cast_fp16 = slice_by_index(begin = var_1561_begin_0, end = var_1561_end_0, end_mask = var_1561_end_mask_0, x = input_49_cast_fp16)[name = string("op_1561_cast_fp16")];
            tensor<fp16, [1, 1024, 1]> vae_encoder_block_4_block_1_block_2_alpha_to_fp16 = const()[name = string("vae_encoder_block_4_block_1_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23954880)))];
            tensor<fp16, [1, 1024, 128]> var_1568_cast_fp16 = mul(x = vae_encoder_block_4_block_1_block_2_alpha_to_fp16, y = x_79_cast_fp16)[name = string("op_1568_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> var_1569_cast_fp16 = sin(x = var_1568_cast_fp16)[name = string("op_1569_cast_fp16")];
            fp16 var_1562_promoted_to_fp16 = const()[name = string("op_1562_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 1024, 128]> var_1570_cast_fp16 = pow(x = var_1569_cast_fp16, y = var_1562_promoted_to_fp16)[name = string("op_1570_cast_fp16")];
            tensor<fp16, [1, 1024, 1]> var_1567_to_fp16 = const()[name = string("op_1567_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23956992)))];
            tensor<fp16, [1, 1024, 128]> var_1571_cast_fp16 = mul(x = var_1567_to_fp16, y = var_1570_cast_fp16)[name = string("op_1571_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> input_51_cast_fp16 = add(x = x_79_cast_fp16, y = var_1571_cast_fp16)[name = string("input_51_cast_fp16")];
            string y_21_pad_type_0 = const()[name = string("y_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_21_strides_0 = const()[name = string("y_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_21_pad_0 = const()[name = string("y_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_21_dilations_0 = const()[name = string("y_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_21_groups_0 = const()[name = string("y_21_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> vae_encoder_block_4_block_1_block_3_weight_to_fp16 = const()[name = string("vae_encoder_block_4_block_1_block_3_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23959104)))];
            tensor<fp16, [1024]> vae_encoder_block_4_block_1_block_3_bias_to_fp16 = const()[name = string("vae_encoder_block_4_block_1_block_3_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26056320)))];
            tensor<fp16, [1, 1024, 128]> y_21_cast_fp16 = conv(bias = vae_encoder_block_4_block_1_block_3_bias_to_fp16, dilations = y_21_dilations_0, groups = y_21_groups_0, pad = y_21_pad_0, pad_type = y_21_pad_type_0, strides = y_21_strides_0, weight = vae_encoder_block_4_block_1_block_3_weight_to_fp16, x = input_51_cast_fp16)[name = string("y_21_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> x_81_cast_fp16 = add(x = x_75_cast_fp16, y = y_21_cast_fp16)[name = string("x_81_cast_fp16")];
            tensor<fp16, [1, 1024, 1]> vae_encoder_block_4_block_2_block_0_alpha_to_fp16 = const()[name = string("vae_encoder_block_4_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26058432)))];
            tensor<fp16, [1, 1024, 128]> var_1596_cast_fp16 = mul(x = vae_encoder_block_4_block_2_block_0_alpha_to_fp16, y = x_81_cast_fp16)[name = string("op_1596_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> var_1597_cast_fp16 = sin(x = var_1596_cast_fp16)[name = string("op_1597_cast_fp16")];
            fp16 var_1590_promoted_to_fp16 = const()[name = string("op_1590_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 1024, 128]> var_1598_cast_fp16 = pow(x = var_1597_cast_fp16, y = var_1590_promoted_to_fp16)[name = string("op_1598_cast_fp16")];
            tensor<fp16, [1, 1024, 1]> var_1595_to_fp16 = const()[name = string("op_1595_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26060544)))];
            tensor<fp16, [1, 1024, 128]> var_1599_cast_fp16 = mul(x = var_1595_to_fp16, y = var_1598_cast_fp16)[name = string("op_1599_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> x_83_cast_fp16 = add(x = x_81_cast_fp16, y = var_1599_cast_fp16)[name = string("x_83_cast_fp16")];
            int32 var_1602 = const()[name = string("op_1602"), val = int32(-1)];
            bool input_53_interleave_0 = const()[name = string("input_53_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1024, 182]> input_53_cast_fp16 = concat(axis = var_1602, interleave = input_53_interleave_0, values = (var_1461_cast_fp16_2, x_83_cast_fp16))[name = string("input_53_cast_fp16")];
            string x_85_pad_type_0 = const()[name = string("x_85_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_85_dilations_0 = const()[name = string("x_85_dilations_0"), val = tensor<int32, [1]>([9])];
            int32 x_85_groups_0 = const()[name = string("x_85_groups_0"), val = int32(1024)];
            tensor<int32, [1]> x_85_strides_0 = const()[name = string("x_85_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_85_pad_0 = const()[name = string("x_85_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [1024, 1, 7]> vae_encoder_block_4_block_2_block_1_weight_to_fp16 = const()[name = string("vae_encoder_block_4_block_2_block_1_weight_to_fp16"), val = tensor<fp16, [1024, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26062656)))];
            tensor<fp16, [1024]> vae_encoder_block_4_block_2_block_1_bias_to_fp16 = const()[name = string("vae_encoder_block_4_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26077056)))];
            tensor<fp16, [1, 1024, 128]> x_85_cast_fp16 = conv(bias = vae_encoder_block_4_block_2_block_1_bias_to_fp16, dilations = x_85_dilations_0, groups = x_85_groups_0, pad = x_85_pad_0, pad_type = x_85_pad_type_0, strides = x_85_strides_0, weight = vae_encoder_block_4_block_2_block_1_weight_to_fp16, x = input_53_cast_fp16)[name = string("x_85_cast_fp16")];
            tensor<int32, [3]> var_1623_begin_0 = const()[name = string("op_1623_begin_0"), val = tensor<int32, [3]>([0, 0, 128])];
            tensor<int32, [3]> var_1623_end_0 = const()[name = string("op_1623_end_0"), val = tensor<int32, [3]>([1, 1024, 182])];
            tensor<bool, [3]> var_1623_end_mask_0 = const()[name = string("op_1623_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 1024, 54]> var_1623_cast_fp16 = slice_by_index(begin = var_1623_begin_0, end = var_1623_end_0, end_mask = var_1623_end_mask_0, x = input_53_cast_fp16)[name = string("op_1623_cast_fp16")];
            tensor<fp16, [1, 1024, 1]> vae_encoder_block_4_block_2_block_2_alpha_to_fp16 = const()[name = string("vae_encoder_block_4_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26079168)))];
            tensor<fp16, [1, 1024, 128]> var_1630_cast_fp16 = mul(x = vae_encoder_block_4_block_2_block_2_alpha_to_fp16, y = x_85_cast_fp16)[name = string("op_1630_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> var_1631_cast_fp16 = sin(x = var_1630_cast_fp16)[name = string("op_1631_cast_fp16")];
            fp16 var_1624_promoted_to_fp16 = const()[name = string("op_1624_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 1024, 128]> var_1632_cast_fp16 = pow(x = var_1631_cast_fp16, y = var_1624_promoted_to_fp16)[name = string("op_1632_cast_fp16")];
            tensor<fp16, [1, 1024, 1]> var_1629_to_fp16 = const()[name = string("op_1629_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26081280)))];
            tensor<fp16, [1, 1024, 128]> var_1633_cast_fp16 = mul(x = var_1629_to_fp16, y = var_1632_cast_fp16)[name = string("op_1633_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> input_55_cast_fp16 = add(x = x_85_cast_fp16, y = var_1633_cast_fp16)[name = string("input_55_cast_fp16")];
            string y_pad_type_0 = const()[name = string("y_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_strides_0 = const()[name = string("y_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_pad_0 = const()[name = string("y_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_dilations_0 = const()[name = string("y_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_groups_0 = const()[name = string("y_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> vae_encoder_block_4_block_2_block_3_weight_to_fp16 = const()[name = string("vae_encoder_block_4_block_2_block_3_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26083392)))];
            tensor<fp16, [1024]> vae_encoder_block_4_block_2_block_3_bias_to_fp16 = const()[name = string("vae_encoder_block_4_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28180608)))];
            tensor<fp16, [1, 1024, 128]> y_cast_fp16 = conv(bias = vae_encoder_block_4_block_2_block_3_bias_to_fp16, dilations = y_dilations_0, groups = y_groups_0, pad = y_pad_0, pad_type = y_pad_type_0, strides = y_strides_0, weight = vae_encoder_block_4_block_2_block_3_weight_to_fp16, x = input_55_cast_fp16)[name = string("y_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> x_87_cast_fp16 = add(x = x_81_cast_fp16, y = y_cast_fp16)[name = string("x_87_cast_fp16")];
            tensor<fp16, [1, 1024, 1]> vae_encoder_block_4_block_3_alpha_to_fp16 = const()[name = string("vae_encoder_block_4_block_3_alpha_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28182720)))];
            tensor<fp16, [1, 1024, 128]> var_1658_cast_fp16 = mul(x = vae_encoder_block_4_block_3_alpha_to_fp16, y = x_87_cast_fp16)[name = string("op_1658_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> var_1659_cast_fp16 = sin(x = var_1658_cast_fp16)[name = string("op_1659_cast_fp16")];
            fp16 var_1652_promoted_to_fp16 = const()[name = string("op_1652_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 1024, 128]> var_1660_cast_fp16 = pow(x = var_1659_cast_fp16, y = var_1652_promoted_to_fp16)[name = string("op_1660_cast_fp16")];
            tensor<fp16, [1, 1024, 1]> var_1657_to_fp16 = const()[name = string("op_1657_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28184832)))];
            tensor<fp16, [1, 1024, 128]> var_1661_cast_fp16 = mul(x = var_1657_to_fp16, y = var_1660_cast_fp16)[name = string("op_1661_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> x_89_cast_fp16 = add(x = x_87_cast_fp16, y = var_1661_cast_fp16)[name = string("x_89_cast_fp16")];
            int32 var_1664 = const()[name = string("op_1664"), val = int32(-1)];
            bool input_57_interleave_0 = const()[name = string("input_57_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1024, 136]> input_57_cast_fp16 = concat(axis = var_1664, interleave = input_57_interleave_0, values = (var_1461_cast_fp16_3, x_89_cast_fp16))[name = string("input_57_cast_fp16")];
            string x_pad_type_0 = const()[name = string("x_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_strides_0 = const()[name = string("x_strides_0"), val = tensor<int32, [1]>([8])];
            tensor<int32, [2]> x_pad_0 = const()[name = string("x_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_dilations_0 = const()[name = string("x_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_groups_0 = const()[name = string("x_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 16]> vae_encoder_block_4_block_4_weight_to_fp16 = const()[name = string("vae_encoder_block_4_block_4_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 16]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28186944)))];
            tensor<fp16, [2048]> vae_encoder_block_4_block_4_bias_to_fp16 = const()[name = string("vae_encoder_block_4_block_4_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(95295872)))];
            tensor<fp16, [1, 2048, 16]> x_cast_fp16 = conv(bias = vae_encoder_block_4_block_4_bias_to_fp16, dilations = x_dilations_0, groups = x_groups_0, pad = x_pad_0, pad_type = x_pad_type_0, strides = x_strides_0, weight = vae_encoder_block_4_block_4_weight_to_fp16, x = input_57_cast_fp16)[name = string("x_cast_fp16")];
            tensor<int32, [3]> var_1685_begin_0 = const()[name = string("op_1685_begin_0"), val = tensor<int32, [3]>([0, 0, 128])];
            tensor<int32, [3]> var_1685_end_0 = const()[name = string("op_1685_end_0"), val = tensor<int32, [3]>([1, 1024, 136])];
            tensor<bool, [3]> var_1685_end_mask_0 = const()[name = string("op_1685_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 1024, 8]> var_1685_cast_fp16 = slice_by_index(begin = var_1685_begin_0, end = var_1685_end_0, end_mask = var_1685_end_mask_0, x = input_57_cast_fp16)[name = string("op_1685_cast_fp16")];
            int32 var_1687 = const()[name = string("op_1687"), val = int32(-1)];
            bool var_1688_interleave_0 = const()[name = string("op_1688_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1024, 86]> var_1688_cast_fp16 = concat(axis = var_1687, interleave = var_1688_interleave_0, values = (var_1499_cast_fp16, var_1561_cast_fp16, var_1623_cast_fp16, var_1685_cast_fp16))[name = string("op_1688_cast_fp16")];
            string var_1688_cast_fp16_to_fp32_dtype_0 = const()[name = string("op_1688_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
            int32 var_1690 = const()[name = string("op_1690"), val = int32(-1)];
            bool input_interleave_0 = const()[name = string("input_interleave_0"), val = bool(false)];
            string cache_5_to_fp16_dtype_0 = const()[name = string("cache_5_to_fp16_dtype_0"), val = string("fp16")];
            tensor<fp16, [1, 2048, 2]> cache_5_to_fp16 = cast(dtype = cache_5_to_fp16_dtype_0, x = cache_5)[name = string("cast_2")];
            tensor<fp16, [1, 2048, 18]> input_cast_fp16 = concat(axis = var_1690, interleave = input_interleave_0, values = (cache_5_to_fp16, x_cast_fp16))[name = string("input_cast_fp16")];
            string var_1706_pad_type_0 = const()[name = string("op_1706_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> var_1706_strides_0 = const()[name = string("op_1706_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> var_1706_pad_0 = const()[name = string("op_1706_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> var_1706_dilations_0 = const()[name = string("op_1706_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 var_1706_groups_0 = const()[name = string("op_1706_groups_0"), val = int32(1)];
            tensor<fp16, [64, 2048, 3]> vae_encoder_fc_mu_weight_to_fp16 = const()[name = string("vae_encoder_fc_mu_weight_to_fp16"), val = tensor<fp16, [64, 2048, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(95300032)))];
            tensor<fp16, [64]> vae_encoder_fc_mu_bias_to_fp16 = const()[name = string("vae_encoder_fc_mu_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(96086528)))];
            tensor<fp16, [1, 64, 16]> var_1706_cast_fp16 = conv(bias = vae_encoder_fc_mu_bias_to_fp16, dilations = var_1706_dilations_0, groups = var_1706_groups_0, pad = var_1706_pad_0, pad_type = var_1706_pad_type_0, strides = var_1706_strides_0, weight = vae_encoder_fc_mu_weight_to_fp16, x = input_cast_fp16)[name = string("op_1706_cast_fp16")];
            string var_1706_cast_fp16_to_fp32_dtype_0 = const()[name = string("op_1706_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
            tensor<int32, [3]> var_1711_begin_0 = const()[name = string("op_1711_begin_0"), val = tensor<int32, [3]>([0, 0, 16])];
            tensor<int32, [3]> var_1711_end_0 = const()[name = string("op_1711_end_0"), val = tensor<int32, [3]>([1, 2048, 18])];
            tensor<bool, [3]> var_1711_end_mask_0 = const()[name = string("op_1711_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [1, 2048, 2]> var_1711_cast_fp16 = slice_by_index(begin = var_1711_begin_0, end = var_1711_end_0, end_mask = var_1711_end_mask_0, x = input_cast_fp16)[name = string("op_1711_cast_fp16")];
            string var_1711_cast_fp16_to_fp32_dtype_0 = const()[name = string("op_1711_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
            tensor<fp32, [1, 2048, 2]> new_cache_5 = cast(dtype = var_1711_cast_fp16_to_fp32_dtype_0, x = var_1711_cast_fp16)[name = string("cast_0")];
            tensor<fp32, [1, 64, 16]> mu = cast(dtype = var_1706_cast_fp16_to_fp32_dtype_0, x = var_1706_cast_fp16)[name = string("cast_1")];
            tensor<fp32, [1, 1024, 86]> new_cache_4 = cast(dtype = var_1688_cast_fp16_to_fp32_dtype_0, x = var_1688_cast_fp16)[name = string("cast_3")];
            tensor<fp32, [1, 512, 86]> new_cache_3 = cast(dtype = var_1454_cast_fp16_to_fp32_dtype_0, x = var_1454_cast_fp16)[name = string("cast_5")];
            tensor<fp32, [1, 256, 83]> new_cache_2 = cast(dtype = var_1220_cast_fp16_to_fp32_dtype_0, x = var_1220_cast_fp16)[name = string("cast_7")];
            tensor<fp32, [1, 128, 80]> new_cache_1 = cast(dtype = var_986_cast_fp16_to_fp32_dtype_0, x = var_986_cast_fp16)[name = string("cast_9")];
            tensor<fp32, [1, 1, 6]> new_cache_0 = cast(dtype = var_752_cast_fp16_to_fp32_dtype_0, x = var_752_cast_fp16)[name = string("cast_11")];
        } -> (mu, new_cache_0, new_cache_1, new_cache_2, new_cache_3, new_cache_4, new_cache_5);
}